title: Chemometric approach to the optimization of HS-SPME/GC-MS for the determination of multiclass pesticide residues in fruits and vegetables.
abstract: An HS-SPME method was developed using multivariate experimental designs, which was conducted in two stages. The significance of each factor was estimated using the Plackett-Burman (P-B) design, for the identification of significant factors, followed by the optimization of the significant factors using central composite design (CCD). The multivariate experiment involved the use of Minitab® statistical software for the generation of a 2(7-4) P-B design and CCD matrices. The method performance evaluated with internal standard calibration method produced good analytical figures of merit with linearity ranging from 1 to 500 μg/kg with correlation coefficient greater than 0.99, LOD and LOQ were found between 0.35 and 8.33 μg/kg and 1.15 and 27.76 μg/kg respectively. The average recovery was between 73% and 118% with relative standard deviation (RSD=1.5-14%) for all the investigated pesticides. The multivariate method helps to reduce optimization time and improve analytical throughput.
authors: Department of Chemistry, Faculty of Science, University of Malaya, Pantai Valley, Kuala Lumpur 50603, Malaysia. Electronic address: abdulrauflukman@siswa.um.edu.my.
authors: Lukman Bola
authors: LB
authors: Abdulra'uf
authors: Department of Chemistry, Faculty of Science, University of Malaya, Pantai Valley, Kuala Lumpur 50603, Malaysia.
authors: Guan Huat
authors: GH
authors: Tan
mesh_terms: D005638:Fruit / Q000737:chemistry*; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D015999:Multivariate Analysis; D010573:Pesticide Residues / Q000032:analysis* / Q000737:chemistry; D052617:Solid Phase Microextraction / Q000379:methods*; D014675:Vegetables / Q000737:chemistry*
chemical_list: D010573:Pesticide Residues
keywords: Central composite design; Fruits and vegetables; GC–MS; Pesticide residues; Plackett–Burma design; SPME