Estimativa da variabilidade genética em acesso de amendoim baseada em modelos uni e multivariados

Abstract

Peanut (Arachis hypogaea) is an important oilseed for the food market. The cultivars available in Brazil belong to two subspecies, hypogaea and fastigiata, each with different morphological and agronomical traits. The hypogaea accessions are runner types, long cycle and absence of flowers on the main stem, while the fastigiata are upright, earliness, with flowers on all branches of plant. Despite to be a autogamous with cleistogamic flowers, it is possible to detect genetic variability between accessions of the same subspecies, depending on the genealogy and some peculiar traits in the population. Such knowledge is essential to planning the strategies adopted in breeding programs. In this work, the genetic variability of a population with eleven fastigiata accessions was estimated, based on uni and multivariate models. Additionally, phenotypic and genotypic correlations were estimated, based on 14 traits associated to reproductive efficiency. The accessions were provided by Federal University of Ceará and later introduced into Peanut Collection, of Embrapa Algodao, Brazil. Assay as carried out in greenhouse, during Oct / 2019 to Jan / 2020. Seeds were grown in pots, following the management recommendations adopted by the crop curator. The experimental design was completely randomized with three repetitions. The descriptors adopted for the univariate and multivariate analyzes were: plant height (PJ), number of pods / plant (NP), weight of pods / plant (WP), weight of 100 pods (W100P), weight of 100 seeds (W100S ), Blooming (B), total number of gynophores / plant (NG), total number of flowers / plant (NF), flowering duration (FD), flower viability (FV), full pod maturation (FPM), harvest index (HI), reproductive efficiency based on the number of flowers (REf) and reproductive efficiency based on the number of gynophores (REg). The statistical procedures were based on analysis of variance (F test) and classification of means (Tukey test) for univariate models, and UPGMA and canonical variables (VC), for multivariate analysis. A statistically significant difference was found for most traits indicating that there is variability in the studied population, excepting to B, FD and FPMV. The accessions PI-268-689, Dwarf, AHK 85-3, Feuri-11 and SR-1-4 were more productive. Through UPGMA and VC analysis, three groups were clustered, G1: Dwarf, Feuri-11, GDM-MUT-1 and SR-1-4, G2: Dixie-Spanish,55114, Georgia, GDM and R-31- 1 and G3: PI-268-689 and AHK-85-3. Of these, G3 had the most promising accessions, based on WP, REg and HI. As to correlations, we found that is possible to selecting accessions with high reproductive efficiency by adopting REg x HI and NP x REg combinations, which showed positive and high to medium magnitudes. It is up to the breeder to select the best convenience traits in order to adopt them in further selection procedures.