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During pregnancy, women are prone to depression, for which selective serotonin reuptake inhibitors (SSRIs), such as fluoxetine, are usually the first-line treatment. However, fluoxetine can cross the placental barrier and affect fetuses, causing changes in serotonin levels early in life. Long-term effects in the brain circuits that control cognitive and emotional behavior are related to early fluoxetine exposure during development. In this study, we aimed to investigate whether fluoxetine exposure (10 mg/kg/day) from the 13th gestational day (GD13) to GD21 may lead to behavioral emotional-cognitive changes in male and female rat offspring approximately 90 days postnatally (~PN90). We have analyzed the performance of individuals in the open field and in the plus-maze discriminative avoidance task, which assesses anxiety and learning/memory processing behaviors. We have found that prenatal (GD13-GD21) exposure to fluoxetine strengthened aversive memory and induced higher anxiety levels in males, and quick extinction of aversive memory in females. Taken together, these results suggest that early exposure to fluoxetine impairs the basal state of anxiety and the cognitive functions of rats during adulthood, which may be in a sex-specific manner because males appear more susceptible than females.

Temporal (or time-evolving) networks are commonly used to model complex systems and the evolution of their components throughout time. Although these networks can be analyzed by different means, visual analytics stands out as an effective way for a pre-analysis before doing quantitative/statistical analyses to identify patterns, anomalies, and other behaviors in the data, thus leading to new insights and better decision-making. However, the large number of nodes, edges, and/or timestamps in many real-world networks may lead to polluted layouts that make the analysis inefficient or even infeasible. In this paper, we propose LargeNetVis, a web-based visual analytics system designed to assist in analyzing small and large temporal networks. It successfully achieves this goal by leveraging three taxonomies focused on network communities to guide the visual exploration process. The system is composed of four interactive visual components: the first (Taxonomy Matrix) presents a summary of the network characteristics, the second (Global View) gives an overview of the network evolution, the third (a node-link diagram) enables community- and node-level structural analysis, and the fourth (a Temporal Activity Map -- TAM) shows the community- and node-level activity under a temporal perspective., 11 pages, 9 figures

Visual analysis of temporal networks comprises an effective way to understand the network dynamics, facilitating the identification of patterns, anomalies, and other network properties, thus resulting in fast decision making. The amount of data in real-world networks, however, may result in a layout with high visual clutter due to edge overlapping. This is particularly relevant in the so-called streaming networks, in which edges are continuously arriving (online) and in non-stationary distribution. All three network dimensions, namely node, edge, and time, can be manipulated to reduce such clutter and improve readability. This paper presents an online and nonuniform timeslicing method, thus considering the underlying network structure and addressing streaming network analyses. We conducted experiments using two real-world networks to compare our method against uniform and nonuniform timeslicing strategies. The results show that our method automatically selects timeslices that effectively reduce visual clutter in periods with bursts of events. As a consequence, decision making based on the identification of global temporal patterns becomes faster and more reliable.

Visualization strategies facilitate streaming network analysis by allowing its exploration through graphical and interactive layouts. Depending on the strategy and the network density, such layouts may suffer from a high level of visual clutter that hides meaningful temporal patterns, highly active groups of nodes, bursts of activity, and other important network properties. Edge sampling improves layout readability, highlighting important properties and leading to easier and faster pattern identification and decision making. This paper presents Streaming Edge Sampling for Network Visualization–SEVis, a streaming edge sampling method that discards edges of low-active nodes while preserving a distribution of edge counts that is similar to the original network. It can be applied to a variety of layouts to enhance streaming network analyses. We evaluated SEVis performance using synthetic and real-world networks through quantitative and visual analyses. The results indicate a higher performance of SEVis for clutter reduction and pattern identification when compared with other sampling methods.

