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THE INFLUENCE OF WOOD EXT RACTIVES ON DURABILITY PROPERTIES OF
HARDWOODS AND SOFI'WOOD EXPOSED TO ARTIFICIAL WEATHERING

presented by

Pascal Nzokou

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THE INFLUENCE OF WOOD EXTRACTIVES ON DURABILITY PROPERTIES
OF HARDWOOD AND SOFI'WOOD SPECIES EXPOSED TO ARTIFICIAL
WEATHERING
By

Pascal N zokou

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Forestry

2004

Abstract
The Inﬂuence of Wood Extractives on Durability Properties of Hardwoods and
Softwoods Exposed to Artificial Weathering
By

Pascal Nzokou

Wood is the prime building material for various structures in outdoors
applications. It is widely used for structures such as decking, railroad crossties, and
playground equipment. However, when exposed to outdoor conditions, wood is
susceptible to weathering degradation.

This project investigated the inﬂuence of wood extractives on the weathering of
red oak (Quercus rubra), black cherry (Prunus serotina), and red pine (Pinus resinosa).

The ﬁrst hypothesis of the study was that wood extractives occupy moisture
sorption sites in wood and prevent water absorption. Therefore, removal of extractives by
the weathering process leads to higher moisture absorption, which in turn leads to higher
shrinkage and higher cracking of the wood surface. The second hypothesis was that wood
extractives acts as antioxidants protecting the wood surface against photodegradation.

To test these hypotheses organic solvents were used to remove extractives from
red pine, red oak, and black cherry wood specimens. Their physical, chemical and
aesthetic degradation processes were monitored during laboratory conducted artiﬁcial
weathering.

Fourier Transformed Infrared and X-Rays Photoelectron spectroscopy analysis
demonstrated the removal of high carbon contents (from extractives and lignin), and

increased exposure of cellulose and hemicellulose on the extracted wood surfaces.

Water sorption of extracted wood surfaces was higher than that of un-extracted
surfaces at high relative humidities as a result of availability of moisture sorption sites
previously occupied by extractives, which became available follow extraction.
Application of the Hailwood Horrobin model and calculation of the free energy change
for the hydrated water showed that lower energy was required to swell the wood structure
due to the increase in hydrophilic sites available. The contact angle decreased
signiﬁcantly following extraction as a consequence of the higher ability of wood surfaces
to absorb water.

Analysis of the surface roughness, weight loss and microscopic degradation,
however, showed no statistically signiﬁcant difference between control and extracted
samples for red oak and black cherry, and a signiﬁcant difference in the direction
disproving our hypothesis for red pine. These observations suggest that the increased
susceptibility to absorb water demonstrated in the sorption study did not result in higher
susceptibility to physical degradation when exposed to artiﬁcial weathering.

The photo-discoloration study of wood surfaces evidenced a signiﬁcant inﬂuence
of water extractives on the overall discoloration of wood surface when exposed to
artiﬁcial weathering. The presence of extractives slowed the discoloration process with
polyphenolic water extractives acting as antioxidant protecting the wood against
photodegradation.

These results suggest that extractives affect the chemical processes occurring on
the wood surface, but their inﬂuence on the physical degradation of wood, which is more

affected by the wood structure, is limited.

DEDICATION
To my late parents, Richard Nzokou and Jeanne Mawe Nzokou
To my beloved wife Caroline and my children Aristarque and Richard,

To my brothers and sisters for their patience, and sacriﬁces.

iv

ACKNOWLEDGEMENTS

I would like to express my sincere appreciation and thanks to my major professor,
Pr. D. Pascal Kamdem, for his guidance and assistance in all phases of my graduate
program. I am especially thankful for his trust and friendship, and was impressed and
inﬂuenced by his endless patience, encouragement, kindness, and understanding. I am
also grateful and deeply indebted to Dr. Stanley L. Flegler for his guidance and constant
support during the course of my graduate program. I appreciate the support, interest,
cooperation and valuable suggestions of Pr. Dickmann, and Dr. Han, both from the
Department of Forestry at MSU, and Dr. Tim Ryspstra from Department of Wood
Science at the University of Stellenbosch, South Africa

I would also like to extend my gratitude and appreciation to Ewa Danielewicz,
Carol Flegler, and Dr. Shirley Owens for their assistance at the Center for Advanced
Microscopy, and Dr. Kathy Severin of the Department of Chemistry for her assistance
with contact angle work.

I am particularly indebted to Joe Pennock, Haihong Jiang, Kyle Wehner, Josh
Rawson and Weining Cui for their helpful assistance, cooperation, and support
throughout this study. I also wish to thank the USDA-CSRESS Eastern Hardwood

Utilization Program for funding my graduate studies.

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................................... v
LIST OF FIGURES ......................................................................................................... viii
CHAPTER 1
INTRODUCTION .............................................................................................................. 1
References ........................................................................................................................... 5
CHAPTER 2
LITERATURE REVIEW
2.1 Wood Structure and Anatomy .......................................................................... 7
2.2 Wood Extractives .............................................................................................. 8
2.2.1 Softwood Extractives ....................................................................... 10
2.2.2 Hardwood Extractives ...................................................................... 12
2.2.3 Formation of Wood Extractives ....................................................... 13
2.2.4 Dimensional Stability and Speciﬁc Gravity .................................... 14
2.2.5 Shrinkage and Wettability ................................................................ 16
2.2.6 Mechanical Properties ...................................................................... 17
2.3 Factors Affecting the Weathering of Wood Surfaces ..................................... 18
2.3.1 Factors Inherent to Wood .................................................................. 18
2.3.1.1 Density ........................................................................................... 18
2.3.1.2 Juvenile Wood, Pith and Growth Ring Orientation ....................... 21
2.3.1.3 Knots .............................................................................................. 23
2.3.2 External Factors of Weathering ....................................................... 23
2.3.2.1 Light .............................................................................................. 23
2.3.2.2 Moisture Changes ......................................................................... 25
2.3.2.3 Angle of Exposure ......................................................................... 29
2.3.2.4 Temperature ................................................................................... 29
References .................................................................................................. 30
CHAPTER 3

FFIR AND XPS CHARACTERIZATION OF RED OAK (QUERCUS RUBRA),
BLACK CHERRY (PRUNUS SEROTINA) AND RED PINE (PINUS RESINOSA)
EXTRACTIVES AND WOOD SURFACES

Abstract .................................................................................................................. 36
3.1 Introduction ..................................................................................................... 37
3.2 Materials and Methods .................................................................................... 39
3.2.1 Materials .......................................................................................... 39
3.2.2 Extraction ......................................................................................... 41
3.2.3 Samples Preparation for FF IR and XPS .......................................... 42
3.2.4 FTIR ................................................................................................. 44
3.2.3 X-ray Photoelectron Spectroscopy .................................................. 44

vi

3.3 Results and Discussion ................................................................................... 44

3.3.1 FTIR of Wood Extractives ............................................................... 44
3.3.2 FTIR Spectra of Extracted Wood Surfaces ...................................... 52
3.3.3 XPS Characterization of Extracted Wood Surfaces ......................... 55
3.4 Conclusion ...................................................................................................... 64
References .............................................................................................................. 65

CHAPTER 4

INFLUENCE OF WOOD EXTRACTIVES ON MOISTURE SORPTION AND
WETTABILITY OF RED OAK (QUERCUS RUBRA), BLACK CHERRY (PRUNUS
SEROTINA) AND RED PINE (PINUS RESINOSA)

Abstract .................................................................................................................. 68
4.1 Introduction ..................................................................................................... 69
4.2 Materials and Methods .................................................................................... 72
4.2.1 Materials .......................................................................................... 72
4.2.2 Sorption Test .................................................................................... 73
4.2.3 Contact Angle .................................................................................. 73
4.2.4 Data Analysis ................................................................................... 74
4.3 Results and Discussion ................................................................................... 76
4.3.1 Sorption ............................................................................................ 76
4.3.2 Contact Angle .................................................................................. 85
4.4 Conclusion ...................................................................................................... 89
References ............................................................................................................. 90
CHAPTER 5

THE INFLUENCE OF WOOD EXTRACTIVES ON THE PHYSICAL
DEGRADATION OF WOOD SURFACES EXPOSED TO ARTIFICIAL

WEATHERING
Abstract .................................................................................................................. 93
5.1 Introduction ..................................................................................................... 94
5.2 Materials and Methods .................................................................................... 95
5.2.1 Artiﬁcial Weathering ....................................................................... 95
5.2.2 Surface Roughness Estimation ........................................................ 96
5.2.2 Weight Loss ..................................................................................... 97
5.2.3 SEM Observations ........................................................................... 97
5.2.4 Statistical Analysis ........................................................................... 98
5.3 Results and Discussion ................................................................................... 99
5.3.1 Surface Roughness ........................................................................... 99
5.3.2 Weight Loss ................................................................................... 104
5.3.3 SEM Observations ......................................................................... 104
5.4 Conclusion .................................................................................................... 113
References ............................................................................................................ 1 15

vii

CHAPTER 6
THE INFLUENCE OF WOOD EXTRACTIVES ON THE PHOTODISCOLORATION
OF WOOD SURFACES EXPOSED TO ARTIFICIAL WEATHERING

Abstract ................................................................................................................ 117
6.1 Introduction ................................................................................................... 118
6.2 Materials and Methods .................................................................................. 120
6.2.1 Materials ........................................................................................ 120
6.2.2 Artiﬁcial Weathering .................................................................... 120
6.2.3 Color Measurement ........................................................................ 120
6.2.4 Statistical Analysis ......................................................................... 121
6.3 Results and Discussion ................................................................................. 123
6.3.1 Changes in Lightness (L*) ............................................................. 123
6.3.2 Chromaticity Coordinates .............................................................. 126
6.3.3 Color Change (AE) ......................................................................... 135
6.3.4 Conclusion ..................................................................................... 142
References ................................................................................................ 143
CHAPTER 7
CONCLUSIONS AND RECOMMENDATIONS .......................................................... 144
Appendixes ...................................................................................................................... 146

viii

LIST OF TABLES

Table 3.1. Percentage of Extractives Removed (dry weight basis) ................................... 43
Table 3.2. Peak Assignment for FI‘ IR Spectra .................................................................. 45

Table 3.3. Percent of Cls, 01s and O/C peak of red oak, black cherry and red pine wood
surfaces .............................................................................................................................. 56

Table 3.4. Classiﬁcation of Carbon and Oxygen Peak Components, Cls and 013 of

Woody Materials (Kamdem et a1 1991) ............................................................................. 58
Table 3.5. Summary of XPS Spectral Parameters in Red Oak .......................................... 59
Table 3.6. Summary of XPS Spectral Parameters in Black Cherry ................................... 62
Table 3.7. Summary of XPS Spectral Parameters in Red Pine .......................................... 63

Table 4.1. Relative Humidity Values for Selected Saturated Salt Solution (ASTM E104-
85) ...................................................................................................................................... 75

Table 4.2. Adsorption and Desorption EMC of Extracted and Un-Extracted Specimens .77

Table 4.3. Hysteresis Ratio of Specimens at Various Relative Humidity ......................... 78
Table 4.4. Parameters for the Hailwood-Horrobin Sorption Model .................................. 84
Table 4.5. Average (Left and Right) Advancing Contact Angle ....................................... 87
Table 4.6. Rate of Change in Contact Angle (R) over time between distilled water and

wood surface (Degrees/Second) ........................................................................................ 88
Table 5.1. Calculated Indexes of Roughening and Microcracking after 2400b Weathering
Exposure .......................................................................................................................... 103
Table 6.1. Lightness of Wood Specimens After Artiﬁcial Weathering ........................... 124

Table 6.2. Lowering Index of Lightness for Red Pine, Red Oak and Black Cherry After
Artiﬁcial Weathering ...................................................................................................... 125

Table 6.3. Chromaticity Coordinates a* of Wood Specimens After Exposure to Artiﬁcial
Weathering ...................................................................................................................... 128

LIST OF TABLES (Cont)

Table 6.4. Chromaticity Coordinates b* of Wood Specimens After Exposure to Artiﬁcial

Weathering ....................................................................................................................... 130
Table 6.5. Extractives Removed and Color Change After Artiﬁcial Weathering ........... 138
Table 6.6. AE and Visual Observation in the CIELAB System ..................................... 139
Table 6.7. Color Change After Artiﬁcial Weathering ..................................................... 140

LIST OF FIGURES

Figure 3.1. FTIR Spectra of Black Cherry Extractives Removed With Ethanol-Toluene

(Eth-T01), Ethanol (Eth) and Water ................................................................................... 46
Figure 3.2. FT IR Spectra of Red Oak Extractives Removed With Ethanol-Toluene (Eth-

Tol), Ethanol (Eth) and Water ........................................................................................... 49
Figure 3.3. FTIR Spectra of Red Pine Extractives Removed With Ethanol-Toluene (Eth-

Tol), Ethanol (Eth) and Water ........................................................................................... 51
Figure 3.4. FTIR Spectra of Black Cherry Extracted Wood Surfaces ............................... 53
Figure 3.5. FT IR Spectra of Red Oak Extracted Wood Surfaces ...................................... 53
Figure 3.6. FT IR Spectra of Red Pine Extracted Wood Surfaces ...................................... 54
Figure 4.1. Adsorption Curves of Extracted and Non Extracted Black Cherry ................ 79
Figure 4.2. Adsorption Curves of Extracted and Non Extracted Red Oak ........................ 80
Figure 4.3. Adsorption Curves of Extracted and Non Extracted Red Pine ........................ 81
Figure 5.1. Change in Roughness (Ra) After Extraction ................................................. 101
Figure 5.2. Change in Maximum Peak to Valleys (Rmax) After Extraction ................... 102
Figure 5.3. Weight Loss of Wood Samples After 2400b Artiﬁcial Weathering ............. 105

Figure 5.4. SEM Micrographs of Red Pine Wood Surfaces After 2400h Artiﬁcial
Weathering. (A) Un-Extracted. (B) Eth-T01 Extracted (C) Eth-T01 + Water Extracted (D)
Eth Extracted. (E) Eth + Water Extracted ....................................................................... 106

Figure 5.5. SEM Micrographs of Red Oak Wood Surfaces After 2400b Artiﬁcial
Weathering. (A) Un-Extracted. (B) Eth-T01 Extracted (C) Eth-To] + Water Extracted (D)
Eth Extracted. (E) Eth + Water Extracted ....................................................................... 108

Figure 5.6. SEM Micrographs of Black Cherry Wood Surfaces After 2400b Artiﬁcial
Weathering. (A) Un-Extracted. (B) Eth-T01 Extracted (C) Eth-T01 + Water Extracted (D)
Eth Extracted. (E) Eth + Water Extracted ....................................................................... 110

Figure 5.7. SEM Micrographs of Eth—T01 Extracted Black Cherry Wood Surfaces After
Artiﬁcial Weathering. (A) 400h Exposure. (B) 2400b Exposure .................................. 112

xi

LIST OF FIGURES (Cont.)

Figure 6.1. Color L*, a*, b* of Solids ............................................................................. 122
Figure 6-2(a-c) Change in Chromaticity Coordinates a (Da*) over the exposure time...129
Figure 6-3(a-c) Change in Chromaticity Coordinates b (Db*) over the exposure time ..131

Figure 6.4. Relation Between Chromaticity Coordinates a* and b* for Red Pine After

Artiﬁcial Weathering ...................................................................................................... 132
Figure 6.5. Relation Between Chromaticity Coordinates a* and b* for Red Pine After

Artiﬁcial Weathering ...................................................................................................... 133
Figure 6.6. Relation Between Chromaticity Coordinates a* and b* for Black Cherry After
Artiﬁcial Weathering ....................................................................................................... 134
Figure 6.7. Color Change (AE) of Wood Samples After Artiﬁcial Weathering .............. 141

xii

Chapter 1

Introduction

Wood is the material of choice for several exterior applications such as poles,
fencing, decking, siding, and walls. However, like other biological materials wood is
susceptible to degradation. When exposed to the weather, wood undergoes a complex
process of physical, chemical, and mechanical degradations commonly known as
weathering (Feist 1982; Feist and Hon 1984). This process results from the combined
action of weather factors such as oxygen, ultraviolet light, relative humidity, and wind,
that induce discoloration and physical deterioration of wood surfaces (Feist and Hon
1984; Owen et a1. 1993). The wood color quickly changes towards a brown color, and
later to a whitish gray (Browne 1960; Feist and Hon 1984). These factors destroy the
aesthetic quality of wood and reduce its service life.

Wood in exterior applications faces stiff competition from various substitutes and
there is a great need to investigate and understand all the factors causing its degradation
in outdoor uses. This will help develop strategies to overcome those shortcomings.

Several intrinsic wood factors have been reported to affect the weathering
process. These include wood density, the presence of earlywood and latewood, juvenile
wood, and wood extractives (Feist and Hon 1984). A great deal of research has been
performed to describe the inﬂuence of density and juvenile wood on the weathering
process, but there are only limited published results describing the mechanisms by which
wood extractives interact with other weathering factors to degrade wood in outdoor

applications.

Wood extractives are deﬁned as components of wood removable by leaching or
extraction with water or organic solvents (Dadswell and Hillis 1962; Hillis 1987). They
usually include many different classes of organic compounds, ranging from relatively
simple molecules such as phenols and sugars, to highly complex coloring matters like
tannins and resins.

It is well established that the presence and amount of extractives in wood plays a
signiﬁcant role in wood properties, including affecting physical and mechanical
properties, equilibrium moisture content, and dimensional stability (Chen and Chong
1994). Wood extractives also play an important role in the natural decay resistance of
several temperate wood species such as osage orange, black locust, and redwood (Schultz
et al. 1995; Kamdem 1994; Nzokou and Kamdem 2003) and in tropical woods such as
teak (Tectona grandis) and grenadillo (Platymiscium yucatanum) (Waterman 1946;
Reyes-Chilpa et al. 1998, Rudman 1963; Thevenon et al. 2001).

Frequently the inﬂuence of extractives on physical properties of wood are
explained by the following hypotheses:

a) A bulking effect. It is suggested that large molecules of wood extractives keep
the wood structure in a semi-swollen condition and hinder the number of available sites
for the formation of intermolecular lignin-cellulose and/or lignin-lignin bonds (Ajuong
and Breese 1997). In addition, studies during non-steady state drying from green
condition have suggested that the presence of extractives induce signiﬁcant reductions in
both creep and shrinkage at lower temperature, while increasing both phenomena at

higher temperature (Ajuong and Breese 1997)

b) A plasticizing effect. The presence of extractives may promote plastic ﬂow
(Narayanamurti 1957) i

c) An effect of stiffening the cell walls. This is supported by claims that
extractives exert a small but signiﬁcant increase in short term mechanical properties of
wood (Panshin and De Zeeuw 1980; Ajuong and Breese 1997).

In addition, Pizzi and Cameron (1986) demonstrated that tannin extractives within
the cell wall of drought resistant species act as springs limiting the cracking of cell walls.

Although there are numerous references characterizing wood extractives and
investigating their inﬂuence on water related and durability properties of several wood
species, the relationship between wood extractives content and the weathering properties
of wood surfaces is not well understood.

The goal of this project was to investigate possible correlations between wood
extractives and the susceptibility to weathering. This will help in explaining and
predicting the durability or weathering resistance observed in some species.

It is anticipated that the removal of extractives and their washing out by the
weathering process would induce increased shrinkage, leading to a higher susceptibility
to cracking. In addition, the modiﬁcation of the extractive content and wood composition
by weathering may affect wood structure by increasing the hydrophilic nature of wood
and subsequently its susceptibility to decay fungi.

The experimental hypotheses are based on the likely mechanisms on how

extractives inﬂuence the weathering of wood.

Hypothesis 1: Wood extractives bulk cell walls, lower shrinkage, and affect speciﬁc

Hui

gravity (Nearn 1955; Ajuong and Breese 1997). Therefore, the removal of
extractives makes available additional moisture sorption sites and induces
higher dimensional change, leading to more cracks when exposed to
weathering.

Extracted wood will be more physically unstable than non-extracted wood,
and will therefore display increase in surface roughness, and weight loss,
higher and more injurious macroscopic and microscopic cracks after

weathering.

Hypothesis II: Extractives are the cause of wood color, and have a plasticizing effect in

H211

wood. Flavonoids, lignans, and tannins are polyphenolic substances with
the natural tendency to greasiness (Ajuong and Breese 1997). They act as
antioxidants capable of protecting wood surface against photooxidation
(Maldas and Kamdem 1999). Therefore extracted wood will be more
susceptible to photodegradation caused by the weathering process than
un-extracted wood.

Extracted wood samples will be more prone to discoloration due to
weathering compared to un-extracted wood samples due to the loss or

reduction of its antioxidant protection.

References

Ajuong, Elijah-M. A. and Breese M. C. 1997. The role of extractives on short term creep
in compression parallel to grain of pai wood (Afzelia africana Smith). Wood and Fiber
Science. 29(2): 161-170.

Browne F. L. 1960. Wood siding left to weather naturally. Southern Lumberman 201 (2513):
141-143.

Chen Y., and Chong E. T., 1994. Determining the effect of extractives on moisture movement
using a continuous measuring system. Wood and Fiber Science. 26(3): 390-396.

Dadswell, H. E., and W. E. Hillis 1962. Wood. In Wood Extractives and their signiﬁcance
to the pulp and paper industries. pp 1-49. W.E. Hillis ed. Academic Press London, UK.

Feist, W. C. 1982. Weathering of wood in structural uses. In “Structural Use of Wood in Adverse
Environments” (R. W. Meyer and R. M. Kellogg, eds.), pp. 156-178. Society for Wood
Science and Technology, University of British Columbia.

Feist, W. C., and Hon, D. N. S. 1984. Chemistry of Weathering and Protection. In ”The
Chemistry of Solid Wood” (R. Rowell, ed.), pp. 401-451. American Chemical Society,
Washington DC.

Hillis W. E., 1987. Heartwood and Tree Exudates. Springer-Verlag, Berlin Germany.
268pp.

Kamdem, D. P. 1994. Fungal decay resistance of aspen blocks treated with heartwood extracts.
Forest Products Journal 44 (1), 30-32.

Maldas, D. C., and Kamdem, D. P. 1999. Wettability of extracted southern pine. Forest Products
Journal 49 (1 1/12), 91-93.

Narayanamurti, D. 1957. The role extractions in wood. Holz als Roh-und Werkstoff. 15: 370-380.

Neam, W. J. 1955. Effect of water soluble extractives on the volumetric shrinkage and
equilibrium moisture content of eleven tropical and domestic woods. Bull. 598. Penn.
State Univ., Agric. Exp. Sta., University Park, PA. 38pp.

Nzokou, P. and Kamdem D. P. 2003. Fungal Decay Resistance of Non-Durable Aspen Wood
Treated with Extractives from African Padauk (Pterocatpus soyauxii). Journal of
Tropical Forest Products 9( 1&2): 125-133.

Owen, J. A., Owen, N. L., and Feist, W. C. 1993. Scanning Electron-Microscope and Infrared
Studies of Weathering in Southern Pine. Journal of Molecular Structure 300, 105-114.

Panshin and Dezeeuw 1980. Textbook of wood technology. Vol. 1. 3rd ed., McGraw-Hill Co.,
New York, NY.

Pizzi, A., and Cameron F. A. 1986. Flavonoid tannins-structural wood components for drought
resistance mechanisms of plants. Wood Science and Technology 20: 119-124.

Reyes-Chilpa R., F. Gomez-Garibay, G. Moreno-Torres, G. J imenez-Estrada and R. I.
Quiroz-Vasquez 1998. Flavonoids and isofavonoids with antifungal properties from
Platymiscium yucatanum heartwood. Holzforschung 52(5): 459-462.

