scholarly journals The effect of tree (and cambium) age on genomic prediction for solid wood properties in Norway spruce

2020 ◽  
Author(s):  
Linghua Zhou ◽  
Zhiqiang Chen ◽  
Lars Olsson ◽  
Thomas Grahn ◽  
Bo Karlsson ◽  
...  
Keyword(s):  
Norway Spruce ◽  
Genomic Prediction ◽  
Microfibril Angle ◽  
Predictive Ability ◽  
Tree Breeding ◽  
Wood Properties ◽  
Solid Wood ◽  
Breeding Cycle ◽  
Old Trees ◽  
The Impact

Abstract Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce ( Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. GS predictive abilities (PA) were comparable with those based on pedigree-based selection. The highest PAs were reached with at least 80-90% of the dataset used as training set. Use of different statistical methods had no significant impact on the estimated PAs. We also compared the abilities to predict density, MFA and MOE of 19 year old trees with use of models trained on data from coring at different ages and to different depths into the stem. The comparison indicated that close to the maximal PAs can be reached at age 10-12 by drilling only half way (ringwise) towards the pith, thereby reducing the impact on the tree.

scholarly journals Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce

2020 ◽  
Author(s):  
Linghua Zhou ◽  
Zhiqiang Chen ◽  
Lars Olsson ◽  
Thomas Grahn ◽  
Bo Karlsson ◽  
...  
Keyword(s):  
Norway Spruce ◽  
Microfibril Angle ◽  
Predictive Ability ◽  
Tree Breeding ◽  
Wood Properties ◽  
Solid Wood ◽  
Tree Age ◽  
Breeding Cycle ◽  
Old Trees ◽  
The Impact

AbstractGenomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. GS predictive abilities were comparable with those based on pedigree-based prediction. The highest PAs were reached with at least 80-90% of the dataset used as training set. Use of different statistical methods had no significant impact on the estimated PAs. We also compared the abilities to predict density, MFA and MOE of 19 year old trees with models trained on data from coring at different ages and to different depths into the stem. 78-95% of the maximal PAs obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3-5 rings towards the pith at tree age 10-12, thereby shortening the cycle and reducing the impact on the tree.

scholarly journals Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce 

2020 ◽  
Author(s):  
Linghua Zhou(Former Corresponding Author) ◽  
Zhiqiang Chen ◽  
Lars Olsson ◽  
Thomas Grahn ◽  
Bo Karlsson ◽  
...  
Keyword(s):  
Norway Spruce ◽  
Microfibril Angle ◽  
Predictive Ability ◽  
Tree Breeding ◽  
Wood Properties ◽  
Tree Age ◽  
Breeding Cycle ◽  
Standing Tree ◽  
Increment Core ◽  
The Impact

Abstract BACKGROUND: Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. RESULTS: GS predictive abilities were comparable with those based on pedigree-based prediction. Marker-based PAs were generally 25-30% higher for traits density, MFA and MOE measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman. Prediction accuracy (PC) of the standing tree-based methods were similar or even higher than increment core-based method. 78-95% of the maximal PAs of density, MFA and MOE obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3-5 rings towards the pith at tree age 10-12. CONCLUSIONS: This study indicates standing tree-based measurements is a cost-effective alternative method for GS. PA of GS methods were comparable with those pedigree-based prediction. The highest PAs were reached with at least 80-90% of the dataset used as training set. Density could be conducted at an earlier age than for MFA and MOE. Operational breeding can also be optimized by training the model at an earlier age or using 3 to 5 outermost rings at tree age 10 to 12 years, thereby shortening the cycle and reducing the impact on the tree.

scholarly journals Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Linghua Zhou ◽  
Zhiqiang Chen ◽  
Lars Olsson ◽  
Thomas Grahn ◽  
Bo Karlsson ◽  
...  
Keyword(s):  
Norway Spruce ◽  
Microfibril Angle ◽  
Predictive Ability ◽  
Tree Breeding ◽  
Wood Properties ◽  
Tree Age ◽  
Breeding Cycle ◽  
Standing Tree ◽  
Increment Core ◽  
The Impact