Physicians work at a very tight schedule and need decision-making support tools to help on improving and doing their work in a timely and dependable manner. Examining piles of sheets with test results and using systems with little visualization support to provide diagnostics is daunting, but that is still the usual way for the physicians' daily procedure, especially in developing countries. Electronic Health Records systems have been designed to keep the patients' history and reduce the time spent analyzing the patient's data. However, better tools to support decision-making are still needed. In this paper, we propose ClinicalPath, a visualization tool for users to track a patient's clinical path through a series of tests and data, which can aid in treatments and diagnoses. Our proposal is focused on patient's data analysis, presenting the test results and clinical history longitudinally. Both the visualization design and the system functionality were developed in close collaboration with experts in the medical domain to ensure a right fit of the technical solutions and the real needs of the professionals. We validated the proposed visualization based on case studies and user assessments through tasks based on the physician's daily activities. Our results show that our proposed system improves the physicians' experience in decision-making tasks, made with more confidence and better usage of the physicians' time, allowing them to take other needed care for the patients., 14 pages and 8 figures

Information Visualisation strategies can be applied in a variety of domains. In the context of temporal networks, i.e., networks in which interactions between individuals occur throughout time, efforts have been conducted to develop visual approaches that allow finding interaction patterns, anomalies, and other behaviours not previously perceived in the data. This paper presents two case studies involving real-world education networks from a primary school and a high school. For this purpose, we used the Massive Sequence View (MSV) layout with the Community-based Node Ordering (CNO) method, two well established approaches for visual analysis of temporal networks. Our results show that the identified patterns involving students/students and students/teachers represent important information to benefit and support decision making about school management and teaching strategies, especially those related to strategic group formation.

Networks are often used to model the structure of interactions between parts of a system. One important characteristic of a network is the so-called network community structures that are groups of nodes more connected between themselves than with nodes from other groups. Such community structure is fundamental to better understand the organization of networks. Although there are several community detection algorithms in the literature, choosing the most appropriate for a specific task is not always trivial. This paper introduces a methodology to analyze the performance of community detection algorithms using network visualization. We assess the methodology using two widely adopted community detection algorithms: Infomap and Louvain. We apply both algorithms to four real-world networks with a variety of characteristics to demonstrate the usefulness and generality of the methodology. We discuss the performance of these algorithms and show how the user may use statistical and visual analytics to identify the most appropriate network community detection algorithm for a certain network analysis task.

The current COVID-19 pandemic has promoted the periodic release of several health databases aimed at discovering relationships in the data, detecting similar problems in patients, and studying the evolution of the disease. A way to exploit the data is to use visualization techniques, which can lead to the discovery of insights and patterns, as well as to guide analysis procedures to understand the data. In this paper, we present I-CovidVis, a visualization tool to explore data from interoperable healthcare systems, able to compare and navigate in both global and local perspectives. Our approach is to model data as a graph and explore its structural and temporal views. Our proposal facilitates the perception of patterns, trends, periodicity, and anomalies, resulting in faster decision making.

Temporal networks have been used to map the structural evolution of social, technological, and biological systems, among others. Due to the large amount of information on real-world temporal networks, increasing attention has been given to issues related to the visual scalability of network visualization layouts. However, visual clutter due to edge overlap remains the main challenge calling for efficient methods to improve the visual experience. In this paper, we propose a novel and scalable node reordering approach for temporal network visualization, named Community-based Node Ordering (CNO), combining static community detection with node reordering techniques to enhance the identification of visual patterns. The perception of trends, periodicity, anomalies, and other temporal patterns, is facilitated, resulting in faster decision making. Our method helps not only the study of network activity patterns within communities but also the analysis of relatively large networks by breaking down its structure in smaller parts. Using CNO, we further propose a taxonomy to categorize activity patterns within communities. We performed a number of experiments and quantitative analyses using two real-world networks with distinct characteristics and showed that the proposed layout and taxonomy speed up the identification of patterns that would otherwise be difficult to see.

