, Volume 81, Issue 4, pp 677–688 | Cite as

Method Validation Using Normal and Weighted Linear Regression Models for Quantification of Pesticides in Mango (Mangifera indica L.) Samples

  • Fátima Itana Chaves Custódio Martins
  • Pablo Gordiano Alexandre Barbosa
  • Guilherme Julião Zocolo
  • Ronaldo Ferreira do Nascimento


A fast and efficient method was developed and validated for the determination of pesticides in mangos, which uses the QuEChERS citrate and gas chromatography–mass spectrometry (GC–MS) techniques. A detailed statistical analysis was performed to study the matrix effect. The calibration model using the method of weighted least squares is used in cases, where heteroscedasticity is observed. The matrix effect was observed for most studied compounds using analytical curves based on a spiked matrix. The limits of detection were 0.0025–0.01 mg kg−1, and the limits of quantification (LOQ) were 0.008–0.03 mg kg−1. The LOQ values were minor or equal to the established MRLs by major regulatory agencies in Brazil (ANVISA), the United States (US-EPA), and Europe (CE). The compounds showed acceptable recovery levels of 71–109% with a standard deviation less than 15%. The method was applied to determine pesticide residues in mango samples. For 12 samples, five compounds (chloroneb, propachlor, α-chlordane, chlorpyrifos, DCPA, chlorobenzilate, and trans-permethrin) were detected, with contents of 0.004–0.042 mg kg−1. For chloroneb, propachlor, and α-chlordane, the found concentrations were above the maximum permitted residue limit, according to data from the European Commission.


Pesticides Matrix effect Statistical analysis Heteroscedasticity Weighted regression 



The authors gratefully the Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq (Grant Number 405167/2015-6 and 304888/2014-1) and Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico—FUNCAP for financial support of this research and the UFC for providing the laboratory infrastructure for the chromatographic analysis.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

This article does not contain any studies with human participants, so no informed consent was necessary for this study.

Supplementary material

10337_2018_3483_MOESM1_ESM.docx (691 kb)
Supplementary material 1 (DOCX 691 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Analytical Chemistry and Physical ChemistryFederal University of CearaFortalezaBrazil
  2. 2.Federal Institute of EducationScience and Technology of CearáSobralBrazil
  3. 3.Embrapa Agroindústria TropicalFortalezaBrazil

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