Breeding for low input conditions and consequences for participatory plant breeding: Examples from tropical maize and wheat

Participatory plant breeding (PPB) has been suggested as an effective alternative to formal plant breeding (FPB) as a breeding strategy for achieving productivity gains under low input conditions. With genetic progress through PPB and FPB being determined by the same genetic variables, the likelihood of success of PPB approaches applied in low input target conditions was analyzed using two case studies from FPB that have resulted in significant productivity gains under low input conditions: (1) breeding tropical maize for low input conditions by CIMMYT, and (2) breeding of spring wheat for the highly variable low input rainfed farming systems in Australia. In both cases, genetic improvement was an outcome of long-term investment in a sustained research effort aimed at understanding the detail of the important environmental constraints to productivity and the plant requirements for improved adaptation to the identified constraints, followed up by the design and continued evaluation of efficient breeding strategies. The breeding strategies used differed between the two case studies but were consistent in their attention to the key determinants of response to selection: (1) ensuring adequate sources of genetic variation and high selection pressures for the important traits at all stages of the breeding program, (2) use of experimental procedures to achieve high levels of heritability in the breeding trials, and (3) testing strategies that achieved a high genetic correlation between performance of germplasm in the breeding trials and under on-farm conditions. The implications of the outcomes from these FPB case studies for realizing the positive motivations for adopting PPB strategies are discussed with particular reference for low input target environment conditions.

Subantarctic Macquarie Island - a model ecosystem for studying animal-derived nitrogen sources using N-15 natural abundance

Plants collected from diverse sites on subantarctic Macquarie Island varied by up to 30 parts per thousand in their leaf delta(15)N values. N-15 natural abundance of plants, soils, animal excrement and atmospheric ammonia suggest that the majority of nitrogen utilised by plants growing in the vicinity of animal colonies or burrows is animal-derived. Plants growing near scavengers and animal higher in the food chain had highly enriched delta(15)N values (mean = 12.9 parts per thousand), reflecting the highly enriched signature of these animals' excrement, while plants growing near nesting penguins and albatross, which have an intermediate food chain position, had less enriched delta(15)N values (> 6 parts per thousand). Vegetation in areas affected by rabbits had lower delta(15)N values (mean = 1.2 parts per thousand), while the highly depleted delta(15)N values (below -5 parts per thousand) of plants at upland plateau sites inland of penguin colonies, suggested that a portion of their nitrogen is derived from ammonia (mean N-15 = -10 parts per thousand) lost during the degradation of penguin guano. Vegetation in a remote area had delta(15)N values near -2 parts per thousand. These results contrast with arctic and subarctic studies that attribute large variations in plant N-15 values to nitrogen partitioning in nitrogen-limited environments. Here, plant N-15 reflects the N-15 Of the likely nitrogen sources utilised by plants.

An integration bridge for heterogeneous e-service environments

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Identification of research to improve the efficiency of breeding strategies for white clover in Australia - a review

A major challenge faced by today's white clover breeder is how to manage resources within a breeding program. It is essential to utilise these resources with sufficient flexibility to build on past progress from conventional breeding strategies, but also take advantage of emerging opportunities from molecular breeding tools such as molecular markers and transformation. It is timely to review white clover breeding strategies. This background can then be used as a foundation for considering how to continue conventional plant improvement activities and complement them with molecular breeding opportunities. In this review, conventional white clover breeding strategies relevant to the Australian dryland target population environments are considered. Attention is given to: (i) availability of genetic variation, (ii) characterisation of germplasm collections, (iii) quantitative models for estimation of heritability, (iv) the role of multi-environment trials to accommodate genotype-by-environment interactions, (v) interdisciplinary research to understand adaptation to dryland environments, (vi) breeding and selection strategies, and (vii) cultivar structure. Current achievements in biotechnology with specific reference to white clover breeding in Australia are considered, and computer modelling of breeding programs is discussed as a useful integrative tool for the joint evaluation of conventional and molecular breeding strategies and optimisation of resource use in breeding programs. Four areas are identified as future research priorities: (i) capturing the potential genetic diversity among introduced accessions and ecotypes that are adapted to key constraints such as summer moisture stress and the use of molecular markers to assess the genetic diversity, (ii) understanding the underlying physiological/morphological root and shoot mechanisms involved in water use efficiency of white clover, with the objective of identifying appropriate selection criteria, (iii) estimation of quantitative genetic parameters of important morphological/physiological attributes to enable prediction of response to selection in target environments, and (iv) modelling white clover breeding strategies to evaluate the opportunities for integration of molecular breeding strategies with conventional breeding programs.

