Determination of multiclass pesticide residues in fruits and vegetables with headspace solid phase microextraction gas chromatography mass spectrometry using experimental factorial design / Abdulra’uf Lukman Bola

• Main Author: Bola, Abdulra’uf Lukman
• Format: Thesis
• Published: 2013
• Subjects: QD Chemistry
• Online Access: http://studentsrepo.um.edu.my/5727/1/Abdulra'uf%2C_L.B_Front_matters.pdf; http://studentsrepo.um.edu.my/5727/2/Abdulra'uf%2C_L.B_Thesis_Full.pdf; http://studentsrepo.um.edu.my/5727/

The focus of this study is the development and validation of headspace solid phase microextraction and chromatographic techniques for the analysis of pesticide residues in fruit and vegetable samples. The developed method is based on the comparison of the optimized HS-SPME parameters using univariate and multivariate experimental designs. Modern trends in sample preparation and subsequent instrumental analysis are aimed towards reliable and accurate analysis of pesticide residues and other contaminants from food. It is focused on the simplifications, miniaturization, improvement and reduction in volume of sample and solvents used while maintaining high throughput performance. The microextraction techniques have been developed in order to reduce sample preparation time, improve sensitivity and selectivity as well as to corroborate the recent advances in the development of highly sensitive and efficient analytical instrumentation. The method developed was based on the optimization of both GC-MS and SPME parameters using univariate method, followed by the screening for the significant factors using multivariate experimental design. The multivariate experimental design was conducted in two stages. First, the significance of each factor is estimated using the first-order experimental design called the Plackett-Burman (P-B) design, used as a preliminary study for the identification of significant factors. The second stage involves the optimization of the significant factors using second-order models such as central composite design. The multivariate experiment involved the use of Minitab® statistical software for the generation of a 27-4 Plackett-Burman (P-B) and central composite design (CCD) matrices. Factors studied and optimized included, selection of fiber coatings, chromatographic parameters, extraction temperature and time, stirring rate, salt addition, pH, dilution factor and organic solvent addition. A simplex lattice design was employed for the determination of the best combination of organic solvent which enhances extraction efficiency. The optimized conditions for the multivariate design was slightly different from that of the univariate design, this could be due to the fact that the univariate design does not take the possible interaction of factors into consideration. For the validation studies, both the multivariate optimized factors (for significant factors) and univariate conditions obtained were: 100 μm PDMS, 10 % NaCl, optimum dilution varied with sample matrices, extraction temperature and extraction time of 65 0C and 35 min respectively, stirring rate of 350 rpm at pH 6. The desorption temperature and time were 270 0C and 7 min respectively. The method produced good analytical figures of merit with linearity ranging from 1 – 500 μg/kg with correlation coefficient greater than 0.99, low limits of detection and quantification which were found between 0.14 and 8.33 μg/kg and 0.38 and 27.76 μg/kg respectively. The recoveries achieved were greater than 74% and less than 120 % with relative standard deviation of less than 15 % for all the investigated pesticides. The use of the multivariate method helps to reduce sampling time and improve analytical throughput. The developed method was used to analyze fourteen multi-class and multi-residue pesticides in 4 fruit and 4 vegetable samples and the results obtained were found to be satisfactory in accordance with various guidelines for the validation of analytical methods.