Rudman, P. 1963. The causes of natural durability in timber: Part IX. The antifungal
activity of heartwood extractives in a wood substrate. Holzforschung 16(3): 74-77.

Schultz T. P, W. B. Harms, T. H. Fisher, K. D. Minn. and D. D. Nicholas 1995.
Durability of angiosperm heartwood- The importance of extractives. Holzforschung
49(1): 29-34.

Thevenon, M. F., C. Roussel, and J. P. Haluk. 2001. Possible durability transfer from non durable
wood species. The study case of teak wood. Paper presented at the International Research
Group on Wood Preservation (IRG) Nara, Japan, 20-25 May, 2001.

Waterman M. A., 1946. The effect of water-soluble extractives from the heartwood of tropical
American woods on the growth of two wood decay fungi. Tropical Woods 88: 1-11.

Chapter 2

Literature review

2.1 Wood Structure and Anatomy

The anatomical structure, the chemical composition and the physical properties of
wood play an important role in the weathering of wood.

Wood is the secondary xylem formed by cell division of the vascular cambium in
a living tree (Kollman and Cote 1984). Wood cells make up the xylem portion of the tree
as contrasted to the phloem (bark), which forms the protective layer surrounding the
xylem. Softwood shows a simple structure with tracheids arranged in radial rows
representing the only major type of longitudinal elements. Tracheids represent 90 to 95%
of the total structure in softwoods. They are long cells with ﬂattened or tapered ends
(Haygreen and Bowyer 1996). Their cell walls contain pits, which provide pathways for
conduction of ﬂuids to adjoining cells. In hardwoods, in addition to ﬁbers, there are cells
of relatively large diameter known as vessels or pores. These cells are the main conduits
of the movement of liquid and sap. The other cell types found in hardwoods are ﬁber
tracheids, rays, and parenchyma. The wood rays are horizontally oriented tissue through
the radial plane of the tree. They vary in size from one cell wide and a few millimeters
high to more than 25 cells wide and several centimeters high. The rays connect various
layers from pith to bark for storage and transfer of starch and food.

Wood cell walls are complex in structure. Most are composed of primary (P) and
secondary (S) layers. The secondary layer is composed of several layers: S1,. 82, and S3
from the outside to the inner layer lining the cell lumen (Kollman and Cote 1984). Within

each layer the microﬁbrils are oriented more or less uniformly into a rather dense parallel

array. The 81 layer has its microﬁbrils oriented predominantly almost perpendicular to
the long axis of the cell. The S2 is the principal layer of the wall. It is generally thicker
than either the 81 or the S3 and since it is oriented approximately parallel to the cell axis,
it contributes most of the mechanical properties of the cells. Finally, the S3 is a thin layer
whose orientation runs parallel to that of the 81.

The structure and anatomy of wood and the presence of certain extractives in the
cells can signiﬁcantly affect the weathering properties of wood in use.
2.2 Wood extractives

Extractives are heterogenous chemical compounds naturally occurring in woody
plants (Panshin and DeZeeuw 1980). Hillis (1987) deﬁned extractives as non-structural
constituents of plants. They have lower molecular weight than other polymeric
constituents of wood and are distributed in lumina or in speciﬁc plant tissues. Extractives
may be within the cell wall, but are not chenrically attached to it. In addition to organic
extractives, plant cells contain insoluble extraneous constituents such as crystalline
inclusions of calcium oxalate and silica, starch granules, and other polymeric materials.

The term extractive covers a large number of compounds of different classes,
which can be extracted from wood with polar and nonpolar solvents (Hillis 1987). A
large number of compounds in extractives from different trees have been identiﬁed, and
they represent several classes of organic compounds. The polyphenolic compounds,
which do not include lignin, are the most common. Nearn (1955) classiﬁed wood
extractives into two groups: (a) extractives soluble only in organic solvents which are
distributed in the gross capillaries of the wood, (b) extractives which are soluble in water

and are present in both the coarse capillary structure and within the ﬁne cell-wall. The

chemical composition of extractives varies with species, different zones inside the tree,
and various wood tissues.
Wood extractives can be divided in four major classes (Hillis 1987):
Galactans and Cyclitols: These are rarely found coniferous wood extractive compounds.
They are heavily branched polysaccharides based on residues of arabinose and galactose.
Terpenoids: This is a large group of compounds, which are widespread and largely
found in softwoods. They are built from a number of ﬁve carbon isoprene units. The
terpenoids also have functional groups such as hydroxyl, carboxylic acid, carbonyl etc...
Fatty acids and related compounds: These include fats, fatty acids with glycerol and
triglycerides, and waxes deﬁned as esters of fatty acids with saturated straight chain
alcohols with 16-28 carbon atoms. Waxes usually occur in smaller amounts than fats.
Phenolic compounds: These are the most widespread components of the wood
extractives. There are thousands of polyphenols, which can be classiﬁed as follows;
0 Lignans: These are dimeric phenylpropane units linked covalently at the B carbon
atom.
0 Stilbenoids (C6-C2-C6): Stilbenes and Stilbenoids are diphenyl compounds joined
by complex arrangement of the propane group, often involving a ring structure.
They are present in both hardwoods and softwoods.
o Flavonoids (C6-C3-C6): The ﬂavonoids comprise many thousands of C6-C3-C6
compounds subdivided into ﬂavones, ﬂavanes, ﬂavanonols, and isoﬂavones.
Many types of ﬂavonoids can occur in hardwoods. The large number of
ﬂavonoids is not only due to the degree of saturation, but also to the variation of

hydroxylation of the rings.

0 Quinones biosynthesized from acetate units: Quinones are usually responsible
for strong colors, high durability, and dermatitic properties of some woods.
0 Polymerized polyphenols: Most of the phenolic extractives are present in wood in

a polymerized form and with largely unknown constitutions (Hillis 1987).

Extractives are found in greater amounts in heartwood than in sapwood, and
changes in content can be very abrupt in heartwood periphery. They are found largely in
the parenchyma, but can also be found in vessels and ﬁbers, and in some specialized cells
(Hillis 1987). In most cases, the extractives of the heartwood are stable, and there is little
or no change within plant species (Hillis 1968). However, several authors observed
variation from normal in a few wood species of the genera Cinnamomum, Pinus,
Pterocarpus (Hillis 1968), 0cotea (Gottlieb and Magalhaes 1959) and Acacia (Clark-
Lewis and Dainis 1967). However the occurrence of these variants is rather uncommon
(Hillis 1968).

There is considerable variation in the occurrence and distribution of extractives
within vascular plants. No single species contains all of the possible compounds or even
all of the different classes of compounds. However it is well established that extractives
from related species are similar and are often used for taxonomic purposes (Buchanan
1963). In that sense, there are noticeable differences between extractives occurring in
softwood species and those found in hardwood species.

2.2.1 Softwood extractives

According to Koch (1972), softwood extractives comprise a heterogeneous group

of compounds present in low concentrations. Among the most important are terpenes and

wood resins, both of which are composed of isopropene units, polyphenols such as

10

ﬂavonols, anthocyanins, quinones, Stilbenes, lignans and tannins, tropolones, glycosides,
sugars, fatty acids and inorganic constituents.
Teppenes: The common chemical characteristic of terpenes is their composition of
isopropene units. The terpenes are subdivided into monoterpenes (2 units), sesquiterpenes
(3 units), diterpenes (4 units), sesterterpenes (5 units), and triterpenes (6 units). In
general, the terpenes are pre hydrocarbons, while terpenoids are terpenes bearing radical
functional groups (Fengel and Wegener 1984). The most common terpenes are alpha
pinene and beta pinene (Kollman and Cote 1984). The relative proportion and
distribution of each of these terpenes vary within the tree. For example, a high shift in
terpene quantity has been found in slash pine oleoresins as a result of induced wounds on
the tree (Koch 1972). However, oleoresin in softwoods is always rich in diterpenes and
diterpenoidic acids (Fengel and Wegener 1984).
Fat and waxes: Fats are deﬁned as esters of high carbonic acids and glycerol. Waxes are
esters of fatty acids with higher alcohols. Softwoods contain less than 1% fat and waxes
(Fengel and Wegener 1984).
Phenolic compounds: Most wood species contain a large number of phenolic
compounds, usually resulting from the biosynthesis of lignin (Fengel and Wegener 1984).
For example, some of the simplest compounds found in spruce extractives include
vanillin, p-hydroxyladehyde, and coniferyl aldehyde as well as coniferin and syringin
(Fengel and Wegener 1984).

Another group of phenolic compounds is composed of lignans, consisting of two

phenylpropane units. The most common lignans in softwoods are lariciresinol in larches,

ll

pineresinol in spruce and pine and conidendrin in spruce and hemlock (Kollman and Cote
1984).

There is a great variety of polyphenols occurring in both softwoods and
hardwoods. Among these, stilbenes are particularly common in the heartwood of pines.
Polyphenols are usually species speciﬁc and have been used to create a chemical
taxonomy for the genus Pinus (Kollman and Cote 1984). The most important polyphenol
is pinosylvin, known to be strongly toxic and responsible for the heartwood decay
resistance of some pine species (Kollman and Cote 1984). The tropolones found only in
the Cupressales include alpha, beta and gamma thujaplicin (Kollman and Cote 1984).
Among polyphenols, ﬂavonoids are also well represented in softwoods. This group is
comprised of ﬂavone, ﬂavanes, ﬂavanones and isoﬂavones. The ﬂavonoids identiﬁed in
softwood include chrysin, taxifolin, pinocembrin and pinobanksin (Fengel and Wegener
1984).

2.2.2 Hardwood extractives

The bark and sapwood of hardwoods is reported to be rich in simple monomers
and nutrients such as fats, starch, sucrose, simple sugars, inositols, simple glycosides, free
esteriﬁed sterols, phenylpropanoids, and other simple phenolics (Rowe and Conner
1979). The heartwood has fewer nutrients, glycosides and metabolic intermediates, but is
rich in hydrolysable and condensed tannins and many other alkaloids, resins, essential
oils, and specialized compounds (Rowe and Conner 1979).

The speciﬁc chemical composition in hardwoods varies with species and possibly,
even individuals within the species. The description of the chemical constituents of most

northern hardwood extractives has been conducted by Rowe and Conner (1979).

12

Hardwoods sapwood contains leucoanthocyanins and pinoresinol. In addition,
coumarin and lignans are usually present. Wood extractives from secondary metabolism
tend to be especially abundant in some particular groups of hardwoods. For example
Koch (1985) reported that alkaloids were particularly abundant in magnolias and yellow
poplar, sesquiterpenes in yellow poplar and elms, acetogenins in hickories, complex
coumarins in sugar maple, and lignans in magnolias, elms, and oaks.

2.2.3 Formation of wood extractives

Extractives are formed in wood tissues at different stages in the life of the tree.
The biochemical processes leading to the formation of wood extractives are not clearly
established. There are two conﬂicting theories on the formation of wood extractives; the
translocation theory and the in situ formation theory of extractive formation.

The translocation theory of wood extractive formation postulates that the
extractives in the heartwood are accumulated by translocation from other regions (Hillis
1987). It is suggested that the precursors to heartwood extractives are formed in the
foliage and other parts of the tree and diffuse radially to the heartwood periphery.
However, this theory is however not able to explain the variability in amount and
components observed in wood extractives.

The in situ theory states that wood extractives, particularly polyphenols, are
formed in situ and are not mobile beyond the cell in which they are formed (Chattaway
1952; Hillis 1987). Hemingway and Hillis (1970) showed that extractives from Douglas
ﬁr heartwood and those formed in the living stump after the stem had been removed had
similar composition, supporting the fact that it was unlikely that they originated from the

foliage as proposed by the translocation theory. Apparently, physiological conditions near

13

the sapwood-heartwood boundary have a great effect on the rate and duration of aromatic
biosynthesis during formation of heartwood extractives (Nelson 1975). Extractives in
injured tissues, knot wood, and heartwood at various height of the tree can have
differences in composition. Hillis (1987) reported that extractives obtained from
mistletoe contain extractives with different composition from those of the adjacent
eucalyptus on which they grow parasitically. These ﬁndings support the view that
extractives are formed in situ from translocated primary metabolites.

Starch and sugars stored in the xylem ray and parenchyma cells are reported to be
the raw materials for extractive production (Bosshard 1968; Hillis 1968; Hemingway and
Hillis 1970). Hillis (1987) proposed that the biosynthesis of polyphenols involves both
the shikimic acid and tricarboxylic acid pathways and takes place in the transition zone
between sapwood and heartwood.

The function of extractives in the living tree is not clearly deﬁned. However,
wood extractives are believed to provide blockage of tissue from translocation stream
(Hillis 1987). They also provide trees with resistance to destructive agents.

2.2.4 Dimensional Stability and Speciﬁc Gravity

How wood extractives affect the dimensional stability of wood depends on their
chemical composition and location in the wood structure.

In gymnosperms, the longitudinal elements consist mainly of radially arranged
tracheids, which can make up to 90 percent of their structure (Haygreen and Bowyer
1996). In addition to tracheids, some softwoods also have longitudinal resin canals in

which the tree exudates most of its oleoresin.

l4

The only possible locations for softwood extractives are either in the lumen of the
tracheids and/or as inclusions in the cell wall structure. In hardwoods, extractives can be
contained in the vessel elements, in the lumen of ﬁbers or included in the cell wall.

The chemical constitution of extractive components, their size and molecular
weight, and their afﬁnity with the ligno-cellulosic wood complex will dictate their
location within the wood structure. Low molecular weight monomers will be found in
voids in cell walls, while high molecular weight components will be mostly located in the
lumen of vessels, tracheids, or ﬁbers.

Aromatic compounds derived from glucose such as ﬂavonoids and condensed
tannins usually have free hydroxyl groups and are water-soluble. Consequently, they will
be more susceptible to adsorb water and induce greater dimensional change. This also
applies to terpenoids, which usually have a hydrophilic functional group attached to the
hydrocarbon radical. In the contrary, pure hydrocarbons such as terpenes are volatile and
will not affect dimensional stability.

Extractives are known to have a bulking effect in the wood structure (Hillis 1987).
When located in the lumen, they have an additive effect, increasing the weight and
speciﬁc gravity of wood. They also increase the apparent speciﬁc gravity of wood
(DeZeeuw 1965).

There are numerous publications in the open literature demonstrating this effect.
For example, Taras and Saucier (1967) referring to speciﬁc gravity, wrote that in practice
speciﬁc gravity is measured without removing the extractives, resulting in an
overestimate of the amount of wood substance. They noted that speciﬁc gravity is

overestimated by 6 to 7.5% in southern pines due to the extractive content.

15

Taylor (1974) obtained increased tangential and longitudinal dimensions and
reduced radial dimension in extracted hardwoods and softwoods, resulting in a lower
speciﬁc gravity for extracted woods. Lee (1986) also obtained a signiﬁcant correlation
between alcohol-benzene extractives and speciﬁc gravity of red pine. In addition, after
extraction, he also observed an increase in the tangential as well as in the longitudinal
dimension and a decrease in the radial dimension, sufﬁcient enough to induce a decrease
in speciﬁc gravity. This phenomenon is explained by the fact that the volume increase is
due to an expansion of wood substance caused by water molecules occupying sorption
sites where extractives have been removed (Taylor 1974).

Extractives within the cell wall structure would likely affect some mechanical
properties of wood (Ajuong and Breese 1997). Hillis (1987) revealed that the hydrated 82
layers of tracheids in red pine contained 25% free space having cross sections of 16 to
60A, large enough to contain molecules of extractives (A monomer of ﬂavonoid is 6.3A).
This results in molecules of wood extractives maintaining the wood structure in a semi-
swollen condition, and hindering the number of available sites for the formation of
intermolecular lignin-cellulose and/or lignin-lignin bonds (Ajuong and Breese 1997).
2.2.5 Shrinkage and Wettability

There is evidence in the literature linking extractive content to checking and
collapse when drying at high temperatures. Erikson (1968) obtained a highly signiﬁcant
positive correlation between hot-water soluble extractives and shrinkage in redwood
implying a greater susceptibility to drying checks. Meyer and Barton (1971) looked at the
extractives content of boards after drying and found collapsed boards to average 18.8%

acetone soluble extractives while un-collapsed boards averaged 12.6%. Demaree and

16

Erickson (1976) investigated the relationship between extractive content and volumetric
shrinkage for wood samples dried at various dry bulb temperatures. They found that at
temperatures of lower than 190°F, the quantity of extractives was directly related to
shrinkage. They hypothesized that at low drying temperatures, the extractives were acting
as bulking agents, but at higher temperatures they become heat sensitive and made wood
cell susceptible to collapse during apparent free water loss.

Wood extractives are also reported to affect the wettability of wood surfaces.
Polar and hydrophilic extractives might increase wetting and non-polar extractives might
decrease wetting. Chen (1970) obtained improved wettability and increased pH in all
tropical woods used in his study. Jordan and Wellons (1977) also attributed the poor
wettability found in keruing (Dipterocarp spp.) to extractives present in the veneer
samples tested. Maldas and Kamdem (1999) observed the opposite effect. In their
experiment, wood extracted with an ethanol-toluene solvent exhibited a higher contact
angle (lower wettability) compared to un-extracted samples. They suggested that the
higher contact angle was due to the hydrophobic nature of the extracted wood surface
promoted by the migration of hydrophobic extractives to the wood surface. They
suggested that the more hydrophobic extractives such as waxes and long chain
hydrocarbons are present in wood, the less water this species will absorb.

Furthermore, wood extractives are reported to reduce wood permeability
(Bosshard 1968; Bailey and Preston 1969).
2.2.6 Mechanical Properties

There is some controversy regarding the inﬂuence of wood extractives on

mechanical properties. Brown et al. (1952), observed an appreciable effect from wood

17

extractives on compression parallel to grain, but there was no signiﬁcant effect on shock
resistance. Kellogg and Itju (1962) argued that the effect of the removal of extractives
could be positive or negative depending upon the mechanical properties under
consideration and the location of extractives in the wood structure. Ajuong and Breese
(1997) investigated the creep behavior of extracted and un-extracted blocks of Pai wood
(Afzelia africana Smith) and concluded that the extractive fractions located in the lumen
have no signiﬁcant effect on short term creep, while the removal of cell wall-resident
components permitted signiﬁcant and accelerated creep development.
2.3 Factors Affecting the Weathering of Wood Surfaces
2.3.1 Factors Inherent to Wood
2.3.1.1 Density Variation

Density is one of the most studied properties of wood and is the primary factor
inﬂuencing the properties of wood surfaces. Density is deﬁned as the ratio of mass per
unit volume at a given moisture content (Kollman and Cote 1984). The density of the
solid wood substance is about 1.5g/cm3 and is similar for most timber species. The
relative proportion of the main constituents of wood affects wood density. Kollman and
Cote (1984) estimated that the speciﬁc gravity of cellulose from spruce wood was about
1.58, while that of lignin was about 1.38 to 1.41. This explains why the proportion of
cellulose to lignin will certainly inﬂuence density. Variations in densities are also due to
the proportional amounts of different tissue types such as ﬁbers, tracheids, vessels, resin
ducts, wood rays, and their dimensions, especially the thickness of the cell wall.

The density across a wood section is affected by the width of the annual ring and

the percentage of summerwood. However, there are variations between species. For

18

example, in spruce, the wood of lowest speciﬁc gravity is always produced near the pith
of the tree where wide rings are usually formed. In pine and larch trees, the density
increases outward from the center of the stem and reaches a maximum correlated with an
optimum width of the growth rings; later, with the formation of narrow rings, the density
decreases. Wood density and structural properties play an important role in the
weathering behavior of wood surfaces (Sell and Feist 1986). For example, Yalinkilic et
al. (1999) revealed that wood density and extractive content were the key wood
properties interacting with varnish and wood preservatives in outdoor exposure of
chestnut (Castanea sativa Mill.) and Scotch pine (Pinus sylvestris L.). Anderson et al.
(1961) exposed four hardwood species (yellow poplar, quaking aspen, white oak and hard
maple) to artiﬁcial weathering conditions, and observed a degradation pattern from
poplar and aspen similar to that of softwoods. They explained this result by differences in
the density of species used in their experiment. Feist (1994) also reported results showing
that aspen had ﬁnishing and weathering characteristics similar to those of softwoods like
ponderosa pine, ﬁr, hemlock, and spruce.

Williams et al. (2001-a), reporting results of a 14 year outdoors weathering tests
on lodgepole pine, Engelmann spruce, ponderosa pine and western hemlock, revealed
that large differences exist between earlywood and latewood erosion rates during
weathering. Erosion rates varied from 33trm/year for lodgepole pine latewood to 58
mm/year for western hemlock and red alder earlywood. This was in contrast with another
project on tropical species with no clear delimitation between earlywood and latewood

with uniform density distribution across the diameter of the trunk, which showed that

19

erosion rates were less variable and more uniform across the surface (Williams et al.
2001-c).

The orientation of the annual rings is an important factor for outdoor exposure.
Cracks usually develop along rays. A board with a high proportion of horizontal annual
rings (ﬂat sawn) has rays oriented face to face and cracks can easily develop. A board
with a high proportion of vertical annual rings oriented from the edge to the center of the
board (quarter sawn) may show less cracks, because rays will reinforce parts of the board
and prevent face to face cracks to force through. Williams et al. (2001-b) reported that for
Douglas ﬁr, loblolly pine, southern pine, western red cedar, red oak, and yellow poplar,
the erosion rate increased as the angle of exposure decreased from 90 to 0 degrees.
However, they noticed a notable exception to this for western red cedar, which had the
fastest erosion rate at a 45 degrees exposure. For some species, particularly western red
cedar and southern pine (earlywood), erosion rates differed for tangential and radial
surfaces. Little difference was observed between erosion rates of tangential and radial
surfaces for the other species.

The mechanism through which density affects wood shrinkage and ultimately the
development of cracks and checks on the wood surface is still the subject of
investigation. Some of the hypotheses proposed summarized by Quirk (1984) include:
alternation of latewood and earlywood layers within the annual ring, effects of ray tissue,
differing ﬁbril angle in radial and tangential walls, presence of extractives, differences in
number of transverse walls per unit of planar direction, and the degree of ligniﬁcations in

the radial or tangential cell wall.

20

2.3.1.2. Juvenile wood, pith, and growth ring orientation

The pattern of weathering degradation from pith to bark is also variable due to the
occurrence of juvenile wood. Juvenile wood can be deﬁned as the portion of the xylem
surrounding the pith in a cylindrical column whose cells were formed by a young
cambium (Smith and Briggs 1986). Another deﬁnition provided by Rendle (1960)
considers juvenile wood as secondary xylem produced by cambial regions that are
inﬂuenced by activity in the apical meristem. Juvenile wood is also referred to as core,
inner or pith wood as opposed to outer or mature wood (Panshin and DeZeeuw 1980;
Zobel and Sprague 1998). The occurrence of juvenile wood is explained by the prolonged
inﬂuence of the apical meristem in the region of active crown growth during the growing
season (Panshin and DeZeeuw 1980). As the tree crown growths upward, the cambium at
a lower height becomes less subject to the direct inﬂuences of the elongating crown
region and adult wood is formed (Panshin and DeZeeuw 1980).

