Home About Browse Search
Svenska


Quantitative genetics of wood quality traits in Scots pine

Fundova, Irena (2020). Quantitative genetics of wood quality traits in Scots pine. Diss. (sammanfattning/summary) Sveriges lantbruksuniv., Acta Universitatis Agriculturae Sueciae, 1652-6880 ; 2020:9
ISBN 978-91-7760-536-2
eISBN 978-91-7760-537-9
[Doctoral thesis]

[img]
Preview
PDF - Published Version
2MB

Abstract

Wood quality of commercial tree species is important for many wood processing industries and thus should be considered for inclusion in forest tree improvement programs. This thesis evaluated the suitability of various proxy methods for rapid and non-destructive assessment of wood quality traits on standing trees of Scots pine and the potential for genetic improvement of different wood quality traits through recurrent selective breeding.

Penetrometer Pilodyn and micro-drill Resistograph were tested for non-destructive assessment of wood density (DENPIL and DENRES, respectively), using SilviScan density (DENSILV) as a benchmark. A strong additive genetic correlation was observed between DENSILV and DENRES (rA = 0.96), whilst the correlation with DENPIL was substantially lower (rA = 0.74). Furthermore, SilviScan stiffness (MOESILV) was used as a benchmark for evaluation of several approaches of calculating the dynamic modulus of elasticity (MOE) from standing-tree acoustic velocity (VELTREE). The combination of VELTREE and adjusted DENRES provided the most accurate estimate of MOETREE (rA = 0.91). Additionally, non-destructive acoustic sensing tools were tested at different stages of wood processing (on standing trees, felled logs and sawn boards) using destructively measured sawn-board stiffness (static modulus of elasticity, MOES) and strength (modulus of rupture, MOR) as benchmarks. They proved to be capable of accurately predicting MOES (rA ≈ 0.8) while VELTREE, adjusted DENRES and MOETREE well reflected MOR (rA ≈ 0.9). Genetic variation of shape stability of sawn boards (bow, crook and twist) was also investigated. Under-bark grain angle (GRA) was found to be a good predictor of sawn-board twisting and crooking (rA = 0.84 and 0.62, respectively). The chemical composition of juvenile wood (proportion of cellulose, hemicelluloses, lignin and extractives) was predicted from Fourier transform infrared (FTIR) spectra using partial least squares regression (PLSR) modeling. Individual-tree narrow-sense heritabilities (ℎi2) for all of the studied wood quality traits varied from low to moderate.

Genetic improvement of sawn-board DEN, MOES and MOR as the target traits could be achieved through selective breeding for MOETREE, DENRES, stem straightness (STR) or GRA. Selection focusing on GRA would also result in lower bow, crook and twist. Despite the negative genetic correlations between growth and wood quality traits, a possibility of their simultaneous improvement was identified. An index combining stem diameter (DBH) and MOETREE provided the best compromise.

Authors/Creators:Fundova, Irena
Title:Quantitative genetics of wood quality traits in Scots pine
Year of publishing :2020
Volume:2020:9
Number of Pages:59
Publisher:Department of forest genetics and plant physiology, Swedish university of agricultural sciences
ISBN for printed version:978-91-7760-536-2
ISBN for electronic version:978-91-7760-537-9
ISSN:1652-6880
Language:English
Publication Type:Doctoral thesis
Article category:Other scientific
Version:Published version
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Wood Science
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 404 Agricultural Biotechnology > Genetics and Breeding
Keywords:Density, stiffness, strength, shape stability, chemical composition, non-destructive testing, genetic correlation, heritability, breeding, genetic improvement
URN:NBN:urn:nbn:se:slu:epsilon-p-105018
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-105018
ID Code:16809
Faculty:S - Faculty of Forest Sciences
Department:(S) > Dept. of Forest Genetics and Plant Physiology
Deposited By: SLUpub Connector
Deposited On:06 Apr 2020 14:16
Metadata Last Modified:06 Apr 2020 14:16

Repository Staff Only: item control page

Downloads

Downloads per year (since September 2012)

View more statistics

Downloads
Hits