Rapid and direct determination of glyphosate,glufosinate, and aminophosphonic acid by online preconcentration CE with contactless conductivity detection

Rapid and direct online preconcentration followed by CE with capacitively coupled contactless conductivity detection (CE‐C⁴D) is evaluated as a new approach for the determination of glyphosate, glufosinate (GLUF), and aminophosphonic acid (AMPA) in drinking water. Two online preconcentration techniques, namely large volume sample stacking without polarity switching and field‐enhanced sample injection, coupled with CE‐C⁴D were successfully developed and optimized. Under optimized conditions, LODs in the range of 0.01–0.1 μM (1.7–11.1 μg/L) and sensitivity enhancements of 48‐ to 53‐fold were achieved with the large volume sample stacking‐CE‐C⁴D method. By performing the field‐enhanced sample injection‐CE‐C⁴D procedure, excellent LODs down to 0.0005–0.02 μM (0.1–2.2 μg/L) as well as sensitivity enhancements of up to 245‐ to 1002‐fold were obtained. Both techniques showed satisfactory reproducibility with RSDs of peak height of better than 10%. The newly established approaches were successfully applied to the analysis of glyphosate, glufosinate, and aminophosphonic acid in spiked tap drinking water.     

Validated TLC-densitometry method for the simultaneous analysis of pyrethroid insecticides in agricultural and domestic products

ABSTRACT: BACKGROUND: Pyrethroids are widely used for the control of pests and insects, as pyrethroids are believed to pose very little risk to human health and environment. However, exposure to the pyrethroids exceeding the label directions might adversely affect human health and environment. Hence a careful selection of environment friendly household product is required that must contain exactly the label claimed pyrethroids amount. RESULTS: A sensitive and robust TLC-densitometric method for simultaneous quantification of commonly used synthetic pyrethroids including esbiothrin, alpha-cypermethrin and cis/trans permethrin in agricultural and domestic products has been developed and validated. TLC aluminum plates, precoated with 0.2 mm thick layer of silica gel 60 F-254, were used for chromatographic process. Densitometric analysis of chromatoplates was carried out in absorbance mode at corresponding lamdamax of each pyrethroid. Equally valid common mobile phase for all pyrethroids consisted of hexane-dichloromethane-ethylacetate-formic acid (8:1.5:0.4:0.1 v/v/v/v) which provided sharp and symmetrical peaks of esbiothrin, alpha-cypermethrin, trans-permethrin and cis-permethrin, at Rf 0.31, 0.53, 0.6 and 0.65, respectively. Linear regression data for respective calibration curves showed a good linearity for all pyrethroids with r = 0.991-0.996. Limits of detection (LOD) and limits of quantification (LOQ) for all pyrethroids were found in the range of 1.6-2.8 and 4.9-8.5 ng/spot, respectively. CONCLUSIONS: The developed method is applicable for separating the mixture of pyrethroids and at the same time, it is also valid for separating their isomers. The method is reproducible, precise and accurate for the quantitative determination of pyrethroids in agricultural and domestic products.     

Synthesis,physicochemical characterization and biological activity of nano complexes of iron(III) of 3(2'‐hydroxyphenyl)‐5‐(4′‐substituted phenyl) pyrazolines and aspartic acid

Mixed ligand complexes of Iron(III) with aspartic acid and 3(2′‐hydroxy phenyl)‐5‐(4′‐substituted phenyl) pyrazolines of type [Fe(C₄O₄NH₆)₂(C₁₅H₁₂N₂OX)] and [Fe(C₄O₄NH₆)(C₁₅H₁₂N₂OX)₂], where (C₄O₄NH₆) = aspartate, (C₁₅H₁₂N₂OX) = deprotonated 3(2′‐hydroxyphenyl)‐5‐(4′‐substituted phenyl) pyrazolines (X = H, CH₃, OCH₃, Cl), have been synthesized. These newly synthesized derivatives have been physicochemically characterized by elemental analysis (C, H, N, Cl and Fe), magnetic moment data, thermogravimetric analysis, molar conductance, cyclic voltammetry, spectral analysis (UV–visible, IR, far IR and fast atom bombardment mass spectrometry). Scanning electron microscopy, transmission electron microscopy and X‐ray powder diffraction studies have been carried out for powdered samples, which show nanometric particles of these derivatives. Antibacterial and antifungal potential of free pyrazoline and some iron(III) complexes have been evaluated. Copyright © 2012 John Wiley & Sons, Ltd.     

