ABSTRACT
The objective of this study was to evaluate the efficiency of the phenotypic models of competition, through spatial analysis in the genetic evaluation of Pinus taeda L progenies. For this, four competition covariates were used to adjust the phenotypic values in a P. taeda progeny test installed in four different locations in the state of Santa Catarina. The test was implemented in randomized block design, with seven repetitions, linear plots containing six plants per plot in 2.5 m x 2.0 m spacing. The test installed in sites A, B, and D present 63 families and site C 53 families. At nine years old, the diameter at the breast height was measured for all individuals. The presence or absence of competition was based on the residual autocorrelation coefficients, which had its significance tested by the Durbin-Watson test. In general, the use of covariates corrected the competition effect. The variances among and within plots, as well as the residual variation coefficient, were reduced. The classification by the genetic effect of the individuals in the progeny test was extremely altered for this data set with and without the use of covariates for sites A and D, as well as the genotype x environment interaction. The use of these two tools is of great importance in the analysis of data in P. taeda progeny tests, since the effects of competition can lead to mistakes in the selection of individuals and in the definition of improvement zones.
Keywords:
Spatial analysis; Covariate; REML/BLUP; Components of variance
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) in P. taeda progeny test in four test sites in the state of Santa Catarina.
