Phenotypic markers in early selection for tolerance to dieback in Eucalyptus

Abstract

Eucalyptus dieback is a physiological disorder characterized by lesions on the apex of the branches and the death of the shoot apex. Some clones are considered tolerant to this disorder, although, up to now, there are no reports on the use of phenotypic markers for selecting tolerant material. The use of phenotypic markers may contribute to an efficient selection, where the estimation of genetic parameters of the candidate markers are essential to knowledge of the population structure, the genetic potential and effectiveness of markers as selection criteria. In this study, we estimated the genetic parameters of morphological and nutritional markers in 13 commercial eucalyptus clones aiming early selection of tolerant genotypes to eucalyptus dieback. Estimates of the genetic parameters of all characteristics were obtained by the mixed model methodology, REML (Restricted Maximum Likelihood)/BLUP (Best Linear Unbiased Prediction) procedure. Water deficit, one of the factors that promote this disorder, was simulated in eucalyptus cuttings conducted in a greenhouse. Simulated water stress was carried out for 12 weeks by applying polyethylene glycol at different concentrations and by limiting water applied to seedlings. In order to select the most promising markers, 34 morphological and nutritional variables were evaluated for early selection and discrimination of genotypes tolerant to eucalyptus dieback and water deficit. Among the 34 evaluated characteristics, plant height, stem diameter, height increment, leaf area, N, K and B, exhibited significant heritability and high accuracy (greater than 70%). Promising phenotypic markers were identified for early selection of genotypes tolerant to water deficit and eucalyptus dieback. Tolerant clones were pooled and correctly discriminated from the susceptible ones under stressful conditions by the use of seven phenotypic markers in REML/BLUP analysis, selection index ranking and graphic dispersion analysis.