Entender como as preferências dos usuários evoluem ao longo do tempo é uma importante tarefa de personalização. As abordagens existentes não levam em consideração a influência social queuns usuários exercem sobre os demais em redes sociais.Neste trabalho, a proposta é modelar os perfis de preferências dos usuários por meio de redes de similaridade temporal. Elas são capazes de capturar características sociais e temporais das preferências, levando em conta a semelhança entre o comportamento dos usuários. A modelagem proposta foi instanciada sobre uma rede social de músicas com o objetivo de entender o que direciona a evolução do gosto musical das pessoas. Como resultado, foi detectado que a tendência é que artistas e usuários semelhantes mantenham suas similaridades ao longo do tempo.

Nitrous oxide (N2O) is an important greenhouse gas. Emissions of this gas are generated by the combustion of fossil fuels, mainly in the transportation sector worldwide. Biofuel is a promising alternative instead of diesel considering that it allows a reduction on the emissions of polluting gases. In Brazil, there is a large program on the use of biofuels, which according to the Intergovernmental Panel on Climate Change (IPCC) reduces greenhouse gas emissions. This work shows the N2O emissions resulting from combustions of diesel/beef tallow biodiesel blends of B7, B15, B20, B25, B35, and B50. In parallel, another experiment was done with fuel sample adopted by a bus fleet from Sao Paulo using blends comprising 10% of sugarcane diesel in diesel (CD10) and blends with beef tallow biodiesel of CD10: CD-B15, CD-B20, CD-B25, CD-B35, and CD-B50. The photoacoustic spectroscopy technique coupled to a quantum cascade laser (QCL) was used to detect N2O. Concentrations of the emissions were detected in the range of 5.3 to 7.4 ppmv for diesel/beef tallow biodiesel blends combustion and in the range of 4.3 to 11.0 ppmv for diesel/sugar cane diesel/beef tallow biodiesel blends combustion. The technique used was very sensitive and selective to identify and determine the emission concentrations of N2O.

Temporal networks are widely used to map phenomena into complex systems in several research disciplines, such as computer science, business, and biology. Several layouts can be used in visual analyses of temporal networks. The identification of the most suitable for a given task is, however, not trivial. This paper presents a user study that analyzes the performance of four different layouts: Massive Sequence View (MSV), Temporal Activity Map, matrix animation, and structural animation, when applied to pattern detection tasks of time-evolving networks. Our results show that all four layouts are appropriate to perform the evaluated tasks; however, the structural animation and MSV scored higher across different types of users.

CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Redes temporais representam interações entre entidades do domínio com a informação adicional de quando essas comunicações ocorrem. A visualização de redes temporais tem um importante papel no reconhecimento de propriedades das redes que seriam difíceis de serem percebidas sem uma estratégia de visualização adequada. Devido à grande quantidade de informação nessas redes, mais atenção tem sido dada em relação a escalabilidade visual associada com visualizações produzidas, mas ainda representa um problema não resolvido e com falta de abordagens específicas. Neste trabalho são propostas novas estratégias para melhorar a visualização de redes temporais. Especificamente, é proposta uma técnica de ordenação de nós escalável para a visualização de redes temporais, chamada de Community-based Node Ordering (CNO), que combina detecção de comunidade estática com técnicas de ordenação de nós, juntamente com uma taxonomia para categorizar os padrões das atividades. É apresentado também um método de visualização que permite a comparação entre dois algoritmos de detecção de comunidades para ajudar a decidir qual deles é melhor para a análise visual de comunidades. Também são abordados estratégias para a visualização de processos dinâmicos em redes, como espalhamento de rumores e doenças. Além disso, é conduzido um experimento com usuário com a definição de diferentes tarefas em redes temporais, a fim de identificar quais são as melhores formas de visualizar de acordo com diferentes tarefas. Por fim, é descrito o sistema Dynamic Network Visualization (DyNetVis), mostrado suas especificações, requisitos, funcionalidades e impacto na área. Os experimentos foram gerados com análises quantitativas e qualitativas utilizando redes reais em diferentes contextos, para mostrar que as visualizações propostas e suas categorizações ajudaram na identificação de padrões que seriam difíceis de serem vistos sem o uso dessas técnicas de visualização. Temporal networks represent interactions among entities of a given domain with additional information about when such interactions occur. The visualization of temporal networks plays a key role in the recognition of properties that would be difficult to perceive without an adequate visualization strategy. Due to a large amount of information provided by these networks, more attention has been given to issues related to the visual scalability associated with the produced layouts, but this still represents an unsolved problem and lacks effective techniques. We propose in this thesis novel techniques to enhance the visualization of temporal networks. Specifically, a scalable node reordering technique for temporal network visualization, named Community-based Node Ordering (CNO), combining static community detection with node reordering techniques, along with a taxonomy to categorize activity patterns. In addition, a visualization method that allows the comparison of two community detection algorithms is presented in order to decide which one is better for visual analysis of communities. Another contribution is the analysis of dynamic processes, as spreading rumors, diseases, applied in the visualization of temporal networks. Furthermore, we conducted a user experiment consisting of the application of different tasks in temporal networks, in order to find the relation of the layouts with the most appropriate tasks. Finally, the Dynamic Network Visualization (DyNetVis) system demonstrates the software specifications, examples, functionalities, and impact in the study field. We performed experiments with qualitative and quantitative analyses using real networks in several fields to show that the proposed layouts and categorization helped in the identification of patterns that would otherwise be difficult to see. Tese (Doutorado)