Artificial neural network‐based modeling of snow properties using field data and hyperspectral imagery

This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region. Recommendations for resource managers

• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.

     

Offline estimation of 2D crystal lattice parameters by processing the electron diffraction image

Electron diffraction provides useful information about the internal composition of materials and has been in the use of material scientists for more than fifty years. In order to extract useful information from offline diffraction images, they are manually analyzed by using some photometric technique. Manual analysis is however a cumbersome, laborious and difficult task. To reduce the labors of material scientists one can employ image processing techniques to perform automated analysis, due to the well established popularity and clear evidence of widely used image processing techniques. In this work an image processing technique is being proposed for the extraction of 2D unit cell information from diffraction images on one hand and finding the 2D point group contained by the lattices on the other. The technique employs a morphological shrinking operation to find the center of each spot in the underlying preprocessed diffraction image. This is followed by the extraction of eight points with reference to the spot produced by the transmitted electron beam. The resultant nine points, i.e. the extracted eight plus the reference spot generated by the transmitted electron beam, are then subjected to symmetry operations, rotation symmetry and mirror symmetry, in polar coordinate system, to classify the point group of the lattice produced by the electron diffraction. One of the difficult task, even in manual analysis, is to ascertain the exact spot where the transmitted electron beam hit the sample at the time of realization of the image. This has been accurately and intuitively done by employing the notion that the transmitted spot must have greater number of pixels, with the highest gray value, among the diffracted spots. The proposed strategy has been applied to a sample set of various images and the results shows that the technique is efficient in determining the unit cell in 2D and classify the point group with good accuracy.     

SYNTHESIS AND CHARACTERIzATION OF TRIPHENYLANTIMONY (V) (O-ALKYL,O-CYCLOALKYL AND O-ARYLTRITHIOPHOSPHATES)

Triphenylantimony (V) (O-alkyl,O-cycloalkyl and O-aryltrithiophosphates) of the type Ph ₃ Sb[S ₂ (S)P(OR)] (R = Me, Et, Pr ⁿ , Pr ⁱ , Bu ⁿ , Bu ^s , Bu ⁱ , Am ⁱ , Ph and C.h. = cyclohexyl) have been synthesized for the first time by the reaction of triphenylantimony (V) dibromide with potassium trithiophosphates in 1:1 molar ratio in methanol. These new compounds have been characterized by elemental analysis, molecular weight determinations, and spectroscopic (IR,¹³C and ³¹P NMR) studies. On the basis of these data trigonal bipyramidal geometry has been proposed for these compounds.     

A simple microextraction and preconcentration approach based on a mixed matrix membrane

A simple adsorption/desorption procedure using a mixed matrix membrane (MMM) as extraction medium is demonstrated as a new miniaturized sample pretreatment and preconcentration technique. Reversed-phase particles namely polymeric bonded octadecyl (C₁₈) was incorporated through dispersion in a cellulose triacetate (CTA) polymer matrix to form a C₁₈-MMM. Non-steroidal anti-inflammatory drugs (NSAIDs) namely diclofenac, mefenamic acid and ibuprofen present in the environmental water samples were selected as targeted model analytes. The extraction setup is simple by dipping a small piece of C₁₈-MMM (7 mm × 7 mm) in a stirred 10 mL sample solution for analyte adsorption process. The entrapped analyte within the membrane was then desorbed into 100 μL of methanol by ultrasonication prior to high performance liquid chromatography (HPLC) analysis. Each membrane was discarded after single use to avoid any analyte carry-over effect. Several important parameters, such as effect of sample pH, salting-out effect, sample volume, extraction time, desorption solvent and desorption time were comprehensively optimized. The C₁₈-MMM demonstrated high affinity for NSAIDs spiked in tap and river water with relative recoveries ranging from 92 to 100% and good reproducibility with relative standard deviations between 1.1 and 5.5% (n = 9). The overall results obtained were found comparable against conventional solid phase extraction (SPE) using cartridge packed with identical C₁₈ adsorbent.     