A yield architecture framework to explain adaptation of pearl millet to environmental stress

Functional knowledge of the physiological basis of crop adaptation to stress is a prerequisite for exploiting specific adaptation to stress environments in breeding programs. This paper presents an analysis of yield components for pearl millet, to explain the specific adaptation of local landraces to stress environments in Rajasthan, India. Six genotypes, ranging from high-tillering traditional landraces to low-tillering open-pollinated modern cultivars, were grown in 20 experiments, covering a range of nonstress and drought stress patterns. In each experiment, yield components (particle number, grain number, 100 grain mass) were measured separately for main shoots, basal tillers, and nodal tillers. Under optimum conditions, landraces had a significantly lower grain yield than the cultivars, but no significant differences were observed at yield levels around 1 ton ha(-1). This genotype x environment interaction for grain yield was due to a difference in yield strategy, where landraces aimed at minimising the risk of a crop failure under stress conditions, and modem cultivars aimed at maximising yield potential under optimum conditions. A key aspect of the adaptation of landraces was the small size of the main shoot panicle, as it minimised (1) the loss of productive tillers during stem elongation; (2) the delay in anthesis if mid-season drought occurs; and (3) the reduction in panicle productivity of the basal tillers under stress. In addition, a low investment in structural panicle weight, relative to vegetative crop growth rate, promoted the production of nodal tillers, providing a mechanism to compensate for reduced basal tiller productivity if stress occurred around anthesis. A low maximum 100 grain mass also ensured individual grain mass was little affected by environmental conditions. The strategy of the high-tillering landraces carries a yield penalty under optimum conditions, but is expected to minimise the risk of a crop failure, particularly if mid-season drought stress occurs. The yield architecture of low-tillering varieties, by contrast, will be suited to end-of-season drought stress, provided anthesis is early. Application of the above adaptation mechanisms into a breeding program could enable the identification of plant types that match the prevalent stress patterns in the target environments. (C) 2003 E.J. van Oosterom. Published by Elsevier Science B.V. All rights reserved.

A shared-disk parallel cluster file system

Dissertação apresentada para obtenção do Grau de Doutor em Informática Pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Reconstruction of the join time-delay Doppler-scale reflectivity density in the wide-band regime. A frame theory based approach

The inverse scattering problem concerning the determination of the joint time-delayDoppler-scale reflectivity density characterizing continuous target environments is addressed by recourse to the generalized frame theory. A reconstruction formula,involving the echoes of a frame of outgoing signals and its corresponding reciprocalframe, is developed. A ‘‘realistic’’ situation with respect to the transmission ofa finite number of signals is further considered. In such a case, our reconstruction formula is shown to yield the orthogonal projection of the reflectivity density onto a subspace generated by the transmitted signals.

Yield prediction and inbreeding of maize synthetics generated with lines and single crosses : classic probability

reduce costs and labor associated with predicting the genotypic mean (GM) of a synthetic variety (SV) of maize (Zea mays L.), breeders can develop SVs from L lines and s single crosses (SynL,SC) instead of L+2s lines (SynL). The objective of this work was to derive and study formulae for the inbreeding coefficient (IC) and GM of SynL,SC, SynL, and the SV derived from (L+2s)/2 single crosses (SynSC). All SVs were derived from the same L+2s unrelated lines whose IC is FL, and each parent of a SV was represented by m plants. An a priori probability equation for the IC was used. Important results were: 1) the largest and smallest GMs correspond to SynL and SynL,SC, respectively; 2) the GM predictors with the largest and intermediate precision are those for SynL and SynL,SC, respectively; 3) only when FL=1, or m is large, SynL and SynSC are the same population, but only with SynSC prediction costs and labor undergo the maximum decrease, although its prediction precision is the lowest. To determine the SV to be developed, breeders should also consider the availability of lines, single crosses, manpower and land area; besides budget, target farmers, target environments, etc.

A WD Repeat Protein Controls the Cell Cycle and Differentiation by Negatively Regulating Cdc2/B-Type Cyclin Complexes

In the fission yeast Schizosaccharomyces pombe, p34cdc2 plays a central role controlling the cell cycle. We recently isolated a new gene named srw1+, capable of encoding a WD repeat protein, as a multicopy suppressor of hyperactivated p34cdc2. Cells lacking srw1+ are sterile and defective in cell cycle controls. When starved for nitrogen source, they fail to effectively arrest in G1 and die of accelerated mitotic catastrophe if regulation of p34cdc2/Cdc13 by inhibitory tyrosine phosphorylation is compromised by partial inactivation of Wee1 kinase. Fertility is restored to the disruptant by deletion of Cig2 B-type cyclin or slight inactivation of p34cdc2. srw1+ shares functional similarity with rum1+, having abilities to induce endoreplication and restore fertility to rum1 disruptants. In the srw1 disruptant, Cdc13 fails to be degraded when cells are starved for nitrogen. We conclude that Srw1 controls differentiation and cell cycling at least by negatively regulating Cig2- and Cdc13-associated p34cdc2 and that one of its roles is to down-regulate the level of the mitotic cyclin particularly in nitrogen-poor environments.

