Generating and evaluating a novel genetic resource in wheat in diverse environments

The principal objective of the project is to develop composite cross populations of wheat based on a wide range of key parent varieties. The parents will be selected partly on past knowledge of successful performance in terms of yield, quality and disease resistance and partly on the basis of molecular ancestry to try to ensure as wide range of diversity as possible. Following parental inter-crossing in all possible combinations, progeny population samples will be exposed to a range of widely different agricultural environments and systems through several seasons of, largely, natural selection. Performance of the population samples will be compared at different stages against both the parents grown as pure stands and as physical mixtures. Our objective is to increase the sustainability and competitiveness of organic and other extensive farming systems by developing genetically diverse wheat populations that will respond rapidly to on-farm selection for improved productivity and yield. It is well established that modern varieties of wheat perform poorly under the conditions and management options encountered in organic farming systems. This is due to a number of factors including poor competition against weeds, narrow resistance against pests and disease, inability to efficiently utilise soil bound nutrients and the lack of genetic flexibility to buffer against environmental variation. To develop a conventional, new wheat breeding programme, from start to release of adapted varieties, would take many years. The approach we propose can deliver this material quickly. This will be achieved through the production of appropriate composite-cross populations of winter wheat. The research will provide material adapted to basic organic conditions that can then be further selected on-farm. This will also be of benefit to non-organic farms as the populations will posses broad resistance to pests and disease and improved competitive ability against weeds, so minimising the need for crop protection inputs. The research will deliver a unique insight into the evolution of genetically diverse wheat populations, under a diverse range of environments, which will allow the elucidation of gene x environment interactions. In addition, it will provide information on the characters of winter wheat that confer improved productivity under a diversity of environmental conditions. Samples of the resulting winter wheat composite cross populations will be placed in the gene bank at the John Innes Centre. Overall objective: To increase the sustainability and competitiveness of both non-organic and organic farming systems by developing genetically diverse wheat populations that will respond rapidly to on-farm selection for improved productivity and yield. 1. To generate six distinct, highly heterogeneous composite-cross populations of winter wheat for further development and selection. The populations will comprise; one with parental material selected for good milling potential, one with parents selected for high yield potential and one comprising both sets of parent material. Each of these populations will then be split to either include or exclude heritable male sterility. 2. To evaluate the performance and evolution of composite-cross populations over time under a diverse range of environmental conditions and identify characteristics that confer improved productivity in these environments. 3. To track the genetic changes that accompany selection, so providing a better understanding of the assemblages of traits that underlie improved productivity in diverse environments. 4. To provide genetically diverse crop material for further selection by farmers and as a resource for future publicly funded research. 5. To disseminate the results to the scientific community and industr

Pioneer 10 Jupiter atmospheric definition results: A summary

The various entry probes for measuring outer planetary atmospheric compositions are discussed. Considered are chemical components and physical accumulation processes observable by spectroscopic studies, as well as pressure gauges, temperature gauges, accelerometers, nephelometers, and visible and infrared sensors for determining abundances

Co-clustering separately exchangeable network data

This article establishes the performance of stochastic blockmodels in addressing the co-clustering problem of partitioning a binary array into subsets, assuming only that the data are generated by a nonparametric process satisfying the condition of separate exchangeability. We provide oracle inequalities with rate of convergence $\mathcal{O}_P(n^{-1/4})$ corresponding to profile likelihood maximization and mean-square error minimization, and show that the blockmodel can be interpreted in this setting as an optimal piecewise-constant approximation to the generative nonparametric model. We also show for large sample sizes that the detection of co-clusters in such data indicates with high probability the existence of co-clusters of equal size and asymptotically equivalent connectivity in the underlying generative process.Comment: Published in at http://dx.doi.org/10.1214/13-AOS1173 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Skellam shrinkage: Wavelet-based intensity estimation for inhomogeneous Poisson data

The ubiquity of integrating detectors in imaging and other applications implies that a variety of real-world data are well modeled as Poisson random variables whose means are in turn proportional to an underlying vector-valued signal of interest. In this article, we first show how the so-called Skellam distribution arises from the fact that Haar wavelet and filterbank transform coefficients corresponding to measurements of this type are distributed as sums and differences of Poisson counts. We then provide two main theorems on Skellam shrinkage, one showing the near-optimality of shrinkage in the Bayesian setting and the other providing for unbiased risk estimation in a frequentist context. These results serve to yield new estimators in the Haar transform domain, including an unbiased risk estimate for shrinkage of Haar-Fisz variance-stabilized data, along with accompanying low-complexity algorithms for inference. We conclude with a simulation study demonstrating the efficacy of our Skellam shrinkage estimators both for the standard univariate wavelet test functions as well as a variety of test images taken from the image processing literature, confirming that they offer substantial performance improvements over existing alternatives.Comment: 27 pages, 8 figures, slight formatting changes; submitted for publicatio

"Rewiring" Filterbanks for Local Fourier Analysis: Theory and Practice

This article describes a series of new results outlining equivalences between certain "rewirings" of filterbank system block diagrams, and the corresponding actions of convolution, modulation, and downsampling operators. This gives rise to a general framework of reverse-order and convolution subband structures in filterbank transforms, which we show to be well suited to the analysis of filterbank coefficients arising from subsampled or multiplexed signals. These results thus provide a means to understand time-localized aliasing and modulation properties of such signals and their subband representations--notions that are notably absent from the global viewpoint afforded by Fourier analysis. The utility of filterbank rewirings is demonstrated by the closed-form analysis of signals subject to degradations such as missing data, spatially or temporally multiplexed data acquisition, or signal-dependent noise, such as are often encountered in practical signal processing applications