The temporal dimension increases the complexity of network models but also provides more detailed information about the sequence of connections between nodes allowing a more detailed mapping of processes taking place on the network. The visualisation of such evolving structures thus permits faster identification of non-trivial activity patterns and provides insights about the mechanisms driving the dynamics on and of networks. In this chapter, we introduce key concepts and discuss visualisation methods of temporal networks based on 2D layouts where nodes correspond to horizontal lines with circles to represent active nodes and vertical edges connecting those active nodes at given times. We introduce and discuss algorithms to re-arrange nodes and edges to reduce visual clutter, layouts to highlight node and edge activity, and visualise dynamic processes on temporal networks. We illustrate the methods using real-world temporal network data of face-to-face human contacts and simulated random walk and infection dynamics.

The COP 21 (21st Conference of Parties) held in 2015, in Paris, proposed to limit the average global temperature increase at a maximum of 2 °C. Brazil has programs for reducing GHGs through Intended Nationally Determined Contributions (INDC) in the energy sector. Between 2012 and 2015 Brazil faced a drastic reduction in rainfall volumes which led to a decrease in hydroelectric generation, then offset by thermoelectric generation, with an increase in its emissions. The objective herein is to review the expansion in the use of renewable energy sources to meet the INDC's goals, given the future vulnerability of the Brazilian electricity matrix. The use of renewable energy such as wind, solar and co-generation for electric production has grown considerably in Brazil. The growth of wind power generation was a result of the investment initiated by these public policies to promote the Brazilian wind industry through the Programme of Incentives for Alternative Electricity Sources (PROINFA), the increase of wind generation in both South and Northeast subsystems. Wind energy is aimed to reach 20 GW of electricity production by 2024. The public and private initiatives in the solar energy segment reflect, first and foremost, upon the creation of a solar photovoltaic industry in the country and, from there, a consequent expansion of this energy's usage. The cogeneration processes have contributed to industries in a positive way, both in supplying electricity for internal energy plants' demands as well as those of the national electric system. Therefore, the diversification of the energy matrix is a goal to be achieved. The use of new renewable energy sources and the maintenance of investments in hydropower are part of the Brazilian strategy to turn its electric matrix less vulnerable climate change consequences..

As preferências dos usuários são muito dinâmicas, uma vez que eles tendem a explorar uma vasta gama de informações e modificar seus gostos ao longo do tempo. Modelos existentes que capturam a evolução de preferências no domínio de músicas são muito restritos e não levam em conta a influência social. Este trabalho propõe uma análise sobre a evolução das preferências musicais dos usuários de uma rede social de músicas, utilizando redes temporais de similaridade. Como resultado, foi detectado que poucos usuários variam significativamente suas preferências. A tendência é que artistas e usuários semelhantes mantenham suas similaridades ao longo do tempo.

