Shading and controlled-release fertilizer in the production of Oenocarpus bataua Mart. Seedlings

When associated an adequate shading and nutrition the seedlings to reach characteristics that allow them tosurvive in the field and increase production. Thus, this work aimed to evaluate the production of Oenocarpusbataua seedlings in response to different shade environments and controlled-release fertilizer doses. Thestudy was carried out from at the Embrapa nursery located in the municipality of Rio Branco, Acre state. Theexperimental design was complete randomized blocks with three replications and six plants per plot. Thetreatments were distributed according to a 4 x 5 factorial scheme, i.e., four shade environments (20%, 30%, 50%and 75%) and five CRF doses (0.0, 1.5, 3.0, 4.5 and 6.0 kg m–3) mixed with the substrate. Biometric, biomass andquality variables were evaluated at 305 days after transplanting. The ANOVA was applied for the qualitativefactor and regression analysis was performed for the quantitative factor, both at 5% probability. The treatmentswere grouped by analyzing canonical variables, a multivariate statistical and realized the Pearson’s correlationbetween variables was determined through correlation networks. The shading environment and the controlledreleasefertilizer positively influenced the growth and quality of Oenocarpus bataua seedlings. The seedlings ofOenocarpus bataua have better biometric characteristics produced in a nursery with 50% shading. Oenocarpusbataua seedlings show better quality when 3.88 kg m-3 of controlled release fertilizer are used

Uso da metodologia REML/BLUP para seleção de genótipos de laranjeira-doce

The objective of this work was to select superior sweet orange (Citrus sinensis) genotypes with higher yield potential based on data from eight harvests, using the residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology. The experiment was carried out from 2002 to 2008 and in 2010 in the municipality of Rio Branco, in the state of Acre, Brazil. Analyzes of deviance were performed to test the significance of the components of variance according to the random effects of the used model, and parameters were estimated from individual genotypic and phenotypic variances. A selection intensity of 20% was adopted regarding genotypic selection, i.e., only the best 11 of the 55 genotypes tested were selected. The estimates of the genetic parameters show the existence of genetic variability and the selection potential of the studied sweet orange genotypes. The genotypic correlation between harvests is of low magnitude, except for the variable average fruit mass, and, as a reflex, there is a change in the ordering of the genotypes. Genotypes 5, 48, 19, 14, and 47 stand out as being the most productive, and, therefore, are the most suitable for selection purposes. Genotypes 14 and 47 show superior performance for the character set evaluated.O objetivo deste trabalho foi selecionar genótipos superiores de laranjeira-doce (Citrus sinensis) com maior potencial produtivo com base em dados de oito safras, com uso da metodologia “residual or restricted maximum likelihood/best linear unbiased prediction” (REML/BLUP). O experimento foi realizado de 2002 a 2008 e em 2010, no município de Rio Branco, no estado do Acre, Brasil. Análises de deviance foram realizadas para testar a significância dos componentes da variância de acordo com os efeitos aleatórios do modelo utilizado, e os parâmetros foram estimados a partir das variâncias genotípicas e fenotípicas individuais. Foi adotada uma intensidade de seleção de 20% em relação à seleção genotípica, ou seja, apenas os melhores 11 dos 55 genótipos testados foram selecionados. As estimativas dos parâmetros genéticos mostram a existência de variabilidade genética e o potencial de seleção dos genótipos de laranjeira-doce estudados. A correlação genotípica entre as safras é de baixa magnitude, exceto para a variável massa média dos frutos, e, como reflexo, há uma mudança na ordenação dos genótipos. Os genótipos 5, 48, 19, 14 e 47 se destacam como os mais produtivos e, portanto, são os mais adequados para fins de seleção. Os genótipos 14 e 47 apresentam desempenho superior para o conjunto de caracteres avaliados

