ABSTRACT Most studies on genomic selection in plant breeding compare different statistical methods of univariate approach. However, multi-trait methodologies should be considered since they allow the simultaneous selection of superior genotypes in several economic traits. Here, the aims were to compare the selection accuracy and efficiency of the multivariate partial least square (MPLS) method compared with random regression best linear unbiased predictor (rrBLUP), Bayesian Lasso (Blasso) and univariate partial least square (UPLS) and to develop genomic selection indexes efficient for superior genotypes identification in plant breeding. Ten F2 populations with 800 individuals were simulated, considering four traits with different heritabilities. Genomic selection analyses using rrBLUP, Blasso, UPLS, and MPLS were conducted. Four genomic selection indexes were elaborated by the sum of the marker effects obtained for each trait, weighted by the respective residual variance. Multi-trait indexes were developed based on the assumptions of each methodology mentioned (rrBLUP, Blasso, UPLS, and MPLS), and were denominated I-rrBLUP, I-Blasso, I-UPLS, and I-MPLS. Processing time, selective accuracy, selection gains, and selection coincidence were used to compare the methods and the selection indexes proposed. The MPLS method had similar results compared to UPLS method for the low heritability traits and was less efficient than the rrBLUP and Blasso. The genome selection indexes provided the highest total genetic gains. The I-rrBLUP and I-MPLS indexes stood out for high efficiency in selecting superior genotypes in the shortest processing time. Results suggest that the genomic selection indexes proposed in this study may be promising for plant breeding programs.

Abstract The objectives of this study were to estimate the general and specific combining ability of the parents, and to verify the existence of maternal effect and inbreeding depression in Jatropha. The experiment was carried out from 2010 to 2015, in the municipality of Planaltina, Distrito Federal. The following traits were evaluated: plant height, stem diameter, canopy projection between the row, canopy projection on the row, number of branches, mass of one hundred grains, and grain yield. Cytoplasmic effects and effects of female parent nuclear genes were observed for all traits. Dominance effects were predominant in the genetic control of all traits. Genotypes 107 and 190 were the superior parents for the reduction of the size, and for the increase of grain yield. No inbreeding depression was observed for grain yield. The most promising crosses for the conduction of segregating populations and increment in grain yield were 190x107, 107x190 and 259x107.

O objetivo deste trabalho foi avaliar a metodologia das redes neurais artificiais (RNA) para predizer o volume de madeira nos programas de melhoramento de eucalipto e na seleção de famílias comparando as RNA com modelos de regressão. O delineamento foi em blocos casualizados com 140 famílias de meios-irmãos, 5 e 4 repetições para 3 e 6 anos respectivamente, ambos com 5 plantas por parcela. Para o treinamento da rede, foi utilizado 2000 e 1500 indivíduos, e para validação foram utilizados 1500 e 1300 indivíduos, respectivamente, para 3 e 6 anos. Foi concluído que as RNA pode ajudar a melhorar a acurácia na medição do volume em árvores de eucalipto e automatizar o processo do inventário florestal. As RNA foram mais acuradas na predição do volume de madeira que quase todos os modelos de regressão.

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.

O objetivo deste trabalho foi selecionar famílias com desempenho superior e ampla variabilidade genética para cruzamentos dialelos e com potencial utilização no pré-melhoramento de dendê. O experimento consistiu em 42 famílias de irmãos completos, divididas em três ensaios com 16 famílias e 3 testemunhas comuns, sendo estes em delineamento em blocos ao acaso com quatro blocos, e 12 plantas por bloco. As características avaliadas no experimento foram número de cachos por planta (NCP), produção de cachos por planta (PCP) e peso médio de cacho (PMC). Com estimação dos componentes de variância verificou-se que existe uma maior variância genética dentro de famílias do que entre famílias. A herdabilidade para todas as características foram altas, acima de 0,75 e o coeficiente de variação ambiental encontrado para todas as características foi de baixo a moderado (entre 4 e 13). As famílias foram separadas em sete grupos pelo método de Tocher e em seis grupos com o método UPGMA. Visando a utilização das melhores famílias em cruzamentos dialelos, as famílias 15, 14, 22, 21, 28, 37, 33 e 39 foram selecionadas com base na performance individual, através do teste de Scott-Knott, e diversidade genética através do agrupamento.

The objective of this work was to select families with superior performance and large genetic variability for diallel crosses for potential use in the pre-breeding of oil palm. The experiment consisted of 42 full-sib families divided into three trials with 16 families and 3 witnesses in common in randomized blocks, with four blocks and 12 plants per block. The characteristics evaluated in the experiment were number of bunches per plant (NBP), bunch weight per plant (BWP) and bunch average weight per plant (BAW). The estimation of variance components showed that there was greater genetic variance within families than between families. The heritability for all traits was high, above 0.75, and the coefficient of environmental variation was low to moderate for all traits (between 4 and 13). Tocher's method separated families into seven groups, whereas the UPGMA method identified six groups. To use the best families in diallel crosses, families 15, 14, 22, 21, 28, 37, 33 and 39 were selected based on individual performance as determined by the Scott-Knott test and genetic diversity by grouping.

