Abstract
AbstractChemical 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 sylvestrisL.) 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.
Highlights
Wood is a natural organic material that has been utilized by humans for millennia in many aspects of their daily lives
Fourier-transform infrared (FTIR) spectroscopy, coupled with multivariate regression modeling, has proved to be a promising technique for Scots pine breeding as it can rapidly, inexpensively, non-destructively, and with good accuracy determine the chemical composition of wood in a large number of samples. It suffices with fractional amounts of wood material (~5 mg) and offers the possibility of skipping the extraction of increment cores from most trees included in the genetic evaluation. This would considerably reduce the stress load posed on trees, as increment core borers typically create big holes in their stems, which might jeopardize young trees’ physical stability as well as increase the risk of fungal infections, in particular in trees that are to be maintained in their plantations or stands for a long time, e.g., until the rotation age
The resistograph appears to be an ideal tool in this regard, especially when wood density is already involved in the evaluation, as wood shavings produced during drill needle penetration can be collected and later utilized in the FTIR analysis
Summary
Wood is a natural organic material that has been utilized by humans for millennia in many aspects of their daily lives. Large genetic variation in the chemical compositional traits has been observed in juvenile wood of several pine species (Shupe, Choong, & Yang, 1996; Sykes, Li, Isik, Kadla, & Chang, 2006). Since these traits are directly linked with the usability of wood for different applications, including pulp, paper and biofuel production, it is appealing to incorporate them in forest tree breeding programs. In this study we intended to (a) quantify the extent of additive genetic variation in growth, wood quality and chemical compositional traits in juvenile wood of Scots pine (Pinus sylvestris L.), (b) estimate all traits’ narrow-sense heritabilities, (c) determine the magnitude and direction of phenotypic and additive genetic correlations between all pairs of the studied traits and (d) evaluate the potential of the chemical compositional traits for genetic improvement via selective breeding to produce wood materials with desired chemical compositions
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