Author:
Gort Jaume,Zubizarreta Gerendiain Ane,Peltola Heli,Pulkkinen Pertti,Routa Johanna,Jaatinen Raimo
Abstract
In forest breeding, stem volume growth and sawn timber quality indicators have been used as the most important selection traits for Scots pine, whereas less attention has been given to characteristics such as fibre properties. In the above context, we investigated the differences in fibre properties (i.e. fibre length, fibre width and coarseness) in 20 year old Scots pine (Pinus sylvestris L.) genetic entries as affected by spacing and site, but also the phenotypic correlations between fibre properties, yield and wood density. The study was based on materials harvested from 10 genetic entries grown in a spacing trial (site 1) in central Finland, with a current stand density of 2000 (spacing 1), 2000â2500 (spacing 2) and 4000 trees/ha (spacing 3). In order to study the effects of site, we harvested additional material (4 of 7 genetic entries same as on site 1) from a trial located in southern Finland with a corresponding stand density of 2000 trees/ha (site 2). On site 1, spacing 1 and 3, all average values for analysed fibre properties were similar. In spacing 2 average values were slightly higher. On site 2, the average values for different fibre properties were similar compared to the corresponding spacing 1 on site 1. Spacing affected (p < 0.05) all average fibre properties on site 1; as did also site, when comparing same genetic entries grown on both sites. Regardless of spacing and site, the phenotypic correlations between average fibre length, fibre width and coarseness showed, on average, moderate to strong correlation (p < 0.05). Fibre width showed, in general, low and positive phenotypic correlation with diameter at breast height, stem volume and wood density on site 1. However, as a whole, the ranking of genetic entries changed depending on the trait and spacing considered. Thus, no overall ranking between genetic entries was possible.
Publisher
Finnish Society of Forest Science
Subject
Ecological Modeling,Forestry
Cited by
8 articles.
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