We tested two methods for non-destructive assessment of wood density of Scots pine standing trees: one based on penetration depth of a steel pin (Pilodyn) and the other on micro-drilling resistance (Resistograph). As a benchmark we used wood density data from x-ray analysis (SilviScan). We assessed in total 622 trees of 175 full-sib families growing in a single progeny test. Pilodyn was applied with bark (PIL) and without bark (PIL_B). Raw Resistograph drilling profiles (RES) were adjusted (RES_TB) in order to eliminate increasing trend caused by needle friction. Individual narrow-sense heritability of benchmark SilviScan density (DEN; 0.46) was most closely approached by that of adjusted RES_TB (0.43). Heritabilities were lower for unadjusted RES (0.35) as well as for PIL and PIL_B (both 0.32). Additive genetic correlations of the benchmark DEN with RES, RES_TB, PIL and PIL_B were 0.89, 0.96, 0.59 and 0.71, respectively. Our results suggest that Resistograph is a more reliable tool than Pilodyn for wood density assessment of Scots pine; however, we highly recommend adjusting Resistograph drilling profiles prior to further analyses.

The chemical composition of wood is one of the key features that determine wood quality. The focus of this study was on identifying differences between juvenile and mature woods in Scots pine (Pinus sylvestrisL.) and developing models for predicting the chemical composition of these two wood types. Chemical traits, determined by traditional wet chemistry techniques, included the proportion of lignin, polysaccharides and extractives. Partial least squares regression of Fourier transform infrared (FTIR) spectra was used for model building. The model performance was primarily evaluated by root mean squared error of predictions (RMSEP). High predictive power was attained for the content of lignin (RMSEP of 0.476 and 0.495 for juvenile and mature woods, respectively) and extractives (0.302 and 0.471), good predictive power for cellulose (0.715 and 0.696) and hemicelluloses in juvenile wood (0.719) and low predictive power for hemicelluloses in mature wood (0.823). A distinct band was observed at 1693 cm⁻¹, and its intensity was strongly associated with the content of extractives (r = 0.968 and 0.861 in juvenile and mature woods, respectively). FTIR has proved suitable for the rapid, non-destructive, cost-efficient assessment of the chemical composition of juvenile and mature woods in Scots pine. The band at 1693 cm⁻¹is to be further investigated to unravel its link with individual extractive components.

Wood stiffness is an important wood mechanical property that predetermines the suitability of sawn timber for construction purposes. Negative genetic correlations between wood stiffness and growth traits have, however, been reported for many conifer species including Scots pine. It is, therefore, important that breeding programs consider wood stiffness and growth traits simultaneously. The study aims to (1) evaluate different approaches of calculating the dynamic modulus of elasticity (MOE, non-destructively assessed stiffness) using data from X-ray analysis (SilviScan) as a benchmark, (2) estimate genetic parameters, and (3) apply index selection. In total, we non-destructively measured 622 standing trees from 175 full-sib families for acoustic velocity (VEL) using Hitman and for wood density (DEN) using Resistograph and Pilodyn. We combined VEL with different wood densities, raw (DEN_RES) and adjusted (DEN_RES.TB) Resistograph density, Pilodyn density measured with (DEN_PIL) and without bark (DEN_PIL.B), constant of 1000 kg·m⁻³ (DEN_CONST), and SilviScan density (DEN_SILV), to calculate MOEs and compare them with the benchmark SilviScan MOE (MOE_SILV). We also derived Smith–Hazel indices for simultaneous improvement of stem diameter (DBH) and wood stiffness. The highest additive genetic and phenotypic correlations of the benchmark MOE_SILV with the alternative MOE measures (tested) were attained by MOEDEN_SILV (0.95 and 0.75, respectively) and were closely followed by MOEDEN_RES.TB (0.91 and 0.70, respectively) and MOEDEN_CONST and VEL (0.91 and 0.65, respectively for both). Correlations with MOEDEN_PIL, MOEDEN_PIL.B, and MOEDEN_RES were lower. Narrow-sense heritabilities were moderate, ranging from 0.39 (MOE_SILV) to 0.46 (MOEDEN_SILV). All indices revealed an opportunity for joint improvement of DBH and MOE. Conclusions: MOEDEN_RES.TB appears to be the most efficient approach for indirect selection for wood stiffness in Scots pine, although VEL alone and MOEDEN_CONST have provided very good results too. An index combining DBH and MOEDEN_RES.TB seems to offer the best compromise for simultaneous improvement of growth, fiber, and wood quality traits.

