Genetic variation of wood and resin production inPinus caribaeavar.hondurensisBarret & Golfari

Abstract

The purpose of this work was to estimate genetic parameters and selection gain of Pinus caribaea var. hondurensis progeny trial for wood and resin production as well as correlation between them. Experiment was established in complete lattice square 10 × 10 (triple), 100 treatments, 10 plants per plot, 3 m × 3 m spacing. Twelve years after planting the trial had thinned considerably leaving six plants per plot. Twenty-seven years after planting height, diameter at breast height (dbh) and resin production were measured. Deviance analysis, genetic parameter estimates, selection expected gain, genetic and phenotypic correlation were based on REML/BLUP method. Significant phenotypic differences were observed among and within families for all traits. The thinning at 12 years after planting, contributed positively to dbh increase and resin production, with an average of 30.60 cm and 4.83 kg tree−1year−1. The individual narrow sense heritability ranged from 0.25 to 0.38 for dbh and volume. Genetic and phenotypic correlation between growth traits were positive, and significant. Therefore, different selection strategies will be proposed separately for both traits (resin and wood). The selection gains were significant, especially with 10 % selection intensity (individual selection) for dbh (7.53 %) and resin (13.49 %). The trial has had good performance for growth, resin and genetic variability to support the next breeding generation

Domestication provides the key to conservation ofSantalum yasi– a threatened Pacific sandalwood

“…The heritability of sandalwood oil characters has not been assessed in any species to date due to a lack of suitable common-garden trials that are old enough for the determination to be made. It seems probable that the heritability of oil traits will be moderate to high based on studies of genetic variability of plant-chemistry traits and heartwood characters in other tree species (Bush et al 2011;Santos et al 2016;Mazanec et al 2017). It is also likely that genotype-environment interaction is lower for wood-chemistry traits than for the lower-heritability growth traits (White et al 2007, p. 140).…”

Traumatic ducts size varies genetically and is positively associated to resin yield of Pinus oocarpa open-pollinated progenies

“…The large contribution of family variance to the total variance, and the high heritability values for TD´s diameter (h 2 f = 0.51) and TD area (h 2 f = 0.81), suggest a strong genetic control at family level of the inducibility of TD with large diameter (and consequently in area) in response to the wounds inflicted by resin extraction. These values could be considered as high heritability, considering that <0.15 is low, 0.15 to 0.50 is moderated and >0.50 is high (Resende 2002;dos-Santos et al 2016). The strong positive association between the TD diameter and the amount of resin production, indicates that possibly the individual trees that are high resin yielders are so, because of their capability to vigorously respond to a mechanical wounding by creating large (in diameter and area) TD, and that such capability is heritable.…”

“…Since the narrow-sense heritability for resin production at family level was much higher than at individual level, the selection would be more efficient if conducted on a family basis, and then for best individual within selected families (Susilowati et al, 2013;Zeng et al, 2013;dos-Santos et al, 2016;Lai et al, 2017).…”

Selection strategies for growth characters and rubber yield in two populations of rubber trees in Brazil

“…Another interesting procedure for the prediction of genetic values is the BLUP (Best Linear Unbiased Prediction), being more appropriate when considering the genotypic effects as random, aiming to obtain the BLUPs of said effects (Resende, 2004). The REML/ BLUP methodology is used in several species, such as in Hevea (Souza et al, 2017), Eucalyptus (Costa et al, 2015); Pinus (Santos et al, 2016), Acacia (black wattle) (Dunlop et al, 2005). Resende (2016) suggests the use of the Selegen-REML/BLUP software for the application of analysis of mixed models in the estimation of variance components and estimation of genetic parameters to optimize the conduction of plant breeding programs.…”

“…In this method, selection is based on genetic measures (net genetic value) and non-phenotypic measures of the candidates for selection (Resende and Higa, 1994). Several studies have been carried out using the MEI method, due to the more expressive gains in selection (Costa et al, 2000a(Costa et al, , 2000bSantos et al, 2016;Arantes et al, 2010;Tung et al, 2010;Silva et al, 2011;Verardi et al, 2013Verardi et al, , 2014Kubota et al, 2015).…”