Application of solid-phase microextraction for determining phenylurea herbicides and their homologous anilines from vegetables

Berrada, Houda; Font, Guillermina; Moltó, J.C.

doi:10.1016/j.chroma.2004.05.017

Cited by 60 publications

(45 citation statements)

References 38 publications

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“…Again, ureas with Cl2 and great retention are grouped into the same class (3,5). Ureas belonging to the same cluster appear highly correlated in the partial correlation diagram (Fig.…”

mentioning

confidence: 98%

“…They are unstable photochemically but they persist in water for several days or weeks depending on temperature and pH. Pesticide pollution of water reservoirs became frequent (Berrada et al, 2004). Phenylurea residues were found in water sources, processed products and crops.…”

Section: Introductionmentioning

confidence: 99%

“…3) shows different behaviour depending on the number of Cl atoms. Once more, ureas with Cl 2 and great retention are grouped into class (3,5). The illustration of the classification above in a radial tree (cf.…”

mentioning

confidence: 99%

“…2 and 3). One more time, ureas with Cl 2 and great retention are grouped into class (3,5). Program SplitsTree allows examining cluster analysis (CA) data.…”

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confidence: 99%

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Molecular Clustering of Phenylurea Herbicides: Comparison with Sulphonylureas, Pesticides and Persistent Organic Pollutants

Torrens

Castellano

2014

ETET

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ABSTRACT. Chromatographic retention times of phenylurea herbicides are modelled by structure-property relationships. Properties are hydration free energy and dipole. Bioplastic evolution is an evolutionary perspective conjugating the effect of acquired characters and relations that emerge among evolutionary indeterminacy, morphological determination and natural selection principles. Classification algorithms are proposed based on information entropy and production. Phenylureas are classified by Cl2, O2 and N2 presence; their different behaviour depends on the number of Cl atoms. When applying procedures to moderate-sized sets, excessive results appear compatible with data and suffer a combinatorial explosion; however, the equipartition conjecture allows a selection criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds and agrees with principal component analyses. Phenylureas periodic table shows that those in the same group present similar properties; phenylureas also in the same period, maximum resemblance. Classification extends to phenylureas, sulphonylureas, pesticides and persistent organic pollutants.

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“…Again, ureas with Cl2 and great retention are grouped into the same class (3,5). Ureas belonging to the same cluster appear highly correlated in the partial correlation diagram (Fig.…”

mentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

“…2 and 3). One more time, ureas with Cl 2 and great retention are grouped into class (3,5). Program SplitsTree allows examining cluster analysis (CA) data.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Molecular Clustering of Phenylurea Herbicides: Comparison with Sulphonylureas, Pesticides and Persistent Organic Pollutants

Torrens

Castellano

2014

ETET

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“…8,9 Most applications are based on the preparation of fruit or vegetable juices and analysis of target compounds by directly dipping of the SPME fibers into the slurry. [9][10][11][12][13][14] However several disadvantages related to fiber stability and sensitivity have been pointed out. Such problems can be overcome if headspace SPME is applied.…”

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confidence: 99%

Optimization of Headspace Solid-Phase Microextraction for the Determination of Pesticide Residues in Vegetables and Fruits

2008

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Pesticides, including organochlorine pesticides (OCPs) and organophosphorous pesticides (OPPs) are examples of wellknown environmental contaminants. OPPs are used as a substitute for OCPs in many countries nowadays because they can degrade more easily in the environment. Although OPPs as a whole are not the most toxic pollutants, they can be traced to a wide range of surface water, fruits, vegetables and foodstuff. 1For fast monitoring of the environmental contamination caused by OCPs and OPPs and to accomplish risk assessment, more sensitive, rapid and simple analytical methods are paramount.Liquid-liquid extraction (LLE) and solid-phase extraction (SPE) are the most popular methods for extracting pesticides. However, they are time consuming and labor-intensive, and require large volumes of sample and solvents. In addition, because pesticides generally are present at ppt levels, mixed with other contaminants at higher concentrations, interfering compounds can produce extraneous peaks. LLE and SPE can carry contaminants into the final sample, producing a high background. 2-4Solid-phase microextraction (SPME), developed by Kataoka et al.,5 has received an increasing amount of attention at the analytical level in numerous scientific disciplines. 6 It is simple 6,7 and, as will be discussed later, offers great flexibility. In comparison with direct SPME, headspace (HP) SPME can shorten the time of extraction significantly because the diffusion rate of the analytes in gaseous phase is faster than that in the aqueous phase.1 Only a few references on the application of HS-SPME for the determination of OCPs and OPPs in fruit and vegetable samples can be found. 8,9 Most applications are based on the preparation of fruit or vegetable juices and analysis of target compounds by directly dipping of the SPME fibers into the slurry. [9][10][11][12][13][14] However several disadvantages related to fiber stability and sensitivity have been pointed out. Such problems can be overcome if headspace SPME is applied. Since the fiber is not in contact with the sample, background adsorption and matrix effects can be reduced, which also enhances the life expectancy of the SPME fibers. The objectives of this study are to evaluate the HS-SPME process by comparing two coating materials and to optimize the main parameters affecting the HS-SPME. Finally, we intended to develop an efficient multi-residue method on the basis of HS-SPME to extract each selected pesticide in fruit and vegetable samples. Experimental Chemicals and reagentsEight pesticides standards which are popular used by local farmers in vegetable and fruit cultivation 15 were > 95% pure and were purchased from AccuStandard Inc., USA. Stock solutions of each pesticide were prepared. Working standard solutions were prepared daily by volume dilution in distilled water. In the calibration and quantitation studies, an internal standard, 1-chloro-4-fluorobenzene, 200 mg/L which is effective as a surrogate to compensate the data of all 8 kinds of pesticides was added to each sample...

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Pesticides: Herbicides and Fungicides

Falcó

Vidal

Canals

2010

Analysis of Endocrine Disrupting Compounds in Food

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Application of solid-phase microextraction for determining phenylurea herbicides and their homologous anilines from vegetables

Cited by 60 publications

References 38 publications

Molecular Clustering of Phenylurea Herbicides: Comparison with Sulphonylureas, Pesticides and Persistent Organic Pollutants

Molecular Clustering of Phenylurea Herbicides: Comparison with Sulphonylureas, Pesticides and Persistent Organic Pollutants

Optimization of Headspace Solid-Phase Microextraction for the Determination of Pesticide Residues in Vegetables and Fruits

Pesticides: Herbicides and Fungicides

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