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Selected papers from the latest issue:
Detection of adulteration in hydrated ethyl alcohol fuel using infrared spectroscopy and supervised pattern recognition methods
05 February 2012, 21:54:18
Publication year: 2012
Source: Talanta, Available online 3 February 2012
Adenilton Camilo Silva, Liliana Fátima Bezerra Lira Pontes, Maria Fernanda Pimentel, Márcio José Coelho Pontes
This paper proposes an analytical method to detect adulteration of hydrated ethyl alcohol fuel based on near infrared (NIR) and middle infrared (MIR) spectroscopies associated with supervised pattern recognition methods. For this purpose, linear discriminant analysis (LDA) was employed to build a classification model on the basis of a reduced subset of wavenumbers. For variable selection, three techniques are considered, namely the successive projection algorithm (SPA), the genetic algorithm (GA) and a stepwise formulation (SW). For comparison, models based on Partial least squares discriminant analysis (PLS-DA) were also employed using full-spectrum. The method was validated in a case study involving the classification of 181 hydrated ethyl alcohol fuel samples, which were divided into three different classes: (1) authentic samples; (2) samples adulterated with water and (3) samples contaminated with methanol. LDA/GA and PLS-DA models were found to be the best methods for classifying the spectral data obtained in NIR region, which achieved a correct prediction rate of 100% in the test set, while the LDA/SPA and LDA/SW were correctly classified at 84.4% and 97.8%, respectively. For MIR data, all models (PLS-DA and LDA coupled with the SW, SPA and GA) employed in this study correctly classified all samples in the test set.
Source: Talanta, Available online 3 February 2012
Adenilton Camilo Silva, Liliana Fátima Bezerra Lira Pontes, Maria Fernanda Pimentel, Márcio José Coelho Pontes
This paper proposes an analytical method to detect adulteration of hydrated ethyl alcohol fuel based on near infrared (NIR) and middle infrared (MIR) spectroscopies associated with supervised pattern recognition methods. For this purpose, linear discriminant analysis (LDA) was employed to build a classification model on the basis of a reduced subset of wavenumbers. For variable selection, three techniques are considered, namely the successive projection algorithm (SPA), the genetic algorithm (GA) and a stepwise formulation (SW). For comparison, models based on Partial least squares discriminant analysis (PLS-DA) were also employed using full-spectrum. The method was validated in a case study involving the classification of 181 hydrated ethyl alcohol fuel samples, which were divided into three different classes: (1) authentic samples; (2) samples adulterated with water and (3) samples contaminated with methanol. LDA/GA and PLS-DA models were found to be the best methods for classifying the spectral data obtained in NIR region, which achieved a correct prediction rate of 100% in the test set, while the LDA/SPA and LDA/SW were correctly classified at 84.4% and 97.8%, respectively. For MIR data, all models (PLS-DA and LDA coupled with the SW, SPA and GA) employed in this study correctly classified all samples in the test set.
Highlights
► Hydrated ethyl alcohol fuel adulteration problem is addressed. ► PLS-DA and LDA are applied to NIR and MIR data. ► Satisfactory classification performance of PLS-DA and LDA models is demonstrated.Evaluation of new mixed-mode UHPLC stationary phases and the importance of stationary phase choice when using low ionic–strength mobile phase additives
03 February 2012, 23:22:38
Publication year: 2012
Source: Talanta, Available online 2 February 2012
Nováková Lucie, Vlčková Hana, Petr Solich
In this study, the selectivity, retention properties, peak shape and loading capacity for bases were practically evaluated using two UHPLC mixed-mode hybrid CSH stationary phases modified by C18 or Phenyl group. The data were compared with the data obtained on other UHPLC hybrid stationary phases (BEH C18, BEH C8, BEH Phenyl and BEH Shield RP18) at both basic and acidic conditions using conventional HPLC buffers (50 mM ammonium formate/acetate) as well as low ionic-strength additives such as e. g. 0.1–0.01% formic/acetic acid and 1 mM solution of ammonium formate/acetate, which are widely used in LC-MS applications.Ten pharmaceutically important compounds encompassing acids, bases and neutrals were included into the study. Due to properties of CSH sorbent (which possess positively charged surface besides RP group), much improved peak shapes and weaker retention was obtained for bases even at very low concentration of acidic additives. Such conditions are ideally suited for LC-MS analysis of bases, where typical RP chromatographic separation (retention and good selectivity at basic pH) and LS-MS conditions (efficient ionization at acidic pH) are not in agreement. On the other hand, acids were more strongly retained and for some compounds the peak shape was influenced negatively due to ion-exchange mechanism. Further, the behavior of acidic, basic and neutral solutes is discussed using various additives at both basic and acidic pH for all above stated columns. The robustness of retention times after pH change from basic to acidic was also evaluated. The new CSH stationary phases represent an interesting selectivity tool preferably for separation of basic compounds.