Compared to mature wood, juvenile wood of conifers is known to possess lower
quality compared to mature wood. It usually has lower speciﬁc gravity, shorter tracheids
length, larger ﬁbril angle, lower transverse shrinkage, lower percentage latewood, more
compression wood and higher equilibrium moisture content (Bendtsen 1978; Haygreen
and Bowyer 1996). Large ﬁbril angles and high amounts of reaction wood in juvenile
wood cause excessive longitudinal shrinkage and instability in service (Bendtsen and
Senft 1986). Short ﬁbers, high ﬁbril angles, thin cell walls, and low percentages of
latewood in the annual ring contribute to lower bending strength and cause unusual

warping problems (Zobel and Sprague 1998).

21

Chemical characteristics also differ between juvenile and mature wood. For
example, Zobel and Sprague (1998) reported a higher proportion of cellulose to lignin in
radiata pine (Pinus radiata) mature wood and higher hollocellulose and alpha cellulose
proportions in juvenile wood in short leaf pine (Pinus echinata).

A juvenile core is also present in most hardwood species (Maeglin 1987), where it
is characterized by excessive amounts of tension wood. This has been observed on
Populus species (Isebrands and Bensend 1972) and ash (White and Robards 1965) when
rapidly grown. Like compression wood, tension wood shrinks more than normal wood,
frequently causes dimensional instability in lumber during seasoning and is more prone to
collapse (Bendtsen 1978). The juvenile core in hardwoods is also known to possess poor
physical properties, low speciﬁc gravity, low strength, and high shrinkage (Fukazawa
1984; Smith and Briggs 1986).

Based on the above difference in properties, it is reasonable to expect that wood
located near the pith would show high instability resulting in crack development, and low
weathering degradation due to its low lignin content. Sandberg (1996, 1997) found that
the distance between sawn timber in the log and the pith with the surrounding juvenile
wood was of vital signiﬁcance for cracking. Timber from nears the pith or distinctly
containing the pith has a higher relative crack length compared to timber sawn away from
and lacking the pith. In addition, he hypothesized that the proportion of cracks can be
related to pith cracks, which were present before the log was sawn, or the reduction in the
angle of annual rings near the pith. Stehr and Ostlund (2000) investigating the tendency
of wood surfaces to develop cracks after machining operations concluded that there were

greater risks for cracks on the pith side than on the bark side. However, Flaete (2000)

22

observed the opposite effect and hypothesized that despite the fact that juvenile wood
induces more crack formation; its straight grain direction may prevent cracks from
propagating. The inﬂuence of juvenile wood and variation from pith to bark therefore
needs to be further investigated.
2.3.1.3 Knots

A knot is a branch base that is embedded in the wood of a tree trunk or of larger
limb or branch (Panshin and DeZeeuw 1980). The presence of knots in wood is
detrimental and causes a loss in value and properties. The inﬂuence of knots depends
upon their size, location, shape, and soundness. The orientation of the grain is usually
distorted around the knot. The presence of knots in lumber affects its mechanical and
physical properties. The knot itself is harder, more dense, often more resinous, and
shrinks in a different manner that the surrounding wood tissue (Panshin and DeZeeuw
1980). These characteristics lead to uneven wear, higher susceptibility to checking, and

difﬁculty in painting.

2.3.2 External Factors of Weathering

Environmental and biological factors such as light, temperature, moisture
changes, wind, and microorganisms affect the weathering of wood surfaces. Among
these, light, moisture, oxygen are the most important.
2.3.2.1 Light

Sunlight induces photochemical reactions leading to the discoloration of wood
surfaces (Hon and Itju 1978). Wavelengths of sunlight reaching to earth range from the

ultraviolet region (200nm) to infrared (2300nm) (Bird et al. 1982).

23

Color is deﬁned as a sensation evoked as a response to the stimulation of the eye
by the radiation of certain wavelengths and intensities (Wengert 1966). The human eye
generally responds to wavelengths from 400 to 700 nm, the visible range. Shorter
wavelengths, from 200 to 400 nm are the UV range, and longer wavelengths from 700 to
50,000nm are the infrared range (Wengert 1966). The most common form of radiation
used by the eye to determine color is that emitted from the sun or from artiﬁcial sources.
When radiation strikes an object, it is absorbed, reﬂected or transmitted. The reﬂected
wavelength received by the eye indicates the color of the object. For example, a white
color would reﬂect nearly 100% at all wavelengths, while reﬂection from a black color is
nearly zero.

The UV component of light (200nm-400nm) representing about 6% of the total
solar irradiation has been reported to be the fraction inducing photochemical reactions in
wood (Browne and Simonsen 1957; Sanderrnann and Schlumbom 1962; Hon and Ifju
1978; Feist and Hon 1984; Grelier et al. 2000). The initial color change of wood exposed
to sunlight is a yellowing or browning, later followed by graying of the wood surface.
These changes are superﬁcial, occurring only to a depth of 0.05 to 0.5 mm, and are
caused by ultraviolet (UV) light, which initiates the photodegradation by changing the
chemical composition of the wood surface especially lignin. However, Browne and
Simonson (1957) found that infrared light penetrated deeper in wood than visible light,
while penetration by UV light was negligible, no more than a few millimeters. They also
reached the conclusion that light turns wood brown in color, and browning occurred more
rapidly in UV light than in visible or infrared light. Stout (1958) showed that absorption

of UV light in wood is primarily due to lignin and lignin like substances. In his study,

24

pine cellulose exhibited a high reﬂectance, whereas the reﬂectance curve for lignin
substances approximated that for wood.

Wengert (1966) reported that atmospheric gases were an important factor in the
color change of wood exposed outdoors. In his project, air, oxygen, nitrogen, and argon
each had a different effect on wood subjected to intense UV light. Redwood and birch
samples showed rapid darkening during the ﬁrst hours of exposure to air, oxygen,
nitrogen, and argon. After initial darkening, samples exposed in oxygen and air stopped
darkening and became lighter, while samples exposed to nitrogen continued to darken
throughout the exposure period.
2.3.2.2 Moisture changes

Wood normally shrinks as it dries and swells as it absorbs moisture. The forces
exerted in shrinking and swelling are great and have a marked effect on the permanence
and serviceability of anything made of wood. As water leaves the spaces between wood
strands during drying, they are drawn together, causing the ﬁber walls to be reduced in
thickness and the ﬁbers themselves to be reduced in girth. This contraction of the ﬁbers
causes the whole piece of wood to shrink. When green or wet wood dries, the water
leaves the ﬁber lumens ﬁrst; only when they are empty does continued drying remove the
water from the ﬁber walls.

The weathering of unprotected woodwork exposed to the weather is due to same
basic principles. When the surface layers of a dry board become damp, they try to swell
but are restrained by the dry interior. As a result, the surface layers of ﬁbers become
somewhat crushed. As the surface dries out again, the crushed wood shrinks more than

originally, causing ﬁne cracks to open up. If this is repeated over and over again, as is the

25

case in unpainted wood, numerous little cracks develop that not only mar its appearance
but also permit the deeper penetration of moisture. Although moisture will pass through
protective paint, it does so slowly and, as a result, such large differences in moisture
content between surface and interior layers do not develop, and serious compression set
does not occur (Anon 1957). Visible cracks arise on the wood surface during outdoor
exposure because of the growth of microcracks formed during the drying of the wood,
photochemical reactions, or moisture induced stress ﬁeld (Coupe and Watson, 1967).
Wood shrinks most in the direction of the annual growth rings (tangentially),
somewhat less across these rings (radially), and very little, as a rule, along the grain
(longitudinally). Sandberg (1999) measured the number and average lengths of cracks
occurring on wood surfaces exposed outdoors for 33 months, and found that the radial
surfaces had signiﬁcantly smaller number of cracks than on tangential surfaces. On the
radial surfaces, the cracks were primarily found in the annual ring border and the early
wood, while on the tangential surface, they appeared in the latewood and across the
whole exposed surface. The difference in crack susceptibility between radial and
tangential surfaces is mainly the result of stresses, which arise in the wood as a
consequence of anisotropic moisture movement of wood material and the moisture
gradient between the surface of the test pieces and their internal regions (Sandberg,
1999). The shrinkage and swelling in the tangential direction are about twice as large as
the radial movement. Stamm (1964) proposed that wood for outdoor use should have
vertical annual rings (quarter sawn). This minimizes the risks of cracks as a consequence
of anisotropic moisture movement (Browne 1960; Stamm 1964). Sandberg (1996 and

1997) researching the inﬂuence of annual ring orientation on crack formation in pine and

26

spruce found that timber exposed to cycles of wetting and drying developed increasing
crack length irrespective of their prior cross sectional location on the stem.

Flaete et al. (2000) investigated cracks formation in solid wood sidings of aspen
and Norway spruce exposed to accelerated weathering. They observed a high number of
short cracks in aspen and a fewer but more injurious number of cracks in spruce. They
explained this result as a consequence of the more asymmetrical cross sectional pattern in
aspen, eventually preventing cracks from propagating.

Severity of shrinkage varies between species, but is particularly high in refractory
woods such as oak, which contains up to 32% of its wood volume as ray tissue (Gaby,
1963). It is well known that tangential shrinkage is greater than radial shrinkage.
Consequently, shrinkage is more severe in ﬂat sawn boards. Since the long axis of the
wood rays is at a right angle to annual rings, they are subjected to a sawing action that
differs from longitudinal elements. The combination of ray orientation and the sawing
action may be compounding factors leading to localized drying stresses that result in
increased surface checking of oak boards.

Shrinkage not only differs with the three directions of grain, but also differs
amongst species. It varies widely in material cut from the same species and even in
material cut from the same tree. In general, heavier species of wood shrink more across
the grain (transversely) than lighter ones. The overall, or volumetric, shrinkage of wood
also generally increases with an increase in speciﬁc gravity. This relationship holds not
only within a species, but also fairly well for a large number of species of both softwoods
and hardwoods. Deviations from this relationship are usually caused by stresses, such as

those set up in drying, and by water-soluble extractives (Anon 1999), which reduce

27

shrinkage because of their bulking effect when held between the strands within the ﬁber
walls.

When a piece of wood of high moisture content dries, stresses are set up in
various parts of the structure resulting in the phenomena which are normally referred to
as checking, shaking, warping and twisting (Coupe and Watson 1967). Although
seasoning and weathering are different processes (the former resulting from a single
drying cycle and the latter from many), they appear to manifest themselves in a similar
way. Both involve dimensional changes due to moisture changes in wood cells.

Many researchers have studied seasoning checks. Schniewind (1959) stated that
seasoning checks normally occur as a result of setting up of moisture gradients leading to
high tensile stresses on the faces of drying boards. This results in the formation of checks,
which often occur in the rays and extend radically into the boards. The assumption has
been made that this problem resulted from the low tensile strength of the ray tissue in the
tangential direction. However, work on black oak by Schniewind (1959) showed that the
rays in this species exhibited considerably higher tensile strength than found in
longitudinally oriented cells.

The microscopic structure of wood has a major inﬂuence on the development of
cracks and checks. Booker (1998) suggested that most of the resistance to crack
development and propagation occur in S2 layers, which are the thickest of the cell wall
layers. In a single cell wall, a crack would propagate by cutting through the matrix
material in the same direction as the microﬁbrils since the energy required to cut
microﬁbrils is much larger than that to cut the matrix material. Consequently, the cracks

propagate at an angle to the axis similar to the rrricroﬁbrils angle. This suggests that the

28

position and properties of the specimen from the pith will inﬂuence the extent and pattern
or crack formation.
2.3.2.3 Angle of Exposure

The angle of exposure of samples in the ﬁeld can affect the performance of wood
exposed to weathering. This was conﬁrmed by Evans and Banks (1986), who
investigated the inﬂuence of the season and angle of exposure on the weathering of wood
samples in Australia. Williams et al. (2001-b) reported that for Douglas ﬁr, loblolly pine,
southern pine, western red cedar, red oak and yellow poplar, the erosion rate increases as
the angle of exposure decreased from 90 degrees to 0 degrees from the horizontal.
However, they noticed a notable exception to this for western red cedar, which had the
fastest erosion at 45 degrees.
2.3.2.4 Temperature

The role of temperature in the natural weathering process is generally felt to be of
less importance than that of light or water (Rowell 1984). However, Derbyshire et al.
(1997) investigated the inﬂuence of temperature on photodegradation rates in wood
exposed to up to 400 hours of artiﬁcial weathering. Their results conﬁrmed that
photodegradation rates for the different species were temperature dependent and

increased with rising temperature.

29

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Lee, C. H. 1986. A Note on the Effect of Alcohol-Benzene Extractives on Juvenile Wood
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33

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34

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35

Chapter 3

Fourier Transformed Infrared and X-ray Photoelectron Spectroscopy
Analysis of Red Oak (Quercus rubra), Black Cherry (Prunus serotina)
and Red Pine (Pinus resinosa) Extractives and Wood Surfaces

ABSTRACT

The Fourier Transformed Infrared (FTIR) analysis of extractives removed from
black cherry (Prunus serotina), red oak (Quercus rubra), and red pine (Pinus resinosa)
wood samples using ethanol, ethanol-toluene, and water was conducted to obtain basic
understanding of the nature of the components removed using those solvents.

Results indicated that substances removed from black cherry and red oak with
ethanol and ethanol-toluene are made up of fatty acids and their esters as well as aromatic
compounds probably from ﬂavonoids. Water extraction predominantly removed low
molecular weight carbohydrates, sugars, and condensed tannins. The FTIR spectra of
surfaces revealed no major difference between extracted and non-extracted wood
surfaces. However, there were signs of increased exposure of cellulose and
hemicelluloses on extracted wood surfaces. X-ray Photoelectron Spectroscopy (XPS)
indicated a rise in the oxygen to carbon (O/C) values following extraction treatments due
to the partial removal of extractives including fatty acids, esters, sterols, terpenes, and
phenolic compounds such as lignans. The Cls peaks indicated a decrease in the area of
the C1 peak following extraction. The C2 peak increased as a result of increased
exposure of cellulose components on the wood surface. The 015 peaks showed an

increase in the 01 peak originating from cellulose.

36

3.1 Introduction

Wood extractives include several classes of organic compounds ranging from
relatively simple molecules such as phenols and sugars to highly complex ﬂavonoids,
tannins, and resins (Hillis 1987). Extractives are soluble in different organic solvents, and
polar and non-polar organic solvents are used to remove extractives without any great
alteration in either their structure or that of the wood.

Extractives have different solubility characteristics, which enable their selective
removal through the use of various organic solvents (Laks 1991). Toluene is a non-polar
solvent, traditionally used to remove the extractable non-polar compounds located within
the cell lumen (Ajuong and Breese 1998). Previous reports indicate that such substances
are long chain fatty acids, fats, resins, waxes, terpenes, and phytosterols with relatively
high molecular weights (Hillis 1987; Anon 1999). It is reported that ethanol solvent can
penetrate the cell wall and swell the wood structure (Laks 1991; Ajuong and Breese
1998). Thus, ethanol would be expected to remove materials from within the wall
structure, including condensed tannins, ﬂavonoids and phenolics (Laks 1991). Hot water
extraction recovers condensed tannins and water soluble, low molecular weight
carbohydrates (Ajuong and Breese 1998).

Conventional methods based on the oven dry extractive-free weight have been
developed for determination of the total extractive content of wood. They include ASTM
standards D1105-96, D1107-96, D1108-96, and D1110-84 (ASTM 1999), T APPI
standards T204 OM-88, T207 OM-88, and T264 OM-88 (TAPPI 1993). These methods
are based on the reﬂux of hot organic solvents into wood and provide satisfactory

information for the determination of the total extractive content of a given species. Fine

37

analytical methods are needed to identify the chemical components of the extractives and
characterize their structure. These include solid, liquid, and gas chromatography, mass
spectrometry, X-rays photoelectron Spectroscopy (XPS), Infrared Spectroscopy (IR), and
Hydrogen and Carbon Nuclear Magnetic Resonance (1H and 13C NMR).

Infrared spectrometry has been widely used to investigate various aspects of wood
and its chemical structure. It has been successfully used to monitor chemical changes
occurring on the surface of weathered wood (Owen et al. 1993; Dawson and Torr 1992;
Cui et al. 2003). Diffuse Reﬂectance Infrared Fourier Transformed (DRIFT)
spectroscopy was used to determine the klaxon lignin and the polyﬂavonoid content of
Pinus pinaster bark (Vasquez 2000). Fourier Transformed Infrared Reﬂectance (FT IR)
was also used to indirectly measure the lignin content in Sitka spruce (Picea sitchensis
(Bong) Carr.) wood (Costa e Silva et al. 1999).

FTIR has been employed to study pulp (Berben et al. 1987), chemically modiﬁed
wood (Schultz 1985), and treated wood (Liu 1994; Zhang and Kamdem 2000). DRIFT
was also used to characterize and identify the major functional groups of extractives
recovered from Pai wood (Afzelia Africana Smith) using various organic solvents
(Ajuong and Breese 1998). The FTIR technique was combined with Phosphorous-31
NMR, Carbon-13 NMR, and GC/MS to characterize the polyphenolic compounds related
to the color of western red cedar (Thuja plicata Donn) heartwood (Johansson 2000).

Another spectroscopic solid-state non-destructive technique used to monitor
chemical changes on the surface of wood samples is X-ray Photoelectron Spectroscopy
(XPS). XPS is based on a direct analysis of the kinetic energy of electrons which are

excited by high energy X-rays and ejected (Kamdem et al. 1991). XPS has been used in

38

several applications in wood science for surface characterization. XPS has been used to
study the chemical interaction between waterborne copper naphthenate and wood
surfaces (Cracium and Kamdem 1997). XPS was used to analyze changes occurring
during the ﬁxation of CCA on the surface of treated wood, and to estimate the amount of
cuprous oxide formed after post steam treatment (Ruddick et al. 1993; Maldas and
Kamdem 1998; Kamdem et al. 1998). Other applications of XPS include surface analysis
of different wood species (Sinn et al. 2001), surface characterization of chemically
modiﬁed pulp and wood (Chtourou et al. 1995; Torr et al. 1996), evaluation of surface
lignin on cellulose ﬁbers (Kamdem et al. 1991; Johansson et al. 1999), and weathering of
wood and wood-plastic composites (Owen et al. 1993; Matuana and Kamdem 2002).

The goals of this study were to use solid-state non-destructive tools such as FTIR
and XPS to characterize the surface of wood before and after extraction using several
organic solvents, and the extractives removed in order to understand the role of
extractives in the durability of wood.

3.2 Materials and Methods
3.2.1 Materials

Three wood species were selected for this study: black cherry (Prunus serotina),
red oak (Quercus rubra) and red pine (Pinus resinosa). All three species are largely
available resources in the Northeastern United States. Oak and red pines are largely used
in outdoor applications where wood is susceptible to variations in moisture content.
Black cherry is mainly used in indoor applications. However, due to its speciﬁc color
(due to its extractive content), it was a potentially interesting hardwood species for

comparison with red oak.

39

Black cherry and red oak logs measuring 1.2m (4 feet) with top diameters larger
than 35cm were randomly selected from the lumberyard at the Devereaux sawmill in
Pewamo, Michigan. Red pine logs measuring 35cm in diameter and 2.4m (8 feet) in
length were obtained from the Kellogg Forest in Augusta, Michigan.

The logs were sawn in a traditional ﬂat sawn scheme to obtain exterior boards
with the main face in tangential direction and boards closer to the pith in radial direction.
The thickness of each cut was set at 2.5cm (linch), and 14 to 16 boards were obtained
from each log, with approximately seven to eight boards for each half of the cross
section. Care was taken to keep track of the position of each board from pith to bark.
From each half section, the ﬁrst two to three boards were ﬂat sawn and the last four to
ﬁve boards were quarter-sawn.

All boards were dried in a laboratory kiln following drying schedules
recommended by the Forest Products Laboratory (Anon 1999). Drying schedule T8-B4
was used for black cherry, T4-C2 for red oak and T12-B4 for red pine. The ﬁnal moisture
content was between 6 and 8%. The boards were then stored until further use.

The density of samples at 12% moisture content from each log, determined
according to ASTM standard D2395-93 were 393kg/m3 for red pine, 624kg/m3 for red
oak, and 540kg/m3 for black cherry.

Boards numbers 4 and 5 (heartwood), measuring 2.5cm x 400m x 1200m from
areas of the log at least 30m away from the pith, and 50mm from the bark, therefore not
including any sapwood material, were selected to prepare the samples.

The samples measured 4mm x 44mm x 80mm (T x W x L). Care was taken to

keep the radial face as the main surface to be exposed.

40

The samples were then planed and successively sanded with 60, 100, 150, and
220mm grit sanding paper. Sanded specimens were conditioned to equilibrium moisture
content of 10: 2 % before extraction.

3.2.2 Extraction

The samples were extracted with various combinations of solvents including
ethanol, toluene, and water according to modiﬁed ASTM and TAPPI standards.

Water extraction was conducted according to ASTM 1110-96 (ASTM 1999) and
TAPPI T207 OM-88 (TAPPI 1993). Solvent extractions were conducted according to
TAPPI T204 om-88 (TAPPI 1993) and ASTM D1107-96 (ASTM 1999). The main
modiﬁcation was related to the fact that solid wood samples were used in the extraction
process instead of grinded wood (powder) as recommended in the standards. The
extraction time was consequently increased to remove more extractives from the
specimens. Preliminary tests to determine the appropriate extraction time suggested that
an extraction cycle of 72hours was sufﬁcient.

Conditioned samples were divided into ﬁve groups. The ﬁrst group was extracted
with a mixture of ethanol: toluene (1:2 by volume) (Eth-T01), the second group was
extracted with ethanol: toluene for 72 hours and then extracted with water for 72 hours
(Eth-T01 + Water), the third group was extracted with ethanol (Eth), the fourth group was
extracted with ethanol for 72 hours and water for 72 hours (Eth + Water), and the ﬁfth
group was kept un-extracted as a reference (control). Twenty-four samples were extracted
for each treatment from each species.

The total amount of extractives removed (Table 3.1) was calculated by the weight

difference of the moisture free samples before and after extraction as recommended by

41

the standard (ASTM 1999; TAPPI 1993). Extracted specimens were stored under dark in
the conditioning room until further tests.
3.2.3 Sample Preparation for FTIR and XPS

Extractives collected from the extraction process as well as extracted wood
samples were characterized with FT IR and XPS to monitor the modiﬁcations that
occurred.

Extractives solution was concentrated by using roto-evaporation under 25 inches
vacuum at 40°C. Two milligrams of extractives were thoroughly mixed with 200mg of
dry potassium bromide (KBr). About 10mg of the mix was subjected to FTIR analysis.
For solid wood samples, specimens measuring 4mm x 12mm x 12mm were used for the

FTIR and XPS.

42

Table 3.1: Extractives Removedl as a percentage of wood dry weight

 

 

 

 

 

 

 

 

 

 

Eth-Tol Eth-Tol +Water Eth Eth + Water Water
[Red Plne 2.67 (0.52)2 3.54 (0.39L 3.32 (0.67) 4.6 (0.64) 1.80(0.25)
[Black Cherry 2.02 (0.54) 3.1 (1.17) 3.21 (0.97) 4.79 (0.53) 3.46(O.44)
Red Oak 2.03 (0.59) 2.76 (0.12) 1.59 (0.08) 4.07 (0.41) 3.44(0.10)

 

1 Mean of four replicas

2 Numbers in parenthesis are standard deviation

43

 

3.2.4 FTIR

FTIR was performed on a Nicolet Protege 460 spectrometer equipped with
Spectra-Tech diffuse reﬂectance accessory. The Diffuse Reﬂectance Infrared Fourier
Transform (DRIFT) technique was used for solid samples. A total of 64 scans were
collected from 400 to 4000cm'l wavenumbers at a resolution of 4cm'1.
3.2.5 X-ray Photoelectron Spectroscopy Analysis

XPS analysis was performed on a PHI 5400 ESCA System from Physical
Electronics with a base pressure of less than 10'8 Torr, equipped with a non-
monochromatized Mg anode X-ray source. Kinetic energy measurements were made
using a hemispherical electrostatic analyzer with a ISO-mm radius working at a constant-
pass energy mode.

