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Abstract The objective of this work was to evaluate the genetic variability and associations of yield traits of pigeon pea, for indication of this crop for the breeding program in Mozambique. Eleven pigeon pea traits were evaluated in a experimental design with three randomized complete blocks, in the environments of Namapa (I) and Montepuez (II), in 2017/2018. To evaluate the traits, analyses of variance, genetic parameters, correlations, correlation network, and path analysis were used. In both environments, there is a high genetic and phenotypic variability for primary branches, secondary branches, pods per plant, number of seed per pod, pod width, pod length, and yield, as well as a high heritability for all traits except for plant height. The primary and secondary branches have a high correlation with yield and a positive direct effect on it. However, plant height and pods per plant show a high phenotypic variability and a positive correlation with yield in environment I. Pods per plant, weight of 100 seed, and primary branches show high direct positive effects in environment I, and secondary branches and number of seed per pod, in environment II. The primary and secondary branches show high variability and associations with yield in both environments and are indicated for the pigeon pea breeding program in Mozambique.

Abstract: 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.

Resumo: O objetivo deste trabalho foi avaliar a eficiência da análise estatística espacial, em comparação a análises usuais em blocos ao acaso e em látice, na classificação de famílias de feijoeiro ( Phaseolus vulgaris), sob diferentes cenários de dependência espacial e de precisão experimental. Foram considerados 12 cenários, formados por quatro classes de dependência espacial entre erros (nula, baixa, média e alta) e três classes de precisão experimental (moderada, alta e muito alta). Para as três classes de precisão experimental, foram definidos os valores de acurácia seletiva de: 0,60, 0,80 e 0,95, respectivamente. Já as quatro classes de dependência espacial entre erros assumiram, respectivamente, os seguintes valores de alcance do modelo geoestatístico exponencial: 0, 10, 20 e 40 m. Para experimentos com precisão experimental muito alta ou ausência de dependência espacial, a eficiência da análise espacial para classificação de famílias do feijoeiro é semelhante à eficiência das análises usuais. Para experimentos com alta e, principalmente, com moderada precisão experimental, a análise espacial é mais eficiente que as análises usuais para classificação de famílias de feijoeiro, quando os erros apresentam dependência espacial.