Portugûes Stability and adaptability of sweet orange using mixed models

Evaluations with sweet oranges are usually performed in several harvests and places to verify the differential behavior according to the environmental variations. This makes the selection by traditional statistical methodologies more and more difficult since they have limitations in the case of data unbalanced, common in citrus during the experimental phase due to the possibility of plot loss over the years. The objective of this work was to estimate the temporal stability and adaptability of sweet orange genotypes cultivated in eight crops under the edaphoclimatic conditions of Rio Branco, Acre. The experimental design used was in randomized blocks containing 55 genotypes and three replications. Four agronomic characteristics were evaluated during eight harvests. The genetic parameters were estimated using the REML/BLUP methodology. After detecting the presence of significant interaction between genotypes and environments, stability and adaptability analyzes were conducted by the methods of the harmonic mean of the genotypic values ​​(HMGV), the relative performance of the genetic values ​​(RPGV) and the harmonic mean of the relative performance of the genotypic values ​​(HMRPGV). The HMRPGV can be used to select stable, adapted and productive sweet orange genotypes. The number 48, 19, 5, 14, 2, 47 and 37 sweet orange genotypes can be selected for cultivation in an environment similar to the one studied, as they simultaneously present high stability, adaptability and productivity.Evaluations with sweet oranges are usually performed in several harvests and places to verify the differential behavior according to the environmental variations. This makes the selection by traditional statistical methodologies more and more difficult since they have limitations in the case of data unbalanced, common in citrus during the experimental phase due to the possibility of plot loss over the years. The objective of this work was to estimate the temporal stability and adaptability of sweet orange genotypes cultivated in eight crops under the edaphoclimatic conditions of Rio Branco, Acre. The experimental design used was in randomized blocks containing 55 genotypes and three replications. Four agronomic characteristics were evaluated during eight harvests. The genetic parameters were estimated using the REML/BLUP methodology. After detecting the presence of significant interaction between genotypes and environments, stability and adaptability analyzes were conducted by the methods of the harmonic mean of the genotypic values ​​(HMGV), the relative performance of the genetic values ​​(RPGV) and the harmonic mean of the relative performance of the genotypic values ​​(HMRPGV). The HMRPGV can be used to select stable, adapted and productive sweet orange genotypes. The number 48, 19, 5, 14, 2, 47 and 37 sweet orange genotypes can be selected for cultivation in an environment similar to the one studied, as they simultaneously present high stability, adaptability and productivity

Portugûes Stability and adaptability of sweet orange using mixed models

Evaluations with sweet oranges are usually performed in several harvests and places to verify the differential behavior according to the environmental variations. This makes the selection by traditional statistical methodologies more and more difficult since they have limitations in the case of data unbalanced, common in citrus during the experimental phase due to the possibility of plot loss over the years. The objective of this work was to estimate the temporal stability and adaptability of sweet orange genotypes cultivated in eight crops under the edaphoclimatic conditions of Rio Branco, Acre. The experimental design used was in randomized blocks containing 55 genotypes and three replications. Four agronomic characteristics were evaluated during eight harvests. The genetic parameters were estimated using the REML/BLUP methodology. After detecting the presence of significant interaction between genotypes and environments, stability and adaptability analyzes were conducted by the methods of the harmonic mean of the genotypic values ​​(HMGV), the relative performance of the genetic values ​​(RPGV) and the harmonic mean of the relative performance of the genotypic values ​​(HMRPGV). The HMRPGV can be used to select stable, adapted and productive sweet orange genotypes. The number 48, 19, 5, 14, 2, 47 and 37 sweet orange genotypes can be selected for cultivation in an environment similar to the one studied, as they simultaneously present high stability, adaptability and productivity.Evaluations with sweet oranges are usually performed in several harvests and places to verify the differential behavior according to the environmental variations. This makes the selection by traditional statistical methodologies more and more difficult since they have limitations in the case of data unbalanced, common in citrus during the experimental phase due to the possibility of plot loss over the years. The objective of this work was to estimate the temporal stability and adaptability of sweet orange genotypes cultivated in eight crops under the edaphoclimatic conditions of Rio Branco, Acre. The experimental design used was in randomized blocks containing 55 genotypes and three replications. Four agronomic characteristics were evaluated during eight harvests. The genetic parameters were estimated using the REML/BLUP methodology. After detecting the presence of significant interaction between genotypes and environments, stability and adaptability analyzes were conducted by the methods of the harmonic mean of the genotypic values ​​(HMGV), the relative performance of the genetic values ​​(RPGV) and the harmonic mean of the relative performance of the genotypic values ​​(HMRPGV). The HMRPGV can be used to select stable, adapted and productive sweet orange genotypes. The number 48, 19, 5, 14, 2, 47 and 37 sweet orange genotypes can be selected for cultivation in an environment similar to the one studied, as they simultaneously present high stability, adaptability and productivity