Samples were mounted on a stainless steel sample holder with stainless steel rings
and screws. Care was taken to obtain a ﬂat surface and to avoid contamination of the
sample. Data was collected using a MgK (1253.6 eV) anode source at 300 watts. For each

sample, the spectral data for C1, and 01, were collected.

3.3 Results And Discussion
3.3.1 FTIR of Wood Extractives

FT IR spectra of components extracted by ethanol, ethanol-toluene, and water are
presented in Figure 3.1 (black cherry), Figure 3.2 (red oak), and Figure 3.3 (red pine).
3.3.1.1 Black Cherry Extractives
FT IR spectra of black cherry (BC) extractives (Figure 3.1) indicate the removal of several

functional groups with both ethanol and ethanol-toluene extractions.

 

Table 3.2: Peak assignment for FT IR spectra

 

 

 

 

 

 

 

 

 

 

 

 

Range (Wavenumbers in cm") Peak Assignment
1738-1709 C=O stretch in unconjugated ketone, carbonyl and ester groups
1675-1655 C=O stretch on conjugated p-substituted aryl ketones
1605-1593 Aromatic skeletal vibration plus C=O stretch
1515-1505 Aromatic Skeletal vibration
1470-1460 C-H deformation in CH; and CH2
1430-1422 Aromatic skeletal vibration combined with C-H in-plane
deformation
1370-1365 Aliphatic in CH stretch in CH;
1330-1325 S-ring plus G-ring condensed
1270-1266 C=O stretching
1230-1221 C-C plus C-O plus C=O stretch
1166 C=O in ester group

 

 

45

 

1166
1637 1511 1466

:‘/

n42 ' .

 

oosmcrnomc-gs

.’
."-'
O

Eth-Tol

i'lueIO.

th

Water
cm-1

 

 

‘I" ‘0 9 O ' I I 0 I O O ' O O ‘ '9' ' I 0 I ‘ O C O I I I
2000 1 800 1 600 1400 1 200 1 000 800 600

 

 

Figure 3.1: FTIR spectra of black cherry extractives removed with Ethanol-Toluene
(Eth-T01), Ethanol (Eth) and Water

46

Peak assignments reveal similar strong absorption bands at 1705cm", 1608cm'l
and 1511cm'l, originating from carbonyl vibrations (C=O), carboxylic stretching and
weak skeletal carbon-to-carbon single bonded vibration respectively. It has been
suggested that carbonyl stretching at 1705cm'l arises from dimerized saturated aliphatic
acids (Ajuong and Breese 1998). Ethanol-Toluene and Ethanol extraction systems also
revealed strong peaks at 1466cm’l, which were attributed to methylene vibration. Next to
the methylene peak appeared a broad band at 1364 cm"1 attributed to methyl symmetrical
bending. This band was coupled with a band at 1260 cm”, which was attributed to a
carbon bonded to single oxygen. Ethanol-toluene spectra revealed a strong band at
1166cm’l that arose from saturated esters. This band was not present in the spectra of
components removed with ethanol. Ethanol and ethanol-toluene substances both had
broad bands at 1079 cm" and 1042cm‘l arising from aryl alkyl ether, which normally
absorbs between 1070-1020cm'l (Ajuong and Breese 1998). The peak at 833cm“l from
the ethanol-toluene component’s spectra was probably due to an out of ring carbon single
bonded hydrogen vibration. Previous reports indicate that ethanol-toluene removes
waxes, fats, some resins, and portions of wood gums. Hot water extracts are made up of
tannins, gums, sugars, starches and coloring matter (Anon 1999). Consequently, it can be
hypothesized that the carbonyl and carboxylic group peaks detected indicate the presence
of fatty acids and their esters. It can also be inferred that the strong carbon-to-carbon
absorption bands are an indication of aromatic - predominantly ethanol soluble
compounds.

The spectra of extractive components removed with water displayed a shifted

carboxylic absorption band at 1742cm'1. Absorption bands at 1615cm'1 were due to

47

carbonyl stretching and the 1505cm’l bands were due to skeletal carbon-to-carbon ring
vibration. Both bands were weak, probably due to the low content in substances with
aromatic structure. However, absorption bands at 1371cm'l (methyl asymmetrical
bending), 1269cm'l (carbon bonded to a single oxygen) and 1166cm’l (carboxylic double
bond) were all relatively strong and probably originated from low molecular weight
carbohydrates (Anon 1999).
3.3.1.2 Red oak Extractives

The red oak extractives spectra presented in Figure 3.2 also showed similar
absorption peaks for ethanol and ethanol-toluene. Both spectra showed strong absorption
peaks at 1703cm'1 attributed to carbonyl stretching; 1615cm'l attributed to carboxylic
vibrations; 1515cm’l caused by within ring skeletal carbon-to-carbon single bonded
stretching. Absorption bands at 1459cm'l (due to methylene vibrations), 1372cm'1 (due to
methyl asymmetrical bending) and 1238cm'l (from an unknown origin) were also
present. The absorption band at 1166 cm’1 - due to carboxylic stretching from saturated
esters was not present as was the case for black cherry. The water extraction components
showed similar patterns to that observed in cherry with a shifted absorption band for
carboxyl vibrations at 1744cm'1, a weak carboxylic shoulder and within ring carbon to
carbon vibration at 1615cm'l and 1515cm'l respectively. The conclusion derived for red
oak is similar to that obtained for cherry. It is believed that ethanol and ethanol-toluene
removes fatty acids and their esters, and components removed by water extractions are

probably made up of low molecular weight carbohydrates, sugars, and condensed tannins.

48

 

170

O “40’. ‘0

1744

(b O :3 a: an o m o‘)
I
T““‘ “4....

 

-Z Eth-Tol

.

J... 0.0....
: \
i

Eth

 

2000” ““1800

Water

1600 I

 

 

 

cm-1

ow- ﬁveir-ra-v—w—u- WE, on-u-o -

400 1 200

1 006

-gv——-o- o

800

'-“1‘

' 600

 

 

Figure 3.2: FTIR spectra of red oak extractives removed with Ethanol-Toluene (Eth-

Tol), Ethanol (Eth) and Water

49

 

3.3.1.3 Red pine Extractives

The FTIR spectra of red pine extractives are presented in Figure 3.3. The most
characteristic peaks for ethanol and ethanol-toluene extracts were 1738cm'l for C20 in
unconjugated ketones, carbonyls, and in esters groups; 1596cm'l for aromatic carbon to
carbon (C=C) skeletal vibrations, 1454cm’l for C-H vibrations in methylene; 1372cm’l
for methyl asymmetrical bending; 1155cm'l for C=C from saturated esters. For water
extraction a weak C=O peak occurred at 1738cm'1, followed by a weak skeletal C-C
vibration at 1567cm". There was also a broad absorption band at 1169 cm'1 due to C-O-C

asymmetric stretch vibration.

50

 

 

 

 

 

   

 

1738
‘ 1416 1069
A
b H 1567
o '-.
r 1596
b
a
n 0“}...
c
e “ -...
Eth cm-1
2600.'18'oo."16'oo".14'oo."12bo'.'1doo..aoo "60'3" ””1

 

 

 

Figure 3.3: FT IR spectra of red pine extractives removed with ethanol-toluene (Eth-T01),

Ethanol (Eth) and Water

51

3.3.2 FTIR Spectra of Extracted Wood Surfaces

The FTIR spectra of extracted and non-extracted wood surfaces are presented in
Figure 3.4 (black cherry), Figure 3.5 (red oak), and Figure 3.6 (red pine). The three
ﬁgures show similar spectral characteristics between extraction treatments for all species.
The characteristic peaks are bands at 1735cm'1 from C=O stretching in COOH, a broad
band at 1650 cm'1 from C=O vibrations in or-ketone groups, and 1505cm'l caused by
aromatic skeletal vibrations. There are also C-H deformations at l465cm'1, aromatic
skeletal vibrations at 1425cm‘l, symmetric C-H deformations at 1370cm'l, C-O-C
asymmetric stretching at 1230cm", as well as C-O deformation at 1150cm". The main
difference between the un-extracted and extracted wood spectra was the low peak
expression in the wavenumbers region below 1500cm'l in un-extracted samples
compared to extracted samples. It has been previously reported that the 1742cm'l
carbonyl peaks and the 1505cm'l peaks originate from lignin molecules, while major
peaks below 1500cm'l - especially C-H deformations at l465cm’l and 1370cm'1 and
asymmetric C-O-C deformations at 1265cm’l and 1230cm'l mainly originate from wood
carbohydrates (Owen et al. 1993; Schultz et al. 1985). Consequently, the stronger
expression of these peaks from extracted wood surfaces can be interpreted as a sign of

increased exposure of cellulose and hemicelluloses on the wood surface.

52

 

1505 1250
1464

: Eth-Tol __

. Water

00:”0‘“O"’O‘>

‘h

§ - ’
’\ Un-Extracted

cm-1

" ‘ Q

‘I‘ '7' ' ' 1 ‘ ° v 1 v o o g o --o «9 -7
2000 1800 1600 1400 1200

 

1000 800

 

    
   

 

Figure 3.4: FT IR Spectra of black cherry extracted wood surfaces

 

1744

1255
1505 1372

I {3 ~ 3'
.0: E .. 5 an”. .'. . ash”
1'; :1: \ '°
‘ 0' o E .0. ’ .. ‘ “

5 Un-extract- - .1 5 1 \
:0: ’2 E ‘ :°o .0
i ‘3" \ "

{.9

(Donovan-roman,

oOo-ool no

in 4..

olgo

cm-1

1 ' ° ' r - ' ~ 1 r ~ ~ 1 - v r ‘1 ' v ' r ' - r v
2000 1800 1600 1400 1200 1000 800

 

 

Figure 3.5: FTIR spectra of red oak extracted wood surfaces

53

 

 

 

1740

 

mosmdﬂomq>
y-s
a
U!
c

:“i '\ '
511$: ’ .'

 

 

Un-extractu .3 F. 5'
, ,1 Eth-T01 c“
.- - - Th! ’
‘roooo.o...ooocooo' Water cm-1
j'w'. ""‘"" O " 0 0 0 ‘ C P Q ' V ‘0“ " "'*-' 0 0 '. ' ' 0 0 ' 0 0 0 "—-'_."'— ‘0'—
2000 1800 1600 1400 1200 1000 800 600

 

 

 

Figure 3.6: FTIR spectra of red pine extracted wood

54

3.3.3 XPS Surface Characterization of Extracted Wood Surfaces

It has been previously reported that the degradation of cellulosic materials and
polymers can be detected by a change in the C1, spectra and by a change in the O/C
atomic ratio (Kamdem et al. 1991).

XPS spectra revealed the presence of O, C, N, and traces of Si (on untreated red
oak). The relative composition of O and C atoms and the calculated oxygen to carbon
(O/C) ratio for all species and extraction treatments are listed in Table 3.3.

The data presented shows that for red oak, the percentage of oxygen detected
increased from 25.35% to 33.95% following ethanol-toluene extraction. The percentage
rose to 34.05% when ethanol-toluene extraction was followed by water extraction,
resulting in an increased O/C ratio (0.34 to 0.51). A similar trend was observed with
specimens extracted with ethanol and ethanol followed by water, where the percentage
oxygen detected increased from 25.35 to 29.45% and 31.12% respectively, resulting in
the O/C ratio increasing from 0.34 to 0.42 and 0.46.

For black cherry, the total oxygen from the wood surface also increased, raising
the O/C ratio from 0.32 (un-extracted samples) to around 0.50 for extracted samples. This
effect was somehow less pronounced in red pine where the O/C rose from 0.29 to 0.35

for ethanol-toluene based extractions and 0.38-0.43 for ethanol based extractions.

55

Table 3.3: Percent of C 1s. 01, and O/C peak of red oak, black cherry and red pine

wood surfaces

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Treatment C1, 01, O/C
Control 73.74 25.35 0.34
Red Oak Eth —Tol 66.05 33.95 0.51
Eth —Tol + W 65.95 34.05 0.51
Eth 69.88 29.45 0.42
Eth + W 67.07 31.12 0.46
Control 75.19 24.81 0.32
Black cherry Eth —Tol 66.35 33.65 0.50
Eth —Tol + W 67.62 32.38 0.47
Eth 64.36 35.64 0.55
Eth + W 68.49 31.51 0.46
Control 77.36 22.64 0.29
Eth —Tol 74.73 25.27 0.35
R .
ed ”me Eth —Tol + w 74.05 25.95 0.35
Eth 69.70 30.30 0.43
Eth + W 72.29 27.71 0.38

 

 

 

 

 

56

 

The O/C ratios observed in control samples for all three species were lower or
very close to the theoretical value of O/C for lignin (0.33) and signiﬁcantly lower than
that of pure cellulose (0.83) (Kamdem et al. 1991; Barry and Zoran 1990). The high
carbon content in wood samples has been reported to be an indication of the presence of
lignin and extractives on the wood surface (Kamdem et al. 1991; Barry and Zoran 1990).
The increase in O/C following extraction treatments is due to the partial removal of
carbon rich extractives such as resin, fatty acids, esters, sterols, terpenes, and phenolic
materials.

C1, Peaks

There is general agreement in the literature on the assignment of deconvoluted
peaks C1, for lignocellulosic materials (Kamdem et al. 1991; Barry and Zoran 1990; Liu
et al. 1998; Kamdem et al. 2001; Briggs 1990). Cls deconvoluted in 4 components, C1,
C2, C3 and C4. The assignment of deconvoluted carbon peaks is presented in Table 3.4
The C1 peak corresponds to a carbon atom bound only to other carbon atoms and/or
hydrogen atoms. It is established that this component arises mainly from lignin and wood
extractives (Kamdem et a1 1991). The C2 component is due to a carbon bound to a single
non-carbonyl oxygen atom, which has been shown to mainly derive from cellulose
(Kamdem et al. 1991). The C3 represents a carbon atom bound to one carbonyl oxygen or
to two non-carbonyl oxygen atoms. The C4 represents a carbon atom linked to one
carbonyl oxygen and one non-carbonyl oxygen. The area of the C1 peak (from lignin and
extractives) logically decreased following extraction treatments for all three species.
However, differences in magnitude were observed between the two hardwood species

and the softwood species.

57

Table 3.4: Classiﬁcation of carbon and oxygen peak components, Cls and 018 for woody

 

 

 

 

 

 

 

 

 

 

materials.
Group Chemical shift Symbol Carbon Atom or
AE (eV) Oxygen Atom
Binding
Carbon
1 0.0 i 0.4 C1 C-C or/and C-H
II 1.5 i 0.4 C2 C-0
111 3.0 i 0.4 C3 C=O or/and
O-C-O
IV 4.5 i 0.4 C4 O-C=O
Oxygen
I 0.0 i 0.4 01 0-C=0
II 1.5i 0.4 02 C-0

 

 

 

 

Source: Kamdem et al. 1991

58

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 3.5: Summary of XPS Spectral Parameters in red oak
Peak Control Eth-T01 Eth-Tol+ Eth Eth + W
W
C; BE (eV) 284.67 284.41 284.68 284.45 284.51
Area (%) 53.98 34.32 30.07 43.87 42.21
C2 BE (eV) 286.28 286.26 286.39 286.27 286.25
Area (%) 37.00 53.60 58.13 45.72 49.08
C3 BE (eV) 287.95 287.95 287.95 287.95 287.95
Area (%) 7.01 10.16 9.87 8.18 8.40
C4 BE (eV) 289.16 289.16 289.16 289.16 289.16
Area (%) 2.01 1.93 1.93 2.23 0.31
01 BE (eV) 531.43 530.91 531.09 531.37 531.15
Area (%) 11.02 2.91 4.49 10.55 7.55
02 BE (eV) 532.75 532.72 532.88 532.91 532.71
Area (%) 88.98 97.09 95.51 89.45 92.45

 

 

 

 

 

 

 

59

 

In red oak, C1 decreased from 53.9% to 34.6% (36% decrease) following ethanol-
toluene extraction (Table 3.5) and a similar decrease was observed in black cherry (Table
3.6). For red pine however, the C1 changed from 62.8% to 58.6% (Table 3.7) representing
a decrease of only 4%. These differences are due to the nature of extractives contained in
each species. A previous study reported a two-dimensional paper chromatogram of the
sapwood and heartwood red oak extractives removed with a mixture of acetone and water
(95:5) (Rowe and Conner 1979). They reported that hydrolyzable gallotannins such as
hamamelitannin [5-galloyl-2-(galloylhydroxy- methyl)-ribofuranose] and ellagitannins
were the predominant compounds. The characteristic compounds found in the black
cherry family (Rosaceae) include cyanogenetic glycosides (Prunasin) and polyphenols
(Rowe and Conner 1979). The wood of Prunus species has been also reported to contain
up to 4.5 percent tannins (Rowe and Conner 1979). These are all simple phenols known
to be present in heartwood either as free acids or esteriﬁed with glucose, polyols, and
other phenols (Hillis 1987). Their removal would consequently cause signiﬁcant
variation to the C1 peak. Pines known to be richer in less branched terpenes and terpenes
derivatives had less variation in the C1 peak.

The C2 peak increased with extraction treatment as result of increased exposure of
cellulose components on the wood surface. The effect was higher with ethanol
extractions than with ethanol-toluene. Black cherry (72% increase) and red pine (93%
increase) increased more than red oak (23% increase). A possible explanation is that the
ethanol extractions were more effective at removing extractives associated with the cell
wall, wood ﬁbers and tracheids, which resulted in more cellulose components being

exposed after extraction. The differences observed between black cherry, red pine, and

60

red oak are probably due to the amount of extractable material present in the wood
structure before the treatment.

A slight increase in the C3 peak was observed for red oak and black cherry and no
signiﬁcant difference was observed in red pine.

The C4 peak representing a carbon atom linked to a carbonyl and a non-carbonyl
oxygen was insigniﬁcant in all three species (only about 2%). This could be explained by
a possible low concentration of carboxylic groups at the wood ﬁber surface (Kamdem et
al. 1991).

01, Spectra

The assignment of 01s peaks of wood materials have been previously discussed
by several researchers (Kamdem et a1. 1998; Liu et al. 1998; Hua et a1. 1993). There is
common agreement that the 01 peak originates from an oxygen atom linked to a carbon
atom by a double bond, and the 02 peak with higher binding energy represents an oxygen
atom linked by a single bond to a carbon atom. It has been previously shown that the 01
fraction can be associated with lignin and extractives, the elimination of which decreases
the 01 fraction and increases the 02 fraction (Barry and Zoran 1990; Hua et al. 1993).
Results obtained (Tables 3.5, 3.6, and 3.7) showed a decrease in the 01 peak with
extractives in agreement with previous ﬁndings. At the same time the 02 peaks
originating from cellulose and hemicelluloses increased as a result of more cellulose

being exposed to the wood surface.

61

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 3.6: Summary of XPS Spectral Parameters in black cherry
Peak Control Eth-T01 Eth-Tol+ Eth Eth + W
W

C. BE (eV) 284.65 284.51 284.51 284.51 284.60
Area (%) 58.00 36.02 39.29 29.94 41.37

C2 BE (eV) 286.26 286.26 286.22 286.20 286.32
Area (%) 31.96 53.85 48.84 55.17 48.36

C3 BE (eV) 287.78 287.94 287.69 287.76 288.01
Area (%) 7.26 9.40 9.26 11.96 9.19

C4 BE (eV) 288.93 289.19 288.79 289.06 289.53
Area (%) 2.78 0.74 2.61 2.93 1.08

01 BE (eV) 531.48 530.90 531.11 531.29 531.05
Area (%) 7.25 2.34 8.25 5.91 5.23

02 BE (eV) 532.71 532.66 532.72 532.70 532.78
Area (%) 92.75 97.66 91.75 94.09 94.77

 

 

 

 

 

 

 

62

 

Table 3.7:

Summary of XPS Spectral Parameters in red pine

 

 

 

 

 

 

 

 

 

 

 

 

 

Peak Control Eth-Tol Eth-Tol+ Eth Eth + W
W
C1 BE (eV) 284.78 284.73 284.73 284.46 284.73
Area (%) 62.85 58.68 57.01 41.90 49.50
C2 BE (eV) 286.32 286.25 286.26 285.97 286.32
Area (%) 23.72 30.34 32.76 45.87 39.88
C3 BE (eV) 287.55 287.77 287 .94 287.56 287.94
Area (%) 6.14 6.71 7.25 9.76 8.60
C4 BE (eV) 288.96 289.01 289.23 289.01 289.23
Area (%) 7.29 4.27 2.98 2.47 2.02
01 BE (eV) 531.72 531.49 531.49 531.44 531.69
Area (%) 18.94 4.69 4.75 11.59 14.59
02 BE (eV) 532.82 532.66 532.66 532.53 532.82
Area (%) 81.06 95.31 95.25 88.41 85.41

 

 

 

 

 

 

 

 

63

 

3.4 CONCLUSION

FT IR and XPS were successfully used to characterize extractives removed with
organic solvents and to analyze wood surfaces after extraction. The FT IR spectra showed
that components removed by ethanol and ethanol-toluene are made up of fatty acids,
saturated esters, and cyclic polyphenolic compounds. The water extracts mainly consisted
of coloriﬁc matter, condensed tannins, and low molecular weight carbohydrates. The
spectra obtained from extracted wood surfaces were very similar to that of un-extracted
samples. However, absorption peaks related to polysaccharides were enhanced in
extracted samples, as a result of henricelluloses and cellulose becoming more exposed on
the surface. This was conﬁrmed by the XPS analysis that showed a decrease in the O/C
ratio and a decrease in the C1 peak resulting from the removal of higher carbon content
compounds from the wood surface. Therefore, the O2 spectra originating from cellulose

increased considerably.

References

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65

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Johansson, L. S., J. M. Campbell, K. Koljonen, and P. Stenius 1999. Evaluation of
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66

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67

Chapter 4

Inﬂuence of Wood Extractives on Moisture Sorption and Wettability of
Red Oak (Quercus rubra), Black Cherry (Prunus serotina) and Red Pine
(Pinus resinosa)

Abstract

Red oak, black cherry, and red pine wood samples were soxhlet extracted with
various combinations of organic solvents including ethanol, toluene and water according
to ASTM 1110-96, ASTM D1107-96, TAPPI T207 om-88 and TAPPI T204 om-88
standards.

Contact angle and sorption isotherms with distilled water of extracted and un-
extracted specimens were determined to evaluate the role of wood extractives on the
wettability and sorption properties of these wood species.

Extracted specimens adsorbed more water than un-extracted specimens at high
relative humidities in agreement with the literature. The contact angle decreased with
increased extraction due to the removal of hydrophobic extractives. However, the
absorption rate of water measured as the decrease in contact angle over time suggests a
physical/chemical modiﬁcation of the wood surface and structure by solvent extraction

due to the migration and redistribution of hydrophobic extractives.

68

4.1 Introduction

Extractives are heterogeneous chemical compounds naturally occurring in woody
plants (Panshin and DeZeeuw 1980). Hillis (1970) deﬁned extractives as non-structural
constituents of plants. They have lower molecular weights than other polymeric
constituents of wood and are distributed in the lumen or other speciﬁc tissues in plants.
The term extractive covers a large number of compounds of different classes, which can
be extracted from wood with polar and non-polar solvents (Hillis 1987).

