New values to the bio‐based industryby precision wood characterisation and delivery
Lars Wilhelmsson & John ArlingerBackground picture from:The Swedish Forest Sector Research Agenda (2017)© Swedish Forest Industries Federation
The worldinMercatorprojectione.g. Google Maps
Reference: Google Maps
”True size” projection
Reference: www.thetruesize.com
”True size” of Sweden
Reference: www.thetruesize.com
73 %
80 %
Sweden = forest
cultivatedforest
forest
The forest Sweden’s mostimportant raw material
Forestry and the forest branch contributes to solutions!
Forestry and the forest branch contributes to solutions!
Production value ofSwedish forest based
products€ 12,000,000,000
Market value of sustainablyproduced roundwood
€ 3,000,000,000
• Sustainability• More forest based materials
• Value chains• Right from initiation
• Other ecosystem services
Forests and forestry
Background picture from:The Swedish Forest Sector Research Agenda (2017)© Swedish Forest Industries Federation
Stiffness, bending strengthShape stabilityDurabilitySurface propertiesVisual properties
From the Swedish Forest Sector Research Agenda© Swedish Forest Industries Federation
Fibre properties(length, cell-wallthickness etc)Tear, tensile strengthPorosityExtractives…..
From the Swedish Forest Sector Research Agenda© Swedish Forest Industries Federation
Material: Sample plots from the Swedish National Forest Inventory
• DBH• Tree height• Tree age (BH)• Coordinates• Species composition• Plot areas
~ 45000 Scots pine trees ~ 70 000 Norway spruce trees
56 57 58 59 60 61 62 63 64 65 66 67 68Latitud°
• DBH• Tree height• Age (BH)• Coordinates• Species • Plot areas
Simulated harvesting
• Basic density- Bending strength- & stiffness, C-class- Surface hardness- Chip and fiber properties,- Yield (material) & Combustion value
• Thickest branch/whorl
+ Distance between whorles
• Heartwood- durability
Some wood properties harder to measure during operation,but possible to predict
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56 57 58 59 60 61 62 63 64 65 66 67 68Latitude °
Thickestbranch/whorl
(mm)Basic density, kg/m3sub
Dens Grövsta gren/varv
Basic densityThickestbranch/whorl
Scots pine all sawlogs, small end diameter > 140 mm
52699 logs
Mean values& ---- 95% ofpredicted variation
Results from simulated harvesting of plots from The Swedish National Forest Inventory, Bucking simulations by TimAn (Skogforsk) and models for predicting wood properties (Skogforsk, Innventia, SLU)
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Thickest branch/whorl
(mm)
Basic density, kg/m3sub
Latitude°
DensGrövsta gren/varv
Basic densityThickestbranch/whorl
Scots pine all butt logs > 140 mm Mean values& ---- 95% of
predicted variation
Results from simulated harvesting of plots from The Swedish National Forest Inventory, Bucking simulations by TimAn (Skogforsk) and modelsfor predicting wood properties (Skogforsk, Innventia, SLU)
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56 57 58 59 60 61 62 63 64 65 66 67 68Latitude °N
Thickestbranch/whorl
(mm)
Basic density kg/m3sub
Dens Grövsta gren/varv
Example Butt logs Scots pine Small end diameters 220 -239 mm (ub)
3269 logs
Mean values& ---- 95% of
predicted variation
Basic densityThickestbranch/whorl
Results from simulated harvesting of plots from The Swedish National Forest Inventory, Bucking simulations by TimAn (Skogforsk) and modelsfor predicting wood properties (Skogforsk, Innventia, SLU)
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56 57 58 59 60 61 62 63 64 65 66 67Latitude °N
Thickestbranch/whorl
(mm)
Basic density kg/m3sub
Dens Grövsta gren/varv
Example 2:nd logs Scots pine Small end diameters 220 -239 mm (ub)
1370 logs
Basic densityThickestbranch/whorl
Results from simulated harvesting of plots from The Swedish National Forest Inventory, Bucking simulations by TimAn (Skogforsk) and modelsfor predicting wood properties (Skogforsk, Innventia, SLU)
0102030405060708090
100
56 57 58 59 60 61 62 63 64 65 66 67 68
Heartwoodpercentage
%
Latitude°N
Kärnved%Heartwood %
Scots pine, all sawlogs > 140 mm
Results from simulated harvesting of plots from The Swedish National Forest Inventory, Bucking simulations by TimAn (Skogforsk) and modelsfor predicting wood properties (Skogforsk, Innventia, SLU)
Example Buttlogs Scots pine, Toppdiameter 220 -239 mm (ub)
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Heartwoodpercentage
%
Latitude °N
Kärnved%Heartwood %
Results from simulated harvesting of plots from The Swedish National Forest Inventory, Bucking simulations by TimAn (Skogforsk) and modelsfor predicting wood properties (Skogforsk, Innventia, SLU)
05
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56 57 58 59 60 61 62 63 64 65 66 67
Distance between branch whorls, cm
Latitude °N
Kvistvarvsavstånd
Example: 2:nd logs Scots pineSmall end diameter 220 -239 mm (ub)
Distance betweenwhorls
Results from simulated harvesting of plots from The Swedish National Forest Inventory, Bucking simulations by TimAn (Skogforsk) and modelsfor predicting wood properties (Skogforsk, Innventia, SLU)
0%
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56 57 58 59 60 61 62 63 64 65 66 67 68Latitude˚N
Percentage trees without any crooks or damage over latitudes
Norway spruce Scots pine
Results based on analysis of the Swedish National Forest Inventory 2005-2009 (Wilhelmsson 2017 unpubl.)
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12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37SI (m, H100)
Percentage trees without any crooks or visible damage over site fertility index (SI)
Norway spruce Scots pine
Results based on analysis of the Swedish National Forest Inventory 2005-2009 (Wilhelmsson 2017 unpubl.)
Mapping of stem properties by harvester production files (StanForD)
• Data on individual logs/stems reportedfrom all harvested objects• Log diameters, length and longitudinal
positions in stems• Species• Coordinates• Stem faults (operator’s forced cuts)
• Stems can be ”reconstructed” to analysealternative bucking regimes
• Skogforsk has established a nationwidedatabase of harvester production files. More results coming……
Example from a randomlypickedharvesting object”Labbo” ~ latitude 60˚
350370390410430450
140 190 240 290 340
kg/m3sub
Log small end diameter (ub), mm
Basic density
101520253035
140 190 240 290 340
mm
Small end diameter (ub), mm
Thickest branch per whorl, mm
Labbo, Örbyhusex. Ala pine quality 3
Reference: amaozon.com
Mastering the variationsopens new opportunities
Conclusions• Large variation in wood properties – turn problem to opportunity!• The variation pattern is similar for pine and spruce
• Internal properties of logs can be calculated and partly predictedby tree height, diameter (along stem) tree age (bh) coordinates+ models of wood properties
• All this can be utilized for- improving utilization of the variability of forest raw materials- improving planning and yield calculations
General aim - EFFORTE
to develop and adopt novel technology and tools that improve:
• efficiency and sustainability of forestry
• throughout the entire forest based value chain within the EU
Connection harvestingto silvicultureValue chain
perspective
The next generation forests