996 resultados para Random variability
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The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of São Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of São Paulo.
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A simple way to quickly optimize microsatellites in nonmodel organisms is to reuse loci available in closely related taxa; however, this approach can be limited by the stochastic and low cross-amplification success experienced in some groups (e.g. amphibians). An efficient alternative is to develop loci from transcriptome sequences. Transcriptomic microsatellites have been found to vary in their levels of cross-species amplification and variability, but this has to date never been tested in amphibians. Here, we compare the patterns of cross-amplification and levels of polymorphism of 18 published anonymous microsatellites isolated from genomic DNA vs. 17 loci derived from a transcriptome, across nine species of tree frogs (Hyla arborea and Hyla cinerea group). We established a clear negative relationship between divergence time and amplification success, which was much steeper for anonymous than transcriptomic markers, with half-lives (time at which 50% of the markers still amplify) of 1.1 and 37 My, respectively. Transcriptomic markers are significantly less polymorphic than anonymous loci, but remain variable across diverged taxa. We conclude that the exploitation of amphibian transcriptomes for developing microsatellites seems an optimal approach for multispecies surveys (e.g. analyses of hybrid zones, comparative linkage mapping), whereas anonymous microsatellites may be more informative for fine-scale analyses of intraspecific variation. Moreover, our results confirm the pattern that microsatellite cross-amplification is greatly variable among amphibians and should be assessed independently within target lineages. Finally, we provide a bank of microsatellites for Palaearctic tree frogs (so far only available for H. arborea), which will be useful for conservation and evolutionary studies in this radiation.
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Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.
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The objective of this work was to determine the effect of male sterility or manual recombination on genetic variability of rice recurrent selection populations. The populations CNA-IRAT 4, with a gene for male sterility, and CNA 12, which was manually recombined, were evaluated. Genetic variability among selection cycles was estimated using14 simple sequence repeat (SSR) markers. A total of 926 plants were analyzed, including ten genitors and 180 individuals from each of the evaluated cycles (1, 2 and 5) of the population CNA-IRAT 4, and 16 genitors and 180 individuals from each of the cycles (1 and 2) of CNA 12. The analysis allowed the identification of alleles not present among the genitors for both populations, in all cycles, especially for the CNA-IRAT 4 population. These alleles resulted from unwanted fertilization with genotypes that were not originally part of the populations. The parameters of Wright's F-statistic (F IS and F IT) indicated that the manual recombination expands the genetic variability of the CNA 12 population, whereas male sterility reduces the one of CNA-IRAT 4.
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Several hypotheses have been elaborated to account for the evolutionary decay commonly observed in full-fledged Y chromosomes. Enhanced drift, background selection and selective sweeps, which are expected to result from reduced recombination, may all share responsibilities in the initial decay of proto-Y chromosomes, but little empirical information has been gathered so far. Here we take advantage of three markers that amplify on both of the morphologically undifferentiated sex chromosomes of the European tree frog (Hyla arborea) to show that recombination is suppressed in males (the heterogametic sex) but not in females. Accordingly, genetic variability is reduced on the Y, but in a way that can be accounted for by merely the number of chromosome copies per breeding pair, without the need to invoke background selection or selective sweeps.
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Invasive candidiasis is the most commonly reported invasive fungal infection worldwide. Although Candida albicans remains the main cause, the incidence of emerging Candida species, such as C. parapsilosis is increasing. It has been postulated that C. parapsilosis clinical isolates result from a recent global expansion of a virulent clone. However, the availability of a single genome for this species has so far prevented testing this hypothesis at genomic scales. We present here the sequence of three additional strains from clinical and environmental samples. Our analyses reveal unexpected patterns of genomic variation, shared among distant strains, that argue against the clonal expansion hypothesis. All strains carry independent expansions involving an arsenite transporter homolog, pointing to the existence of directional selection in the environment, and independent origins of the two clinical isolates. Furthermore, we report the first evidence for the existence of recombination in this species. Altogether, our results shed new light onto the dynamics of genome evolution in C. parapsilosis.
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We report Monte Carlo results for a nonequilibrium Ising-like model in two and three dimensions. Nearest-neighbor interactions J change sign randomly with time due to competing kinetics. There follows a fast and random, i.e., spin-configuration-independent diffusion of Js, of the kind that takes place in dilute metallic alloys when magnetic ions diffuse. The system exhibits steady states of the ferromagnetic (antiferromagnetic) type when the probability p that J>0 is large (small) enough. No counterpart to the freezing phenomena found in quenched spin glasses occurs. We compare our results with existing mean-field and exact ones, and obtain information about critical behavior.