A visualização de redes temporais, isto é, a visualização de redes que representam interações entre as instâncias de um domínio e que possuem informações sobre quando essas interações ocorreram, exerce um papel relevante na identificação de propriedades que seriam de difícil percepção sem uma adequada estratégia de visualização. Este trabalho apresenta um estudo de caso de aplicação de um sistema de análise visual em uma rede de contato hospitalar. O objetivo é demonstrar a aplicabilidade dessa ferramenta no auxílio a tomadas de decisão em relação a dados daárea da saúde. Os resultados alcançados demonstram a facilidade da análise da rede e a percepção de padrões, agilizando e deixando as tomadas de decisão mais confiáveis.

The concept of networks has been important in the study of complex systems. In networks, links connect pairs of nodes forming complex structures. Studies have shown that networks not only contain structure but may also evolve in time. The addition of the temporal dimension adds complexity on the analysis and requests the development of innovative methods for the visualization of real-life networks. In this paper we introduce the Dynamic Network Visualization System (DyNetVis), a software tool for visualization of dynamic networks. The system provides several tools for user interaction and offers two coordinated visual layouts, named structural and temporal. Structural refers to standard network drawing techniques, in which a single snapshot of nodes and links are placed in a plane, whereas the temporal layout allows for simultaneously visualization of several temporal snapshots of the dynamic network. In addition, we also investigate two approaches for temporal layout visualization: (i) Recurrent Neighbors, a node ordering strategy that highlights frequent connections in time, and (ii) Temporal Activity Map (TAM), a layout technique with focus on nodes activity. We illustrate the applicability of the layouts and interaction functionalities provided by the system in two visual analysis case studies, demonstrating their advantages to improve the overall user experience on visualization and exploratory data analysis on dynamic networks.

There are many proposals in the literature that use Information Visualization to visualize networks, but there still exist several challenges in the area, as the lack of thechniques that improve the interpretation of big data and their relationships. This thesis presents the study and application of data visualization techniques in Temporal Networks. The goal is to identify patterns that will help to explain phenomena and behavior from various scenarios. As a result of this study, we present a system, called DyNetVis, which can be used to test the effectiveness of the proposed techniques, well be make these techniques available to the scientific community. Finally, we present results of the application of the proposed techniques in temporal networks using the developed system. With the utilization of the propose techniques, it is possible to recognize patterns that were difficult to identify without the techniques. Existem diversas propostas na literatura para utilizar Visualização da Informação em redes, mas ainda existem vários desafios na área, como a falta de técnicas que melhorem a interpretação de grandes quantidades de dados e relacionamentos. Este trabalho apresenta o estudo e aplicação de técnicas de visualização para análise e exploração de redes temporais. A ideia é identificar a presença de padrões e tendências que ajudem a explicar fenômenos e comportamentos em diversos cenários. Este trabalho apresenta também o sistema computacional DyNetVis, que pode ser utilizado para comprovar a eficácia das estratégias propostas, bem como tornar essas estratégias disponíveis à comunidade científica. Finalmente, são apresentados resultados da aplicação das técnicas propostas em diversas redes temporais, utilizando o sistema desenvolvido. Com a utilização das técnicas propostas, é possível que se reconheça padrões que antes eram difíceis de serem identificados. Mestre em Ciência da Computação

A cultivar de trigo BRS Guamirim foi desenvolvida pela Embrapa e resultou de um cruzamento entre os genitores Embrapa 27/Buck Nandu e PF 93159. Possui ciclo precoce, baixa estatura de planta e intenso afilhamento. Apresenta equilibrada reação às principais moléstias do trigo, pertence à classe pão e demonstra adaptabilidade às diferentes regiões tritícolas do país, com estabilidade de produção. Seu potencial de rendimento é superior a 5 t ha-1. Wheat cultivar BRS Guamirim was developed by Embrapa and resulted from a cross among Embrapa 27/Buck Nandu and PF 93159. BRS Guamirim has early cycle, short plant stature and high tillering. It shows equilibrate behaviour to mainly wheat deseases, belongs to bread class and is adapted to different wheat regions, showing production stability. Its grain yield potential is higher than 5 t ha-1.