Source: Talanta, Available online 2 February 2012
Nováková Lucie, Vlčková Hana, Petr Solich
In this study, the selectivity, retention properties, peak shape and loading capacity for bases were practically evaluated using two UHPLC mixed-mode hybrid CSH stationary phases modified by C18 or Phenyl group. The data were compared with the data obtained on other UHPLC hybrid stationary phases (BEH C18, BEH C8, BEH Phenyl and BEH Shield RP18) at both basic and acidic conditions using conventional HPLC buffers (50 mM ammonium formate/acetate) as well as low ionic-strength additives such as e. g. 0.1–0.01% formic/acetic acid and 1 mM solution of ammonium formate/acetate, which are widely used in LC-MS applications.Ten pharmaceutically important compounds encompassing acids, bases and neutrals were included into the study. Due to properties of CSH sorbent (which possess positively charged surface besides RP group), much improved peak shapes and weaker retention was obtained for bases even at very low concentration of acidic additives. Such conditions are ideally suited for LC-MS analysis of bases, where typical RP chromatographic separation (retention and good selectivity at basic pH) and LS-MS conditions (efficient ionization at acidic pH) are not in agreement. On the other hand, acids were more strongly retained and for some compounds the peak shape was influenced negatively due to ion-exchange mechanism. Further, the behavior of acidic, basic and neutral solutes is discussed using various additives at both basic and acidic pH for all above stated columns. The robustness of retention times after pH change from basic to acidic was also evaluated. The new CSH stationary phases represent an interesting selectivity tool preferably for separation of basic compounds.
Highlights
► Evaluation of new mixed-mode stationary phases–CSH hybrid phases ► Analysis of basic compounds using low ionic-strength additives ► The effect of pH change to column equilibrationA portable Raman sensor for the rapid discrimination of olives according to fruit quality
03 February 2012, 23:22:38
Publication year: 2012
Source: Talanta, Available online 2 February 2012
Elena Guzmán, Vincent Baeten, Juan Antonio Fernández Pierna, José A. García-Mesa
In the real marketplace, providing high-quality olive oil is important from the perspective of both consumers and producers. Quality control should meet all requirements in the production process, from farm to packaging. The quality of olive oil can be affected by several factors, including agricultural techniques, seasonal conditions, farming systems, maturity, method and duration of storage, and process technology.The quality of oil produced also depends largely on the quality of the olives. In an enterprise aimed at producing high-quality oils, olives with defects (‘ground’; i.e., fallen to the ground) should be separated from healthy fruit (‘sound’; i.e., collected directly from the tree), because a very small portion of low-quality fruit can ruin the whole batch.The fruit falls partly because of its maturation process, but also because of pest and disease attack or weather conditions (strong wind). Fruit that has fallen to the ground can suffer a rapid deterioration in quality.Currently, the separation of fruits is based mainly on visual inspection or information provided by the farmer. These are not very reliable procedures. Methods using analytical parameters to characterize the oil, such as acidity and peroxide value, can be applied, but they require a lot of time and materials. Alternative techniques are therefore needed for the rapid and inexpensive discrimination of olives as part of a quality control strategy.The work described here aims to determine the potential of low-resolution Raman spectroscopy for the discrimination of olives before the oil processing stage in order to detect whether they have been collected directly from the tree (i.e., healthy fruit) or not. Low-resolution Raman spectroscopy wasapplied together with multivariate procedures to achieve this aim. PCA was used to find natural clusters in the data. Supervised classification methods were then applied: Soft Independent Modeling of Class Analogy (SIMCA), PLS Discriminate Analysis (PLS-DA) andK-nearest neighbors (KNN). Thebest results were obtained using the KNN method, with prediction abilities of 100% for ‘sound’ and 97% for ‘ground’ in an independent validation set.These results demonstrated the potential of a portable Raman instrument for detecting good quality olives before the oil processing stage, by developing models that could be applied before this stage, thus contributing to an overall improvement in quality control.
