Open AccessGENETIC SELECTION OF Pinus taeda L. THROUGH MULTI-ENVIRONMENT TRIAL
Author(s) -
Vanessa Ishibashi,
Paulo César Flôres,
Diego Tyszka Martinez,
Antônio Rioyei Higa
Publication year - 2020
Publication title -
floresta
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.386
H-Index - 13
eISSN - 1982-4688
pISSN - 0015-3826
DOI - 10.5380/rf.v51i1.68057
Subject(s) - seed orchard , best linear unbiased prediction , biology , selection (genetic algorithm) , heterosis , population , restricted maximum likelihood , mixed model , progeny testing , tree breeding , genetic gain , randomized block design , statistics , genetic variation , hybrid , agronomy , ecology , mathematics , demography , horticulture , genetics , woody plant , maximum likelihood , artificial intelligence , sociology , computer science , gene
The aim of this study is to select progenies of Pinus taeda through multi-environmental trial to establish clonal seed orchards and advance breeding–program generations. Progeny test was carried out with 53 open-pollinated families planted in four different locations. The study followed a randomized block statistical design, with seven replications in linear plots planted with six plants each. DBH variable was measured in individuals at the age of nine years. All estimates were carried out in Selegen REML/BLUP® software. Genotype x environment interaction was detected; therefore, it required the definition of two breeding zones to minimize its effects. The genetic basis of the assessed population is restricted. Families were distributed into nine different groups, based on genetic divergence analysis, and grouping through the Tocher method, by using Mahalanobis distances. Based on the results, and by taking into consideration the balance between variability maintenance and genetic gains, it is recommended to establish a clonal seed orchard with 50 selected individuals in the experiment, based on a limited number of individuals per family. Intraspecific crossing between divergent families can also be used to increase heterosis and genetic variability in the assessed population.