A novel and simple method for the determination of some pesticide residues in strawberries using both focused microwave-assisted extraction (FMAE) and solid-phase micro extraction (SPME), coupled with high-performance liquid chromatography (HPLC), has been developed. The pesticides were first extracted from strawberries with water and the assistance of focused microwaves at 30 W for 7 min. Then, an aliquot of the resulting aqueous extract was subjected to SPME with a 60-microm thick poly(dimethylsiloxane)/divinylbenzene (PDMS/DVB) fiber for 45 min at room temperature, with the solution being stirred at 1000 rpm. The extracted pesticides on the SPME fiber were desorbed into the SPME/HPLC interface for quantitative analysis with a diode array detector (DAD). The whole sample pretreatment procedure before chromatographic analysis did not use any organic solvents or involve any blending or centrifugation steps. The five compounds (carbendazim, diethofencarb, azoxystrobine, napropamide, and bupirimate) were chosen because they cannot be analyzed easily by GC. The efficiency of this relatively fast procedure was comparable to that of previously reported methods, with detection limits at low microg/kg levels and linear responses in the range from 0.05 to 1 mg/kg of pesticide in strawberries, with RSDs between 3 and 7.3%, depending on the analyte. In all but one case results obtained by this method for field-incurred samples were comparable to those obtained with traditional methods.
To provide an efficient and running analytical tool to strawberry plant breeders who have to characterize and compare the aromatic properties of new cultivars to those already known, a HS-SPME/GC-MS analysis method has been coupled with a statistical treatment method issued from the current development of artificial neuron networks (ANN), and more specifically, the unsupervised learning systems called Kohonen self-organizing maps (SOMs). So, 70 strawberry samples harvested at CIREF from 17 known varieties have been extracted by using a DVB/Carboxen/PDMS SPME fiber according to the headspace procedure, and then chromatographed. A panel of 23 characteristic aromatic constituents has been selected according to published results relative to strawberry aroma. The complex resulting matrix, collecting the relative abundance of the 23 selected constituents for each sample, has been input into the SOM software adapted and optimized from the Kohonen approach described by one of the authors. After a period of training, the self-organized system affords a map of virtual strawberries to which real samples are compared and plotted in the best matching unit (BMU) of the map. The efficiency for discriminating the real samples according to their variety is dependent on the number of units selected to define the map. In this case, a 24-unit map allowed the complete discrimination of the 17 selected varieties. Moreover, to test the validity of this approach, two additional samples were blind-analyzed and the results were computed according to the same procedure. At the end of this treatment, both samples were plotted into the same unit as those of the same variety used for training the map.
Solid-phase microextraction coupled with high performance liquid chromatography has been studied for the analysis of methiocarb, napropamide, fenoxycarb and bupirimate in strawberries. The strawberries were blended and centrifuged. Then, an aliquot of the resulting extracting solution was subjected to solid-phase microextraction (SPME) on a 60 microns polydimethylsiloxane/divinylbenzene (PDMS/DVB) fibre for 45 min at room temperature. The extracted pesticides on the SPME fibre were desorbed into SPME/high performance liquid chromatography (HPLC) interface for HPLC analysis with diode-array detection (DAD). The method is organic solvent-free for the whole extraction process and is simple and easy to manipulate. The detection limits were shown to be at low microgram kg-1 level and the linear response covered the range from 0.05 to 2 mg kg-1 of pesticides in strawberries with a regression coefficient larger than 0.99. A good repeatability with RSDs between 2.92 and 9.25% was obtained, depending on compounds.
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