Source: Talanta, Available online 2 February 2012
Elena Guzmán, Vincent Baeten, Juan Antonio Fernández Pierna, José A. García-Mesa
In the real marketplace, providing high-quality olive oil is important from the perspective of both consumers and producers. Quality control should meet all requirements in the production process, from farm to packaging. The quality of olive oil can be affected by several factors, including agricultural techniques, seasonal conditions, farming systems, maturity, method and duration of storage, and process technology.The quality of oil produced also depends largely on the quality of the olives. In an enterprise aimed at producing high-quality oils, olives with defects (‘ground’; i.e., fallen to the ground) should be separated from healthy fruit (‘sound’; i.e., collected directly from the tree), because a very small portion of low-quality fruit can ruin the whole batch.The fruit falls partly because of its maturation process, but also because of pest and disease attack or weather conditions (strong wind). Fruit that has fallen to the ground can suffer a rapid deterioration in quality.Currently, the separation of fruits is based mainly on visual inspection or information provided by the farmer. These are not very reliable procedures. Methods using analytical parameters to characterize the oil, such as acidity and peroxide value, can be applied, but they require a lot of time and materials. Alternative techniques are therefore needed for the rapid and inexpensive discrimination of olives as part of a quality control strategy.The work described here aims to determine the potential of low-resolution Raman spectroscopy for the discrimination of olives before the oil processing stage in order to detect whether they have been collected directly from the tree (i.e., healthy fruit) or not. Low-resolution Raman spectroscopy wasapplied together with multivariate procedures to achieve this aim. PCA was used to find natural clusters in the data. Supervised classification methods were then applied: Soft Independent Modeling of Class Analogy (SIMCA), PLS Discriminate Analysis (PLS-DA) andK-nearest neighbors (KNN). Thebest results were obtained using the KNN method, with prediction abilities of 100% for ‘sound’ and 97% for ‘ground’ in an independent validation set.These results demonstrated the potential of a portable Raman instrument for detecting good quality olives before the oil processing stage, by developing models that could be applied before this stage, thus contributing to an overall improvement in quality control.
Highlights
► The work described here aims to determine the potential of low-resolution Raman spectroscopy for the discrimination of olives before the oil processing stage in order to discriminate healthy and diseased olives ► Low-resolution Raman spectroscopy was applied together with multivariate procedures to achieve this aim ► Supervised classification methods were then applied ► The best results were obtained using the KNN method, with prediction abilities of 100% for ‘sound’ and 97% for ‘ground’ in an independent validation set.A label-free aptasensor for the sensitive and specific detection of cocaine using supramolecular aptamer fragments/target complex by electrochemical impedance spectroscopy
03 February 2012, 23:22:38
Publication year: 2012
Source: Talanta, Available online 2 February 2012
De-Wen Zhang, Fang-Ting Zhang, Yi-Ran Cui, Qin-Pei Deng, Steffi Krause, ...
