ESTs from a wild Arachis species for gene discovery and marker development

BACKGROUND: Due to its origin, peanut has a very narrow genetic background. Wild relatives can be a source of genetic variability for cultivated peanut. In this study, the transcriptome of the wild species Arachis stenosperma accession V10309 was analyzed. RESULTS: ESTs were produced from four cDNA libraries of RNAs extracted from leaves and roots of A. stenosperma. Randomly selected cDNA clones were sequenced to generate 8,785 ESTs, of which 6,264 (71.3%) had high quality, with 3,500 clusters: 963 contigs and 2537 singlets. Only 55.9% matched homologous sequences of known genes. ESTs were classified into 23 different categories according to putative protein functions. Numerous sequences related to disease resistance, drought tolerance and human health were identified. Two hundred and six microsatellites were found and markers have been developed for 188 of these. The microsatellite profile was analyzed and compared to other transcribed and genomic sequence data. CONCLUSION: This is, to date, the first report on the analysis of transcriptome of a wild relative of peanut. The ESTs produced in this study are a valuable resource for gene discovery, the characterization of new wild alleles, and for marker development. The ESTs were released in the [GenBank:EH041934 to EH048197]

Theoretical and experimental study on electron interactions with chlorobenzene: Shape resonances and differential cross sections

9 págs.; 6 figs.; 1 tab.In this work, we report theoretical and experimental cross sections for elastic scattering of electrons by chlorobenzene (ClB). The theoretical integral and differential cross sections (DCSs) were obtained with the Schwinger multichannel method implemented with pseudopotentials (SMCPP) and the independent atom method with screening corrected additivity rule (IAM-SCAR). The calculations with the SMCPP method were done in the static-exchange (SE) approximation, for energies above 12 eV, and in the static-exchange plus polarization approximation, for energies up to 12 eV. The calculations with the IAM-SCAR method covered energies up to 500 eV. The experimental differential cross sections were obtained in the high resolution electron energy loss spectrometer VG-SEELS 400, in Lisbon, for electron energies from 8.0 eV to 50 eV and angular range from 7 to 110. From the present theoretical integral cross section (ICS) we discuss the low-energy shape-resonances present in chlorobenzene and compare our computed resonance spectra with available electron transmission spectroscopy data present in the literature. Since there is no other work in the literature reporting differential cross sections for this molecule, we compare our theoretical and experimental DCSs with experimental data available for the parent molecule benzene. Published by AIP Publishing.A.S.B., M.T.N.V., S.d’A.S., and M.H.F.B. acknowledge the Brazilian Agency Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), under CAPES/FCT Programme (Process No. 23038.002465/2014-87). M.T.N.V., S.d’A.S., and M.H.F.B. acknowledge support from the Brazilian Agency Conselho Nacional de Desenvolvimento Científico e Tecnológico. M.H.F.B. acknowledges support from Finep (under project CT-Infra), and M.T.N.V. from São Paulo Research Foundation (FAPESP). A.S.B., S.d’A.S., and M.H.F.B. acknowledge computational support from Professor Carlos M. de Carvalho at LFTC-DFis-UFPR and at LCPADUFPR and from CENAPAD-SP. F.F.S. acknowledges the Portuguese National Funding Agency FCT through researcher Contract No. IF-FCT IF/00380/2014 and together with P.LV. the research Grant No. UID/FIS/00068/2013. F.B. and G.G. acknowledge partial financial support from the Spanish Ministry MINECO (Project No. FIS2012-31230).Peer Reviewe

A feasibility cachaca type recognition using computer vision and pattern recognition

Brazilian rum (also known as cachaça) is the third most commonly consumed distilled alcoholic drink in the world, with approximately 2.5 billion liters produced each year. It is a traditional drink with refined features and a delicate aroma that is produced mainly in Brazil but consumed in many countries. It can be aged in various types of wood for 1-3 years, which adds aroma and a distinctive flavor with different characteristics that affect the price. A research challenge is to develop a cheap automatic recognition system that inspects the finished product for the wood type and the aging time of its production. Some classical methods use chemical analysis, but this approach requires relatively expensive laboratory equipment. By contrast, the system proposed in this paper captures image signals from samples and uses an intelligent classification technique to recognize the wood type and the aging time. The classification system uses an ensemble of classifiers obtained from different wavelet decompositions. Each classifier is obtained with different wavelet transform settings. We compared the proposed approach with classical methods based on chemical features. We analyzed 105 samples that had been aged for 3 years and we showed that the proposed solution could automatically recognize wood types and the aging time with an accuracy up to 100.00% and 85.71% respectively, and our method is also cheaper.info:eu-repo/semantics/publishedVersio

Relationship between Field Measurements in Three \u3cem\u3eBrachiaria\u3c/em\u3e Species with Leaf Area Index and Light Interception by Indirect Methods

