Successful long-term ultra dry storage of seed of 15 species of Brassicaceae in a genebank: variation in ability to germinate over 40 years and dormancy

Seed of 15 species of Brassicaceae were stored hermetically in a genebank (at -5 degrees C to -10 degrees C with c. 3% moisture content) for 40 years. Samples were withdrawn at intervals for germination tests. Many accessions showed an increase in ability to germinate over this period. due to loss in dormancy. Nevertheless, some dormancy remained after 40 years' storage and was broken by pre-applied gibberellic acid. The poorest seed survival occurred in Hormatophylla spinosa. Even in this accession the ability to germinate declined by only 7% between 1966 and 2006. Comparison of seeds from 1966 stored for 40 years with those collected anew in 2006 from the original sampling sites, where possible, showed few differences, other than a tendency (7 of 9 accessions) for the latter to show greater dormancy. These results for hermetic storage at sub-zero temperatures and low moisture contents confirm that long-term seed storage can provide a successful technology for ex situ plant biodiversity conservation.

A model of seed dormancy in wild oats (Avena fatua) for investigating genotype x environment interactions

Dormancy is an adaptive trait in seed populations that helps ensure that seed germination is distributed over time and occurs in environmental conditions suitable for seedling growth. Several genes.. associated with seed dormancy in various plant species, have been integrated into a hypothetical dormancy model for Avena fatua L. (wild oats). Generally, the synthesis of, and sensitivity to, abscisic acid (ABA) during imbibition determines whether genes similar to those during maturation are expressed leading to a maintenance of dormancy during extended imbibition. Alternatively, there may be a shift towards expression of genes associated with gibberellins leading to germination. Environmental factors during maturation, after-ripening and imbibition are likely to interact with the genotype to affect gene expression and hence whether or not a seed germinates. In spite of the difficulties of working on a hexaploid species, A. fatua was selected for study because of its worldwide importance as a weed. Dormant and non-dormant genotypes of this species were also available. Gene expression studies are being carried out on three A.fatua genotypes produced tinder different environmental conditions to investigate the role of specific genes in dormancy and genotype X environment interactions in relation to dormancy.

The effects of seed mix and management on the abundance of desirable and pernicious unsown species in arable buffer strip communities

Buffer strips are refuges for a variety of plants providing resources, such as pollen, nectar and seeds, for higher trophic levels, including invertebrates, mammals and birds. Margins can also harbour plant species that are potentially injurious to the adjacent arable crop (undesirable species). Sowing perennial species in non-cropped buffer strips can reduce weed incidence, but limits the abundance of annuals with the potential to support wider biodiversity (desirable species). We investigated the responses of unsown plant species present in buffer strips established with three different seed mixes managed annually with three contrasting management regimes (cutting, sward scarification and selective graminicide). Sward scarification had the strongest influence on the unsown desirable (e.g. Sonchus spp.) and unsown pernicious (e.g. Elytrigia repens) species, and was generally associated with higher cover values of these species. However, abundances of several desirable weed species, in particular Poa annua, were not promoted by scarification. The treatments of cutting and graminicide tended to have negative impacts on the unsown species, except for Cirsium vulgare, which increased with graminicide application. Differences in unsown species cover between seed mixes were minimal, although the grass-only mix was more susceptible to establishment by C. vulgare and Galium aparine than the two grass and forb mixes. Annual scarification can enable desirable annuals and sown perennials to co-exist, however, this practice can also promote pernicious species, and so is unlikely to be widely adopted as a management tool in its current form.

Effects of seed mixture and management on beetle assemblages of arable field margins

Beetle assemblages and their response to plant community composition and architectural structure were monitored from 2002 to 2006 within arable field margins. Field margins were sown with either tussock grass and forbs, fine grass and forbs or grass only seed mixtures. After an establishment year, field margins were managed using standard sward cuts, scarification, or graminicide application. For predatory beetles, overall density was greatest where tussock grasses were included within the seed mixtures, while the densities of phytophagous beetles were greatest where forbs were present. Unexpectedly, species rarefaction curves suggested that phytophagous beetle species richness was greatest where field margins were established using a grass only seed mixture. The structure of the beetle assemblages, i.e., the relative abundances of individual species, was largely dependent on seed mixture, although margin management also played an important role. The results suggest that field margins established using seed mixtures containing tussock grasses and forbs would be expected to provide the greatest resources for beetles, at least at local scales. However, the use of a single standardised seed mixture for margin establishment would result in a homogenisation of beetle assemblages at a regional scale. (C) 2008 Elsevier B.V. All rights reserved.