According to Koch (1972), softwood extractives comprise a heterogeneous group
of compounds present in low concentrations. Among the most important are terpenes and
wood resins, both of which are composed of isopropene units, polyphenols such as
ﬂavonols, anthocyanins, quinones, stilbenes, lignans and tannins, tropolones, glycosides,
sugars, fatty acids, and inorganic constituents (Kollman and Cote 1984).

The description of the chemical composition of most northern hardwood
extractives has been conducted (Rowe and Conner 1979). In most hardwoods,
hydrolyzable gallotannins and ellagitannins are the predominant compounds. The
sapwood also contains leucoanthocyanins and possibly pinoresinol. In addition, coumarin
and lignans are usually present. How extractives affect water properties and the
dimensional stability of wood depends upon their chemical composition and location in
the wood structure. The chemical constitution of extractive components, their size and
molecular weight, and their afﬁnity to the ligno-cellulosic wood complex will dictate
their location within the wood structure. Low molecular weight monomers are found in
voids in cell walls, while high molecular weight components will be mostly located in the

lumen of vessels, tracheids, or ﬁbers.

69

Aromatic compounds derived from glucose such as ﬂavonoids and condensed
tannins, usually have free hydroxyl groups and are water-soluble. Consequently, they will
be more susceptible to absorbing water and inducing greater dimensional change. This
can also be applied to terpenoids, which usually have hydrophilic functional groups
attached to the hydrocarbon radical. To the contrary, pure hydrocarbons such as terpenes
are volatile and will not affect dimensional stability.

The dimensional stability of wood when exposed to various humidity conditions
is the main obstacle for its efﬁcient use. It has been reported that wood-water
relationships are affected by the type and total extractive content in the wood. For
example, Nearn (1955) reported early work that concluded that the increased shrinkage
samples of Acacia melanoxylon was due to the increase of the ﬁber saturation point (fsp)
of that species caused by the presence of water-soluble extractives. This was later
conﬁrmed by Wangaard and Granados (1967), when they showed that one of the
principal effects of extractives is to depress the sigmoid isotherm in the upper range of
relative humidity.

Recent publications are in line with these views (Choong and Achmadi 1991;
Chen and Chong 1994). Stamm (1952) investigated the anti-shrink efﬁciency of wood
treated with organic salts, sugars, and water-soluble phenol-formaldehyde resinoids. He
observed that extractives rich species do not conform to the usual shrinkage-speciﬁc
gravity relationship and concluded that water-soluble extractive solutes reduce the
shrinkage of wood in proportion to the fraction of transient cell wall capillary structure

that is occupied by the solute.

7O

Nearn (1955) focused on the effect of extractives on the volumetric shrinkage of
15 tropical and temperate species. He found that wood with low ﬁber saturation points
have lower than normal equilibrium moisture contents at high relative humidity due to
the bulking action of extractives. The removal of extractives caused an increase in
equilibrium moisture content at higher relative humidities. Chong (1969) observed wide
variations in hygroscopic properties related to extractive content in ten southern pine
woods samples. Cooper (1974), working on black walnut, also observed a lower ﬁber
saturation point on extracted samples. He obtained higher swelling at low relative
humidities, attributed to the fact that some of the sites formerly blocked by extractives
were made available for water which is consistent with the theory of extractives
functioning as bulking agents in the cell wall.

Wood extractives are also known to affect the wettability of wood surfaces
(Maldas and Kamdem 1999). Polar and hydrophilic extractives might increase wetting,
and non-polar extractives might decrease wetting. Chen (1970) observed increased
wettability with distilled water in all 70 tropical woods used in his study. To the contrary,
Jordan and Wellons (1977) observed lower wettability with keruing wood and attributed
that ﬁnding to extractives present in veneer samples tested. Maldas and Kamdem (1999)
also observed decreased wettability. In their experiment, wood extracted with an ethanol-
toluene solvent exhibited higher contact angle (lower wettability) compared to un-
extracted samples. They suggested that the high contact angle was due to the hydrophobic
nature of the extracted wood surface promoted by the migration of hydrophobic

extractives from the wood surface. They also concluded that the more hydrophobic

71

extractives such as waxes and long chain hydrocarbons are present in a wood species, the
less water this species will absorb.

From measurement of the contact angle and moisture adsorption properties, the
surface free energy of the wood surface can be calculated. The surface free energy of
solids is known to govern their wettability and coatability by liquids. It controls their
propensity to absorb species from adjacent ﬂuid phases, and inﬂuences their catalytic
activity (Sun and Berg 2002).

Most studies on sorption and wettability properties have been focused on tropical
woods known for their high extractive content. Several temperate woods possess limited
amount of extractives compared to tropical woods (Spalt 1957). I am hypothesizing that
they would affect in a similar way most water properties of wood surfaces. How
signiﬁcant is the inﬂuence of wood extractives on sorption and equilibrium constant?
How is the free energy change and contact angle affected? What are implications of these
property changes on the dimensional stability of some temperate woods are all areas that
need to be further investigated.

The goal of this study is to investigate the inﬂuence of wood extractives on the

sorption and wettability behavior of northern red oak, black cherry, and red pine.

4.2 Materials and Methods

4.2.1 Materials
Black cherry (Prunus serotina), red oak (Quercus rubra) and red pine (Pinus

resinosa) samples were prepared and extracted according to the procedure described in

Chapter 3, section 3.2.1 and 3.2.2.

72

4.2.2 Sorption Test

From each treatment four samples were selected for the sorption test. Specimens
were divided into two matching halves measuring 4x22x40mm each (tangential, radial,
longitudinal). One half was used in adsorption and the matching half was used in
desorption. Four specimens from each extraction type were exposed at various relative
humidity conditions in saturated salt solutions (Table 4.1) in a conditioning room
maintained at 20°C according to ASTM E104-85 (ASTM 2000).

Samples were considered to have reached equilibrium at any given humidity
when the daily weight changes were less than 0.1mg. The equilibrium moisture contents
(MC) were calculated on the basis of the oven-dried weight of the samples.

4.2.3 Contact angle

The left and right contact angle between each specimen’s surface and a drop of
distilled water was measured using a VCA 2000 system from AST Inc. Wood specimens
were set on a stage and a droplet of Sal of water was placed on the specimen with a
syringe. The mean value of the contact angles of 8 measurements for left and right
contact angles (CA) between the droplet and wood surface at l-second intervals were
collected. The initial contact angle (to) was described as the point where the regression
line of contact angle values over time crossed the Y-axis (Maldas and Kamdem 1999;
Nzokou and Kamdem 2002).

The rate of decrease of the contact angle was computed as an indication of the
absorption rate of the water on the wood surface (Maldas and Kamdem 1999). The

following equation was used to calculate the rate:

Rig
dt

73

Where:

R = Rate of decrease of the contact angle

d8 = Variation of the contact angle

dt = variation of the time
4.2.4 Data Analysis

Adsorption and desorption moisture contents were plotted against the various

relative humidities and the hysteresis ratio (AID) was calculated at each condition. The
Hailwood-Horrobin (1946) equation was applied to the data and the free energy was
calculated. The statistical signiﬁcance of the difference between the various extraction
types and control specimens was evaluated using the one-way analysis of variance
procedure in SigmaStat version 2.0 for Windows (SPSS Inc. 1997). Tukey’s multiple
comparisons test (95% conﬁdence) was employed to determine differences between

average CA values for the various extractions.

74

Table 4.1: Relative Humidity Values for Selected Saturated Salt Solutions

(ASTM E104-85)

 

 

 

 

 

 

 

 

 

Salt Relative Humidity (%) at 20°C
Lithium Chloride (LiCl.H2O) 1110.3

Magnesium Chloride (MgCl2.6H2O) 3310.2

Magnesium Nitrate (Mg(NO3).6H2O) 5410.2

Sodium Chloride (NaCl) 7510.1

Potassium Chloride (KCl) 8510.3

Potassium Nitrate (KNO3) 94:0.7

Distilled Water 100

 

 

75

 

4.3 Results and Discussion

4.3.1 Sorption

Adsorption and desorption EMC for each species and extraction type are
summarized in Table 4.2. Desorption EMC, were consistently higher than adsorption
EMC as result of hysteresis. Hysteresis ratio data (Table 4.3), calculated by dividing
adsorption EMC to the desorption EMC showed that ethanol extracted samples had
higher hysteresis than control samples. According to the Urquhart theory, hysteresis is
believed to be caused by the development of hydrogen bonds between hydroxyl groups
on adjacent cellulose molecules upon initial drying (Spalt 1957). Consequently, higher
hysteresis in ethanol-extracted samples is an indication that extractives removed by
ethanol prevent some of the Urquhart type hydrogen bonding reactions from occurring.

Adsorption data comparing extracted and un-extracted specimens for each species

are presented in Figures 4.1, 4.2 and 4.3.

76

Table 4.2:

Adsorption and Desorption EMC (% average of four specimens) of Extracted and

Un-Extracted Specimens

 

Black cherry

 

Control

Eth-T01

Eth-T01 + Water

Eth

Eth + Water

 

RH

Ads

Des

Ads

Des

Ads

Des

Ads

Des

Ads

Des

 

0.0

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

 

11.0

2.5(0.05)*

4.9(0.09)

2.3(0.03)

4.8(0.03)

2.7(0.02)

4.8(0.01)

2.9(0.05)

5.0(0.08)

2.9(0.02)

4.8(O.l7)

 

33.1

5.3(O.10)

6.1(0.02)

5.1(0.04)

6.4(0.09)

5.5(0.03)

6.4(0.07)

5.7(0.07)

6.9(0.04)

5.7(0.08)

6.5(0.03)

 

54.0

8.3(0.02)

9.1(0.10)

8.1(0.07)

9.4(0.01)

8.5(0.03)

9.4(0.01)

8.7(0.03)

9.9(0.06)

8.7(0.08)

9.5(0.02)

 

75.5

11.2(0.06)

l4.3(0.02)

l l.l(0.06)

15.4(0.02)

l l.8(0.03)

15.8(0.0l)

12.1(0.10)

15.3(0.02)

12.1(0.0l)

15.6(0.02)

 

85.1

12.8(0.02)

15.1(0.03)

12.5(0.02)

l6.4(0.01)

l3.6(0.03)

l7.0(0.02)

l3.9(0.01)

l6.4(0.02)

l4. l(0.02)

l6.8(0.09)

 

94.6

16.1(0.02)

l8.7(0.03)

l6.6(0.08)

20.0(0.02)

l8.5(0.07)

20.6(0.02)

18.2(0.02)

19.9(0.03)

l8.7(0.01)

20.5(0.07)

 

100.0:23.8(0.01)

 

24.5(0.03

 

23.3(0.06)

25.3(0.05)

26.1(0.06)

 

26.9(0.03)

25.7(0.03)

 

25.5(0.03)

26.6(0.03)

 

26.8(0.03)

 

Red oak

 

Control

Eth-T01

Eth-T01 + Water

Eth

Eth + Water

 

Ads

Des

Ads

Des

Ads

Des

Ads

Des

Ads

Des

 

0.0

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

 

11.0

2.1(0.06)

4.5(0.06)

2.0(O.14)

4.2(0. l4)

2.2(0.05)

4.4(0. 10)

2.3(0.03)

4.2(0.1 l)

2.4(0.l l)

4.4(0.01)

 

33.1

4.5(0.05)

5.6(0.04

4.3(0. l4)

5.7(0.10)

4.4(0. l4)

5.7(0.07)

4.6(0.05)

5.6(0.09)

4.8(0.06)

5.8(0.12)

 

54.0

7.5(0.07)

9.6(0.06)

7.2(0.09)

9.7(0.02)

7.5(0.04)

9.7(0.04)

7.6(013)

9.6(0.02)

7.8(0. l6)

9.7(0.01)

 

75.5

10.5(0.10)

15.2(0.01)

10.5(0.25)

[6.1(0.02)

10.7(0.16)

15.9(0.02)

11.2(0.08)

l6.1(0.01)

11.5(0.21)

16.0(0.03

 

85.1

12.3(0.10)

18.0(0.01)

12.3(0.06)

19.1(0.06)

12.5(0.04)

18.9(0.02)

13.2(0.15)

18.9(0.01)

13.8(0. 12)

l9.2(0.02)

 

94.6

16.3(0.08)

20.5(0.01)

16.5(0.07)

21.4(0.03)

16.2(0.12)

21.7(o.04)

l7.5(0.09)

21.9(0.02)

18.4(0.07)

22.3(0.02)

 

100.0

 

21 .2(0. 1)

26.4(0.12)

 

22. l (0.07)

26.6(0.06)

23.0mm)

 

27.2(0.04)

23.7(0.09)

 

27.1(0.11)

24.2(0.09)

 

27.3(0.03

 

Red pine

 

Control

Eth-T01

Eth-T01 + Water

Eth

Eth + Water

 

RH

Ads

Des

Ads

Des

Ads

Des

Ads

Des

Ads

Des

 

0.0

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

 

11.0

2.5(0.06)

4.8(0.08)

2.7(0.05)

4.9(0.09)

2.7(0.08)

4.7(0.01)

2.6(0.04)

4.9(0.03)

2.7(0.04)

4.7(0.08)

 

33.1

5.3(0.02)

7.6(0.02)

5.5(0.01)

7.7(0.06)

5.5(0.02)

7.5(0.05)

5.5(0.02)

7.6(0.03)

5.5(0.03)

7.3(0.06)

 

54.0

8.3(0.09)

9.5(0.02)

8.5(0.05)

9.8(0.02)

8.5(0.04)

9.4(0.02)

8.5(0.06)

9.5(0.03)

8.5(0.03)

9.3(0.01)

 

75.5

l2.4(0.01)

16.3(0.09)

l3. l(0.09)

l6.8(0.01)

13.2(0.01)

l6.4(0.02)

12.9(0.01)

l6.6(0.03)

13.1(0.06)

l6.4(0.04)

 

85.1

14.4(0.03)

l7.3(0.02)

15.1(0.04)

l7.7(0.06)

15.2(0.03)

l7.3(0.03)

l4.9(0.01)

l7.3(0.02)

15.4(0.02)

17.2(0.01)

 

94.6

l7.7(0.07)

l8.0(0.02)

19.1(0.03)

18.7(0.01)

18.7(0.07)

l8.3(0.03)

l8.7(0.04)

18.4(0.04)

19.1(0.04)

18.3(0.0l)

 

 

 

100.0126.8(0.03)

 

27.6(0.06)

 

 

28.0(0.05)

27.9(0.03)

 

29.7(0.03)

 

29.3(0.06)

 

28.8(0.05)

 

29.0(0.08)

 

30.4(0.03)

 

29.6(0.05)

 

* Numbers in parenthesis are standard deviation

Ads: Adsorption

Eth:

Ethanol

Eth-T01: Ethanol-Toluene

Note: Adsorption EMC higher than Desorption EMC for all treatments.

Des: Desorption
Eth + Water: Ethanol + Water
Eth-T01 + Water: Ethanol-Toluene + Water

77

 

Table 4.3: Hysteresis Ratio of Specimens at Various Relative Humidities

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Black che
Control Eth-T01 Eth-T01 + Water Eth Eth + Water
11.0% 0.51 0.48 0.56 0.59 0.60
33.1% 0.87 0.79 0.86 0.82 0.87
54.0% 0.92 0.86 0.90 0.87 0.91
75.5% 0.78 0.72 0.75 0.79 0.78
85.1% 0.85 0.76 0.80 0.85 0.84
94.6% 0.86 0.83 0.89 0.92 0.91
100.0% 0.97 0.92 0.97 1.01 0.99
Red oak
1 1.0% 0.48 0.48 0.49 0.54 0.54
33.1% 0.80 0.75 0.77 0.82 0.84
54.0% 0.78 0.75 0.77 0.80 0.80
75.5% 0.69 0.65 0.67 0.70 0.72
85.1% 0.68 0.64 0.66 0.70 0.72
94.6% 0.80 0.77 0.75 0.80 0.82
100.0% 0.80 0.83 0.85 0.87 0.89
Red pine
11.0% 0.52 0.54 0.57 0.53 0.57
33.1% 0.68 0.71 0.74 0.72 0.75
54.0% 0.86 0.86 0.91 0.89 0.92
75.5% 0.76 0.78 0.80 0.78 0.80
85.1% 0.84 0.86 0.88 0.86 0.89
94.6% 0.98 1.02 1.02 1.02 1.04
100.0% 0.97 1.00 1.02 0.99 1.02
Eth: Ethanol Eth + Water: Ethanol + Water
Eth-T01: Ethanol-Toluene Eth-T01 + Water: Ethanol-Toluene + Water

78

 

 

30%

 

“—66.4161“
25% 7+ rm + Eth-Tol

—a— Eth-Tol + Water

l_. ._ -__E ___._.__5

 

20% ..__- EAL .

—a— Eth
--)(- Eth + Water

 

 

 

 

15%..3—4 - l

EMC (%)

 

1 0%

 

5%

 

 

 

 

00/0 1 1 T . T
0% 20% 40% 60% 80% 1 00% 1 20%
Fblatlve I'llm dlty (%)

 

 

 

Figure 4.1: Adsorption Curves of Extracted and Non Extracted Black Cherry

specimens

79

 

30% <—— —— —— ~ #-

-II—Control

 

   
   
    

 

25% 1 -—Eth-Toi 1 i m- — —————
-'—Eth-Tol + Water ’

Amok AT *Eth y *7? .4 —

"95"“ _# —N—Eth+Water . ——- - ——

 

10% . . _ __ _-- - . - ‘ A _, ________. ..__ .

5%

 

 

 

 

 

Relative Humidity (95)

 

 

Figure 4.2: Adsorption Curves of Extracted and Non Extracted Red Oak
Specimens

80

 

35%

20%

EMC (%)

1 5%

5%

 

25% .1

10% —

 

30% - -

 

** *7 l —t—Control ﬂ

 

I -I— Eth-Tol
—I— Eth-Tol + Water

—— Eth

-—)<-— Eth + Water

 

 

   

   
   
 

 

 

   

  

  

 

 

  

 

 

0%) H -

0%

60%
mintlve mm Itlty (%)

20% 40%

80% 1 00%

1 20%

 

Figure 4.3: Adsorption Curves of Extracted and Non Extracted Fled Pine

Specimens

81

 

For black cherry, ethanol-toluene extracted samples had an adsorption curve
similar to that of control samples (Figure 4.1). However, when ethanol-toluene extraction
was subsequently followed by water extraction, the adsorption curve for extracted
samples was higher than the curve for un-extracted specimens, especially in the higher
range of the relative humidity values. Samples extracted with ethanol and ethanol + water
had consistently slightly higher EMC than control samples. A similar trend was observed
in red oak (Figure 4.2). For red pine (Figure 4.3), the adsorption curves for all extraction
treatments were consistently higher than the curve for un-extracted specimens. From
these observations, it can be concluded that extracted samples generally adsorbed more
water than un-extracted samples at high relative humidity. This conclusion is in
agreement with previously published data on tropical and domestic hardwoods by Spalt
(1957), Wangaard and Granados (1967) and Chong and Achmadi (1991). The higher
EMC in extracted samples is explained by the increased availability of moisture sites
previously occupied by extractives, which became available to water once extractives
were removed (Nearn 1955; Spalt 1979).

Analysis of Adsorption Data by the Hailwood-Horrobin Sorption Model
The Hailwood-Horrobin (1946) model considers that part of the sorbed water

forms a hydrate with wood, and the balance forms a solid solution in the cell wall (Spalt
1958; Spalt 1979; Cao and Kamdem 2003). Water therefore exists in two states, hydrated
water and dissolved water. The sorption equation of the Hailwood-Horrobin model is

expressed as:
V = A + bh — Ch 2
m

Where h is the relative vapor pressure

(1)

82

m is the equilibrium moisture content,

A, B, and C are empirical constants.

A, B, and C are obtained by ﬁtting the W values to equation ( 1) by the least
square method, and the physical constants or, B, and W can be calculated using equation

(2), equation (3), and equation (4) (Spalt 1958).

82 82 2
2+— + 2+— —4
AC AC

a=%(ﬂ—I) 0

W
1566'" A(ﬂ + 1)a (4)

 

 

(2)

or is the equilibrium constant between free dissolved water and the hydrated

water,

B is the equilibrium constant between dissolved water and the external vapor

pressure,

W is the molecular weight of wood substance necessary to be associated with
one molecular weight of water molecules (mol/mol).

From the above constants, the free energy change for hydrated water can be

calculated using equation (5).

AG}. = "RT 111(76 ) (5)

83

Table 4.4: Parameters of the Hailwood-Horrobin Sorption Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A B C R2 (3 or w AG,
Control 0.07 0.08 0.11 0.92 2.48 0.81 347.1 526.7
Eth-T01 0.06 0.09 0.12 0.91 2.94 0.83 347.5 490.5
. Eth-T01 + Water 0.06 0.09 0.12 0.90 2.88 0.83 346.1 486.6
Red pme
Eth 0.06 0.08 0.11 0.92 2.63 0.81 341.2 503.1
Eth+Water 0.06 0.09 0.12 0.92 2.84 0.83 350.1 467.0
Control 0.03 0.17 0.16 0.96 7.32 0.78 405.4 578.0
Eth-T01 0.038 0.16 0.16 0.94 6.57 0.79 41 1.2 549.9
Eth-T01 + Water 0.03 0.17 0.16 0.91 7.34 0.79 408.7 547.7
Red oak
Eth 0.032 0.16 0.15 0.95 7.45 0.79 387.6 548.3
Eth + Water 0.03 0.16 0.15 0.97 7.74 0.80 377.2 544.7
Control 0.027 0.17 0.15 0.87 9.23 0.77 379.0 643.1
Eth-T01 0.025 0.17 0.14 0.85 9.96 0.76 381.6 663.7
Eth-Tol+Water 0.024 0.17 0.15 0.88 10.16 0.78 372.5 588.4
Black cherry
Cherg Eth 0.021 0.16 0.14 0.87 11.37 0.77 354.7 637.9
Eth + Water 0.021 0.17 0.14 0.88 11.11 0.78 361.1 601.4
A, B, and C are empirical constants.
or: Equilibrium constant between free dissolved water and the hydrated water
B: Equilibrium constant between dissolved water and the external vapor pressure
W: Molecular weight of wood substance necessary to be associated with one

molecular weight of water molecules (mol/mol).

AG: Free energy change for hydrated water

84

Parameters from the Hailwood-Horrobin model are listed in Table 4.4 From that
table, it can be observed that adsorption data for all three species had a good ﬁt with the
model with R2 values above 80% for all the treatments. The data also shows that or and B
equilibrium constants were consistently higher for all red pine extracted samples resulting
in lower values for W and AGh. AG}, is the energy required to swell the wood structure,
and lower values of AG. mean less energy is required to swell the wood structure.
Therefore, lower values obtained for extracted red pine specimens are indications that the
wood structure requires less energy to swell due to the increase of hydrophilic sites.
Similar trends were observed for red oak specimens (Table 4.4) and for black cherry
samples extracted with ethanol. The AGh value for black cherry samples extracted with
ethanol-toluene (663.7 j/mol) was higher than that of control samples (643.1 j/mol).
However, this value decreased to 588j/mol when ethanol-toluene extraction was followed
by water extraction. The reason for the variation is unknown, however it could be
hypothesized that this is the result of the migration and relocation of some hydrophobic
extractives not removed by the extraction process, but washed out by the subsequent
water extraction.

