Estimativa de parâmetros genéticos em progênies de irmãos completos de eucalipto e otimização de seleção

SCIENTIA FORESTALIS(2019)

Cited 3|Views4
No score
Abstract
The present study aimed to select the best progenies and individuals of an eucalyptus full-sib progeny test based on effective population size and endogamy. The experiment consisted of 7,261 individuals. The experimental design was established in incomplete blocks, containing 18 progenies, 75 replications, 1,800 randomized blocks within the replicates and with a single tree plot. In the same experiment, 388 E. urophylla x E. grandis different elite clones were used as controls. At 6 years of age, the evaluated characters were diameter at the breast height, total height, tree volume, mean annual increment (MAI) and survival. All analyzes were performed based on the genetic-statistical procedure of mixed models using REML/ BLUP. Selection optimization of the population was done through simulation of 30 scenarios in which different effective population sizes, endogamy rates and accumulated gains corrected by inbreeding were obtained. The individual heritabilities and heritabilities of average progenies presented values of high magnitude (h (2)a> 50% and h(2)mp> 80%), indicating high genetic control for the evaluated traits. The plot determination coefficient (c(2) parc) presented low values for all the characters and the accuracy was above 90%, which demonstrates low environmental influence. The progeny with the highest predicted genetic value was a triple hybrid (E. dunni x E. grandis) x E. urophylla that presented potential transgressive segregant individuals for cloning or directed crosses. The more indicated situation reached a genetic gain of 114.53% for the variable MAI, with an inbreeding rate of 3.92%. These results will enable reduction of related individuals crossing, maximization of genetic gains and the transformation of the experiment in seed orchards.
More
Translated text
Key words
full-sib families,endogamy,effective population size,progenies tests
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined