996 resultados para Resurrection Plant
Resumo:
Quantitative analysis by mass spectrometry (MS) is a major challenge in proteomics as the correlation between analyte concentration and signal intensity is often poor due to varying ionisation efficiencies in the presence of molecular competitors. However, relative quantitation methods that utilise differential stable isotope labelling and mass spectrometric detection are available. Many drawbacks inherent to chemical labelling methods (ICAT, iTRAQ) can be overcome by metabolic labelling with amino acids containing stable isotopes (e.g. 13C and/or 15N) in methods such as Stable Isotope Labelling with Amino acids in Cell culture (SILAC). SILAC has also been used for labelling of proteins in plant cell cultures (1) but is not suitable for whole plant labelling. Plants are usually autotrophic (fixing carbon from atmospheric CO2) and, thus, labelling with carbon isotopes becomes impractical. In addition, SILAC is expensive. Recently, Arabidopsis cell cultures were labelled with 15N in a medium containing nitrate as sole nitrogen source. This was shown to be suitable for quantifying proteins and nitrogen-containing metabolites from this cell culture (2,3). Labelling whole plants, however, offers the advantage of studying quantitatively the response to stimulation or disease of a whole multicellular organism or multi-organism systems at the molecular level. Furthermore, plant metabolism enables the use of inexpensive labelling media without introducing additional stress to the organism. And finally, hydroponics is ideal to undertake metabolic labelling under extremely well-controlled conditions. We demonstrate the suitability of metabolic 15N hydroponic isotope labelling of entire plants (HILEP) for relative quantitative proteomic analysis by mass spectrometry. To evaluate this methodology, Arabidopsis plants were grown hydroponically in 14N and 15N media and subjected to oxidative stress.
Resumo:
Rate coefficients for reactions of nitrate radicals (NO3) with the anthropogenic emissions 2-methylpent-2-ene, (Z)-3-methylpent-2-ene.. ethyl vinyl ether, and the stress-induced plant emission ethyl vinyl ketone (pent-1-en-3-one) were determined to be (9.3 +/- 1.1) x 10(-12), (9.3 +/- 3.2) x 10(-12), (1.7 +/- 1.3) x 10(-12) and (9.4 + 2.7) x 10(-17) cm(3) molecule(-1) s(-1). We performed kinetic experiments at room temperature and atmospheric pressure using a relative-rate technique with GC-FID analysis. Experiments with ethyl vinyl ether required a modification of our established procedure that might introduce additional uncertainties, and the errors suggested reflect these difficulties. Rate coefficients are discussed in terms of electronic and steric influences. Atmospheric lifetimes with respect to important oxidants in the troposphere were calculated. NO3-initiated oxidation is found to be the strongly dominating degradation route for 2-methylpent-2-ene, (Z)-3-methylpent-2-ene and ethyl vinyl ether. Atmospheric concentrations of the alkenes and their relative contribution to the total NMHC emissions from trucks can be expected to increase if plans for the introduction of particle filters for diesel engines are implemented on a global scale. Thus more kinetic data are required to better evaluate the impact of these emissions.
Resumo:
Artificial diet studies were used to differentiate among physical and chemical mechanisms affecting the suitability to diamondback moth (Plutella xylostella L.), of 16 food substrates obtained by growing four different brassicas in the glasshouse or field and measuring the pest's performance on either leaf discs or a diet incorporating leaf powders. Leaves of Chinese cabbage and the cabbage cultivar 'Minicole' were, respectively, the most and least suitable leaves for the insect, but this ranking was reversed on artificial diet. Leaves of glasshouse-grown plants were more suitable than those of plants grown in the fields. Differences in the suitability of leaves to diamondback moth appeared to be largely determined by leaf toughness and surface wax load. Concentrations of individual glucosinolates in the brassicas probably acted as phagostimulants, so increasing their intrinsic susceptibility to diamondback moth, but the effect of the physical factors appeared more important.