Comparison of HPLC and MEEKC for Miconazole Nitrate Determination in Pharmaceutical Formulation

A simple solid phase extraction (SPE) method coupled with high performance liquid chromatography (HPLC) using UV detector and microemulsion electrokinetic chromatography (MEEKC) has been developed and compared for the quantitative determination of miconazole nitrate in pharmaceutical formulation. For HPLC method, two parameters were optimized, namely, the wavelength and the mobile phases. The optimized condition was at the 225 nm wavelength and the mobile phase of ACN:MeOH (90:10 v/v). There are seven MEEKC parameters that were optimized, in this research, which were applied to voltage, temperature, wavelength, sodium dodecyl sulfate (SDS) concentration, buffer pH, buffer concentration and butan-1-ol concentration. The optimum MEEKC condition was obtained using 86.35 % (w/w) 2.5 mM borate buffer pH 9, 0.25 % (w/w) SDS, 0.8 % (w/w) ethyl acetate, 6.6 % w/w butan-1-ol and 6.0 % (w/w) acetonitrile. The combination of SPE using a diol column with HPLC–UV and the MEEKC methods were successfully applied for the determination of miconazole nitrate in a pharmaceutical formulation with the recovery percentage of 98.35 and 92.50 %, respectively.     

Ethylene Glycol as New Mobile Phase for Resolution of Two-Component Mixture of Cationic Surfactants on Alumina Surface

Aqueous ethylene glycol (ethane 1,2 diol) as a green mobile phase has been used for thin layer chromatographic (TLC) studies of cationic surfactants on alumina layers. Nineteen solvent systems were used to examine the mobility of the surfactants and to discover the best TLC system for the selective separation of dodecyl trimethylammonium bromide (DTAB) from multi-component mixture of other surfactants. Among the TLC systems studied, M₃ (ethylene glycol: water, 8:2) was best for achieving the selective separation of DTAB from multi-component mixture of other surfactants because in this mobile phase mobility of all surfactants except DTAB were insignificant. Effect of organic additives in aqueous ethylene glycol mobile phase on the mobility of surfactants was examined. The results obtained on laboratory made alumina TLC plates and commercially available precoated alumina HPTLC plates were compared. The lower limits of detection of DTAB, CPC, CTAB, HDTAC, and TTAB were 0.02, 0.05, 0.04, 0.06, or 0.08 µg per zone respectively. The resolution of mixture of cationic surfactants was also examined in the presence metal cations as an impurity in the analyzed sample.     

Ultra Moisturizing Anti-Wrinkle Lotion Enriched with Tocotrienols

A stable palm-based anti-wrinkle lotion enriched with tocotrienols was successfully prepared. The stability of the product was due to the presence of liquid crystalline structure in the emulsion system. It helps in bringing the active to the dermis layer. Functionality active ingredients such as tocotrienols and anti-wrinkle were added in the formulation. A commercial plant extract was used to strengthen the collagen seated at the dermis layer. The product was formulated to pH 5.5 which is suitable for the skin. The mean droplet size is 10.2 µm with a monomodal distribution pattern which prevents agglomeration. This will decrease Brownian motion, thus prolonging its stability. Long-term acute moisturizing tests show a significant increase of between 24% and 17% hydration for five and six weeks respectively. The efficacy testing on 12 subjects confirmed a reduction in natural fine wrinkles on faces during aging or premature aging at ?7.6%.