Abstract Background Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. Results GS predictive abilities were comparable with those based on pedigree-based prediction. Marker-based PAs were generally 25–30% higher for traits density, MFA and MOE measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman. Prediction accuracy (PC) of the standing tree-based methods were similar or even higher than increment core-based method. 78–95% of the maximal PAs of density, MFA and MOE obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3–5 rings towards the pith at tree age 10–12. Conclusions This study indicates standing tree-based measurements is a cost-effective alternative method for GS. PA of GS methods were comparable with those pedigree-based prediction. The highest PAs were reached with at least 80–90% of the dataset used as training set. Selection for trait density could be conducted at an earlier age than for MFA and MOE. Operational breeding can also be optimized by training the model at an earlier age or using 3 to 5 outermost rings at tree age 10 to 12 years, thereby shortening the cycle and reducing the impact on the tree.

scholarly journals Estimating solid wood properties using Pilodyn and acoustic velocity on standing trees of Norway spruce

2015 ◽  
Vol 72 (4) ◽  
pp. 499-508 ◽  
Author(s):  
Zhi-Qiang Chen ◽  
Bo Karlsson ◽  
Sven-Olof Lundqvist ◽  
María Rosario García Gil ◽  
Lars Olsson ◽  
...  
Keyword(s):  
Norway Spruce ◽  
Wood Properties ◽  
Solid Wood ◽  
Acoustic Velocity ◽  
Standing Trees

Inheritance of basic density and microfibril angle and their variations among full-sib families and their parental clones in Picea glehnii

Holzforschung ◽  
2015 ◽  
Vol 69 (5) ◽  
pp. 581-586 ◽  
Author(s):  
Jun Tanabe ◽  
Akira Tamura ◽  
Futoshi Ishiguri ◽  
Yuya Takashima ◽  
Kazuya Iizuka ◽  
...  
Keyword(s):  
Microfibril Angle ◽  
Basic Density ◽  
Correlation Coefficients ◽  
Tree Breeding ◽  
Wood Properties ◽  
Picea Glehnii ◽  
Mean Values ◽  
Tree Breeding Program ◽  
Plantation Species ◽  
Sib Families

Abstract Picea glehnii is one of the most important plantation species in Hokkaido, Japan. Basic density (BD) and microfibril angle (MFA) of the S2 layer in latewood tracheid in 16 full-sib families and their six parental clones planted in Hokkaido were examined to clarify among-family and clonal variations of wood properties and their inheritance from parents to offspring. Mean values of BD and MFA in full-sib families and parental clones were 0.36 and 0.35 g cm-3 and 16.1° and 10.7°, respectively. Estimated repeatabilities of BD and MFA in juvenile wood (jW) were higher than those in mature wood. In addition, larger genetic coefficient of variation was detected for jW, indicating that improvement of jW properties is important to Hokkaido’s tree breeding program. Parent-offspring correlation coefficients were positive and significant in all properties. These results suggest that the influence of parental clones on wood properties is inheritable to offspring. Moreover, there were no significant differences between reciprocal crosses of wood properties, suggesting that plus-tree clones with good wood properties can be used as either female or male parents for producing offspring. There is a possibility of improving wood properties in P. glehnii by crossing clones with desirable properties.

scholarly journals Genomic prediction accuracies and abilities for growth and wood quality traits of Scots pine, using genotyping-by-sequencing (GBS) data

2019 ◽  
Author(s):  
Ainhoa Calleja-Rodriguez ◽  
Jin Pan ◽  
Tomas Funda ◽  
Zhi-Qiang Chen ◽  
John Baison ◽  
...  
Keyword(s):  
Scots Pine ◽  
Genomic Prediction ◽  
Prediction Models ◽  
Wood Quality ◽  
Genotyping By Sequencing ◽  
Tree Breeding ◽  
Snp Markers ◽  
Progeny Testing ◽  
Quality Traits ◽  
The Impact