4.3.2 Contact Angle

The average contact angle values and standard deviations of eight replicates for
each treatment are reported in Table 4.5 Extracted samples had contact angle values
consistently lower than control samples for all three species, and the difference analyzed
by one-way ANOVA (95% conﬁdence level) was statically signiﬁcant between all
extraction types and control samples. In addition, the results also show that following
organic solvent (ethanol or ethanol-toluene) extraction by water extraction resulted in

slightly lower contact angle values. Lower contact angles for extracted samples conﬁrms

85

observations of the sorption experiment and reinforces the hypothesis of a removal of
hydrophobic compounds during the extraction process. This result is in agreement with
results from Chen (1970) and Maldas and Kamdem (1999) who also obtained increased
wettability in eight tropical woods and southern yellow pine following extraction.
However, Nussbaum and Sterley (2002) obtained a more complex relationship between
the contact angle, total extractives, and storage time. They explained the variability in
their results by the migration of extractives spreading on the wood surface and causing
chemical changes to the surface.

Computed values of the water absorption rate estimated as the decrease in contact
angle of the water drop overtime are summarized in Table 4.6. Results presented show a
tendency to a lower absorption rate of the water drop after initial solvent extraction.
However, subsequent water extraction induced a higher absorption rate, similar or higher
to the values for control samples. This is explained by the migration phenomenon
suggested by Nussbaum and Sterley (2002) during the ﬁrst solvent extraction. Migrates
are subsequently washed out during the following water extractions, resulting in wood

surfaces with more afﬁnity for water.

86

Table 4.5: Average (Left and Right) Advancing Contact Angle

 

 

 

 

 

 

 

 

 

 

 

 

(Degrees)*
Red oak Black cherry Red pine
Control 88.1 (7.2)** 89.2 (4.1) 116.2 (6.5)
IEth-Tol 49.4 (7.5) 50.1 (6.2) 103.3 (6.9)
lEth-Tol + Water 48.3 (9.2) 42.4 (6.3) 45.6 (7.9)
[Eth 62.1 (9.1) 57.6 (11.0) 80.4 (17.3)
[Eth + Water 50.8 (9.2) 54.6 (6.6) 53.1 (6.5)
* Control samples were statistically different from extracted samples. Details of the one-

way AN OVA are presented in Appendix 1.

** Numbers in parenthesis are standard deviation.
Eth: Ethanol Eth + Water: Ethanol + Water
Eth-T01: Ethanol-Toluene Eth-T01 + Water: Ethanol-Toluene + Water

87

Table 4.6: Rate of Change in Contact Angle (R) over time between

distilled water and wood surface (Degrees/Second)*

 

 

 

 

 

 

 

 

 

 

 

 

Contol Eth-Tol Eth-Tel + Water Eth Eth + Water
Oak 2.75 (0.64 ** 1.44 (0.38) 2.34 (0.75) 2.54 (0.65) 2.77 (0.84)
Cherry 1.62 (0.81) 0.82 (0.18) 2.82 (0.71) 0.69 (0.25) 3.16 (0.96)
Pine 5.19 (0.91) 6.95 (1.45) 3.66 (1.02) 2.78 (0.73) 3.31 (0.86)
* The difference between the various groups was statistically signiﬁcant. Details of the

one-way ANOVA procedure are presented in Appendix 2.

** Numbers in parenthesis are standard deviations.
Eth: Ethanol Eth + Water: Ethanol + Water
Eth-T01: Ethanol-Toluene Eth-T01 + Water: Ethanol-Toluene + Water

88

4.4 Conclusion

The inﬂuence of wood extractives on sorption and wettability of two hardwoods
and one softwood species was investigated in this project. Results showed that wood
extractives lowered the equilibrium moisture content of wood at high relative humidities.
The difference between extracted and un-extracted specimens was less pronounced when
toluene was included in the solvent system. This was explained as a result of the
migration and redistribution of hydrophobic extractives following the extraction resulting
in lower hysteresis.

Analysis of data using the Hailwood-Homobin sorption model showed that
extracted red pine and ethanol extracted cherry and oak had more adsorption sites
available and needed lower energy to absorb water. However, this trend was not veriﬁed
for black cherry samples extracted with ethanol-toluene mixture. This observation is
probably due to the migration of some extractives to the wood surface following ethanol-
toluene extraction.

The contact angle was found to decreases with increased extraction. The
absorption rate after an initial increase, due to the modiﬁcation of the wood surface
caused by extractive migration, decreased following water extraction.

These results suggest that the increased ability of wood surfaces to absorb water
due to their extractive content could lead to increased dimensional instability and

eventually lead to more cracks and checks in extracted wood.

89

References

Ajuong, Elijah-M. A., and C. M. Breese 1998. The Roles of Extractives on Short
Term Creep in Compression Parallel to Grain of Pai wood (Afzelia aﬁ'icana
Smith). Wood and Fiber Science 29(2): 161-170.

Anon 1999. American Wood Handbook. Wood as an Engineering Material. Gen.
Tech. Rep. FPL-GTR-l 13. Forest Product Laboratory. USDA Forest Service.
Madison, Wisconsin. 463p.

American Society for Testing Materials 1999. Standard Test Methods D 1105-96;
D1107-96; D1110-96; D2395-93. Vol 04.10 on Wood. Annual Book of ASTM
Standards. ASTM, West Conshohocken, Pa. 676pp

American Society for Testing Materials 2000. Standard Practice for Maintaining
Constant Relative Humidity by Means of Aqueous Solutions. E 104-85 Vol 14.01
on Wood. Annual Book of ASTM Standards. ASTM, West Conshohocken, Pa.
Pp. 965-967.

Cao, J ., and D. P. Kamdem 2003. Moisture adsorption Characteristics of Copper-
ethanolamine (CuEA) Treated Southern Pine (Pinus spp.). Submitted to
Holzforschung.

Chen C. M. 1970. Effect of Extractive Removal on Adhesion and Wettability of Some
Tropical Woods. Forest Products Journal 20(1): 36-41.

Chen Y., and E. T. Chong 1994. Determining the Effect of Extractives on Moisture
Movement Using a Continuous Measuring System. Wood and Fiber Science.

26(3): 390-396.

Chong, E. T. 1969. Effect of Extractives on Shrinkage and Other Hygroscopic
Properties of Ten Southern Pine Woods. Wood Fiber 1: 124-133.

Choong E. T., and S. S. Achmadi 1991. Effect of Extractives on Moisture Sorption and
Shrinkage in Tropical Woods. Wood and Fiber Science. 23(2): 185-196.

Coopers, G. A. 1974. The Effect of Black Walnut Extractives on Sorption, Shrinkage,
and Swelling. Wood Science. 6: 380-388.

Hailwood, A. J. and S. Horrobin. 1946. Absorption of Water by Polymers: Analysis in
Terms of a Simple Model. Trans. Far. Soc. 42B: 84-102.

Hillis, W. E. 1970. Distribution, Properties and Formation of Some Wood Extractives.
Wood Science and Technology 5: 272-289.

90

Hillis W. E., 1987. Heartwood and Tree Exudates. Springer-Verlag, Berlin Germany.
268pp.

Jordan D. L., and J. D. Wellons 1977. Wettability of Dipterocarp Veneers. Wood
Science 1: 22-27.

Koch, P. 1972. Utilization of the Southern Pines. Vol I. The Raw Material.
Agriculture Handbook No. 420. US. Department of Agriculture. Forest Service.
Southern Forest Experiment Station. 734pp.

Koch, P. 1985. Utilization of Hardwoods Growing on the Southern Pine Sites. Vol
1. Raw Material. Agriculture Handbook No. 605. US. Department of Agriculture.
Forest Service. Southern Forest Experiment Station. 1418pp.

Kollmann, F. F. P., and W. A. Cate 1984. Principles of Wood Science and Technology.
Vol I Solid Wood. Springer-Verlag New York. 592pp

Laks, P. E. 1991. The Chemistry of Wood Bark. Pages 257-330 in D. N.-S. Hon and N.
Shiraishi, eds. Wood and Cellulosic Chemistry. Marcel Dekker Inc., New York
and Basel.

Maldas, D. C., and D. P. Kamdem 1999. Wettability of Extracted Southern Pine.
Forest Products Journal. 49 (1 1/12), 91-93.

Nearn, W. J. 1955. Effect of Water-Soluble Extractives on the Volumetric Shrinkage and
Equilibrium Moisture Content of Eleven Tropical and Domestic Woods. Bull.
598. Penn. State Univ., Agric. Exp. Sta., University Park, PA. 38pp.

Nussbaum M. R. and M. Sterley. 2002. The Effect of Wood Extractive Content on Glue
Adhesion and Surface Wettability of Wood. Wood and Fiber Science 34 (1): 57-
71.

Nzokou, P. and D. P. Kamdem 2002. Weathering of two Hardwood Species:
African padauk (Pterocarpus soyauxii) and red maple (Acer rubrum). Journal of
Tropical Forest Products 8(2): 200-209.

Panshin, A. J., and C. Dezeeuw 1980. Textbook of Wood Technology. Vol. 1. 3rd ed.,
McGraw-Hill Co., New York, NY. 643 pp.

Rowe, W. J., and A. H. Conner 1979. Extractives in Eastern Hardwoods: A Review. US.
Departement of Agriculture. Forest Service, Forest Products Laboratory. General
Technical Report FPL 18. 67pp.

Spalt, H. A. 1957. The Sorption of Water by Domestic and Tropical Woods. Forest
Products Journal. 7 (10): 331-335.

91

Spalt, H. A. 1958. The Fundamentals of Water Vapour Sorption by Wood. Forest
Products Journal 8(10): 288-295.

Spalt, H. A. 1979. Water-Vapor Sorption by Wood of High Extractive Content.
Proceeding of the Wood Moisture Content, Temperature and Humidity
Relationship Symposium at Virginia Polytechnic Institute and State University.
Blacksburg, Virginia, October 29, 1979. pp 55-61.

Stamm, A. J. 1952. Surface Properties of Cellulosic Materials. In Wise, Louis E
and Jahn, Edwin J. (Eds): Wood Chemistry (2nd Edition). New York, Reinhold.

Stamm, A. J. 1964. Wood and Cellulose Science. Ronald Press, New York, NY.
549pp.

Sun, C., and C. J. Berg 2002. Effect of Moisture on the Surface Free Energy and Acid-
Base Properties of Mineral Oxides. Journal of Chromatography A 969(2002): 59-
72.

Technical Association for the Pulp and Paper Industry (TAPPI) 1993. TAPPI Standards
and Suggested Methods. Methods TAPPI T204 OM-88; TAPPI T207 OM-88.
Technical Association of the Pulp and Paper Industry. New York.

Taras, M. A., and R. J. Saucier 1967. Inﬂuence of Wood Extractives on the Speciﬁc
Gravity of Southern Pine. Forest Products Journal 17(9): 97-99.

Wangaard, F. F., and L. A. Granados 1967. The Effect of Extractives on Water-Vapor
Sorption by Wood. Wood Science and Technology. 1(4): 253-277.

92

Chapter 5

The Inﬂuence of Wood Extractives on the Physical Degradation of
Wood Surfaces Exposed to Artificial Weathering
Abstract

Organic solvents were used to remove extractives from red pine (Pinus resinosa),
red oak (Quercus rubra), and black cherry (Prunus serotina) wood samples before
exposure to artiﬁcial weathering. Surface roughness, weight loss, and scanning electron
microscopy were used to assess the damages caused to the wood surface by the
weathering process and to evaluate the inﬂuence of wood extractives on the physical
degradation of these wood species.

As expected, the average roughness and maximum peak to valley increased with
exposure time for all species and extraction treatments. However, comparison between
the various extraction treatments and un-extracted specimens showed no statistically
signiﬁcant differences.

All three species had considerable weight loss after weathering; 8-10% for red
pine, 13.1-15% for black cherry, and l6.2-19% for red oak; but there was no signiﬁcant
difference between extractive treatments within each species.

Scanning Electron Microscopic observations showed severe roughening,
cracking, breakage of wood ﬁbers and erosion of wood structures, but revealed no
distinguishable trend due to extractive treatments.

These results suggest no detectable effect of extractives on the roughening, weight

loss, and microscopic degradation of wood surfaces.

93

5.1 Introduction

Wood is one of the most efﬁcient natural materials and exhibits major technical,
economic, and environmental advantages over other construction materials: It is a
renewable resource and sustainable and sound forestry can ensures its continuous supply
and ecological advantage. It is generally cheaper, lighter, and more versatile compared to
its competitors. However, like other biological materials wood is susceptible to
degradation.

Exposed board surfaces become rough as the grain surface becomes eroded,
develops cracks, and ultimately warps (Feist 1982). The process also leads to formation
of microscopic inter and intra-larninar checks or cracks. The wood color quickly changes
towards a brown color, and later to whitish gray (Browne 1960; Feist & Hon 1984,
Nzokou and Kamdem 2002).

However, the effects of weathering on wood surfaces vary between and within
species and even in material cut from the same tree. The reasons for this variability are
often attributed to wood variability, which itself is partly caused by its extractive content.

Several authors have investigated the inﬂuence of species variation and wood
structure on the weathering of wood surfaces. Flaete et a1. (2000) investigated cracks
formation in solid wood sidings of aspen and Norway spruce exposed to accelerated
weathering. They observed a high number of short cracks in aspen and a fewer but more
injurious number of cracks in spruce. They explained this result as a consequence of the
more asymmetrical cross sectional pattern in wood of aspen, eventually preventing cracks

from propagating. Kamdem and Zhang (2000) used a surface proﬁlometer to measure

94

several surface roughness parameters and correlated those to the number and size of
checks on the wood surface after weathering.

The amount of such cracking differs considerably with species..For example,
Gaby (1963) found particularly high shrinkage in refractory wood such as oak, which
contains up to 32% of its wood volume as ray tissue.

The inﬂuence of extractives on physical properties of wood has been reported to
result from the bulking effect of extractives on wood, which suggests that large molecules
of wood extractives keep the wood structure in a semi-swollen condition and hinders the
number of available sites for the formation of intermolecular lignin-cellulose and/or
lignin-lignin bonds (Ajuong and Breese 1998). Therefore, the removal of extractives
should make available additional moisture sorption sites, and induce higher dimensional
change leading to increased roughening, weight loss, and cracks on the wood surface
when exposed to weathering.

The goal of this project was to investigate the inﬂuence of wood extractives on
physical changes occurring on wood surfaces after artiﬁcial weathering.

5.2 Materials and Methods

Samples were selected, prepared and extracted according to methods presented in
Chapter 3, section 3.2.1 and 3.2.2.

5.2.1 Artificial weathering

Artiﬁcial weathering was conducted in a QUV weathering tester (Q-Panel Ltd.,
Ohio, USA) ﬁtted with UV ﬂuorescent lamps. The samples were subjected to a repeated

weathering cycle comprised of 2hours of UV light and 18 minutes of water spray.

95

The average irradiance was set at about 0.85 W/m2 at 340 nm wavelengths with a
chamber temperature set at 50°C during the UV irradiation. The spray temperature was
set at a constant value of 25°C. It is essential to use both UV irradiance and water spray
to accelerate the weathering rate of the specimens’ surfaces. This was conﬁrmed by the
work of Horn et a1. (1994) who found that changes on the surface of western red cedar
and southern pine after artiﬁcial weathering were considerably greater when irradiation
and water were used together, compared to water or irradiation only. Specimens were
removed for roughness measurement after 100, 200, 400, 800, 1600, and 2400b.
Specimens were removed for SEM imagery after 400, 800, 1600, and 2400b exposure.
5.2.2 Surface Roughness

A stylus model RC-4000 system manufactured by Hommel America was used to
evaluate and monitor the modiﬁcation of the wood surface roughness after weathering.
The roughness-measuring device consists of a main unit, a pick-up unit, and a drive unit.
The pick-up unit has a skidless-type diamond stylus with 196-micro-inch (5-micro
meters) radius and a 90 degrees tip angle. The stylus traverses the surface and its vertical
displacement is converted into an electrical signal. The signal is later ampliﬁed before it
is converted into digital information. The digital information is transmitted to the
computer and the surface roughness parameters are automatically calculated from this
information (Mummery, 1992).

The stylus travels at a speed of 0.50 mm/sec across the wood grain within a span
of 25.6 mm. The peak-to-valley maximum was set at 800 um, and an average of 5

measurements were taken from each specimen.

96

Several surface-texture parameters can be obtained from this method: R,, R2,
Rmax, Rk, Rpk, and Rvk (Kamdem and Zhang 2000; Nzokou and Kamdem 2002). R, is the
average surface roughness, and it represents the deviation from the mean peak. R, is often
used to deﬁne surface roughness, but it does not differentiate between the peaks and
valleys of a surface proﬁle (Maldas and Kamdem 1998; Nzokou and Kamdem 2002).
Rmax is the maximum of the peak-to-valley height. Ra, and Rmax were selected to
characterize the physical changes of the wood surface.
5.2.3 Weight Loss
Before weathering exposure the MC of a subset of specimens was determined by
the oven-dried method and recorded. After 2400h exposure, specimens were oven-dried
and their weight loss determined using the following equation (1).
Weight loss, % = [(Wl-W2)/W1] x 100 (1)
Where: W1 is the initial oven-dried weight (calculated by adjusting with the MC
values from the subset of specimens)
W2 is the ﬁnal oven-dried weight of the specimen (measured after oven
drying the samples).
5.2.4 SEM Observations
Samples measuring 1”xl” (length and width) were cut and mounted on aluminum
stubs with epoxy resin and oven dried at 60° C. After drying, they were kept in vacuum
desiccators to prevent moisture pick up. Immediately before the SEM observation, the
samples were sputter coated with a 35nm layer of gold to avoid charging. The SEM to be

used was a J EOL J SM 6400 located at the Center for Advanced Microscopy at MSU.

97

5.2.4 Statistical Analysis
Statistical analysis based on non-parametric one-way ANOVA was used to
compare the difference in average values of the various parameters considered between

extraction treatments at the 95% signiﬁcance level.

98

5.3 Results and Discussion
5.3.1 Surface Roughness

The changes in roughness (Ra) and maximum peak to valley (Rmax) before
weathering exposure for extracted and un-extracted samples are presented in Figures 5.1
and 5.2. Ra for red pine increased from 0.97pm to 3.911m and 4.711m following ethanol-
toluene and ethanol-toluene + water extractions respectively. Similar increases were
found for ethanol (2.8um) and ethanol + water (5.8ttm) extractions (Figure 5.1). Figure
5.1 also shows that red oak and black cherry also had higher Ra values following
extraction treatments. Similar results were obtained for Rmax for all three species (Figure
5.2). These results clearly show that the extraction process increased the roughness and
created small valleys on the surface even before specimens were exposed to artiﬁcial
weathering. Based on this observation, in order to compare the various extraction
treatments after artiﬁcial weathering, it was necessary to deﬁne new parameters that take
into account these original variations in Ra and Rmax.

Two parameters named Roughening Index (RI) and Microcracking Index (MCI)

were deﬁned according to equations 2 and 3.

R —R.
R1: “W a'

 

 

Ra, (2)
1
R max — R max .
MCI = .. ' (3)
R max i
Where: RaW is the Average roughness after artiﬁcial weathering

Ra, is the Average roughness before weathering exposure

99

Rmaxw is the maximum peak to valley after artiﬁcial weathering
Rmax, is the maximum peak to valley before weathering exposure

R1 and MCI are estimates of the change in roughness and microscopic cracking
following weathering exposure. They take into consideration the variation in initial Ra
and Rmax of the sample. The higher the R1, the higher is the roughening of the sample.
Similarly, the higher the MCI, the deeper is the cracking of the wood surface.

Average RI and MCI values for all three species and extractives treatments are
presented in Table 5.1.

For red pine, control samples had a R1 of 39 and a MCI of 17, signiﬁcantly higher
than values for all extracted specimens (RI 4-9 and MCI 2-6). This indicates that un-
extracted red pine samples exhibited rougher surfaces and developed more injurious
rrricrocracks than extracted wood samples. This result was unexpected as our hypothesis
was that the removal of extractives would lead to increased roughening in extracted
samples. For red oak and black cherry, RI and MCI for control samples were also higher
than those of extracted specimens, but the differences were not statistically signiﬁcant at
95% conﬁdence level. These results suggest that there is no statistical difference in
roughening and microcracking due to extractive removal and disproves our hypothesis.
The signiﬁcant difference in RI and MCI values between un-extracted and extracted
samples obtained in red pine could be explained by irreversible damages caused to the

wood structure by the extraction process.

100

 

 

if WET Control 7 T
10 ,. .7, E 7 i l mmEth-Tol j
Eth-Tol+Water l
I Eth l
‘ I Eth+Water

    
   

on

Average Roughness (um)
03

 

 

;/
ll 2

Re

 

O.

pine Red oak Cherry

 

Figure 5.1: Change in surface roughness (Ra) after extraction

* Bar represents the standard deviation

101

 

 

 

 

  
    

i DControl 1
9° 1 mEth-Tol l

 

80 ,, IEth-Tol+Water L2 .
1 IEth ' *
70 -- .
j IEth+Water I
60 W i 7 7 W

 

 

ill
ll“

 

 

 

 

 

 

Figure 5.2: Changes in maximum peak to valley (Rmax) after extraction

* Bar represents the standard deviation

102

 

Table 5.1: Calculated Indexes of Roughening and Microcracking after 2400h weathering

 

 

 

 

 

 

 

 

 

 

 

 

Red ine Red oak Black cherry
RI MCI RI MCI R1 MCI
Control 39.8a 17.2a 5.7a 1.6a 2.8a 1.9a
Eth-T01 8. lb 5.2b 4.3b 2.5b 0% 0%
Eth-Tol+Water 5.5b 3.2b 3.3b 1.7a 0.7b 0.6b
Eth 9.9b 6.1b 5.2a 2.2a l.lb 1.3b
Eth+Water 4.3b 2.9b 2.6b l.8a 0.6b 0.4b

 

 

 

 

The letter indicates statistical signiﬁcance at 95% conﬁdence level. Similar letter
indicates no statistical signiﬁcance compare to control. Different letters indicate that the
difference between control and the treatment was statistically signiﬁcant at 95%

conﬁdence level. Details of the statistical analysis are presented in appendixes 3 and 4.

103

5.3.2 Weight Loss

The weight loss of un-extracted and extracted specimens after artiﬁcial
weathering exposure is presented in Figure 5.3. The weight loss of red pine specimens
varied from 8.1% to 10%. Black cherry specimens had weight losses of 13.1% to 15%
and red oak had higher weight losses ranging from 16.2% to 19% (Figure 5.3). The
variation in weight loss values for all three species were well within the standard
deviation values, and there were no statistically signiﬁcant differences between un-
extracted and extracted specimens. This is further evidence that there is no difference in
physical degradation due to the removal of extractives.
5.3.3 SEM observations

A wide range of microscopic observations was conducted to visualize the physical
damages caused by the weathering process. Low magniﬁcation images of wood surfaces
after 2400h exposure are presented in Figures 5.4a-e(red pine), Figures 5.5a-e(red oak)
and Figures 5.6a-e(black cherry). There was no observable difference between the
different extractives treatments, and all surfaces displayed similar patterns of degradation
within each species. All wood surfaces showed severe erosion and degradation of wood
structures. Wood ﬁbers and tracheids were broken at several points, and there were signs
that some broken pieces of had been washed away during exposure to water spray. The
surface appeared brittle and there were large longitudinal cracks, usually along the rays.
Close observation of the cross section of a broken black cherry ﬁber showed early
degradation of pits, which are enlarged and developed radial cracks that propagated

through the cell wall (Figures 5.7a and 5.7b).

