58 resultados para CG Series


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A headspace solid-phase microextraction (HS-SPME) for the determination of 1,4 dioxane in cosmetics by gas chromatography is described. A manual SPME holder with 85 µm polyacrylate coating is utilized. The method is determined to have good resolution, satisfactory linerity (correlation coefficient r=0.997 for 0.20-10.00 mg Kg-1 range), a relative standard deviation of 6.3% and a detection limit of 5.00 µg Kg-1. Some cosmectic products were analyzed.

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Glucocorticosteroids (CT) show a powerful anti-inflammatory effect. In view of this, they are extensively used in sports medicine, but their misuse (systemic administration) can lead to severe injuries on athletes and has been restricted by the IOC in recent years. For GC-MS analysis, a derivatization step is necessary in order to convert them to a stable form, thus preventing thermal breakdown with the loss of the ketone side chain. Derivatization of CT is reviewed and a new approach of silylation is presented for screening of CT in urine.

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A matrix solid phase dispersion and gas chromatography-mass selective detection method for the simultaneous determination of monocrotophos, methyl parathion, cypermethrin and deltamethrin in okra is described. Analyses of 2 g of fortified okra (0.05-0.75 mg kg-1) showed an average recovery of 96.2% (71.4-128.4%) and average relative standard deviation of 11.7% (1.4-37.1%). The cypermethrin recovery at the lower level was above 130%. The limit of detection ranged from 0.02 to 0.15 mg kg-1. The procedure was applied to the okra samples and has found 0.56 mg kg-1 of cypermethrin-cis, 0.75 mg kg-1 of cypermethrin-trans and 2.71 mg kg-1 of deltamethrin.

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The liquid-liquid extraction with the low temperature partition technique was developed for the analysis of four pyrethroids in water by CG. Using a factorial design the extraction technique was optimised evaluating the effect of the variables ionic strength, contact time and proportion between sample and solvent volumes. The validation parameters sensitivity, precision, accuracy and detection and quantification limits were evaluated. The LOD and LOQ of the method varied from 1.1 to 3.2 µg L-1 and 2.7 to 9.5 µg L-1, respectively.

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A simple, specific and sensitive GC-MS procedure with ion m/z 62 was validated for the determination of ethyl carbamate (EC) in spirits. It exhibited linearity over the concentration of 30 to 600 μg/L with 30 μg/L limit of quantification. EC was detected in 70 of the 71 samples analyzed with levels from 33 to 2609 μg/L (mean level = 893 μg/L). 35% of the samples contained 500 to 1000 μg/L and 23% contained 150 to 500 and 1000 to 1500 μg/L. No significant correlation was found between EC and the levels of copper, pH and alcohol content of the samples.

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The use of analytical pyrolysis combined with gas chromatography/mass spectrometry (Py-GC/MS) to determine the syringyl/guaiacyl ratio (S/G) in lignins from Eucalyptus spp woods was investigated. Sample of E. grandis and "E. urograndis" wood, with and without extractives, were subjected to pyrolysis from 300 ºC to 600 ºC. The products that results from pyrolysis were identified by mass spectrometry and the S/G ratio was determined based on the areas of the peaks corresponding to the guaiacyl and syringyl derivatives. The best S/G estimation is achieved when pyrolysis is carried out at 550 ºC. Extractives and carbohydrate present in the woods do not interfere with the results.

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Methyl ethyl ketone (MEK) is a solvent commonly used in chemical, paint and shoe industry. The aim of this study was to develop and validate a method for urinary quantification of MEK, employing headspace solid phase micro extraction sampling (SPME) coupled to gas chromatography with flame ionization detection (GC-FID). The calibration curve (y=4.6851x-0.0011) presented good linearity with r²=0.9993. Accuracy (94-109%), intra-assay precision (4.07-5.91%) and inter-assay precision (3.03-5.62%) were acceptable. The quantification limit was 0.19 mg/L. This low cost method can be used routinely in the biological monitoring of occupational exposure to MEK, according to the requirements of the Brazilian legislation.