ABSTRACTHigher genetic gains can be achieved through genomic selection (GS) by shortening time of progeny testing in tree breeding programs. Genotyping-by-sequencing (GBS), combined with two imputation methods, allowed us to perform the current genomic prediction study in Scots pine (Pinus sylvestrisL.). 694 individuals representing 183 full-sib families were genotyped and phenotyped for growth and wood quality traits. 8719 SNPs were used to compare different genomic prediction models. In addition, the impact on the predictive ability (PA) and prediction accuracy to estimate genomic breeding values was evaluated by assigning different ratios of training and validation sets, as well as different subsets of SNP markers. Genomic Best Linear Unbiased Prediction (GBLUP) and Bayesian Ridge Regression (BRR) combined with expectation maximization (EM) imputation algorithm showed higher PAs and prediction accuracies than Bayesian LASSO (BL). A subset of approximately 4000 markers was sufficient to provide the same PAs and accuracies as the full set of 8719 markers. Furthermore, PAs were similar for both pedigree- and genomic-based estimations, whereas accuracies and heritabilities were slightly higher for pedigree-based estimations. However, prediction accuracies of genomic models were sufficient to achieve a higher selection efficiency per year, varying between 50-87% compared to the traditional pedigree-based selection.

scholarly journals Butt rot occurrence in plus trees of Silver fir Abies alba Mill. and Norway spruce Picea abies (L.) from the Carpathians

2016 ◽  
Vol 77 (3) ◽  
pp. 212-220
Author(s):  
Elżbieta Chomicz-Zegar ◽  
Stanisław Niemtur ◽  
Mariusz Kapsa ◽  
Sławomir Ambroży
Keyword(s):  
Norway Spruce ◽  
Abies Alba ◽  
Wood Decay ◽  
Solid Wood ◽  
Silver Fir ◽  
The Novel ◽  
Butt Rot ◽  
Non Invasive ◽  
Old Trees ◽  
Individual Trees

Abstract Due to its hidden character, butt rot occurrence is not commonly included in the assessment of plus trees’ health status. Thus, the trees’ varied susceptibility to wood decay is not a target of breeding efforts. The aim of the study was to determine the extent of butt rot in fir and spruce plus trees from Carpathian seed stands. We employed the novel and non-invasive diagnostic method of sonic tomography to determine presence and severity of decay at the base of 110 plus trees of silver fir and 42 of Norway spruce. Butt rot in various stages of development occurred in 63% of investigated fir trees and in 45% of spruce trees. The proportion of damaged wood on the tomogram ranged from 0–38% in fir and 0–47% in spruce with similar average proportions of solid wood in all forest districts. The vast majority of trees was in the range of 80–90% solid wood. Plus trees of fir and spruce were affected by butt rot to a similar extent and the degree of damage increased with age in both species. However, a large variation in susceptibility to butt rot was found between individual trees leading to the conclusion that the identification of old trees, which wood is not decayed, may be the basis for further research on the resistance to butt rot.

Hydraulic and biomechanical optimization in norway spruce trunkwood – a review

IAWA Journal ◽  
2013 ◽  
Vol 34 (4) ◽  
pp. 365-390 ◽  
Author(s):  
Sabine Rosner
Keyword(s):  
Structure Function ◽  
Norway Spruce ◽  
Evolutionary Process ◽  
Woody Species ◽  
Wood Properties ◽  
Forest Tree ◽  
Wood Structure ◽  
Tree Survival ◽  
The Impact ◽  
Non Destructive

Secondary xylem (wood) fulfills many of the functions required for tree survival, such as transport of water and nutrients, storage of water and assimilates, and mechanical support. The evolutionary process has optimized tree structure to maximize survival of the species, but has not necessarily optimized the wood properties needed for lumber. Under the impact of global warming, knowledge about structure-function relationships in tree trunks will become more and more important in order to prognosticate survival prospects of a species, individuals or provenances. Increasing our knowledge on functional wood anatomy can also provide valuable input for the development of reliable, fast, and at best quasi-non-destructive (e.g. wood coring of mature trunks) indirect screening techniques for drought susceptibility of woody species. This review gives an interdisciplinary update of our present knowledge on hydraulic and biomechanical determinants of wood structure within and among trunks of Norway spruce (Picea abies (L.) Karst.), which is one of Europe’s economically most important forest tree species. It summarizes what we know so far on 1) withinring variability of hydraulic and mechanical properties, 2) structure-function relationships in mature wood, 3) mechanical and hydraulic demands and their tradeoffs along tree trunks, and 4) the quite complex wood structure of the young trunk associated with mechanical demands of a small tree. Due to its interdisciplinary nature this review is addressed to physiologists, foresters, tree breeders and wood technologists.