104

25°/o

20%

15%

1 0%

Weight Loss (%)

5%

0%

 

 

121 Control

1111 Eth-Tol

E Eth-ToI+Water
a Eth

I Eth+Water

...,...h
s..r:.z:

 

 

 

 

 

 

\

\ \ \\\\

\ \ \\\\

\§\~\\\\\\\\\\~\~\\\

\ 4‘ ‘ § = \
x .\ ‘

\\\
\4\\\‘
:4 =\

:z::=:::\
.......
.3,....

Red Oak
Wood Species

 

 

5.11,;232
IIIIIIIII
;;/:;

...
::::
“.“.

\\»4

“\\4 4\~\

\\\\\\ 44“

\ 44

\»‘\‘-\\\‘\\\4\\44
‘\‘\\\\\\\~4\\44\44
\\\\ss\\\\\\s\\s\\s\\
\~\\\\\\\\\\\\\s\\s\\

44“
s“
\\

.\»\\-\~‘\-\\~4~

\\\\\\\s\\\\\\

“4

\ “\
\

 

 

Figure 5.3: Weight loss of wood samples after 2400b exposure to artiﬁcial weathering

* Bar represents the standard deviation

105

 

Figure 5.4a: Un-extracted
red pine after 2400b
exposure to artificial
weathering

 

 

 

 

Figure 5.4b: Ethanol-
Toluene extracted red pine
surface after 2400b
exposure to artificial
weatherino

 

 

 

 

Figure 5.4c: Ethanol-
Toluene + Water extracted
red pine surface after 2400h
exposure to artificial
weatherino

 

 

 

 

 

 

107

 

 

Figure 5.4d: Ethanol extracted
red pine surface after 2400h
exposure to artificial
weathering

 

 

 

Figure 5.4a: Ethanol + Water
extracted red pine surface after
2400h exposure to artificial
weathering

 

 

 

 

108

 

 

Figure 5.5a: SEM image
of un-extracted red oak
surface after 2400h
exposure to artificial
weathering

 

 

 

Figure 5.5b : SEM image
of Ethanol-Toluene
extracted red oak surface
after 2400h exposure to
artificial weathering

 

 

 

Figure 5.5c : SEM image
of Ethanol-Toluene +
Water extracted red oak
surface after 2400h
exposure to artificial

 

 

 

 

 

 

109

 

 

Figure 5.5d: SEM image
of Ethanol extracted red
oak wood surfaces after
artificial weathering

 

 

 

Figure 5.59: SEM image
of Ethanol + Water
extracted red oak wood
surface after artificial
weathering

 

 

 

 

Figure 5.6a: Un-extracted
black cherry surface after
2400h exposure to artiﬁcial
weathering

 

 

 

 

Figure 5.6b: Ethanol-
Toluene extracted black
cherry surface after 2400b
exposure to artificial
weatherino

 

 

 

 

Figure 5.6c: Ethanol-
Toiuene + Water extracted
black cherry surface after
2400b exposure to artificial
weatherino

 

 

 

 

110

 

 

111

 

 

Figure 5.6d: Ethanol
extracted black cherry
surface after 2400h
exposure to artificial

 

 

 

 

Figure 5.6a: Ethanol + Water
extracted black cherry surface
after 2400h exposure to
artificial weathering

 

 

 

112

 

 

Figure 5.7a: Ethanol-Toluene
extracted black cherry surface
after 400h exposure to artificial
weathering

 

 

 

Figure 5.7b: Ethanol-Toluene
extracted black cherry surface
after 2400b exposure to artificial
weathering

 

 

 

The radial cracks have been reported to be consequences of stresses that develop
in the pit chambers during drying and wetting (Turkulin and Sell 1997; Sandberg 1999).
In red oak and black cherry, rays were enlarged, and exhibited deformations and
delamination. This was expected as it has been previously reported that rays tissues are
tender and porous and susceptible to deteriorate quickly when exposed to adverse
conditions (Minuitti 1970; Turkulin and Sell 1997). Similarly, the larger cracks in red
pine can be associated with resin canals, rays and ring boundaries (Borgin 1971; Turkulin
and Sell 1997). The extent of degradation appears to be much more severe in red oak and
black cherry than that in red pine. This can be explained by the structure and density of
red pine, red oak and black cherry. It has been reported that the overall performance of
exterior wood structures is heavily affected by its water uptake (Turkulin and Sell 1997).
Consequently red oak and cherry, which are porous and multiseriate woods, have more
conducting tissues than red pine where water conduction occurs by tracheids.

5.4 Conclusion

The inﬂuence of wood extractives on the physical degradation of hardwood and
softwood surfaces exposed to artiﬁcial weathering was investigated in this project.

As expected, the Average Roughness (Ra) and the Maximum Peak to Valley
(Rmax) increased with time of exposure to artiﬁcial weathering. However evaluation of
the difference between the various extraction treatments through a roughening index (RI)
and a Microcracking index (MCI) showed no statistically signiﬁcant variation between
un-extracted and extracted samples. Measurements of the weight loss due to artiﬁcial

weathering also showed no signiﬁcant difference between extractive treatments, but

113

weight loss values for the softwood (red pine) were lower than those of hardwood
species.

SEM observations revealed multiple breaking, brittleness, cracking, loosening and
erosion of wood structures, however there were no observable differences between
extraction types.

These results suggest no speciﬁc inﬂuence of wood extractives on the roughening,
weight loss, and microscopic degradation of red pine, red oak, and black cherry following

exposure to artiﬁcial weathering.

114

References

Ajuong, Elijah-M. A., AND C. M. Breese 1998. The Roles of Extractives on Short
Term Creep in Compression Parallel to Grain of Pai wood (Afzelia africana
Smith). Wood and Fiber Science 29(2): 161-170.

Borgin, K. 1971. The Mechanism of Breakdown of the Structure of Wood due to
Environmental Factors. Journal of the Institute of Wood Science 5(4): 26-30

Browne, F. L. 1960. Wood Siding Left to Weather Naturally. Southern Lumberman
201(2513): 141-143.

Chen Y., and Chong E. T., 1994. Determining the effect of extractives on moisture
movement using a continuous measuring system. Wood and Fiber Science 26(3):
390-396.

Flaete, P. O., Hoibo, O. A., Fjaertoft, F., and Nilsen, T. N. 2000. Crack formation in
unﬁsnished siding of aspen (Populus tremula L.) and Norway spruce (Picea abies
(L) Karst.) during accelerated weathering. Holz Als Rob-Und Werkstoff 58(3):
135-139.

Feist, W. C. 1982. Weathering of wood in structural uses. In “Structural Use of Wood in

Adverse Environments” (R. W. Meyer and R. M. Kellogg, eds.), pp. 156-178.
Society for Wood Science and Technology, University of British Columbia.

Feist, W. C., and Hon, D. N. S. 1984. Chemistry of Weathering and Protection. In “The
Chemistry of Solid Wood” (R. Rowell, ed.), pp. 401-451. American Chemical
Society, Washington DC.

Gaby, L. I. 1963. Surface checking of white oak as related to mechanical processing.
Forest Products Journal 13(12): 529-532.

Horn, B. A., Qiu, J. 1., Owen N. L., and Feist, W. C., 1994. FTIR studies of
weathering effects in western red cedar and southern pine. Applied Spectroscopy
48(6): 662-668.

Kamdem, D. P. 1994. Fungal decay resistance of aspen blocks treated with heartwood
extracts. Forest Products Journal 44 ( 1): 30-32.

Kamdem, D. P., and Zhang J. 2000. Characterization of checks and cracks on the surface
of weathered wood. Paper presented at the International Research Group on
Wood Preservation (IRG) Kona, Hawii, 14-19 May 2000.

Maldas, D. C., & Kamdem, D. P. 1998. Surface tension and wettability of CCA treated
red maple. Wood and Fiber Science 30 (4), 368-373.

115

Miniutti, V. P. 1970. Reﬂected Light Scanning Electron Microscopy of Ultra-Violet
Irradiated redwood Surfaces. Microscopy 18:61-72

Mummery, L. 1992. Surface Texture Analysis: The Handbook. Hommelwerke GmbH,
Muhlhausen, Germany. 106pp

Nzokou, P. and Kamdem, D. P. 2002. Weathering of two hardwood species: African
padauk: Pterocarpus soyauxii, and Red maple: Acer rubrum. Journal of Tropical
Forest Products 8(2): 1-10.

Nzokou, P. and Kamdem D. P. 2003. Fungal Decay Resistance of Non-Durable Aspen Wood
Treated with Extractives from African Padauk (Pterocarpus soyauxii). Journal of
Tropical Forest Products 9(1&2): 125-133.

Reyes-Chilpa R., F. Gomez-Garibay, G. Moreno-Torres, G. Jimenez-Estrada and R. I.
Quiroz-Vasquez 1998. Flavonoids and isofavonoids with antifungal properties
from Platymiscium yucatanum heartwood. Holzforchung 52(5): 459-462.

Rudman, P. 1963. The causes of natural durability in timber: Part IX. The antifungal
activity of heartwood extractives in a wood substrate. Holzforschung 16(3): 74-
77.

Sandberg, D. (1999). “Weathering of radial and tangential wood surfaces of pine and
spruce.” Holzforschung 53(4): 355-364.

Schultz T. P, W. B. Harms, T. H. Fisher, K. D. Minn. and D. D. Nicholas 1995.
Durability of angiosperm heartwood- The importance of extractives.
Holzforchung 49(1): 29-34.

Sell, J. and W. C. Feist. 1986. Role of density in the erosion of wood during weathering.
Forest Products Journal 36(3): 57-60.

Thevenon, M. F ., C. Roussel, and J. P. Haluk. 2001. Possible durability transfer from non
durable wood species. The study case of teak wood. Paper presented at the
International Research Group on Wood Preservation (IRG) Nara, Japan, 20-25
May, 2001.

Turkulin, H. and J. Sell 1997. Structural Fractographic Study on Weathered Wood: An
Application of the FE SEM Microscopy to the “Thin Strip” Method. Forschungs-
und Arbeitsbericht 115/36. 45pp

Waterman M. A., 1946. The effect of water-soluble extractives from the heartwood of

tropical American woods on the growth of two wood decay fungi. Tropical
Woods 88: 1-11.

116

Chapter 6

The Inﬂuence of Wood Extractives on the Photo-discoloration of Wood
Surfaces Exposed to Artificial Weathering

Abstract

Extracted and un-extracted black cherry (Prunus serotina), red oak (Quercus
rubra), and red pine (Pinus resinosa) wood specimens were exposed to artiﬁcial
weathering and their discoloration process investigated to obtain basic understanding on
the role of wood extractives in the weathering of hardwoods and softwoods. Color
measurements were made using a spectrometer according to ISO 2470 standards using
the CIELAB system.

Results obtained showed that the rate of whiteness was not signiﬁcantly affected
by extractives removed with organic solvents, but were signiﬁcantly affected when
organic solvent extraction was followed by water extraction. The total discoloration rate
had the same pattern, and Chromaticity coordinates were less affected by wood
extractives. These results conﬁrm the hypothesis that some extractives contained in wood
act as anti-oxidants and are able to provide some protection to wood surfaces against
weathering degradation.

However, more work is needed to understand the chemistry and mechanism of

action of these extractives in order to develop any practical use for this property.

117

6.1 Introduction

The term photodegradation refers to the photochemical deterioration wood
surfaces exposed to light (Feist and Hon 1984). When wood is exposed outdoors, a
complex combination of chemical, mechanical, and light energy factors contribute to
what is described as weathering. The weathering of wood depends on many
environmental factors such as solar radiation, (ultraviolet, visible, and infrared), moisture
(dew, rain, snow, and humidity), temperature, oxygen and air pollutants, and it is well
accepted that the ultraviolet portion of the electromagnetic spectrum of sunlight is
responsible for the primary photochemical process (Hon 1991)

Wood is an excellent light absorber. It is capable of absorbing several different
wavelengths of electromagnetic radiation to initiate photochemical reactions leading to
wood discoloration. The wood polymer blend contains cellulose, hemicellulose, lignin,
and extractives. These wood components contain internal chemical labile entities such as
carbonyl, carboxyl, aldehyde, phenolic hydroxyl, unsaturated double bonds, and external
entities such as waxes, fats, and metal ions. All the chemical constituents of wood
(cellulose, hemicellulose, lignin, and extractives) are sensitive to ultraviolet radiation.

According to Kuo and Hu (1991), lignin contributes 80-95%, carbohydrates 5-
20%, and extractives about 2% to the total UV absorption of wood. Hon and Chang
(1984) reported that after 40 days exposure to UV, the lignin content of southern pine
wood samples was reduced from 28% to 14.5%. Infrared studies revealed that, during UV
irradiation of wood, absorption due to carbonyl groups at 1720 cm'1 and 1735 cm'1
increased, whereas the absorption for lignin at 1265 cm'1 and 1510 cm'1 gradually

decreased. The increment of carbonyl groups was the result of oxidation of cellulose and

118

lignin, and the reduction in the amount of lignin was due to its degradation by light (Feist
and Hon 1984).

Cellulose absorbs little UV radiation in terrestrial sunlight and hemicellulose has
an absorption pattern similar to that of cellulose (Kalnins and Tarkow 1966; Kuo and Hu
1991). An increase in cellulose content of the weathered wood surface has been reported
(Feist and Hon 1984). Data on white pine wood weathered outdoors for 20 years showed
that weathering degraded and solubilized lignin, and cellulose appeared to be affected
considerably less, except for the top surface layer of the wood. Similar results were
obtained with wood exposed on a test fence for 30 years. On those specimens, the top
gray layer consistently exhibited very low lignin content, while the brown layer
immediately under the outer gray layer had lignin content 40 to 60% more than the level
found for fresh unexposed wood (Feist and Hon 1984).

The role of extractives is not well deﬁned. However, Kalnins and Tarkow (1966)
suggested that they possibly act as antioxidants exerting protective effects on
photodegradation. It has been reported that extractives are the cause of wood color, and
have a plasticizing effect in wood. Substances such as ﬂavonoids, lignans, and tannins are
polyphenolic substances with the natural tendency to greasiness (Ajuong and Breese
1998). They can act as antioxidants capable of protecting wood surface against
photooxidation (Maldas and Kamdem 1999). Hon and Minemura (2000) reported that
many woods absorb light beyond 500nm due to the presence of phenolic substances such
as ﬂavonoids, stilbene, lignan, tannin and quinone. In addition, the intrinsic and extrinsic
color of wood is reported to possess functional chromophoric groups such as phenoxyl

hydroxyl groups, double bonds, carbonyl groups, etc., which absorb light and control the

119

course of photoreactions by acting as donors or acceptors in the energy transfer processes
(Hon and Feist 1992).

The discoloration of wood during exposure to weathering is somehow correlated
to the type and content of extractives. Our expectation is that extracted wood samples
will be more prone to discoloration and roughening after weathering compared to un-
extracted wood samples due to the loss or reduction of its antioxidant protection.

The aim of the project is to investigate the inﬂuence of wood extractives on the
discoloration of wood surfaces exposed to artiﬁcial weathering.

6.2 Material and Methods
6.2.1 Materials

Samples were selected, prepared and extracted according to methods presented in
Chapter 3, sections 3.2.1 and 3.2.2.

6.2.2 Artificial weathering test

Artiﬁcial weathering was conducted as described in Chapter 5, Section 5.2.1.

Specimens were removed for color measurement after 2h, 6h, 12h, and 24h during
the ﬁrst 24hours, then at 48, 96, 200, 400, 800, 1600, and 2400h. Special attention was
made to always remove the sample for color measurement at 1h and 55m into the UV
exposure cycle to ensure similar moisture and temperature conditions for the specimens.
6.2.3 Color measurement

The surface color of wood was determined according to ISO 2470 Standard using
a Microﬂash model 200 Reﬂectometer from DataColor. The color in the CIELAB system
is characterized by three parameters, L’, a‘, and b‘ (Figure 6.1). The L. axis represents

the lightness, a' and b. are the Chromaticity coordinates. In the CIELAB coordinates, +a‘

120

is for the red, at for green, +b‘ for yellow, -b* for blue, and L‘ varies from 100 (white) to
zero (black). L‘, a‘ and b‘ color coordinates of each group of samples were measured
after exposure to UV irradiation. These values were then used to calculate the color

change AE' as a function of the UV-irradiation duration according to equations 1, 2, 3

and 4.
AE=4-u a)
Aa‘ = a; —a: (2)
AH=5-M (»

 

AE' = x/AL'Z + M2 + Ab‘2 (4)

Where, AL", Aa‘ and Ab* are the change between the initial (i) and the ﬁnal (f) values.
L’, a' and b' contribute to the color change AE*. A low AE* corresponds to a low color
change or a stable color.
6.2.4 Statistical Analysis

Statistical analysis using F—test on a generalized linear model (GLM) on SAS
version 8.0 (SAS Institute 2000) was used to test the effect of extraction treatments on the
discoloration property of wood surface. The GLM procedure uses the least square to ﬁt
general linear model. The contrast procedure was used to compare control and the various

extraction treatments.

121

 

CIE 1976 L*, a“, 15*
(CIELAB)

 

 

 

 

 

 

 

 

Figure 6.1 Color L*, a*, b* of solid in the CIELAB system (CIE 1976)

122

 

6.3 Results and Discussion
6.3.1 Changes in lightness (L*)

The lightness values for red pine, red oak, and black cherry during the weathering
process are presented in Table 1. The initial L* value for un-extracted red pine specimens
was 85. Extraction with organic solvents (ethanol or ethanol-toluene) did not induce any
signiﬁcant change in L* values, measured at 85.95 and 86.6 respectively. However when
organic solvent extractions were followed by water extraction, the L* values were
signiﬁcantly lower, measured at 81.4 for Eth-T01 + Water and 81.06 for Eth +Water,
indicating that subsequent extraction with water induced some darkening of the wood
surface. Similar trends were observed in red oak and black cherry. The initial lightness
values of red pine samples (80-85) were higher than those of red oak (68-72) and black
cherry (58-64). This trend is expected because the wood surface of red pine is noticeably
lighter than that of red oak and black cherry.

The lightness values for all three species and all extraction types decreased during
the ﬁrst 48h and increased afterwards to values comparable or higher than the initial L*
values (Table 6.1). Weathering generally induces a rapid darkening of wood surfaces due
to the degradation of lignin and extractives into quinones (darker in color), which are
progressively washed out leaving the cellulose rich wood surface lighter in color as the
process progresses (Feist and Hon 1984; Nzokou and Kamdem 2002). After 2400b
exposure to artiﬁcial weathering, all three wood species had similar lightness values (83-

90), indicating that their ﬁnal whitish colors were of the same intensities.

123

Table 6.1: Lightness of wood specimens after artificial weathering (Average of 6 samples,

and 3 measurement for each sample)

 

Red Pine Lightness After Artificial Weathering

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0 12h 24h 48h 100h 200h 400h 800h 1600 2400b
[Control 85.1 71.0 69.8 69.8 72.2 75.2 79.3 83.3 86.8 88.9
[Eth-T01 85.9 70.6 68.3 69.9 73.5 76.8 81.7 85.2 88.5 89.9
[Eth-Tol-t-Water 81.4 72.2 72.2 71.4 73 .6 74.8 80.6 84.2 87 .5 89.4
[Eth 86.7 71.4 69.3 70.2 73.7 78.1 82.1 85.8 88.9 90.4
IEth+Water 81.1 66.5 65.1 66.2 69.8 74.4 81.2 84.4 87.9 89.8
Water 79.5 67.3 65.2 67.9 69.1 73.9 79.5 84.7 87.5 89.8

Red Oak Lightness After Artificial Weathering

0 12h 24h 4811 won 200h 400h 800h 1600 2400b
Control 72.0 64.9 64.9 64.6 67.7 72.1 76.9 80.7 86.4 87.2
[Eth-T01 73.4 67.7 67.5 67.8 70.6 73.3 77.8 82.8 86.4 88.1
[Eth-TOHWater 70.6 67.9 68.5 69.1 70.9 74.6 79.6 83.6 87.2 88.1
[Eth 73.9 68.5 68.1 68.2 69.9 72.9 77.4 81.6 85.8 87.2
IEth+Water 68.4 66.6 67.1 67.8 70.8 74.2 77.8 82.2 85.6 87.4
Water 65.0 64.3 65.7 66.8 69.6 73.4 77.9 82.7 86.5 87.6

Black Cherry Li htness After Artificial Weathering

0 12h 24h 48b 10% 200h 400h 800h 1600 2400b
[Control 64.8 57.3 56.9 56.5 59.8 65.1 70.2 75.5 80.5 83.5
[Eth-T01 67.9 57.0 56.8 56.7 60.3 65.9 70.4 75.4 81.7 84.9
IEth-Tol+Water 58.3 47.5 49.1 52.1 60.1 68.1 76.1 81.5 85.5 87.2
[Eth 69.9 53.9 55.1 58.7 65.1 71.9 78.8 82.9 86.7 88.3
th+Water 58.7 46.7 48.7 53.9 60.8 67.9 76.8 82.6 86.5 87.0
Water 56.2 47.4 49.5 52.9 61.9 70.0 77.3 81.7 85.6 87.6

 

 

 

 

 

Note: SAS “General Linear Model” analysis showed that the differences between
treatments were not due to chance. The SAS “Contrast” procedure showed no signiﬁcant
differences between Control and extraction treatment for lightness over exposure time.

The detail of the statistical output is presented in appendix 5.

124

 

Table 6.2: Lowering index of whiteness for red pine, red oak and black cherry after
artificial weathering

 

Lowering Index of Whiteness (AL/L%) for Red Oak After Artificial Weathering_

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0 12h 24h 48h 100h 200h 400h 800h 1600 2400b
Control 0.00 -9.9 -9.8 - 10.2 -6.0 0.1 6.9 12.1 20.0 21.0
Eth-T01 0.00 -7.9 -8.1 -7.6 -3.9 -0.3 5.9 12.8 17.7 19.9
Eth-Tol+Water 0.00 -3.8 -2.9 -2.1 0.6 5.8 12.7 18.4 23.5 24.8
Eth 0.00 -7.3 -7.9 -7.8 -5.4 -1.3 4.8 10.4 16.0 17.9
Eth+Water 0.00 -2.7 - l .9 -0.9 3.5 8.5 13.7 20.2 25.2 27.8
Water 0.00 -l.1 1.0 2.8 7.0 12.9 19.9 27.2 33.1 34.8

 

 

Lowering Index of Whiteness (AL/L%) for Red Pine After Artificial Weathering_

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0 12h 24h 48h 100h 200h 400h 800h 1600 2400b
Control 0.00 -16.5 -17.91 -17 .9 -15.1 -1 1.6 -6.8 -2.1 2.0 4.6
Eth-T01 0.00 -17.9 -20.50 -l8.7 -14.5 -lO.6 -4.9 -0.9 3.0 4.6
Eth-Tol+Water 0.00 -11.4 -11.29 -12.3 -9.6 -8.1 -0.9 3.4 7.5 9.8
Eth 0.00 -17.6 -l9.99 -19.0 -14.9 -9.9 -5.3 -0.9 2.5 4.3
Eth+Water 0.00 -l7.9 -19.72 -18.3 -13.9 -8.2 0.2 4.1 8.4 10.8
Water 0.00 -9.3 -l7.94 -l4.6 -13.l -7.0 -0.1 6.6 10.1 12.9
LowerinLIndex of Whiteness (AL/L%) for Black Cherry After Artificial Weathering
0 12h 24h 48h 100h 200h 400h 800h 1600 2400b
IControl 0.00 -1 1.6 -12.2 -l2.8 -7.7 0.6 8.4 16.5 24.3 28.9
Eth-T01 0.00 -16.0 -16.3 -16.5 -1 1.1 -2.9 3.7 11.1 20.4 25.2
Eth-Tol+Water 0.00 -18.5 -15.9 -10.6 3.1 16.7 30.6 39.8 46.8 49.6
Eth 0.00 -22.9 -21.2 -l6.1 -6.9 2.8 12.6 18.5 23.9 26.2
Eth+Water 0.00 -20.5 - 17.2 -8.1 3.5 15.7 30.8 40.6 47.3 48.1
Water 0.00 -15.6 -1 1.9 -5.9 10.3 24.7 37.7 45.4 52.4 55.9

 

 

 

 

 

 

 

 

 

 

Note: SAS “General Linear Model” analysis showed that the differences between
treatments were not due to chance. The SAS “Contrast” procedure showed signiﬁcant
differences between Control and Eth-Tol+Water, Control and Eth+Water, and Control
and Water for all three species. The detail of the statistical output is presented in

appendix 6.