Seed orchards’ parental reproductive success is often assessed through surveys of seed- and pollen-cone production (reproductive investment). Although the reliability of this approach has been questioned, its speed and ease made it the method of choice for providing approximate estimates for the genetic quality and quantity of seed orchard crops. In this study, reproductive investment data from various female and male phenotypic assessment methods from three seed orchards (lodgepole pine ( Pinus contorta Dougl. ex. Loud. var. latifolia Engelm.), Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco), and western larch ( Larix occidentalis Nutt.)) were compared with reproductive success estimates based on DNA fingerprinting and parentage analyses. The use of reproductive investment as a proxy to reproductive success on estimating seed crop’s volume genetic worth and diversity (measured by effective number of parents) was evaluated. Regression analyses indicated that the phenotypic assessment methods reflect the true parental reproductive success and that estimates of seed- and pollen-cone volume production appear to be the most appropriate indicators of female and male reproductive success, respectively. Although the best combination of female–male survey methods produced inflated effective number of parents estimates, the genetic worth estimates were similar to those based on DNA, highlighting their robustness to fertility variation assessment.

Given an overall aim of improving Scots pine structural wood quality by selective tree breeding, we investigated the potential of non-destructive acoustic sensing tools to accurately predict wood stiffness (modulus of elasticity, MOE) and strength (modulus of rupture, MOR) of sawn boards. Non-destructive measurements of wood density (DEN), acoustic velocity (VEL) and MOE were carried out at different stages of wood processing chain (standing trees, felled logs and sawn boards), whilst destructively measured stiffness and strength served as benchmark traits. All acoustic based MOE and VEL estimates proved to be good proxies (r_A > 0.65) for sawn-board stiffness while MOE_TREE, VEL_HIT and resistograph wood density (DEN_RES) measured on standing trees and MOE_LOG and VEL_FAK measured on felled logs well reflected board strength. Individual-tree narrow-sense heritability ( $h_i^2$ ) for VEL, MOE and MOR were weak (0.05–0.26) but were substantially stronger for wood density (0.34–0.40). Moreover, additive genetic coefficients of variation for MOE and MOR were in the range from 5.4% to 9.1%, offering potential targets for exploitation by selective breeding. Consequently, selective breeding based on MOE_TREE, DEN_RES or stem straightness (STR) could improve several structural wood traits simultaneously.

Chemical composition is one of the key characteristics that determines wood quality and in turn its suitability for different end products and applications. The inclusion of chemical compositional traits in forest tree improvement requires high‐throughput techniques capable of rapid, non‐destructive and cost‐efficient assessment of large‐scale breeding experiments. We tested whether Fourier‐transform infrared (FTIR) spectroscopy, coupled with partial least squares regression, could serve as an alternative to traditional wet chemistry protocols for the determination of the chemical composition of juvenile wood in Scots pine for tree improvement purposes. FTIR spectra were acquired for 1,245 trees selected in two Scots pine (Pinus sylvestris L.) full‐sib progeny tests located in northern Sweden. Predictive models were developed using 70 reference samples with known chemical composition (the proportion of lignin, carbohydrates [cellulose, hemicelluloses and their structural monosaccharides glucose, mannose, xylose, galactose, and arabinose] and extractives). Individual‐tree narrow‐sense heritabilities and additive genetic correlations were estimated for all chemical traits as well as for growth (height and stem diameter) and wood quality traits (density and stiffness). Genetic control of the chemical traits was mostly moderate. Of the major chemical components, highest heritabilities were observed for hemicelluloses (0.43–0.47), intermediate for lignin and extractives (0.30–0.39), and lowest for cellulose (0.20–0.25). Additive genetic correlations among chemical traits were, except for extractives, positive while those between chemical and wood quality traits were negative. In both groups (chemical and wood quality traits), correlations with extractives exhibited opposite signs. Correlations of chemical traits with growth traits were near zero. The best strategy for genetic improvement of Scots pine juvenile wood for bioenergy production is to decrease and stabilize the content of extractives among trees and then focus on increasing the cellulose:lignin ratio.