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URI permanente para esta coleçãohttps://locus.ufv.br/handle/123456789/11845

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Agora exibindo 1 - 5 de 5
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    Fuzzy control systems for decision-making in cultivars recommendation
    (Acta Scientiarum. Agronomy, 2018) Carneiro, Vinícius Quintão; Prado, Adalgisa Leles do; Cruz, Cosme Damião; Carneiro, Pedro Crescêncio Souza; Nascimento, Moysés; Carneiro, José Eustáquio de Souza
    The objective of the present study was to propose fuzzy control systems to support the recommendation of cultivars of different agronomic crops. Grain yield data from 23 lines and 2 cultivars of red bean were used to evaluate the applicability of these controllers. Genotypes were evaluated in nine environments in the Zona da Mata region, Minas Gerais State, Brazil. Using the parameters of Eberhart and Russell analysis, fuzzy controllers were developed with the Mamdani and Sugeno inference systems. Analyses of adaptability and stability were carried out by the method of Eberhart and Russell. The parameters obtained for each genotype were submitted to the respective controllers. There were significant genotypes x environments interaction, which justified the necessity of performing an adaptability and stability analysis. For both controllers (Mamdani and Sugeno), seven lines presented general adaptability, while only one presented adaptability to unfavorable environments. It was also found that both inference systems were useful for developing controllers that had the aim of recommending cultivars. Thus, it was noted that fuzzy control systems have the potential to identify the behavior of bean genotypes.
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    Direct, indirect and simultaneous selection as strategies for alfalfa breeding on forage yield and nutritive value
    (Pesquisa Agropecuária Tropical, 2018-04) Santos, Iara Gonçalves dos; Cruz, Cosme Damião; Nascimento, Moysés; Rosado, Renato Domiciano Silva; Ferreira, Reinaldo de Paula
    Alfalfa breeding aimed at trait improvement for livestock feed takes longer periods of time, if compared to many other crops. Therefore, better selection methods are necessary for the success of alfalfa breeding programs. Although knowing about selection methods is quite important, there is a notable lack of information, as regards successful solutions. This study aimed to use direct, indirect and simultaneous selection methods for selecting alfalfa cultivars, based on yield traits and nutritive value. The evaluated traits were subdivided into two groups: forage yield and nutritive value. Selection gains were estimated by direct, indirect and simultaneous selection for each group, considering the selection of the 25 % best cultivars. Direct and indirect selections among genotype averages are not efficient to provide the desirable responses to the whole set of traits. The results for simultaneous selection, using the Tai index, provided a more balanced gain distribution to the set of traits in all cuts. The simultaneous selection allowed the identification of the 5681 and Verdor cultivars in the first cut, as well as ProINTA Patricia in the second cut, as superior in the two groups of evaluated traits.
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    Quantile regression for genome-wide association study of flowering time-related traits in common bean
    (Plos One, 2018) Nascimento, Moysés; Nascimento, Ana Carolina Campana; Silva, Fabyano Fonseca e; Barili, Leiri Daiane; Vale, Naine Martins do; Carneiro, José Eustáquio; Cruz, Cosme Damião; Carneiro, Pedro Crescêncio Souza; Serão, Nick Vergara Lopes
    Flowering is an important agronomic trait. Quantile regression (QR) can be used to fit models for all portions of a probability distribution. In Genome-wide association studies (GWAS), QR can estimate SNP (Single Nucleotide Polymorphism) effects on each quantile of interest. The objectives of this study were to estimate genetic parameters and to use QR to identify genomic regions for phenological traits (Days to first flower—DFF; Days for flowering—DTF; Days to end of flowering—DEF) in common bean. A total of 80 genotypes of common beans, with 3 replicates were raised at 4 locations and seasons. Plants were genotyped for 384 SNPs. Traditional single-SNP and 9 QR models, ranging from equally spaced quantiles (τ) 0.1 to 0.9, were used to associate SNPs to phenotype. Heritabilities were moderate high, ranging from 0.32 to 0.58. Genetic and phenotypic correlations were all high, averaging 0.66 and 0.98, respectively. Traditional single-SNP GWAS model was not able to find any SNP-trait association. On the other hand, when using QR methodology considering one extreme quantile (τ = 0.1) we found, respectively 1 and 7, significant SNPs associated for DFF and DTF. Significant SNPs were found on Pv01, Pv02, Pv03, Pv07, Pv10 and Pv11 chromosomes. We investigated potential candidate genes in the region around these significant SNPs. Three genes involved in the flowering pathways were identified, including Phvul.001G214500, Phvul.007G229300 and Phvul.010G142900.1 on Pv01, Pv07 and Pv10, respectively. These results indicate that GWAS-based QR was able to enhance the understanding on genetic architecture of phenological traits (DFF and DTF) in common bean.
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    O uso da variância como metodologia alternativa para integração de mapas genéticos
    (Pesquisa Agropecuária Brasileira, 2010-10-20) Salgado, Caio Césio; Cruz, Cosme Damião; Nascimento, Moysés; Barrera, Carlos Felipe Sanches
    O objetivo deste trabalho foi desenvolver um processo de integração de mapas genéticos, com o uso do inverso da variância, e testar sua eficiência. Foram utilizadas populações simuladas F2 codominante e de retrocruzamento, com tamanhos populacionais de 100, 150, 200 e 400 indivíduos, tendo-se considerado uma espécie diploide fictícia com 2n = 2x = 2 cromossomos, com o comprimento total do genoma por grupo de ligação estipulado em 100 cM, 21 marcas por grupo de ligação e marcadores equidistantes em 5 cM. Os genomas foram comparados quanto ao tamanho do grupo de ligação, variância das distâncias entre marcas adjacentes, correlação de Spearman e quanto ao estresse relativo à adequação das distâncias estimadas. Cada genoma simulado foi fragmentado em quatro novos mapas: três com oito marcadores e um com nove marcadores, cada qual com quatro marcadores âncoras. Os mapas foram alinhados, ordenados, integrados e, em seguida, comparados ao mapa de origem. O processo de integração de mapas proposto mostrou-se eficiente. Os mapas gerados tiveram pequena tensão interna em comparação aos mapas dos quais se originaram. A integração de mapas depende do tipo de população utilizada, tamanho da população, tipo de marcador, da frequência de recombinação e da fase de ligação.
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    Application of neural networks to predict volume in eucalyptus
    (Crop Breeding and Applied Biotechnology, 2015-03-16) Bhering, Leonardo Lopes; Cruz, Cosme Damião; Peixoto, Leonardo de Azevedo; Rosado, Antônio Marcos; Nascimento, Moysés; Laviola, Bruno Galveas
    The aim of this study was to evaluate the methodology of Artificial Neural Networks (ANN) in order to predict wood volume in eucalyptus and its impacts on the selection of superior families, and to compare artificial neural network with regression models. Data used were obtained in a random block design with 140 half-sib families with five replications at three years of age, and four replications at six years of age, both with five plants per plot. The volume was estimated using ANN and regression models. It was used 2000 and 1500 data to train ANN, and 1500 and 1300 to validate ANN for 3 and 6 years of age, respectively. It is concluded that ANN can help improving the accuracy to measure the volume in eucalyptus trees, and to automate the process of forestry inventory and were more accurate in predicting wood volume than almost all regression models.