Brachiaria species play a strategic role in ruminant production systems in Brazil, covering an estimated pasture area of approximately 90 million hectares (Karia et al., 2006), however, these pastures are subject to different degrees of degradation due to inadequate management. In pasture management, field measurements such as canopy height, for example, are used by managers as a tool to establish parameters for the optimal point to cut the forage and for the post-grazing residue, in order to maximize production by harvesting at maximum of herbage mass accumulation, and to avoid problems associated to overgrazing, by setting ideal post-grazing height for forage regrowth. The use of the variables light interception (LI) and leaf area index (LAI) has been recommended as a tool for pasture management, based on the theory that, when the canopy reaches a light interception of 95%, the forage is near its maximum growth rate, which is called critical LAI (Brougham, 1956). The residual LAI refers to the leaf area of the post-grazed stubble. Residual LAI is used to establish the minimum leaf area necessary to ensure an efficient pasture regrowth (Lemos et al., 2014). Light interception and the LAI are difficult to measure at the farm level, due to the high cost of the equipment and technical feasibility of the process. The objective of this study was to evaluate the relationship between LI and LAI measured by two different equipment, with canopy height and soil cover in three species of Brachiaria

Electronic excitation of furfural as probed by high-resolution vacuum ultraviolet spectroscopy, electron energy loss spectroscopy, and ab initio calculations

13 págs.; 7 figs.; 8 tabs.© 2015 AIP Publishing LLC. The electronic spectroscopy of isolated furfural (2-furaldehyde) in the gas phase has been investigated using high-resolution photoabsorption spectroscopy in the 3.5-10.8 eV energy-range, with absolute cross section measurements derived. Electron energy loss spectra are also measured over a range of kinematical conditions. Those energy loss spectra are used to derive differential cross sections and in turn generalised oscillator strengths. These experiments are supported by ab initio calculations in order to assign the excited states of the neutral molecule. The good agreement between the theoretical results and the measurements allows us to provide the first quantitative assignment of the electronic state spectroscopy of furfural over an extended energy range.F.F.S. and P.L.V. acknowledge the Portuguese Foundation for Science and Technology (FCT-MEC) through Grant Nos. SFRH/BPD/68979/2010 and SFRH/BSAB/105792/2014, respectively, the research Grant Nos. PTDC/FIS-ATO/1832/ 2012 and UID/FIS/00068/2013. P.L.V. also acknowledges his Visiting Research Fellow position at Flinders University, Adelaide, South Australia. The Patrimoine of the University of Liège, the Fonds National de la Recherche Scientifique, and the Fonds de la Recherche Fondamentale Collective of Belgium have also supported this research. E.L. and R.F.C.N. thank CNPq (Brazil) and the Science Without Borders Programme for opportunities to study abroad. The authors wish to acknowledge the beam time at the ISA synchrotron at Aarhus University, Denmark. The research leading to these results has received funding from the European Community’s Seventh Framework Programme (Grant No. FP7/2007-2013) CALIPSO under Grant Agreement No. 312284. D.B.J. thanks the Australian Research Council for financial support provided through a Discovery Early Career Research Award. M.J.B. also thanks the Australian Research Council for some financial support, while M.J.B. and M.C.A.L. acknowledge the Brazilian agencies CNPq and FAPEMIG for financial support. F.B. and G.G. acknowledge partial financial support from the Spanish Ministry MINECO (Project No. FIS2012-31230) and the EU COST Action No. CM1301 (CELINA). Finally, R.F.C., M.T.do N.V., M.H.F.B., and M.A.P.L. acknowledge support from the Brazilian agency CNPq.Peer Reviewe

Tribological Performance of Random Sinter Pores vs. Deterministic Laser Surface Textures: An Experimental and Machine Learning Approach

This work critically scrutinizes and compares the tribological performance of randomly distributed surface pores in sintered materials and precisely tailored laser textures produced by different laser surface texturing techniques. The pore distributions and dimensions were modified by changing the sintering parameters, while the topological features of the laser textures were varied by changing the laser sources and structuring parameters. Ball-on-disc tribological experiments were carried out under lubricated combined sliding-rolling conditions. Film thickness was measured in-situ through a specific interferometry technique developed for the study of rough surfaces. Furthermore, a machine learning approach based on the radial basis function method was proposed to predict the frictional behavior of contact interfaces with surface irregularities. The main results show that both sintered and laser textured materials can reduce friction compared to the untextured material under certain operating conditions. Moreover, the machine learning model was shown to predict results with satisfactory accuracy. It was also found that the performance of sintered materials could lead to similar improvements as achieved by textured surfaces, even if surface pores are randomly distributed and not precisely controlled

Transcriptome analysis of the oil-rich seed of the bioenergy crop Jatropha curcas L

<p>Abstract</p> <p>Background</p> <p>To date, oil-rich plants are the main source of biodiesel products. Because concerns have been voiced about the impact of oil-crop cultivation on the price of food commodities, the interest in oil plants not used for food production and amenable to cultivation on non-agricultural land has soared. As a non-food, drought-resistant and oil-rich crop, <it>Jatropha curcas </it>L. fulfils many of the requirements for biofuel production.</p> <p>Results</p> <p>We have generated 13,249 expressed sequence tags (ESTs) from developing and germinating <it>Jatropha </it>seeds. This strategy allowed us to detect most known genes related to lipid synthesis and degradation. We have also identified ESTs coding for proteins that may be involved in the toxicity of <it>Jatropha </it>seeds. Another unexpected finding is the high number of ESTs containing transposable element-related sequences in the developing seed library (800) when contrasted with those found in the germinating seed library (80).</p> <p>Conclusions</p> <p>The sequences generated in this work represent a considerable increase in the number of sequences deposited in public databases. These results can be used to produce genetically improved varieties of <it>Jatropha </it>with increased oil yields, different oil compositions and better agronomic characteristics.</p