Plants and seeds of oat cultivar BRS Centauro, of the species Avena brevis Roth., are highly uniform. The crop cycle is long, the suitability as fodder excellent, and leaf production particularly high, resulting in better quality forage than that of the black oat forage controls.

Wheat cultivar 'BRS Guabiju' was developed by Embrapa. It resulted from a cross of BR 23 and PF 86743. 'BRS Guabiju' has high gluten strength and is stable for this trait in different environments of evaluation.

Wheat cultivar ‘BRS Louro’ was developed by Embrapa (Brazilian Agricultural Research Corporation). It was result of a cross of PF 869114 and BR 23. ‘BRS Louro’ has excellent agronomic features, medium resistance to scab and high grain productivity.

No Centro Nacional de Pesquisa de Trigo (CNPT - Embrapa Trigo), em 1999, genótipos de trigo integrantes do bloco de cruzamento foram avaliados quanto à altura de planta, à duração do ciclo até o espigamento, ao comprimento do pedúnculo e ao número de grãos por espiga. Relacionando essas características, foram estudados 122 genótipos em duas épocas de semeadura, que consistiram os blocos. Foram medidos dez pedúnculos do afilho principal, de cada genótipo, e contou-se o número total de grãos de cada espiga. Para a apresentação dos resultados, foram considerados os valores médios dessas avaliações. Para a análise estatística, considerou-se o experimento como blocos casualizados. Dos resultados obtidos, concluiu-se que os genótipos de trigo BR 18, BR 42 e Sonora 64 destacam-se por porte baixo e ciclo precoce, enquanto Florida 301 e "Trigo de chapéu" destacam-se por porte alto e ciclo longo até o espigamento. A altura de planta mostra elevada correlação com comprimento do pedúnculo e duração do ciclo até o espigamento, e esta, com o comprimento de pedúnculo. Os genótipos de trigo CNT 10 e PF 92130 são indicados com finalidades artesanais por suas características de pedúnculo longo e número de grãos por espiga acima da média. O estudo mostra grande variabilidade genotípica em trigo quanto às características avaliadas, fornecendo informações sobre os genótipos que poderão ser utilizados por melhoristas, técnicos e agricultores.

A cultivar de soja BRS 153, oriunda do cruzamento EMBRAPA 1 x Braxton, é de ciclo médio, possui plantas de crescimento determinado, flor branca, pubescência cinza e grãos de hilo marromclaro. É resistente ao cancro-da-haste (Diaporthe phaseolorum f. sp. meridionalis), à podridão-parda-da-haste (Phialophora gregata), à mancha-olho-de-rã (Cercospora sojina) e ao oídio (Microsphaera diffusa). O rendimento médio de grãos, em 19 ambientes do Rio Grande do Sul, foi 12% e 14% superior aos das cultivares RS 7-Jacuí e BR-16, respectivamente. É indicada para semeaduras em novembro, em todo o Rio Grande do Sul.

A BRS 205, cultivar de soja de ciclo semiprecoce, obtida do cruzamento [BR-16(2) x Ocepar 8] x Tracy-M, é indicada para o Rio Grande do Sul, em semeaduras de novembro. Possui crescimento determinado, plantas de flor branca, pubescência marrom, porte baixo e grãos de hilo preto. Tem resistência ao cancro-da-haste (Diaporthe phaseolorum f. sp. meridionalis), à podridão-parda-da-haste (Phialophora gregata), à mancha-olho-de-rã (Cercospora sojina) e à pústula bacteriana (Xanthomonas axonopodis pv. glycines). É moderadamente resistente ao oídio (Microsphaera diffusa). O rendimento médio de grãos foi 6% e 11% superior ao das cultivares RS 7-Jacuí e BR-16, respectivamente.

