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]
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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 |
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Title: | Quantitative genetics of wood quality traits in Scots pine |
Series Name/Journal: | Acta Universitatis Agriculturae Sueciae |
Year of publishing : | 2020 |
Number: | 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: | 18 Jun 2020 01:39 |
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