Remote gas detection and quantitative analysis from infrared emission spectra obtained by Fourier transform infrared spectroscopy

Techniques for obtaining quantitative values of the temperatures and concentrations of remote hot gaseous effluents from their measured passive emission spectra have been examined in laboratory experiments. The high sensitivity of the spectrometer in the vicinity of the 2397 cm-1 band head region of CO2 has allowed the gas temperature to be calculated from the relative intensity of the observed rotational lines. The spatial distribution of the CO2 in a methane flame has been reconstructed tomographically using a matrix inversion technique. The spectrometer has been calibrated against a black body source at different temperatures and a self absorption correction has been applied to the data avoiding the need to measure the transmission directly. Reconstruction artifacts have been reduced by applying a smoothing routine to the inversion matrix.

Sensitivity of 21st century stratospheric ozone to greenhouse gas scenarios

To understand how greenhouse gas (GHG) emissions may affect future stratospheric ozone, 21st century projections from four chemistry-climate models are examined for their dependence on six different GHG scenarios. Compared to higher GHG emissions, lower emissions result in smaller increases in tropical upwelling with resultant smaller reductions in ozone in the tropical lower stratosphere and less severe stratospheric cooling with resultant smaller increases in upper stratospheric ozone globally. Increases in reactive nitrogen and hydrogen that lead to additional chemical ozone destruction mainly play a role in scenarios with higher GHG emissions. Differences among the six GHG scenarios are found to be largest over northern midlatitudes (∼20 DU by 2100) and in the Arctic (∼40 DU by 2100) with divergence mainly in the second half of the 21st century. The uncertainty in the return of stratospheric column ozone to 1980 values arising from different GHG scenarios is comparable to or less than the uncertainty that arises from model differences in the larger set of 17 CCMVal-2 SRES A1B simulations. The results suggest that effects of GHG emissions on future stratospheric ozone should be considered in climate change mitigation policy and ozone projections should be assessed under more than a single GHG scenario.

Ensemble yield simulations: crop and climate uncertainties, sensitivity to temperature and genotypic adaptation to climate change

Estimates of the response of crops to climate change rarely quantify the uncertainty inherent in the simulation of both climate and crops. We present a crop simulation ensemble for a location in India, perturbing the response of both crop and climate under both baseline (12 720 simulations) and doubled-CO2 (171720 simulations) climates. Some simulations used parameter values representing genotypic adaptation to mean temperature change. Firstly, observed and simulated yields in the baseline climate were compared. Secondly, the response of yield to changes in mean temperature was examined and compared to that found in the literature. No consistent response to temperature change was found across studies. Thirdly, the relative contribution of uncertainty in crop and climate simulation to the total uncertainty in projected yield changes was examined. In simulations without genotypic adaptation, most of the uncertainty came from the climate model parameters. Comparison with the simulations with genotypic adaptation and with a previous study suggested that the relatively low crop parameter uncertainty derives from the observational constraints on the crop parameters used in this study. Fourthly, the simulations were used, together with an observed dataset and a simple analysis of crop cardinal temperatures and thermal time, to estimate the potential for adaptation using existing cultivars. The results suggest that the germplasm for complete adaptation of groundnut cultivation in western India to a doubled-CO2 environment may not exist. In conjunction with analyses of germplasm and local management

Temperature sensitivity of the low-moisture-content limit to negative seed longevity-moisture content relationships in hermetic storage

Background and Aims The negative logarithmic relationship between orthodox seed longevity and moisture content in hermetic storage is subject to a low-moisture-content limit (m(c)), but is m(c) affected by temperature? Methods Red clover (Trifolium pratense) and alfalfa (Medicago sativa) seeds were stored hermetically at 12 moisture contents (2-15 %) and five temperatures (-20, 30, 40, 50 and 65 degrees C) for up to 14.5 years, and loss in viability was estimated. Key Results Viability did not change during 14.5 years hermetic storage at -20 degrees C with moisture contents from 2.2 to 14.9 % for red clover, or 2.0 to 12.0 % for alfalfa. Negative logarithmic relationships between longevity and moisture contents > m(c) were detected at 30-65 degrees C, with discontinuities at low moisture contents; m(c) varied between 4.0 and 5.4 % (red clover) or 4.2 and 5.5 % (alfalfa), depending upon storage temperature. Within the ranges investigated, a reduction in moisture content below m(c) at any one temperature had no effect on longevity. Estimates of m(c) were greater the cooler the temperature, the relationship (P < 0.01) being curvilinear. Above m(c), the estimates of C-H and C-Q (i.e. the temperature term of the seed viability equation) did not differ (P > 0.10) between species, whereas those of K-E and C-W did (P < 0.001). Conclusions The low-moisture-content limit to negative logarithmic relationships between seed longevity and moisture content in hermetic storage increased the cooler the storage temperature, by approx. 1.5 % over 35 degrees C (4.0-4.2 % at 65 degrees C to 5.4-5.5 % at 30-40 degrees C) in these species. Further reduction in moisture content was not damaging. The variation in m(c) implies greater sensitivity of longevity to temperature above, compared with below, m(c). This was confirmed (P < 0.005).