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This paper suggests a method for obtaining efficiency bounds in models containing either only infinite-dimensional parameters or both finite- and infinite-dimensional parameters (semiparametric models). The method is based on a theory of random linear functionals applied to the gradient of the log-likelihood functional and is illustrated by computing the lower bound for Cox's regression model
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The objective of this work was to estimate the genetic variability level and distribution in Brazilian broodstocks of marine shrimp (Litopenaeus vannamei). Nine of the country's largest hatcheries were evaluated using codominant and highly polymorphic microsatellite markers. The results obtained from genotyping of ten microsatellite loci are indicative of genetic variability that is compatible with that found in wild populations of L. vannamei in Mexico and Central America. A possible explanation is the highly diversified and relatively recent origin of the available broodstocks. Bayesian analysis detected a signal for five founding populations. The distribution of genetic distances partially reflects geographical location, and this information will be useful for the creation of new broodstocks. Therefore, L. vannamei genetic variability among nine of the largest national hatcheries can be considered high.
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Peer reviewed
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14C dating of groundwater depends on the isotopic composition of both the solid carbonate and the soil CO2 and requires the use of 14C age correction models. To better assess the variability of the 14C activity of soil CO2 (A14Csoil-CO2) and the δ13C of soil CO2 (δ13Csoil-CO2), which are two parameters used in 14C age correction models, we studied the different processes involving carbon isotopes in the soil. The approach used experimental data from two sites in France (Fontainebleau sands and Astian sands) and a steady-state transport model. In most cases, the 14C activity (A14C) of atmospheric CO2 is directly used in the 14C age correction models as the A14Csoil-CO2. However, we demonstrate that since 1950, the evolution of the A14Csoil-CO2 reflects the competition between the fluxes of root-derived CO2 and organic matter-derived CO2. Therefore, the A14Csoil-CO2 must be used to date groundwater that is younger than 60 years old. Moreover, the δ13C of soil CO2 (δ13Csoil-CO2) showed large seasonal variations that must be taken into account in selecting the δ13Csoil-CO2 for 14C age correction models.
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Physiol Meas. 2007 Oct;28(10):1189-200. Epub 2007 Sep 18.
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The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.
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To optimally manage a metapopulation, managers and conservation biologists can favor a type of habitat spatial distribution (e.g. aggregated or random). However, the spatial distribution that provides the highest habitat occupancy remains ambiguous and numerous contradictory results exist. Habitat occupancy depends on the balance between local extinction and colonization. Thus, the issue becomes even more puzzling when various forms of relationships - positive or negative co-variation - between local extinction and colonization rate within habitat types exist. Using an analytical model we demonstrate first that the habitat occupancy of a metapopulation is significantly affected by the presence of habitat types that display different extinction-colonization dynamics, considering: (i) variation in extinction or colonization rate and (ii) positive and negative co-variation between the two processes within habitat types. We consequently examine, with a spatially explicit stochastic simulation model, how different degrees of habitat aggregation affect occupancy predictions under similar scenarios. An aggregated distribution of habitat types provides the highest habitat occupancy when local extinction risk is spatially heterogeneous and high in some places, while a random distribution of habitat provides the highest habitat occupancy when colonization rates are high. Because spatial variability in local extinction rates always favors aggregation of habitats, we only need to know about spatial variability in colonization rates to determine whether aggregating habitat types increases, or not, metapopulation occupancy. From a comparison of the results obtained with the analytical and with the spatial-explicit stochastic simulation model we determine the conditions under which a simple metapopulation model closely matches the results of a more complex spatial simulation model with explicit heterogeneity.
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The objective of this work was to characterize and quantify the genetic, molecular, and agronomic variability of hull-less barley genotypes, for the selection of parents and identification of genotypes adapted to the irrigated production system in the Brazilian Cerrado. Eighteen hull-less barley accessions were evaluated, and three covered barley accessions served as reference. The characterization was based on 157 RAPD molecular markers and ten agronomic traits. Genetic distance matrices were obtained based on molecular markers and quantitative traits. Graphic grouping and dispersion analyses were performed. Genetic, molecular, and agronomic variability was high among genotypes. Ethiopian accessions were genetically more similar, and the Brazilian ones were genetically more distant. For agronomic traits, two more consistent groupings were obtained, one with the most two-rowed materials, and the other with six-rowed materials. The more diverging materials were the two-rowed CI 13453, CN Cerrado 5, CN Cerrado 1, and CN Cerrado 2. The PI 356466, CN Cerrado 1, PI 370799, and CI 13453 genotypes show agronomic traits of interest and, as genetically different genotypes, they are indicated for crossing, in breeding programs.