A simple and label-free aptasensor for sensitive and specific detection of cocaine was developed by measuring the change in electrochemical impedance spectra (EIS), based on the formation of a supramolecular aptamer fragments/substrate complex. An anticocaine aptamer was divided into two fragments, Cx and Cy. Three different sensing interfaces, called Au/Cx5S/MCE, Au/Cy3S/MCE and Au/Cy5S/MCE, were fabricated by immobilizing Cx or Cy on a gold electrode through modifying their 5′ or 3′ end with a thiolated group followed by the treatment with mercaptoethanol (MCE). The formation of the corresponding supramolecular aptamer fragments/cocaine complex was investigated via monitoring electrochemical impedance spectra in the presence of [Fe(CN)6]. The interfacial electron transfer resistance (Ret) was found to depend strongly on the cocaine concentration. Since the supramolecular aptamer fragments/cocaine complex was formed on the electrode surface, the sensing interface strongly affected the sensitivity of the aptasensor. Au/Cx5S/MCE was shown to have good sensitivity within a cocaine detection range of 0.1-20 μM. Moreover, MCE was shown to improve the sensitivity of the aptasensor greatly. Even without the help of amplification or labeling, cocaine concentrations as low as 100 nM could be easily detected by the impedimetric aptasensor developed. The specificity and regeneration of the cocaine aptasensor were also investigated and satisfactory results were obtained. The developed aptasensor was successfully applied to detect the cocaine in biological fluids.
Source: Talanta, Available online 2 February 2012
De-Wen Zhang, Fang-Ting Zhang, Yi-Ran Cui, Qin-Pei Deng, Steffi Krause, ...
A simple and label-free aptasensor for sensitive and specific detection of cocaine was developed by measuring the change in electrochemical impedance spectra (EIS), based on the formation of a supramolecular aptamer fragments/substrate complex. An anticocaine aptamer was divided into two fragments, Cx and Cy. Three different sensing interfaces, called Au/Cx5S/MCE, Au/Cy3S/MCE and Au/Cy5S/MCE, were fabricated by immobilizing Cx or Cy on a gold electrode through modifying their 5′ or 3′ end with a thiolated group followed by the treatment with mercaptoethanol (MCE). The formation of the corresponding supramolecular aptamer fragments/cocaine complex was investigated via monitoring electrochemical impedance spectra in the presence of [Fe(CN)6]. The interfacial electron transfer resistance (Ret) was found to depend strongly on the cocaine concentration. Since the supramolecular aptamer fragments/cocaine complex was formed on the electrode surface, the sensing interface strongly affected the sensitivity of the aptasensor. Au/Cx5S/MCE was shown to have good sensitivity within a cocaine detection range of 0.1-20 μM. Moreover, MCE was shown to improve the sensitivity of the aptasensor greatly. Even without the help of amplification or labeling, cocaine concentrations as low as 100 nM could be easily detected by the impedimetric aptasensor developed. The specificity and regeneration of the cocaine aptasensor were also investigated and satisfactory results were obtained. The developed aptasensor was successfully applied to detect the cocaine in biological fluids.
Highlights
► A simple label-free aptasensor was developed by electrochemical impedance spectra. ► For the optimization, we designed and compared three different sensing interfaces. ► The sensor could detect as low as 100 nM cocaine without amplification or labeling. ► The aptasensor showed the potential application in biological fluid.A single procedure for the accurate and precise quantification of the rare earth elements, Sc, Y, Th and Pb in dust and peat for provenance tracing in climate and pollution studies
03 February 2012, 23:22:38
Publication year: 2012
Source: Talanta, Available online 2 February 2012
Marion Ferrat, Dominik J. Weiss, Stanislav Strekopytov
The geochemical provenancing of atmospheric dust deposited in terrestrial archives such as peat bogs using trace elements is central to the study of atmospheric deposition over the continents and at the heart of many climate and pollution studies. The use of a single digestion method on all sample types involved in such a study (dust archive and sources) minimizes the contribution of the total analytical error when comparing sample compositions and attributing a source to the deposited dust. To date, this factor is limiting progress in geographical areas where the compositional variations between the sources and within the archive are small. Here, seven microwave and hot plate digestion methods were tested on rock, soil and plant reference materials to establish a unique method optimizing precision and accuracy in all sample types. The best results were obtained with a hot plate closed-vessel digestion with 2 ml HF and 0.5 ml HNO3for 0.1 g of sample, which allowed the precise, accurate and low blank quantification of the trace elements La-Yb, Sc, Y, Th and Pb by ICP-MS. This method was tested in a climate study in central Asia and temporal changes in the dominant dust source were for the first time successfully linked to changes in atmospheric circulation patterns above this region.