Influence of vegetation on the local climate and hydrology in the tropics: sensitivity to soil parameters

Land use change with accompanying major modifications to the vegetation cover is widespread in the tropics, due to increasing demands for agricultural land, and may have significant impacts on the climate. This study investigates (1) the influence of vegetation on the local climate in the tropics; (2) how that influence varies from region to region; and (3) how the sensitivity of the local climate to vegetation, and hence land use change, depends on the hydraulic characteristics of the soil. A series of idealised experiments with the Hadley Centre atmospheric model, HadAM3, are described in which the influence of vegetation in the tropics is assessed by comparing the results of integrations with and without tropical vegetation. The sensitivity of the results to the soil characteristics is then explored by repeating the experiments with a differing, but equally valid, description of soil hydraulic parameters. The results have shown that vegetation has a significant moderating effect on the climate throughout the tropics by cooling the surface through enhanced latent heat fluxes. The influence of vegetation is, however, seasonally dependent, with much greater impacts during the dry season when the availability of surface moisture is limited. Furthermore, there are significant regional variations both in terms of the magnitude of the cooling and in the response of the precipitation. Not all regions show a feedback of vegetation on the local precipitation; this result has been related both to vegetation type and to the prevailing meteorological conditions. An important finding has been the sensitivity of the results to the specification of the soil hydraulic parameters. The introduction of more freely draining soils has changed the soil-moisture contents of the control, vegetated system and has reduced, significantly, the climate sensitivity to vegetation and by implication, land use change. Changes to the soil parameters have also had an impact on the soil hydrology and its interaction with vegetation, by altering the partitioning between fast and slow runoff processes. These results raise important questions about the representation of highly heterogeneous soil characteristics in climate models, as well as the potential influence of land use change on the soil characteristics themselves.

Influence-matrix diagnostic of a data assimilation system

The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society

Headspace volatile markers for sensitivity of cocoa (Theobroma cacao L.) somatic embryos to cryopreservation

The mechanisms that reduce the viability of plant somatic embryos following cryopreservation are not known. The objective of the present study was to evaluate the sensitivity of cocoa (Theobroma cacao L.) somatic embryos at different stages of an encapsulation-dehydration protocol using stress-related volatile hydrocarbons as markers of injury and recovery. The plant stress hormone ethylene and volatile hydrocarbons derived from hydroxyl radicals (methane) and lipid peroxidation (ethane) were determined using gas chromatography headspace analysis. Ethylene and methane were the only volatiles detected, with both being produced after each step of the cryogenic protocol. Ethylene production was significantly reduced following exposure to liquid nitrogen, but then increased in parallel with embryo recovery. In contrast, the production of methane was cyclic during recovery, with the first cycle occurring earlier for embryos recovered from liquid nitrogen and desiccation than those recovered from earlier steps in the protocol. These results suggest that loss of somatic embryo viability during cryopreservation may be related to the oxidative status of the tissue, and its capacity to produce ethylene. This study has demonstrated that headspace volatile analysis provides a robust non-destructive analytical approach for assessing the survival and recovery of plant somatic embryos following cryopreservation.

Dynamics of QoI sensitivity in Mycosphaerella fijiensis in Costa Rica during 2000 to 2003

From 1997 onward, the strobilurin fungicide azoxystrobin was widely used in the main banana-production zone in Costa Rica against Mycosphaerella fijiensis var. difformis causing black Sigatoka of banana. By 2000, isolates of M. fijiensis with resistance to the quinolene oxidase inhibitor fungicides were common on some farms in the area. The cause was a single point mutation from glycine to alanine in the fungal target protein, cytochrome b gene. An amplification refractory mutation system Scorpion quantitative polymerase chain reaction assay was developed and used to determine the frequency of G 143A allele in samples of M. fijiensis. Two hierarchical surveys of spatial variability, in 2001 and 2002,found no significant variation in frequency on spatial scales <10 in. This allowed the frequency of G143A alleles on a farm to be estimated efficiently by averaging single samples taken at two fixed locations. The frequency of G 143A allele in bulk samples from I I farms throughout Costa Rica was determined at 2-month intervals. There was no direct relationship between the number of spray applications and the frequency of G143A on individual farms. Instead, the frequency converged toward regional averages, presumably due to the large-scale mixing of ascospores dispersed by wind. Using trap plants in an area remote from the main producing area, immigration of resistant ascospores was detected as far as 6 km away both with and against the prevailing wind.

