04102naa a2200205 a 450000100080000000500110000800800410001902000220006010000210008224500910010326000090019452034220020365300240362565300180364965300230366770000200369070000170371070000160372777301530374311245562015-11-11       2015    bl uuuu     u00u1 u    #d  a978-85-63273-31-41 aMARIGUELE, K. H.  aRELATIONSHIP BETWEEN PHENOTYPIC TRAITS OF AUSTRALIAN KING PALM.h[electronic resource]  c2015  aSimple correlation allows the magnitude and meaning of an association between two traits to be evaluated, without providing the required information about the direct and indirect effects of a group of traits in relation to a dependent variable of greater importance. In certain cases, simple correlation coefficients may produce significant misunderstandings about the relationship that exists between two variables, and may not represent an actual measurement of cause and effect. A more informative measure of the relationship between variables is the coefficient of partial correlation, which is estimated by removing the effects of other variables on the association under study. Besides, path analysis is a technique that allows the effects of several independent variables on a basic variable to be studied; estimates for those variables are obtained by means of regression equations, in which the variables are initially standardized. The aim of this study was to estimate simple and partial coefficients of correlation, as well as to divide their effects into direct and indirect using path analysis for phenotypic traits of Australian king palm. An Archontophoenix spp population with 539 plants was assessed to five traits: plant height (one year before the harvest), plant height and stem diameter (at harvest), edible basal stem and premium heart-ofpalm yield. The harvest occurred in 3.5 year after planting and the data analyses were performed using the GENES software. Based on the eigenvalues of the correlation matrix, we obtained condition numbers of 26.99 for traits. Since these values were below 100, they indicate a weak multicollinearity, and a path analysis could be run, as the estimates were not biased. Among the ten pairs of simple correlation, three were not significant: the two plant heights/edible basal stem yield and edible basal stem yield/premium heart-of-palm yield. The other correlations were significant and ranged from 0.44 - plant height one year before the harvest/premium heart-of-palm yield - up to 0.88 - between the two plant height measurements. However, when the effects of other traits were removed from the model to estimate partial correlations, only two relationships were significant: steam diameter/premium heartof- palm yield and the two plant height measurements, 0.53 and 0.84, respectively. The premium heart-of-palm was used as the dependent variable, because it is the characteristic of greater economic interest, while the others were considered independent. The direct effects of plant height one year before the harvest, plant height at harvest and the stem diameter on the dependent variable was 0.01, 0.27 and 0.56, respectively. The indirect effects of plant height one year before the harvest via plant height at harvest and stem diameter were 0.24 and 0.22, respectively. The indirect effect of plant height at harvest via stem diameter was 0.28, that value similar to the direct effect (0.27). As for stem diameter, the direct effect was the highest magnitude, compared to the indirect effects. The results of this work led to the conclusion that practicing selection based on simple correlation estimates may not be convenient, since not always a cause and effect relationship can be verified between both traits. Among the traits, stem diameter showed values of larger magnitudes, either by direct or indirect effect, with premium heart-of-palm.  apartial correlation  apath analysis  aSimple correlation1 aZAMBONIM, F. M.1 aVISCONTI, A.1 aHECK, T. C.  tIn: SIMPÓSIO DE RECURSOS GENÉTICOS PARA A AMÉRICA LATINA E CARIBE, 10., 2015, Bento Gonçalves. Resumos... São Carlos, SP: Aptor Software, 2015.