Source: Talanta, Available online 2 February 2012
Marion Ferrat, Dominik J. Weiss, Stanislav Strekopytov
The geochemical provenancing of atmospheric dust deposited in terrestrial archives such as peat bogs using trace elements is central to the study of atmospheric deposition over the continents and at the heart of many climate and pollution studies. The use of a single digestion method on all sample types involved in such a study (dust archive and sources) minimizes the contribution of the total analytical error when comparing sample compositions and attributing a source to the deposited dust. To date, this factor is limiting progress in geographical areas where the compositional variations between the sources and within the archive are small. Here, seven microwave and hot plate digestion methods were tested on rock, soil and plant reference materials to establish a unique method optimizing precision and accuracy in all sample types. The best results were obtained with a hot plate closed-vessel digestion with 2 ml HF and 0.5 ml HNO3for 0.1 g of sample, which allowed the precise, accurate and low blank quantification of the trace elements La-Yb, Sc, Y, Th and Pb by ICP-MS. This method was tested in a climate study in central Asia and temporal changes in the dominant dust source were for the first time successfully linked to changes in atmospheric circulation patterns above this region.
New approaches to extraction techniques in determination of 4,4′-methylenebis(2-chloroaniline) in air and water solutions
03 February 2012, 23:22:38
Publication year: 2012
Source: Talanta, Available online 2 February 2012
Bogusław Buszewski, Paweł Olszowy, Małgorzata Szultka, Anna Jeżewska
Extraction techniques for 4,4′-methylenebis(2-chloroaniline) (MOCA) in air samples and water solutions were developed and compared. Classic techniques for air sampling of MOCA were enhanced by incorporating a derivatization step (3,5-dinitrobenzoyl chloride solution in toluene), thus increasing the limit of detection and limit of quantification. Sampling of MOCA from water solution was performed using novel nanoporous polymeric (polypyrrole and polythiophene) fiber coatings and solid phase microextraction. Samples were analysed by high-performance liquid chromatography coupled with a UV detector. Using the modified method for air sampling of MOCA, we found that the limit of detection was 7.90 ng·mand the limit of quantification was 23.8 ng·m. In contrast, the limit of detection for MOCA in water samples was 11.26 ng·mL(polypyrrole) and 84.62 ng·mL(polythiophene) and the limit of quantification for MOCA was from 33.78 (polypyrrole) and 253.86 ng·mL(polythiophene). Correlation coefficients were 0.9997 for air and 0.8790-0.9852 for water samples, respectively. The techniques presented provide alternative methods for the determination of MOCA in air samples and in water solutions that are more sensitive, quicker and less expensive than previously established procedures.
Source: Talanta, Available online 2 February 2012
Bogusław Buszewski, Paweł Olszowy, Małgorzata Szultka, Anna Jeżewska
Extraction techniques for 4,4′-methylenebis(2-chloroaniline) (MOCA) in air samples and water solutions were developed and compared. Classic techniques for air sampling of MOCA were enhanced by incorporating a derivatization step (3,5-dinitrobenzoyl chloride solution in toluene), thus increasing the limit of detection and limit of quantification. Sampling of MOCA from water solution was performed using novel nanoporous polymeric (polypyrrole and polythiophene) fiber coatings and solid phase microextraction. Samples were analysed by high-performance liquid chromatography coupled with a UV detector. Using the modified method for air sampling of MOCA, we found that the limit of detection was 7.90 ng·mand the limit of quantification was 23.8 ng·m. In contrast, the limit of detection for MOCA in water samples was 11.26 ng·mL(polypyrrole) and 84.62 ng·mL(polythiophene) and the limit of quantification for MOCA was from 33.78 (polypyrrole) and 253.86 ng·mL(polythiophene). Correlation coefficients were 0.9997 for air and 0.8790-0.9852 for water samples, respectively. The techniques presented provide alternative methods for the determination of MOCA in air samples and in water solutions that are more sensitive, quicker and less expensive than previously established procedures.
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