O presente trabalho teve como objetivo comparar a eficiência do Método de Mapeamento de características Oligogênicas (OTMM) e Método por Intervalo (IM) para a detecção de locos de características oligogênica (OTL) em linhagens endogâmicas recombinantes (RILs) de diferentes tamanhos. Foram utilizadas populações constituídas por 200, 500 e 1000 indivíduos e utilizou-se 100 repetições para cada tamanho da população. Quatro características foram avaliadas: C1, determinada por dois genes com 50 e 30% de efeitos sobre a expressão da característica; C2, governada por três genes, com 50, 20 e 10% de efeitos; C3, regulada por dois genes, cada um com 40% de efeito, e C4, controlada por dois genes, cada um com efeito de 50%. O IM foi eficiente na detecção de OTL em todas as características avaliadas, no entanto, para as características determinadas por dois genes com efeitos entre 40 e 50%, o OTMM foi mais eficiente na detecção e localização de OTL das marcas simuladas. O método de MI foi mais eficiente na detecção e localização de OTL nas marcas simulados, quando o efeito do gene variaram de 10 a 30%. Como as características oligogênica são governados por genes com maiores efeitos, a OTMM foi considerado o método mais eficiente para ser usado para este tipo de característica.

The present work aimed to compare the efficiencies of the Oligogenic Trait Mapping Method (OTMM) and Interval Method (IM) for detecting oligogenic trait loci (OTL) in Recombinant Inbred Line (RIL) populations of different sizes. Populations consisting of 200, 500 and 1,000 individuals were employed and 100 repetitions performed for each population size. Four characteristics were evaluated: C1, determined by two genes with 50 and 30% effects on expression of the characteristic; C2, governed by three genes with 50, 20 and 10% effects; C3, regulated by two genes, each with 40% effect; and C4, controlled by two genes, each with 50% effect. The IM was efficient at detecting OTL in all evaluated characteristics; however, for characteristics determined by two genes with effects between 40 and 50%, the OTMM was more efficient at detecting and localizing OTL in simulated marks. In contrast, the IM method was more efficient at detecting and localizing OTL in simulated marks when the gene effect ranged from 10 to 30%. As a result, because oligogenic characteristics are governed by genes with greater effects, the OTMM was considered the most efficient method to be used for this type of characteristic.

Este trabalho teve como objetivo avaliar o potencial risco de ocorrência da monilíase e os impactos das mudanças climáticas sobre esta doença nas décadas futuras, caso este patógeno sejam introduzida no Brasil. Para tal, elaboraram-se mapas de favorabilidade climática à ocorrência da monilíase no período atual e futuro. Os cenários futuros empregados (A2 e B2) foram centrados nas décadas de 2020, 2050 e 2080. Estes cenários foram obtidos a partir de seis modelos climáticos globais (MCG's) disponibilizados pelo terceiro relatório do Painel Intergovernamental de Mudanças Climáticas (IPCC). No período atual existem extensas áreas que apresentam condições de favorabilidade climática a monilíase no Brasil, principalmente em regiões que apresentam alto risco de introdução do patógeno. Considerando os cenários de aquecimento global previsto pelo IPCC, haverá a redução do potencial risco climático de ocorrência da monilíase no Brasil. Tal redução é predita em ambos cenários futuros, porém ocorrerá de forma mais acentuada admitindo-se o cenário A2. No entanto, ainda haverá áreas que apresentaram condições de favorabilidade climática ao desenvolvimento da doença, principalmente nas maiores regiões produtoras do Brasil. Além disso, tanto o patógeno como o hospedeiro poderão sofrer alterações com mudanças climáticas, o que influenciará magnitude dos seus impactos sobre este patossistema.

The aim of this study was to evaluate the potential risk of moniliasis occurrence and the impacts of climate change on this disease in the coming decades, should this pathogen be introduced in Brazil. To this end, climate favorability maps were devised for the occurrence of moniliasis, both for the present and future time. The future scenarios (A2 and B2) focused on the decades of 2020, 2050 and 2080. These scenarios were obtained from six global climate models (GCMs) made available by the third assessment report of Intergovernmental Panel on Climate Change (IPCC). Currently, there are large areas with favorable climate conditions for moniliasis in Brazil, especially in regions at high risk of introduction of that pathogen. Considering the global warming scenarios provided by the IPCC, the potential risk of moniliasis occurrence in Brazil will be reduced. This decrease is predicted for both future scenarios, but will occur more sharply in scenario A2. However, there will still be areas with favorable climate conditions for the development of the disease, particularly in Brazil's main producing regions. Moreover, pathogen and host alike may undergo alterations due to climate change, which will affect the extent of their impacts on this pathosystem.