Mixed model formulations for multi-environment trials

When studying genotype X environment interaction in multi-environment trials, plant breeders and geneticists often consider one of the effects, environments or genotypes, to be fixed and the other to be random. However, there are two main formulations for variance component estimation for the mixed model situation, referred to as the unconstrained-parameters (UP) and constrained-parameters (CP) formulations. These formulations give different estimates of genetic correlation and heritability as well as different tests of significance for the random effects factor. The definition of main effects and interactions and the consequences of such definitions should be clearly understood, and the selected formulation should be consistent for both fixed and random effects. A discussion of the practical outcomes of using the two formulations in the analysis of balanced data from multi-environment trials is presented. It is recommended that the CP formulation be used because of the meaning of its parameters and the corresponding variance components. When managed (fixed) environments are considered, users will have more confidence in prediction for them but will not be overconfident in prediction in the target (random) environments. Genetic gain (predicted response to selection in the target environments from the managed environments) is independent of formulation.

Contributions to 3D Data Registration and Representation

Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

New Technique for Static Target Detection in Dense-Multipath Urban Environments

Synthetic Aperture Radar (SAR) images a target region reflectivity function in the multi-dimensional spatial domain of range and cross-range with a finer azimuth resolution than the one provided by any on-board real antenna. Conventional SAR techniques assume a single reflection of transmitted waveforms from targets. Nevertheless, new uses of Unmanned Aerial Vehicles (UAVs) for civilian-security applications force SAR systems to work in much more complex scenes such as urban environments. Consequently, multiple-bounce returns are additionally superposed to direct-scatter echoes. They are known as ghost images, since they obscure true target image and lead to poor resolution. All this may involve a significant problem in applications related to surveillance and security. In this work, an innovative multipath mitigation technique is presented in which Time Reversal (TR) concept is applied to SAR images when the target is concealed in clutter, leading to TR-SAR technique. This way, the effect of multipath is considerably reduced ?or even removed?, recovering the lost resolution due to multipath propagation. Furthermore, some focusing indicators such as entropy (E), contrast (C) and Rényi entropy (RE) provide us with a good focusing criterion when using TR-SAR.

Nitrogen metabolism in haloarchaea

The nitrogen cycle (N-cycle), principally supported by prokaryotes, involves different redox reactions mainly focused on assimilatory purposes or respiratory processes for energy conservation. As the N-cycle has important environmental implications, this biogeochemical cycle has become a major research topic during the last few years. However, although N-cycle metabolic pathways have been studied extensively in Bacteria or Eukarya, relatively little is known in the Archaea. Halophilic Archaea are the predominant microorganisms in hot and hypersaline environments such as salted lakes, hot springs or salted ponds. Consequently, the denitrifying haloarchaea that sustain the nitrogen cycle under these conditions have emerged as an important target for research aimed at understanding microbial life in these extreme environments. The haloarchaeon Haloferax mediterranei was isolated 20 years ago from Santa Pola salted ponds (Alicante, Spain). It was described as a denitrifier and it is also able to grow using NO3-, NO2- or NH4+ as inorganic nitrogen sources. This review summarizes the advances that have been made in understanding the N-cycle in halophilic archaea using Hfx mediterranei as a haloarchaeal model. The results obtained show that this microorganism could be very attractive for bioremediation applications in those areas where high salt, nitrate and nitrite concentrations are found in ground waters and soils.

Nitrogen ecophysiology of Heron Island, a subtropical coral cay of the Great Barrier Reef, Australia

Coral cays form part of the Australian Great Barrier Reef. Coral cays with high densities of seabirds are areas of extreme nitrogen (N) enrichment with deposition rates of up to 1000 kg N ha(-1) y(-1). The ways in which N sources are utilised by coral cay plants, N is distributed within the cay, and whether or not seabird-derived N moves from cay to surrounding marine environments were investigated. We used N metabolite analysis, N-15 labelling and N-15 natural abundance (delta(15)N) techniques. Deposited guano-derived uric acid is hydrolysed to ammonium (NH4+) and gaseous ammonia (NH3). Ammonium undergoes nitrification, and nitrate (NO3-) and NH4+ were the main forms of soluble N in the soil. Plants from seabird rookeries have a high capacity to take up and assimilate NH4+, are able to metabolise uric acid, but have low rates of NO3- uptake and assimilation. We concluded that NH4+ is the principal source of N for plants growing at seabird rookeries, and that the presence of NH4+ in soil and gaseous NH3 in the atmosphere inhibits assimilation of NO3-, although NO3- is taken up and stored. Seabird guano, Pisonia forest soil and vegetation were similarly enriched in N-15 suggesting that the isotopic enrichment of guano (delta(15)N 9.9parts per thousand) carries through the forest ecosystem. Soil and plants from woodland and beach environments had lower delta(15)N (average 6.5parts per thousand) indicating a lower contribution of bird-derived N to the N nutrition of plants at these sites. The aquifer under the cay receives seabird-derived N leached from the cay and has high concentrations of N-15-enriched NO3- (delta(15)N 7.9parts per thousand). Macroalgae from reefs with and without seabirds had similar delta(15)N values of 2.0-3.9parts per thousand suggesting that reef macroalgae do not utilise N-15-enriched seabird-derived N as a main source of N. At a site beyond the Heron Reef Crest, macroalgae had elevated delta(15)N of 5.2parts per thousand, possibly indicating that there are locations where macroalgae access isotopically enriched aquifer-derived N. Nitrogen relations of Heron Island vegetation are compared with other reef islands and a conceptual model is presented.