Resumo:
The night-time tropospheric chemistry of two stress-induced volatile organic compounds (VOCs), (Z)-pent-2-en-1-ol and pent-1-en-3-ol, has been studied at room temperature. Rate coefficients for reactions of the nitrate radical (NO3) with these pentenols were measured using the discharge-flow technique. Because of the relatively low volatility of these compounds, we employed off-axis continuous-wave cavity-enhanced absorption spectroscopy for detection of NO3 in order to be able to work in pseudo first-order conditions with the pentenols in large excess over NO3. The rate coefficients were determined to be (1.53 +/- 0.23) x 10(-13) and (1.39 +/- 0.19) x 10(-14) cm(3) molecule(-1) s(-1) for reactions of NO3 with (Z)-pent-2-en-1-ol and pent-1-en-3-ol. An attempt to study the kinetics of these reactions with a relative-rate technique, using N2O5 as source of NO3 resulted in significantly higher apparent rate coefficients. Performing relative-rate experiments in known excesses of NO2 allowed us to determine the rate coefficients for the N2O5 reactions to be (5.0 +/- 2.8) x 10(-19) cm(3) molecule(-1) s(-1) for (Z)-pent-2-en-1-ol, and (9.1 +/- 5.8) x 10(-19) cm(3) molecule(-1) s(-1) for pent-1-en-3-ol. We show that these relatively slow reactions can indeed interfere with rate determinations in conventional relative-rate experiments.
Resumo:
A nonlinear regression structure comprising a wavelet network and a linear term is proposed for system identification. The theoretical foundation of the approach is laid by proving that radial wavelets are orthogonal to linear functions. A constructive procedure for building such models is described and the approach is tested with experimental data.
Resumo:
The reuse of treated wastewater (reclaimed water) is particularly well suited for irrigated agriculture as it often contains significant quantities of plant essential nutrients. This work has shown that reclaimed water in Jordan can have adequate concentrations of potassium, phosphate, sulphate and magnesium to meet all or part of the crop’s requirements. To fully benefit from these inputs farmers must have an awareness of the water quality and reduce the application of chemical fertilisers accordingly. Interviews with farmers have shown that 75 per cent of farmers indirectly using reclaimed water are aware of the nutrients. Farmers’ decision making as to the application of chemical fertilisers appears to be influenced by a range of factors which include the type of crops being cultivated, the provision of training on nutrient management and the availability of information on the nutrient content of the reclaimed water.
Resumo:
Geographic distributions of pathogens are the outcome of dynamic processes involving host availability, susceptibility and abundance, suitability of climate conditions, and historical contingency including evolutionary change. Distributions have changed fast and are changing fast in response to many factors, including climatic change. The response time of arable agriculture is intrinsically fast, but perennial crops and especially forests are unlikely to adapt easily. Predictions of many of the variables needed to predict changes in pathogen range are still rather uncertain, and their effects will be profoundly modified by changes elsewhere in the agricultural system, including both economic changes affecting growing systems and hosts and evolutionary changes in pathogens and hosts. Tools to predict changes based on environmental correlations depend on good primary data, which is often absent, and need to be checked against the historical record, which remains very poor for almost all pathogens. We argue that at present the uncertainty in predictions of change is so great that the important adaptive response is to monitor changes and to retain the capacity to innovate, both by access to economic capital with reasonably long-term rates of return and by retaining wide scientific expertise, including currently less fashionable specialisms.
Resumo:
The soil−air−plant pathway is potentially important in the vegetative accumulation of organic pollutants from contaminated soils. While a number of qualitative frameworks exist for the prediction of plant accumulation of organic chemicals by this pathway, there are few quantitative models that incorporate this pathway. The aim of the present study was to produce a model that included this pathway and could quantify its contribution to the total plant contamination for a range of organic pollutants. A new model was developed from three submodels for the processes controlling plant contamination via this pathway: aerial deposition, soil volatilization, and systemic translocation. Using the combined model, the soil−air−plant pathway was predicted to account for a significant proportion of the total shoot contamination for those compounds with log KOA > 9 and log KAW < −3. For those pollutants with log KOA < 9 and log KAW > −3 there was a higher deposition of pollutant via the soil−air−plant pathway than for those chemicals with log KOA > 9 and log KAW < −3, but this was an insignificant proportion of the total shoot contamination because of the higher mobility of these compounds via the soil−root−shoot pathway. The incorporation of the soil−air−plant pathway into the plant uptake model did not significantly improve the prediction of the contamination of vegetation from polluted soils when compared across a range of studies. This was a result of the high variability between the experimental studies where the bioconcentration factors varied by 2 orders of magnitude at an equivalent log KOA. One potential reason for this is the background air concentration of the pollutants under study. It was found background air concentrations would dominate those from soil volatilization in many situations unless there was a soil hot spot of contamination, i.e., >100 mg kg−1.