-The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F 2 population derived from the self-fertilization of the F 1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped, while the Bayesian generalized model identified only two markers belonging to these groups. Lower prediction error rates (1.60%) were observed for predicting leaf rust resistance in Arabica coffee when artificial neural networks were used instead of Bayesian generalized linear regression (2.4%). The results showed that artificial neural networks are a promising approach for predicting leaf rust resistance in Arabica coffee.Index terms: Coffea arabica, Hemileia vastatrix, artificial intelligence, molecular markers, prediction. Redes neurais artificiais comparadas com modelos lineares generalizados sob o enfoque bayesiano para predição de resistência à ferrugem em café arábicaResumo -O objetivo deste trabalho foi avaliar o uso de redes neurais artificiais em comparação à modelagem por meio de modelos lineares generalizados na predição de resistência à ferrugem em café arábica (Coffea arabica). Foram utilizados 245 indivíduos provenientes de uma população F 2 , oriundos da autofecundação do híbrido F 1 H511-1, resultante do cruzamento da cultivar suscetível Catuaí Amarelo IAC 64 (UFV 2148-57) e do genitor resistente Híbrido de Timor (UFV 443-03). Os 245 indivíduos foram genotipados com 137 marcadores. Realizaram-se análises com redes neurais artificiais e com modelos lineares generalizados sob o enfoque bayesiano. As redes neurais identificaram quatro marcadores importantes pertencentes a grupos de ligação que foram recentemente mapeados, enquanto o modelo generalizado bayesiano identificou somente dois marcadores pertencentes a esses grupos. Foram observadas taxas de erro de predição inferiores (1,60%) para predizer a resistência à ferrugem em café arábica, quando foram utilizadas as redes neurais artificiais em vez de modelos lineares generalizados sob o enfoque bayesiano (2,4%). Os resultados mostraram que as redes neurais artificiais são uma abordagem promissora para predizer a resistência à ferrugem em café arábica.Termos para indexação: Coffea arabica, Hemileia vastatrix, inteligência artificial, marcadores moleculares, predição.

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The objective of this work was to evaluate the potential of computational intelligence and canonical variables for studies on the genetic diversity between biomass sorghum (Sorghum bicolor) genotypes. The experiments were carried out in the experimental field of Embrapa Milho e Sorgo, in the municipalities of Nova Porteirinha and Sete Lagoas, in the state of Minas Gerais, Brazil. The following traits were evaluated: days to flowering, plant height, fresh biomass yield, total dry biomass, and dry biomass yield. The study of genetic diversity was performed through the analysis of canonical variables. For the recognition of the organization pattern of genetic diversity, Kohonen’s self-organizing map was used. The use of canonical variables and a self-organizing map were efficient for the study of genetic diversity. The application of computational intelligence using a self-organized map is promising and efficient for studies on the genetic diversity between biomass sorghum genotypes.

ABSTRACT. Brazil is among the five largest producers of cotton in the world, cultivating the species Gossypium hirsutum L. r. latifolium Hutch. The cultivars should have good fiber quality as well as yield. Genetic improvement of fiber traits requires the study of the genetic structure of the populations under improvement, leading to the identification of promising parent plants. To this end, it is important to acquire some information, such as estimates of genetic variance components and heritability coefficients, which will support the appropriate choice of the breeding strategy to be employed as well as enable the estimation of gains from selection. This study aimed to evaluate some agronomic characteristics, such as fiber quality and yield, estimating genetic parameters for the purpose of predicting earnings. Twelve cultivars of cotton, including four male progenitors (CNPA 01-42, BRS Verde, Glandless, and Okra leaf) and eight female progenitors (Delta opal, CNPA 7H, Aroeira, Antares, Sucupira, Facual, Precoce 3, and CNPA 8H), were used in performing crosses according to design I, proposed by Comstock and Robinson (1948). The experimental design was a randomized block with four replications. We observed genetic variability among all traits as well as higher efficiency of selection for the gains related to traits. Our results showed that the combined selection presented the highest genetic gains for all traits. For fiber length, the female/male selection and the combined selection resulted in the highest genetic gain.

Mendel, através da observação dos fenótipos da ervilha, estudou a transmissão dos caracteres e estabeleceu o Princípio da Segregação (PIERCE, 2004). Devido à dificuldade de ministrar estes conteúdos no Ensino Médio, acreditamos, assim como Kishimoto (1996), que o professor deva adotar práticas que atuem nos componentes internos da aprendizagem, importantes para a assimilação de conhecimentos por parte do aluno. [...]

Esta obra visa proporcionar aos técnicos, pesquisadores, e docentes, conhecimentos introdutórios e fundamentais sobre a Genética de Populações. Ela norteia o leitor ao entendimento de conceitos e técnicas em atividade didáticas no aplicativo livre GPOP – Genética de Populações, desenvolvido como ferramenta auxiliar de ensino e aprendizagem. Estudos sobre a Genética de Populações são indispensáveis para profissionais preocupados com a preservação da diversidade genética, com o manejo sustentável e racional de populações e com a história evolutiva de grupos genéticos. Também interessam a profissionais de áreas correlatas, tais como o melhoramento genético, genômica, filogenia e filogeografia, dentre outras. Neste livro são apresentadas teorias e aplicações sobre assuntos relevantes, tais como equilíbrio de Hardy-Weinberg, desequilíbrio de ligação, acasalamentos, endogamia, fixação e oscilação gênica que muito contribuirão para a formação de profissionais da área. Ao apresentar ao público uma obra associada com texto e aplicativo computacional, os autores demonstram preocupação e comprometimento com os ensinamentos fundamentados em ensino e prática que, certamente, irão orientar a melhor utilização de materiais genéticos e recursos humanos, técnicos e financeiros, que normalmente são escassos.

In a society that generates information rapidly, schools have to fulfil their programmes imaginatively. Thus, extra-curricular activities may be helpful for the students to acquire wider knowledge than that they may get within the classrooms. On the other hand, randomness is present in almost all everyday decisions, mainly based on prior information so it is important to have at least a rough idea on how specific events may affect the chances of other events. We explore both ideas here in the context of a science fair, in which two high-school senior students conducted an investigation about conditional probability using a game called "Shut the box". We also want to pose, as a research question, if, after their participation in the science fair, these students have reached higher levels in probabilistic reasoning compared to their classmates or have acquired knowledge about concepts far beyond the official curriculum.