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About 20% of Brazilian raw coffee production is considered inappropriate for exportation. Consequently, these beans are incorporated to good quality beans in the Brazilian market. This by-product of coffee industry is called PVA due to the presence of black (P), green (V) and sour (A) defective beans which are known to contribute considerably for cup quality decrease. Data on the volatile composition of Brazilian defective coffee beans are scarce. In this study, we evaluated the volatile composition of immature, black-immature, black defective beans and PVA compared to good quality beans. Potential defective beans markers were identified.

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The presence of chloramphenicol residues in goat milk can cause toxic effects in the population. The present work consists of the optimization and validation of analytical methodology for determination of chloramphenicol residues in goat milk by GC/ECD. The extraction was made with ethyl acetate and the clean-up with SPE-C18. The identification was made by comparison of retention time and GC/MS, and the quantification by external standard. The method was selective, linearity (0.998), precise (5.8-13.4%), exact (69.87-73.71%) and robust. The LOD and LOQ of method were 0.030 and 0.10 μg/kg, respectively. The method was efficiently for analysis of chloramphenicol in goat milk.

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Multivariate models were developed using Artificial Neural Network (ANN) and Least Square - Support Vector Machines (LS-SVM) for estimating lignin siringyl/guaiacyl ratio and the contents of cellulose, hemicelluloses and lignin in eucalyptus wood by pyrolysis associated to gaseous chromatography and mass spectrometry (Py-GC/MS). The results obtained by two calibration methods were in agreement with those of reference methods. However a comparison indicated that the LS-SVM model presented better predictive capacity for the cellulose and lignin contents, while the ANN model presented was more adequate for estimating the hemicelluloses content and lignin siringyl/guaiacyl ratio.

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SPME-GC-MS, PCA and HCA multivariate techniques were used in order to evaluate their applicability to discriminate the three chemotypes (thymol, carvacrol and mixed) described for L. graveolens of Guatemala. The leaves of L. graveolens are used for treatment of colds, bronchitis, and as seasoning for food preparations, yielding essential oil up to 4.34 %. Leaves of 35 individuals from eight populations, and eight composite samples were analyzed using a DVB/Carboxen/PDMS fiber and GC-MS. PCA and HCA were carried out using eight markers (p-cymene, cis-sabinene hydrate, linalool, terpinen-4-ol, thymol, carvacrol, (E)-caryophyllene and caryophyllene oxide). The three chemotypes of L. graveolens were satisfactorily discriminated.

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The estimation of measurement uncertainty of an analytical result is an important tool to be applied for compliance to ISO IEC 17025. Through the available guides it is possible to establish procedures and criteria for the estimation of measurement uncertainty. This paper presents a case study on the estimation of measurement uncertainty in migration the test of ε-caprolactam from the polyamide 6 packages to fatty foods with determination by GC-FID. The calculation methodology used for the estimation of measurement uncertainty for the migration test was developed based on the guides EURACHEM / CITAC and ISO GUM, taking into account relevant aspects of the migration test. The expanded uncertainty estimated was approximately 23% of the concentration of migration.

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This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

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A bioactive N,N-diacetylglycine (NNDAG) and new organotin(IV) complexes (OTCs) (1-7) were synthesized. Spectroscopic techniques were employed to characterize NNDAG and OTCs. FTIR was employed to verify N,N protection of glycine by acetyl groups. The disappearance of υ(OH) at 3000-2600 cm-1 showed de-protonation of free ligand. The Δυ 150<200 cm-1 of OTCs 4-7 verified bidentate coordination with tetrahedral geometry. The Δυ of OTCs1 and 3 was <200 cm-1 exhibitingtrans -octahedral geometry while OTC 2 dimer was assigned a unique sinusoidal view. The 1H NMR spectra of OTCs verified their synthesis by de-protonation of NNDAG and no chemical shift was found downfield for carboxylic acid proton. The 13C, 119Sn NMR and Mass spectrometric data also supported FTIR and 1H NMR descriptions. The OTCs 4, 5, 6 and7 (500 ppm) proved twice as active against Escherichia coli as the standard antibiotic enoxacin (1000 ppm). The promising property of the OTCs (4, 5, 6 and7) is clearly due to their tetrahedral. The OTCs 4and 5 exhibited excellent activity against M. minimum and good activity against T. castaneum.LD50 of all the compounds were determined and OTCs4, 5 and 7 were found to be active.