Variation in content and composition of lignin in young wood of Norway spruce

Holzforschung ◽  
2004 ◽  
Vol 58 (2) ◽  
pp. 107-115 ◽  
Author(s):  
J. Wadenbäck ◽  
D. Clapham ◽  
G. Gellerstedt ◽  
S. von Arnold
Keyword(s):  
Norway Spruce ◽  
Natural Variation ◽  
Compression Wood ◽  
Lignin Content ◽  
Tree Breeding ◽  
Acetyl Bromide ◽  
Breeding Programs ◽  
Lignin Composition ◽  
Sib Families ◽  
Old Trees

Abstract Lignin content and composition are important traits in several tree breeding programs, but very little is known about their natural variation. This study compares the lignin content in 1-year-old plants and 9-year-old trees of Norway spruce belonging to the same full-sib families. It is shown that the lignin content, according to the modified acetyl bromide method, does not vary significantly within or among the different full-sib families either as plants or as young trees. There is, however, on average 4.0% higher lignin content (31.4% versus 27.4%) and lower standard error for the trees than for the plants. The number of C9-units g−1 lignin, analyzed by thioacidolysis, ranges from 516 to 1186 μmmol C9-units g−1 lignin in plants and from 716 to 953 μmmol C9-units g−1 lignin in trees, with no significant differences among the families. However, the extent of change in C9-units g−1 lignin varies among the families with age. The ratio of erythro and threo stereoisomers does not vary significantly among the families. However, the ratio changes differently with age among the families similar to the C9-units g−1 lignin. Additionally, the content of p-hydroxyphenyl (H) lignin is 0.6% higher in the trees than in the plants (1.4% versus 0.8%), estimated indirectly from GC-MS data by a novel subtractive technique, indicating a higher degree of compression wood in the young trees. In conclusion, the amount and composition of lignin does not vary within or among the families at the same age. However, the amount of lignin increases with age while the change in lignin composition varies between family and age.

scholarly journals Optimizing whole-genomic prediction for autotetraploid blueberry breeding

Heredity ◽  
2020 ◽  
Vol 125 (6) ◽  
pp. 437-448 ◽  
Author(s):  
Ivone de Bem Oliveira ◽  
Rodrigo Rampazo Amadeu ◽  
Luis Felipe Ventorim Ferrão ◽  
Patricio R. Muñoz
Keyword(s):  
Genomic Prediction ◽  
Total Yield ◽  
Substantial Reduction ◽  
Breeding Population ◽  
Fruit Weight ◽  
Sequencing Depth ◽  
Breeding Cycle ◽  
Marker Density ◽  
Training Population ◽  
The Impact

Abstract Blueberry (Vaccinium spp.) is an important autopolyploid crop with significant benefits for human health. Apart from its genetic complexity, the feasibility of genomic prediction has been proven for blueberry, enabling a reduction in the breeding cycle time and increasing genetic gain. However, as for other polyploid crops, sequencing costs still hinder the implementation of genome-based breeding methods for blueberry. This motivated us to evaluate the effect of training population sizes and composition, as well as the impact of marker density and sequencing depth on phenotype prediction for the species. For this, data from a large real breeding population of 1804 individuals were used. Genotypic data from 86,930 markers and three traits with different genetic architecture (fruit firmness, fruit weight, and total yield) were evaluated. Herein, we suggested that marker density, sequencing depth, and training population size can be substantially reduced with no significant impact on model accuracy. Our results can help guide decisions toward resource allocation (e.g., genotyping and phenotyping) in order to maximize prediction accuracy. These findings have the potential to allow for a faster and more accurate release of varieties with a substantial reduction of resources for the application of genomic prediction in blueberry. We anticipate that the benefits and pipeline described in our study can be applied to optimize genomic prediction for other diploid and polyploid species.

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