Electrochemical Production of Ferrate (Iron VI): Application to the Wastewater Treatment on a Laboratory Scale and Comparison with Iron (III) Coagulant

This paper presents a comparative study of the performance of ferrate(VI), FeO ₄ ^2? , and ferric, Fe(III), towards wastewater treatment. The ferrate(VI) was produced by electrochemical synthesis, using steel electrodes in a 16 M NaOH solution. Domestic wastewater collected from Hailsham North Wastewater Treatment Works was treated with ferrate(VI) and ferric sulphate (Fe(III)). Samples were analysed for suspended solids, chemical oxygen demand (COD), biochemical oxygen demand (BOD) and P removal. Results for low doses of Fe(VI) were validated via a reproducibility study. Removal of phosphorous reached 40% with a Fe(VI) dose as low as 0.01 mg/L compared to 25% removal with 10 mg/L of Fe(III). For lower doses (<1 mg/L as Fe), Fe(VI) can achieve between 60% and 80% removals of SS and COD, but Fe(III) performed even not as well as the control sample where no iron chemical was dosed. The ferrate solution was found to be stable for a maximum of 50 min, beyond which Fe(VI) is reduced to less oxidant species. This provided the maximum allowed storage time of the electrochemically produced ferrate(VI) solution. Results demonstrated that low addition of ferrate(VI) leads to good removal of P, BOD, COD and suspended solids from wastewater compared to ferric addition and further studies could bring an optimisation of the dosage and treatment.     

Efficiency of some molecular markers linked to rhizomania resistance gene (Rz 1 ) for marker assisted selection in sugar beet

Sugar beet (Beta vulgaris L.) is one of the two major products supplying sugar (sucroses) in the world. Rhizomania is one of the most destructive diseases of sugar beet world-wide. Holly is the major source of resistance to rhizomania. The objectives of this study were to identify the dominant homozygous genotypes resistant to rhizomania using ZN1 molecular marker, to field evaluate S₁ progenies of plants already proved to be containing the marker and also to determine the relationship of this and other SCAR (sequence characterized amplified region) markers with SNP1 (single nucleotide polymorphism) marker associated with the Rz ₁ gene. Molecular analysis was carried out on 27 O-type populations (consisting of 13 susceptible and 6 resistant genotypes). Field evaluation and scoring of the phenotypic traits including greenness, growth, uniformity and disease score of 12 O-type populations were carried out on a rhizomania-infested field. The percent agreement of coupling marker ZN1 and repulsion marker ZN8 with disease score was 0.91 and 0.93, respectively. Although all O-types had the Rz ₁ resistance gene but the phenotypic differences were observed due to the effect of different genetic backgrounds and modifier genes. Overall, the results showed that the selected markers can be used for marker-assisted selection (MAS) to reduce the time and cost of breeding programs and increase the efficiency of selection.     

Aging of whiskey increases the potentiation of GABA(A) receptor response

It is known that the target of most mood-defining compounds such as ethanol is an ionotropic gamma-aminobutyric acid receptor (GABA(A) receptor). The potentiation of the response of these inhibitory neurotransmitter receptors induces anxiolytic, sedative, and anesthetic activities in the human brain. Because both extracts of whiskey by pentane and fragrant components in whiskey potentiate the GABA(A) receptor-mediated response, GABA(A) receptors were expressed in Xenopus oocyte by injecting cRNAs prepared from the cloned cDNA for the alpha(1) and beta(1) subunits of the bovine receptors in order to study the effects of whiskey itself on the GABA(A) receptor-mediated response. Whiskey itself also potentiated the electrical responses of GABA(A) receptors generally more than ethanol at the same concentration as that of the whiskey. The potentiation of the GABA(A) receptor-mediated response increased with the aging period of the whiskey. Inhalation of whiskey to mice increased the sleeping time induced by pentobarbital more than that of the same concentration of ethanol as the whiskey. These results suggest that not only ethanol but also minor components in whiskey play an important role in the potentiation of GABA(A) receptor-mediated response and possibly the sedative effect of whiskey. Although the minor components are present in extremely small quantities compared with ethanol in alcoholic beverages, they may modulate the mood or consciousness of humans through the potentiation of the GABA(A) receptor response after absorption into the brain, because these hydrophobic compounds are easily absorbed into the brain across the blood-brain barrier and are several thousands times as potent as ethanol in the potentiation of the GABA(A) receptor-mediated response.     