Robust classification of SAR imagery

In this work the G(A)(0) distribution is assumed as the universal model for amplitude Synthetic Aperture (SAR) imagery data under the Multiplicative Model. The observed data, therefore, is assumed to obey a G(A)(0) (alpha; gamma, n) law, where the parameter n is related to the speckle noise, and (alpha, gamma) are related to the ground truth, giving information about the background. Therefore, maps generated by the estimation of (alpha, gamma) in each coordinate can be used as the input for classification methods. Maximum likelihood estimators are derived and used to form estimated parameter maps. This estimation can be hampered by the presence of corner reflectors, man-made objects used to calibrate SAR images that produce large return values. In order to alleviate this contamination, robust (M) estimators are also derived for the universal model. Gaussian Maximum Likelihood classification is used to obtain maps using hard-to-deal-with simulated data, and the superiority of robust estimation is quantitatively assessed.

Classification of lactose and mandelic acid THz spectra using subspace and wavelet-packet algorithms

This work compares classification results of lactose, mandelic acid and dl-mandelic acid, obtained on the basis of their respective THz transients. The performance of three different pre-processing algorithms applied to the time-domain signatures obtained using a THz-transient spectrometer are contrasted by evaluating the classifier performance. A range of amplitudes of zero-mean white Gaussian noise are used to artificially degrade the signal-to-noise ratio of the time-domain signatures to generate the data sets that are presented to the classifier for both learning and validation purposes. This gradual degradation of interferograms by increasing the noise level is equivalent to performing measurements assuming a reduced integration time. Three signal processing algorithms were adopted for the evaluation of the complex insertion loss function of the samples under study; a) standard evaluation by ratioing the sample with the background spectra, b) a subspace identification algorithm and c) a novel wavelet-packet identification procedure. Within class and between class dispersion metrics are adopted for the three data sets. A discrimination metric evaluates how well the three classes can be distinguished within the frequency range 0. 1 - 1.0 THz using the above algorithms.

Optimal discrimination and classification of THz spectra in the wavelet domain

In rapid scan Fourier transform spectrometry, we show that the noise in the wavelet coefficients resulting from the filter bank decomposition of the complex insertion loss function is linearly related to the noise power in the sample interferogram by a noise amplification factor. By maximizing an objective function composed of the power of the wavelet coefficients divided by the noise amplification factor, optimal feature extraction in the wavelet domain is performed. The performance of a classifier based on the output of a filter bank is shown to be considerably better than that of an Euclidean distance classifier in the original spectral domain. An optimization procedure results in a further improvement of the wavelet classifier. The procedure is suitable for enhancing the contrast or classifying spectra acquired by either continuous wave or THz transient spectrometers as well as for increasing the dynamic range of THz imaging systems. (C) 2003 Optical Society of America.

Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

Resource availability and the persistence of seed-eating bird populations in agricultural landscapes – a mechanistic modelling approach

1. Reductions in resource availability, associated with land-use change and agricultural intensification in the UK and Europe, have been linked with the widespread decline of many farmland bird species over recent decades. However, the underlying ecological processes which link resource availability and population trends are poorly understood. 2. We construct a spatial depletion model to investigate the relationship between the population persistence of granivorous birds within the agricultural landscape and the temporal dynamics of stubble field availability, an important source of winter food for many of those species. 3. The model is capable of accurately predicting the distribution of a given number of finches and buntings amongst patches of different stubble types in an agricultural landscape over the course of a winter and assessing the relative value of different landscapes in terms of resource availability. 4. Sensitivity analyses showed that the model is relatively robust to estimates of energetic requirements, search efficiency and handling time but that daily seed survival estimates have a strong influence on model fit. Understanding resource dynamics in agricultural landscapes is highlighted as a key area for further research. 5. There was a positive relationship between the predicted number of bird days supported by a landscape over-winter and the breeding population trend for yellowhammer Emberiza citrinella, a species for which survival has been identified as the primary driver of population dynamics, but not for linnet Carduelis cannabina, a species for which productivity has been identified as the primary driver of population dynamics. 6. Synthesis and applications. We believe this model can be used to guide the effective delivery of over-winter food resources under agri-environment schemes and to assess the impacts on granivorous birds of changing resource availability associated with novel changes in land use. This could be very important in the future as farming adapts to an increasingly dynamic trading environment, in which demands for increased agricultural production must be reconciled with objectives for environmental protection, including biodiversity conservation.

Classification of instability modes in a model of aluminium reduction cells with a uniform magnetic field

A unified view on the interfacial instability in a model of aluminium reduction cells in the presence of a uniform, vertical, background magnetic field is presented. The classification of instability modes is based on the asymptotic theory for high values of parameter β, which characterises the ratio of the Lorentz force based on the disturbance current, and gravity. It is shown that the spectrum of the travelling waves consists of two parts independent of the horizontal cross-section of the cell: highly unstable wall modes and stable or weakly unstable centre, or Sele’s modes. The wall modes with the disturbance of the interface being localised at the sidewalls of the cell dominate the dynamics of instability. Sele’s modes are characterised by a distributed disturbance over the whole horizontal extent of the cell. As β increases these modes are stabilized by the field.