High-throughput proteomics using matrix-assisted laser desorption/ ionization mass spectrometry

It has become evident that the mystery of life will not be deciphered just by decoding its blueprint, the genetic code. In the life and biomedical sciences, research efforts are now shifting from pure gene analysis to the analysis of all biomolecules involved in the machinery of life. One area of these postgenomic research fields is proteomics. Although proteomics, which basically encompasses the analysis of proteins, is not a new concept, it is far from being a research field that can rely on routine and large-scale analyses. At the time the term proteomics was coined, a gold-rush mentality was created, promising vast and quick riches (i.e., solutions to the immensely complex questions of life and disease). Predictably, the reality has been quite different. The complexity of proteomes and the wide variations in the abundances and chemical properties of their constituents has rendered the use of systematic analytical approaches only partially successful, and biologically meaningful results have been slow to arrive. However, to learn more about how cells and, hence, life works, it is essential to understand the proteins and their complex interactions in their native environment. This is why proteomics will be an important part of the biomedical sciences for the foreseeable future. Therefore, any advances in providing the tools that make protein analysis a more routine and large-scale business, ideally using automated and rapid analytical procedures, are highly sought after. This review will provide some basics, thoughts and ideas on the exploitation of matrix-assisted laser desorption/ ionization in biological mass spectrometry - one of the most commonly used analytical tools in proteomics - for high-throughput analyses.

Sensitivity distributions and cross-resistance patterns of Mycosphaerella graminicola to fluquinconazole, prochloraz and azoxystrobin over a period of nine years

The sensitivity of 73 isolates of Mycosphaerella graminicola collected over the period 1993–2002 from wheat fields in South England was tested in vitro against the triazole fluquinconazole, the strobilurin azoxystrobin and to the imidazole prochloraz. Over the sampling period, sensitivity of the population to fluquinconazole and prochloraz decreased by factors of approximately 10 and 2, respectively, but there was no evidence of changes in sensitivity to azoxystrobin. There was no correlation between sensitivity to fluquinconazole and prochloraz, but there was a weak negative cross-resistance between fluquinconazole and azoxystrobin.

The M1 matrix protein controls the filamentous phenotype of influenza A virus

We show that most isolates of influenza A induce filamentous changes in infected cells in contrast to A/WSN/33 and A/PR8/34 strains which have undergone extensive laboratory passage and are mouse-adapted. Using reverse genetics, we created recombinant viruses in the naturally filamentous genetic background of A/Victoria/3/75 and established that this property is regulated by the M1 protein sequence, but that the phenotype is complex and several residues are involved. The filamentous phenotype was lost when the amino acid at position 41 was switched from A to V, at the same time, this recombinant virus also became insensitive to the antibody 14C2. On the other hand, the filamentous phenotype could be fully transferred to a virus containing RNA segment 7 of the A/WSN/33 virus by a combination of three mutations in both the amino and carboxy regions of the M1 protein. This observation suggests that an interaction among these regions of M1 may occur during assembly. (C) 2004 Elsevier Inc. All rights reserved.

High-throughput proteomics using matrix-assisted laser desorption/ionization mass spectrometry

It has become evident that the mystery of life will not be deciphered just by decoding its blueprint, the genetic code. In the life and biomedical sciences, research efforts are now shifting from pure gene analysis to the analysis of all biomolecules involved in the machinery of life. One area of these postgenomic research fields is proteomics. Although proteomics, which basically encompasses the analysis of proteins, is not a new concept, it is far from being a research field that can rely on routine and large-scale analyses. At the time the term proteomics was coined, a gold-rush mentality was created, promising vast and quick riches (i.e., solutions to the immensely complex questions of life and disease). Predictably, the reality has been quite different. The complexity of proteomes and the wide variations in the abundances and chemical properties of their constituents has rendered the use of systematic analytical approaches only partially successful, and biologically meaningful results have been slow to arrive. However, to learn more about how cells and, hence, life works, it is essential to understand the proteins and their complex interactions in their native environment. This is why proteomics will be an important part of the biomedical sciences for the foreseeable future. Therefore, any advances in providing the tools that make protein analysis a more routine and large-scale business, ideally using automated and rapid analytical procedures, are highly sought after. This review will provide some basics, thoughts and ideas on the exploitation of matrix-assisted laser desorption/ionization in biological mass spectrometry - one of the most commonly used analytical tools in proteomics - for high-throughput analyses.