In order to meet the demands for higher grain yielding wheat (Triticum aestivum L.) cultivars, in addition to higher resistance levels to diseases and better breadmaking quality, the cultivar EMBRAPA 52 was released in 1996 for the State of Rio Grande do Sul, Brazil. It was developed at Embrapa-Centro Nacional de Pesquisa de Trigo, showing early cycle, mid-high stature, and resistance to aluminum soil conditions. It can show lodging problems under high soil fertility conditions and sprouting under delayed rains at harvest time. At releasing, it has shown good plant-health performance under field conditions. At seedling stage, it was susceptible to five races of leaf rust and resistant to all races of stem rust found in Brazil. It is moderately susceptible to glume blotch and susceptible to loose smut. It is resistant under field conditions to mildew and soil borne mosaic virus. Over the 1993-95 period, EMBRAPA 52 performed as the highest grain yielding wheat among all cultivars and lines tested in Rio Grande do Sul, producing 13% over the checks in the average of all locations of the State. Considering alveograph and farinograph tests, it was preliminarily classified as superior in the commercial class, being indicated for breadmaking and to manufacture crackers and pastry products.

Rye cultivar BRS Serrano was developed by Embrapa. It resulted from a cross between the rye populations Garcia and Bage. BRS Serrano attains high dry matter yield as forage plant and high grain yields

Wheat cultivar BRS Camboim was developed by Embrapa (Brazilian Agricultural Research Institution). It resulted from a double cross of Embrapa 27/Klein Cartucho and PF 869114/BR 23. BRS Camboim presents short height and good performance regarding main wheat diseases.

BRS Borema is an early maturing, two-rowed spring barley registered in 2003 for commercial production in Southern Brazil, bred by Embrapa Trigo. It combines good yield potential with superior malting quality and a reasonable level of disease (net blotch, powdery mildew, leaf rust) resistance. It is well-adapted to all major production regions of malting barley in Brazil.

The soybean [Glycine max (L.) Merrill] cultivar BRS 154, originated from a crossing between Embrapa1 x Braxton, was developed by Embrapa Wheat along with Embrapa Soybean. The cultivar BRS 154 was released in 1998 and designed to be cropped in southern Brazil. It has a high yield potential and good adaptation under no-tillage. It has field resistance to soybean stem canker, caused by Diaporthe phaseolorum f. sp. meridionalis, and is resistant to brown stem rot, caused by Phialophora gregata , frogeye leaf spot, caused by Cercospora sojina, powdery mildew, caused by Microsphaera diffusa, and bacterial pustule, caused by Xanthomonas axonopodis pv. glycines. . Made available in DSpace on 2018-04-25T00:36:08Z (GMT). No. of bitstreams: 1 c8128f424c436b81.pdf: 160714 bytes, checksum: 7e31e69901672f22b317b2e40a2e853f (MD5) Previous issue date: 2003-10-28

A Cevada BR 2, criada pela Embrapa-Centro Nacional de Pesquisa de Trigo (CNPT), foi lançada para cultivo em 1989. Originou-se de sete plantas selecionadas em F3 do cruzamento FM 424/TR 206, realizado em 1979, em Passo Fundo, RS. A BR 2 é uma cevada de primavera, do tipo de duas fileiras de grãos, com ciclo precoce, ampla adaptação e porte baixo. É a primeira cultivar brasileira resistente a Pyrenophora teres, agente causal da mancha-reticular, principal moléstia da cevada no Brasil. Em oito anos de avaliação no Ensaio Nacional de Cevada, conduzido em 12 locais da Região Sul, a BR 2 rendeu entre 1.621 e 4.014 kg/ha de grãos de primeira qualidade, superando a cultivar Antarctica 05 em 3% no RS e SC, em 13% no PR, e em 6% na média dos 96 experimentos (12 locais x 8 anos). Na lavoura, a BR 2 tem produzido rendimentos acima de 5.000 kg/ha. Aprovada como cervejeira em 1992, ocupou 30% da área semeada em 1993 e 90% em 1997. A BR 2 representa um marco no progresso do melhoramento genético da cevada no país, contribuindo decisivamente para o aumento da competitividade da produção doméstica. Barley cultivar BR 2 developed by the Embrapa-Centro Nacional de Pesquisa de Trigo (CNPT) was released in 1989. BR 2 traces back to seven plants selected in the F3 from the cross FM 424/TR 206 made in Passo Fundo, RS, in 1979. BR 2 is a two row spring barley with wide adaptation, earliness and short straw. It is the first Brazilian cultivar resistant to Pyrenophora teres, causal agent of net blotch, a major barley disease in Brazil. In eight years of yield testing in the National Barley Trial in twelve locations of Southern Brazil, BR 2 yielded between 1,621and 4,014 kg/ha of plump kernels, with 3%, 13% and 6% yield increase over the check cultivar Antarctica 05 in the States of Rio Grande do Sul and Santa Catarina, Paraná and in the mean of 96 trials, respectively. On the farm fields, BR 2 has yielded over 5,000 kg/ha. Since its approval as a malting barley in 1992, it has been widely used, taking up 30% in 1993 and 90% in 1997 of the area sown. Barley BR 2 represents a cornerstone in the history of barley breeding in Brazil and is making a significant contribution to the competitiveness of the domestic barley production.