Effects of coffee components on the response of GABA(A) receptors expressed in Xenopus oocytes

The effects of both coffee components and coffee extract on the electrical responses of GABA(A) receptors expressed in Xenopus oocytes were studied by injecting cRNAs of the alpha(1) and beta(1) subunits of the bovine receptors. The aqueous extract of coffee dose-dependently inhibited the GABA-elicited responses, whereas the lipophilic extract of coffee by diethyl ether slightly potentiated it at low doses (0.1-0.4 microL/mL) but showed inhibition at high doses (0.5-0.8 microL/mL). Theophylline inhibited the response in a noncompetitive mechanism (K(i) = 0.55 mM), whereas theobromine and trigonelline hydrochloride inhibited it in a competitive manner, K(i) = 3.8 and 13 mM, respectively. Benzothiazole, catechol, 2,4-dimethylstyrene, guaiacol, 1-octen-3-ol, sotolone, and 2,3,5-trimethylphenol potentiated the responses significantly. Potentiation elicited by guaiacol and sotolone was independent of GABA concentrations, whereas that by 1-octen-3-ol was dependent. When 1-octen-3-ol (100 mg/kg) was orally administered to mice prior to intraperitoneal administration of pentobarbital, the sleeping time of mice induced by pentobarbital increased significantly.     

Proton toxicity interferes with the screening of common bean (Phaseolus vulgaris L.) genotypes for aluminium resistance in nutrient solution

Common bean (Phaseolus vulgaris L.) proved to be very sensitive of low pH (4.3), with large genotypic differences in proton sensitivity. Therefore, proton toxicity did not allow the screening of common bean genotypes for aluminium (Al) resistance using the established protocol for maize (0.5 mM CaCl₂, 8 μM H₃BO₃, pH 4.3). Increasing the pH to 4.5, the Ca²⁺ concentration to 5 mM, and addition of 0.5 mM KCl fully prevented proton toxicity in 28 tested genotypes and allowed to identify differences in Al resistance using the inhibition of root elongation by 20 μM Al supply for 36 h as parameter of Al injury. As in maize, Al treatment induced callose formation in root apices of common bean. Aluminium‐induced callose formation well reflected the effect of Ca supply on Al sensitivity as revealed by root‐growth inhibition. Aluminum‐induced callose formation in root apices of 28 bean genotypes differing in Al resistance after 36 h Al treatment was positively correlated to Al‐induced inhibition of root elongation and Al contents in the root apices. However, the relationship was less close than previously reported for maize. Also, after 12 h Al treatment, callose formation and Al contents in root apices did not reflect differences in Al resistance between two contrasting genotypes, indicating a different mode of the expression of Al toxicity and regulation of Al resistance in common bean than in maize.     

Nitrogen fertilizer–induced mineralization of soil organic C and N in six contrasting soils of Bangladesh

A 90‐day laboratory incubation study was carried out using six contrasting subtropical soils (calcareous, peat, saline, noncalcareous, terrace, and acid sulfate) from Bangladesh. A control treatment without nitrogen (N) application was compared with treatments where urea, ammonium sulfate (AS), and ammonium nitrate (AN) were applied at a rate of 100 mg N (kg soil)^–1. To study the effect of N fertilizers on soil carbon (C) turnover, the CO₂‐C flux was determined at nine sampling dates during the incubation, and the total loss of soil carbon (TC) was calculated. Nitrogen turnover was characterized by measuring net nitrogen mineralization (NNM) and net nitrification (NN). Simple and stepwise multiple regressions were calculated between CO₂‐C flux, TC, NNM, and NN on the one hand and selected soil properties (organic C, total N, C : N ratio, CEC, pH, clay and sand content) on the other hand. In general, CO₂‐C fluxes were clearly higher during the first 2 weeks of the incubation compared to the later phases. Soils with high pH and/or indigenous C displayed the highest CO₂‐C flux. However, soils having low C levels (i.e., calcareous and terrace soils) displayed a large relative TC loss (up to 22.3%) and the added N–induced TC loss from these soils reached a maximum of 10.6%. Loss of TC differed depending on the N treatments (urea > AS > AN >> control). Significantly higher NNM was found in the acidic soils (terrace and acid sulfate). On average, NNM after urea application was higher than for AS and AN (80.3 vs. 71.9 and 70.9 N (kg soil)^–1, respectively). However, specific interactions between N‐fertilizer form and soil type have to be taken into consideration. High pH soils displayed larger NN (75.9–98.1 mg N (kg soil)^–1) than low pH soils. Averaged over the six soils, NN after application of urea and AS (83.3 and 82.2 mg N (kg soil)^–1, respectively) was significantly higher than after application of AN (60.6 mg N (kg soil)^–1). Significant relationships were found between total CO₂ flux and certain soil properties (organic C, total N, CEC, clay and sand content). The most important soil property for NNM as well as NN was soil pH, showing a correlation coefficient of –0.33** and 0.45***, respectively. The results indicate that application of urea to acidic soils and AS to high‐pH soils could be an effective measure to improve the availability of added N for crop uptake.     