1 ABSTRACT - BRS 224 barley, bred by Embrapa Trigo, is a two-rowed spring barley released in 2002 for cultivation in Southern Brazil. BRS 224 is an early maturing, medium tall and high yielding cultivar, resistant to diseases (net blotch, powdery mildew, leaf rust), lodging-resistant, and broadly adapted to the crop production regions of Southern Brazil.

BRS 66, oriunda do cruzamento BR 83-147 x FT-Abyara, é indicada para cultivo no Rio Grande do Sul. Na média de 21 ambientes no RS, no período de 1993/94 a 1995/96, essa cultivar apresentou rendimento médio de grãos de 2.883 kg/ha. Apresenta resistência ao cancro-da-haste, à podridão-parda-da-haste, à mancha-olho-de-rã, à raça 1 de Phytophthora sojae, à pústula-bacteriana e ao oídio. Tem flor branca, pubescência marrom, tegumento da semente amarelo-fosco, hilo marrom e tipo de crescimento determinado. É de ciclo médio e apresenta estatura da planta de média a alta, com boa resistência ao acamamento. Originated from the cross BR 83-147 x FT-Abyara, BRS 66 is indicated for seeding in the state of Rio Grande do Sul, Brazil. It was evaluated for grain yield and agronomic characteristics in multilocation trials from 1993/94 up to 1995/96 and showed a mean grain yield of 2,883 kg/ha. BRS 66 is resistant to soybean stem canker, brown stem rot, frog-eye leaf spot, race 1 of Phytophthora sojae, bacterial pustule and powdery mildew. This cultivar presents white flowers, brown pubescence, dull yellow seed tegument, brown hila, and determinate growth habit. Plant stature varies from medium to high, with good resistance to lodging. It shows a medium maturity cycle.

The early-maturing soybean [Glycine max (L.) Merrill] cultivar BRS 138 originated from a cross between BR-16 x BR 85-16140, which was developed by Embrapa Wheat in conjunction with Embrapa Soybean. The cultivar BRS 138 was released in 1997 for cropping in the state of Rio Grande do Sul. It has a high yield potential and is resistant to soybean stem canker, caused by Diaporthe phaseolorum f. sp. meridionalis, brown stem rot, caused by Phialophora gregata, frogeye leaf spot, caused by Cercospora sojina, and bacterial pustule, caused by Xanthomonas axonopodis pv. glycines, as well as to race 1 of Phytophthora sojae. It is susceptible to powdery mildew, caused by Microsphaera diffusa. The cultivar presents yield and agronomic characteristics similar to IAS 5, which is a well known cultivar in southern Brazil, but differs from IAS 5 in that BRS 138 is resistant to both brown stem rot and soybean stem canker.

The wheat cultivar ‘BRS 277’ was developed by Embrapa (Empresa Brasileira de Pesquisa Agropecuaria), resulting from a cross between OR1 and Coker 97-33. The plant height of ‘BRS 277’ is short, frost resistance in the vegetative stage is good and resistance to leaf rust moderate.