Effects of vermicompost and salinity stress on growth and physiological traits of Medicago rigidula L.

The use of vermicompost as a biological fertilizer under salinity stress conditions was tested in this research. Accordingly, the seeds of Medicago rigidula were grown in the greenhouse. The experiment was performed based on factorial arrangement in a completely randomized design using 5 replications. Application rates of vermicompost were 0, 10, 20 and 30%. Salinity stress was conducted in three levels (0, 50 and 100 mM sodium chloride (NaCl)). The highest and the lowest values of the plant survival capacity (%), shoot dry weight (g), leaf relative water content (LRWC) (%), total chlorophyll content (%), leaf area (cm²), total nitrogen content (TNC) (%) and potassium (K) content (%) of the plant tissues were found in VC4 × SL1 and VC1 × SL3 treatments, respectively. Whereas, the maximum and minimum values of root dry weight and root:shoot ratio were seen in VC1 × SL3 and VC4 × SL1 treatments, respectively.     

Characterization of char from the pyrolysis of tobacco

Pyrolysis of tobacco was studied in oxidative and nonoxidative (inert) environments at atmospheric pressure and temperatures ranging from 150 to 750 degrees C. The objective was to study the effect of pyrolysis conditions on the characteristics of the solid residue, i.e., char. The char was characterized using cross-polarization (13)C nuclear magnetic resonance (CPMAS NMR), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), the Brunauer-Emmett-Teller (BET) surface area, and the elemental composition. The char yield from pyrolysis (i.e., nonoxidative) decreased sharply with an increase in temperature to ca. 22% (dry, ash-free basis) at high temperatures. In oxidative pyrolysis, i.e., in 5% oxygen, the char was completely oxidized above 600 degrees C. The gaseous product from pyrolysis at high temperatures contained a significant concentration of hydrogen. The surface area of the char was low, with a maximum of 8 m(2)/g at 400 degrees C. SEM analysis indicated that pyrolysis of the tobacco led to a gradual accumulation of inorganic crystals on the exposed surfaces, and some constituents also melted, resulting in the formation of vesicles by evolving gas. NMR analysis showed significant changes in pectin and sugar constituents of the tobacco and breaking of glycosidic bonds of cellulose at 300-500 degrees C before the char became predominantly aromatic at high temperatures. FTIR results showed a continuous decrease in the intensity of the OH stretch with temperature and the aromatic character to be at maximum at 550-650 degrees C. The H/C ratio of the char decreased continuously with temperature, while the O/C ratio became constant above 300 degrees C due to the presence of oxides and carbonates in the char. The results are consistent with the analysis of the evolved gases.     

Methods to interpolate soil categorical variables from profile observations: Lessons from Iran

The paper compares semi-automated interpolation methods to produce soil-class maps from profile observations and by using multiple auxiliary predictors such as terrain parameters, remote sensing indices and similar. The Soil Profile Database of Iran, consisting of 4250 profiles, was used to test different soil-class interpolators. The target variables were soil texture classes and World Reference Base soil groups. The predictors were 6 terrain parameters, 11 MODIS EVI images and 17 physiographic regions (polygon map) of Iran. Four techniques were considered: (a) supervised classification using maximum likelihoods; (b) multinominal logistic regression; (c) regression-kriging on memberships; and (d) classification of taxonomic distances. The predictive capabilities were assessed using a control subset of 30% profiles and the kappa statistics as criterion. Supervised classification and multinominal logistic regression can lead to poor results if soil-classes overlap in the feature space, or if the correlation between the soil-classes and predictors is low. The two other methods have better predictive capabilities, although both are computationally more demanding. For both mapping of texture classes and soil types, the best prediction was achieved using regression-kriging of indicators/memberships (κ = 45%, κ = 54%). In all cases kappa was smaller than 60%, which can be explained by the preferential sampling plan, the poor definition of soil-classes and the high variability of soils. Steps to improve interpolation of soil-class data, by taking into account the fuzziness of classes directly on the field are further discussed.