125

To compare the different extraction types, the measured lightness values were
used to calculate the “Lowering Rate of Whiteness” (LIW) estimated by dividing the
difference in lightness after irradiation by the original lightness before the weathering
procedure (equation 5) (Hon 1991). An increase in the LIW indicates lightening, a
decrease in the LIW indicates darkening.

L — L,
’L (5)

i

 

LIW =

Where: LflS the lightness after weathering exposure,
L, is the lightness before weathering exposure.

The Lowering Index of Whiteness data presented in Table 6.2 show that control
specimens had similar indexes of whiteness with eth-to] and eth extractions across the
range of weathering exposure time. However, the LIW values were consistently higher
for Ethanol-Toluene + Water and Ethanol + Water extractions, indicating that further
extraction with water after organic solvent extraction increased the rate of whiteness for
all three species. Statistical analysis (General Linear Model on SAS version 8) of the
LIW values revealed no signiﬁcant difference between control specimens, Ethanol-
Toluene, and Ethanol specimens. However the differences were statistically signiﬁcant
with 95% conﬁdence between control specimens and samples extracted with the above
organic solvents and further extracted with water.

6.3.2 Chromaticity Coordinates

The Chromaticity coordinates a* and b* over the weathering period for the three
species are presented in Tables 6.3 and 6.4. As for lightness, observation of the values of
a* at time 0 (initial a*) reveals that extraction with solvent systems that include water

(Eth-T01 + Water and Eth + Water) resulted in higher a* (5.21 and 5.15) compared to

126

control samples (3.89), which had similar values to those of solvent only extracted
samples (Eth-T01 and Eth). The same phenomenon was observed for the initial b* values,
and similar trends were found in black cherry. There was no signiﬁcant difference in
initial Chromaticity coordinated for red oak specimens.

Red oak and black cherry had higher initial a* values (redder) than red pine, and
their ﬁnal a* values after 2400h artiﬁcial weathering were slightly lower, indicating that
they were slightly bluer than red pine.

The change in Chromaticity coordinates Aa* and Ab* (Figure 6-2 and 6-3) shows
an increase during the ﬁrst 100 hours and a decrease afterwards for all three species and
extraction treatments. This is due to the sample surface becoming reddish and yellowish
during the ﬁrst phase of the weathering process, and progressively greenish and bluish
with extended exposure to artiﬁcial weathering. Similar trends were observed for red oak
and black cherry. It is important to note that the initial color parameters for the three
wood species were quite different.

Chromaticity coordinates a* and b* were plotted in pairwise plots to evaluate the
direction of the color change. For red pine (Figure 6.4), the ﬁgure shows a clear two
phases process. During the ﬁrst phase, the specimens are becoming increasingly reddish
and yellowish. This is followed by a second phase where the samples are changing
towards green and blue. In red oak (Figure 6.5) and black cherry (Figure 6.6), the ﬁrst
phase is absent, and the samples just changed to a more bluish-green color. There is no

noticeable difference between the various extraction treatments.

127

Table 6.3: Chromaticity coordinate a* of wood specimens after artiﬁcial weathering

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Red Pine Chromatici Coordinate (a* After Artificial Weathering

0 1211 2411 4811 100h 200h 400h 80011 1600 240011
[Control 3.9 8.1 8.9 8.9 9.1 8.2 5.9 4.2 2.3 1.4
[Eth-Tot 3.9 7.5 8.3 8.5 8.6 7.6 5.2 3.5 1.8 1.0
[Eth-ToI+Water 5.2 8.5 10.0 10.2 10.3 9.1 5.4 3.5 1.9 1.1
[Eth 3.5 7.3 8.2 8.3 8.3 7.4 5.1 3.2 1.5 0.8
IEth+Water 5.2 7.5 8.4 8.5 8.5 7.4 4.9 3.4 1.7 0.9

Red Oak Chromatici Coordinate (a*) After Artificial Weather'mg

0 1211 2411 48h 100h 20011 40011 800h 1600 240011
[Control 9.3 10.1 9.5 7.4 4.8 2.3 0.6 0.01 -01 -0.1
[Eth-Tot 7.9 8.7 8.1 6.6 4.3 1.8 0.6 0.1 -0.1 -0.1
[Eth-ToHWater 8.6 8.4 7.9 6.5 3.7 1.7 0.6 0.1 -0.0 -01
[Eth 7.9 8.8 8.6 7.2 4.7 2.0 0.5 0.01 -01 -01
IEth+Water- 9.8 8.9 8.21 6.8 4.4 2.0 0.5 0.1 -01 -0.1
Black Cherry Chromaticity Coordinate (a*) After Artificial Weathering

o 1211 2411 48h 10011 200h 400h soon 1600 240011
[Control 10.6 14.2 13.7 10.8 6.8 2.7 0.9 0.4 0.1 0.01
[Eth-T01 10.7 14.5 13.6 11.2 9.9 6.4 1.9 0.5 0.1 0.01
[Eth-ToI+Wate 15.7 12.7 12.9 11.2 8.8 5.3 2.7 1.6 0.7 0.3
[Eth 10.8 10.0 10.3 8.7 6.4 3.9 2.2 1.2 0.5 0.2
[Eth+Water- 18.7 1 1.2 1 1.5 10.0 7.4 4.3 2.3 1.3 0.5 -00

 

 

 

 

 

 

 

 

 

 

 

128

 

,—_ _ . _ _- ___—____ ~__.— ._— —___——_ _ __

 

 

 

 

 

 

 

 

 

 

 

 

—0—Control (a) __ T7 —7 —

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6 Figure 6-2 (a): Red pine +Eth-TOI (a) ——
; 4 ”7 - a -Eth-Tol+W (a) ‘_ _‘
I —---—Water (b)
2 ‘ ”8.x. —111—Eth (a)
.1 o ' - - -o—Eth+w (a)
I < -2 i ’ \EX
‘ o 500 1000 1500 2000
Exposure tlme (hours)
2 —-o—Control (a) }———

 

 
  
 
 

 

 

 

 

 

+Eth-Tol (a) L.—

- A -Eth-Tol+W (a)

 

 

—O—Eth+W (a)

Water (a) '“
-9K—Eth (a) w

 

 

 

 

 

 

 

 

 

 

 

-3.__.
-10 2,
-12 r . . .
0 500 1 000 1500 2000
Exposure time (hours)

 

2500

 

 

 

 

 

 

—0—Control (a)

‘ Figure 6-2 (c) Black cherry H +Eth'T0' (a)

- a -Eth-Tol+W (b)

 

-->(-—Water (b)
—)It—Eth (a)

 

 

 

 

1000

 

—O—Eth+W (11)

 

 

 

 

 

1500 2000

Exposure tlme (hours)

 

 

 

Figure 6-2: Change in chromaticity coordinate a (Aa*) over the exposure time.

Note: Letters in parenthesis in the legend indicate statistical signiﬁcance compared to control.

Similar letter mean no statistical difference with control. Different letters mean statistical

signiﬁcant 95% conﬁdence level. Details of the statistical analysis are presented in appendix 7.

129

Table 6.4: Chromaticity coordinate b* of wood specimens after artificial weathering

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Red Pine Chromaticity Coordinate (b*) After Artificial Weathering_

0 1211 2411 4811 10011 20011 40011 80011 1600 240011
[Control 21.5 30.9 31.2 29.6 25.2 20.2 13.7 10.2 6.6 4.1
[Eth-To] 19.9 29.3 29.3 27.6 23.3 17.9 12.1 8.2 5.5 3.8
[Eth-Tol+Water 22.0 32.0 33.5 31.3 27.2 21.4 11.5 8.2 5.5 3.6
[Eth 19.3 29.3 29.4 27.2 23.1 17.2 11.9 8.1 5.4 3.6
[Eth+Water 22.6 27.0 27.8 26.6 22.7 17.5 10.2 7.4 6.0 3.9

Red Oak Chromaticity Coordinate (b*) After Artificial WeatherinL

0 1211 2411 4811 10011 20011 40011 80011 1600 240011

Control 19.6 25.8 24.1 19.1 12.8 7.3 3.9 3.1 2.1 2.5
[Eth-To] 19.3 24.2 22.6 18.3 12.0 6.6 4.0 2.8 2.7 2.3
[Eth-Tol-l-Water193 23.8 22.3 18.0 10.9 6.3 3.9 2.9 2.4 2.6
[Eth 19.4 24.8 23.7 19.7 12.9 7.0 3.7 2.6 2.2 2.4
[Eth+Water 21.8 24.5 22.9 19.0 12.2 6.6 3.7 2.6 2.7 2.5
[Black Cher Chromaticity Coordinate (b*) After Artificial Weatherin

0 1211 2411 4811 10011 20011 40011 80011 1600 240011

[Control 19.6 26.3 25.6 21.1 13.9 6.5 3.5 2.0 1.8 2.3
[Eth-Tol 19.9 25.8 24.5 20.3 16.8 10.8 4.8 2.3 1.6 1.5
[ﬁb-ToHWater 21.6 21.3 21.9 19.4 14.6 9.1 5.5 4.6 3.6 2.6
[Eth 20.2 21.2 21.3 17.7 12.4 7.9 4.9 4.6 3.5 3.1
[Eth+Water 22.2 18.7 19.3 17.5 12.6 7.5 4.8 4.1 3.8 2.6

 

 

 

 

 

 

 

 

 

 

 

 

130

 

 

 

 

 

   
   
   

 

 

 

I +Eth-Tol (a)

 

 

5 -‘—~‘——1 - A -Eth-Tol+W (a)
0 ——1—- J-Water (a)
g -5 '1 r —0—Eth+W (a)

 

 

i
J

 

 

 

 

 

 

 

 

-1o —
-15 2
-20 - -—--r--....
-25 1 1 1 T
0 500 1000 1500 2000 2500

Exposure time (hours)

-2 Figure 6-3 (a) Red pine . Control (é)“"' _l

 

 

 

 

 

 

Ii —0—Control a “W

 

 

 

. - +Eth-Tol
1o F1gure 6 3 (b) Red oak - ‘ .1 Eth-TO|+a (a)
5 [I -—-»'----Water (a)

 

0 _ , +Eth Rae,
' —O—Eth+ (a)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Exposure time (hours)

 

 

 

 

 

10 . _ —0—Control (a)
Flgure 6-3 (0) Black cherry +Eth-Tol (a)
~— - A - Eth-Tol+W (a) -- ——w—«
.23.“... Water (a)
-)K—-Eth (a)

 

 

 

 

 

 

-5 ———.— a_ —o—Eth+w (a) _-__._.

 

 

 

 

 

 

 

 

 

-25 -. —- _ _ . ﬂ ,

 

' 0 500 1000 1500 2000 2500

L Exposure tlme (hours)

0 500 1000 1500 2000 2500

 

 

 

 

 

Figure 6-3: Change in chromaticity coordinate b (Ab*) over the exposure time.

Note: Letters in parenthesis in the legend indicate statistical signiﬁcance compared to control.
Similar letter mean no statistical difference with control. Different letters mean statistical

signiﬁcant 95% conﬁdence level. Details of the statistical analysis are presented in appendix 8.

131

 

 

Yellow

 

i oControl 7
‘ Phase 1
30 .. lEth-Tol Ext _ _ ________ 7' gm;
AEth-Tol+Water d g ‘
Eth [

 

b 20 «1 oEth+Water

1o -

 

 

Blue

 

 

 

 

 

 

Figure 6.4: Relation between chromaticity coordinates a* and b* for red pine after

artiﬁcial weathering

132

 

30 I -
[ 0 Control
I Eth-Tol
A Eth-Tol+Water
. Eth g ‘

o Eth+Water [
_ -- A1116/

Phase 1

 

 

 

 

 

 

 

 

Figure 6.5: Relation between chromaticity coordinates a* and b* for red oak after

artiﬁcial weathering

133

 

 

 

  

 

 

 

 

 

 

 

 

30
Yellow
<>Control
IEth-Tol Q
20 ~~ AEth-TOHWater . _ ~ —ﬂ
. Eth ;
‘3 OEth+Water LQ)
1o —_ ~Oil _ .
0 . . . .
Blue -1 Green 4 9 3* 14 19 Red 24

 

 

 

Figure 6.6: Relation between chromaticity coordinates a* and b* for black cherry after

artiﬁcial weathering

134

6.3.3 Color Change (AB)

The overall color change (AE) values after 2400h in relation to the total
extractives removed from the wood specimens are presented in Table 6.5. For red pine
samples, the color change for un-extracted samples was 18.01. The color change value
was 16.91 for ethanol-toluene extracted samples and 16.32 (2.62% extractives) for
ethanol-extracted samples (3.32% extractives). Water extraction of red pine samples
following these solvent extractions induced higher color change; 20.51 and 21.02 for
ethanol-toluene + water (3.54% extractives) and ethanol + water respectively (4.6%
extractives). Similar trends were observed with red oak and black cherry specimens.
These are all observable and very important discolorations according to the scale
proposed by Dirckx et a1 (1992) and presented in Table 6.6. The variability between the
total amount of extractives removed and the color change suggests the quantity removed
is of less importance, and the nature and chemical composition more critical in relation to
discoloration. FT IR spectra of wood extractives reported Chapter 3 showed that
extractives removed by ethanol and ethanol-toluene were made up of fatty acids,
saturated esters and cyclic polyphenolic compounds. Water extracts were mainly made of
coloriﬁc matter, condensed tannins, and low molecular weight carbohydrates. This
explains the observed enhanced discoloration when solvent extractions were followed by
water extraction.

The total discoloration over the weathering duration is presented Table 6.7 and
Figure 6.7(a-c). The general pattern for all species and treatments show a rapid increase
during the ﬁrst 12 hours, followed by a steep decrease in AB extending to about 48 hours

of exposure. This stage is immediately followed by a continuous increase in the value of

135

AE as the sample surface becomes increasingly whiter. Visual observation of AE ﬁgures
for all three species beyond the ﬁrst 48 to 100 hours of rapid change shows a clear
separation between the control curve, the curve for solvent extracted samples (Eth-T01
and Eth), and the curves for samples extracted with solvents and water (Eth-T01 + Water,
and Eth + Water). The discoloration curves for samples extracted with water included in
the system were consistently higher than the control curves, which remained similar to
those of specimens extracted with organic solvents. Analysis of variance using the SAS
version general linear model of AE showed no statistical difference at 95% conﬁdence
level between control, Eth-T01 and Eth. However, there was signiﬁcant difference
between the above treatments and Eth-T01 + Water and Eth + Water. These lower rates of
discoloration for control and solvent extracted samples can only be explained by some
level of weathering protection provided by extractives contained in control samples and
not removed by organic solvents. Such extractives, which could be polyphenolic water
extractable compounds were removed when water extraction was included in the system.
These effects were less marked in red oak where there was no statistical difference
between control, Eth-T01, Eth, Eth-Tol+Water, and the Eth + Water was the only group
signiﬁcantly different from the other treatments.

Wood weathering is caused by the absorption of light energy by active wood
components, which bring them to an excited triplet state that transfers the energy to
triplet ground state oxygen molecules to create singlet oxygen (Feist and Hon 1984).
These radicals rapidly interact with oxygen to produce hydroperoxide impurities that are
decomposed easily to produce chromophoric groups such as carbonyl and carboxyl

groups (Feist and Hon 1984). Free radical chain reactions in the presence of oxygen and

136

light are responsible for the discoloration and deterioration of wood surfaces. Results
obtained in this project suggest that the presence of extractives slow this process, with
polyphenolic water extractives acting as anti-oxidant protecting the wood surface against

photodegradation.

137

Table 6.5: Extractives removed and color change after artificial weathering

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Red Pine

Extractives % AE
Control 0 18.01
Eth-Tol 2.67 16.91
Eth-Tol+Water 3.54 20.5 1
Eth 3.32 16.32
Eth+Water 4.6 21.02
Water 1.8 24.12

Red Oak

Extractives % AE
lControl 0 24.73
Eth-Tol 2.03 23.78
Eth-Tol-I-Water 2.76 25 .7 l
Eth 1.59 23.04
Eth+Water 4.07 28.84
Water 3.44 30.44

Black Cherry

Extractives % AE
Control 0 27.63
Eth-Tol 2.02 27.30
Eth-Tol+Water 3.1 37.90
Eth 3.21 27.18
Eth+Water 4.79 39.16
Water 3.46 41.44

 

138

Table 6.6: Correspondence between AE and visual observation in the CIELAB
system (Dirckx et al. 1992)

 

 

 

 

 

 

 

 

 

 

 

Visual change AE
Trace 0-O.5
Light 0.5-1.5
Noticeable 1 .5 -3
Considerable 3-6
Important 6-12
Very Important > 12

 

 

139

Table 6.7: Color change after artiﬁcial weathering

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Color Change (AE) of Red Pine After Artiﬁcial Weathering

0 12 24 48 100 200 400 800 1600 2400
Control 0.00 17.44 18.76 18.03 14.37 10.87 9.91 11.42 15.08 18.01
Eth-Tol 0.00 18.32 20.41 18.37 13.71 10.04 9.05 1 1.74 14.86 16.91
Eth-Tol+WateH 0.00 14.02 15.45 14.52 10.64 7.72 10.53 14.20 17.88 20.51
Eth 0.00 18.71 20.62 18.89 14.32 9.67 8.84 11.16 14.20 16.32
Eth + Water 0.00 15.38 17.12 15.76 11.75 8.66 12.37 15.60 18.24 21.02
Water 0.00 13.25 15.17 12.06 11.26 9.82 12.87 19.19 21.09 24.12

Color Chan e (AE) of Red Oak After Artiﬁcial Weathering
0 12 24 48 100 200 400 800 1600 2400
iControl 0.00 9.43 8.37 7.59 9.26 14.14 18.59 20.83 24.51 24.73
Eth-T01 0.00 7.62 6.82 5.83 8.59 14.05 17.48 20.50 22.55 23.78
Eth-Tol+Water 0.00 5.24 3.75 2.87 9.70 15.21 19.48 22.56 25.18 25.71
Eth 0.00 7.69 7.27 5.79 8.23 13.76 17.77 20.06 22.36 23.04
Eth + Water 0.00 3.40 2.36 4.11 11.26 18.01 22.39 25.56 27.54 28.84
Water 0.00 3.61 2.67 4.41 l 1.76 17.64 22.63 26.72 29.66 20.44

Color Change (AE) of Black Cherry After Artiﬁcial Weatherin

0 12 24 48 100 200 400 800 1600 2400
Control 0.00 10.66 10.41 8.41 8.52 15.32 19.54 22.99 25.96 27.63
Eth-T01 0.00 12.92 12.35 11.18 8.15 10.23 17.65 21.67 25.26 27 .30
Eth-Tol+Water 0.00 11.19 9.65 7.97 10.06 18.94 27.33 32.03 36.00 37.90
Eth 0.00 16.12 14.89 11.71 10.13 14.22 19.64 22.37 25.79 27.18
Eth + Water 0.00 14.58 12.68 10.92 15.00 22.57 30.01 34.67 37.97 39.16
Water 0.00 12.34 9.30 10.10 16.06 24.97 32.03 35.90 39.51 41.44

 

 

 

Note: SAS “General Linear Model” analysis showed that the differences between
treatments were not due to chance. The SAS “Contrast” procedure showed signiﬁcant
differences between Control and Eth-Tol+Water, Control and Eth+Water, and Control
and Water for black cherry. There was no signiﬁcant difference between control and
ethanol-toluene and control and ethanol for any of the three species. The detail of the
statistical output is presented in appendix 9.

140

 

 

 

" _j"'-—o-Con1161 (a) 2 —I-Bh-To|(a)
. - s -Bh-T01+W (a) —-—Water (11)

 

  
     

 

 

   

 

 

 

 

 

 

 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 
  
  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

    

 

 

 

 

 

 

 

 

 

25 —111-—a11 (a) —o—a11+w (11) 1
20 i
15 -

"<1
16 J
5 ‘ 6-7 (a): Red pine ‘
0 1 1’ 1 _ ‘H'H‘

[ _5 ' 500 1000 1500 2000 2500 i
1 Exposure time (hours) i
:3 ’ 6-7 (h): Red oak w
35 -—~—_,;J,_.1.rr/ . - . 1. - a

30 A“ , - '
111 25 —
<1 20
15 f 41’ —O—Control (a) +Eth-Tol (a)
10 —»~ - A -Eth-Tol+W (11) —-—-——Water(b) —
3 H +5111 (a) —o—Et11+w (11) H H 1
0 500 1000 1500 2000 2500
Exposure tlme (hours)
35 ‘7 6 7 (c) Black cherry
30 1..
25
20 —
<‘ 15 1““ A __ _ _._
1O __4 —o—Control (a) -l—Eth-Tol (a)
- A -Eth-Tol+W (a) ..1....... -Water(b) .
5 " _.__... —)1(—Eth (a) —o—Et11+w (b) ~—
0 1 1 1 ”I
L 1
3 O 500 1000 1500 2000 25001
1 Exposure time (hours) j

 

Figure 6.7: Color change AE of wood samples after artiﬁcial weathering

Note: Letters in parenthesis in the legend indicate statistical signiﬁcance compared to control.
Similar letter mean no statistical difference with control. Different letters mean statistical

signiﬁcant 95% conﬁdence level.

141

 

6.4 Conclusions

This study investigated the inﬂuence of wood extractives on the discoloration
behavior of red pine, red oak, and black cherry. Results obtained showed that the rate of
whitening and the total discoloration rate of wood specimens were signiﬁcantly affected
by the removal of water extractable compounds from wood. Chromaticity coordinates
were less affected by the removal of wood extractives. These extractives, which are
known to be polyphenolic in nature, act as anti-oxidants and provide some level of
protection to wood against photodegradation.

However, more work is required to understand the chemistry of photo-protection
of wood surface by extractives, before any practical and economically viable of use of

this property could be developed.

142

 

References

Ajuong, Elijah-M. A.; Breese M. C. Fourier Transform Infrared Characterization of Pai
Wood (Afzelia africana Smith) Extractives. Holz als Roh-und Werkstoff 1998,
56(4), 139-142.

Dirckx O., Triboboulot M. C. Merlin A. and Deglixe X. 1992. Wood Photodiscoloration
of Abies Grandis under Solar Light Exposure. Annales des Sciences Forestieres
49(5): 425-447

Feist, W. C. 1982. Weathering of wood in structural uses. In “Structural Use of Wood in
Adverse Environments” (R. W. Meyer and R. M. Kellogg, eds.), pp. 156-178.
Society for Wood Science and Technology, University of British Columbia.
Vancouver, Canada

Feist, W. C., and Hon, D. N. S. 1984. Chemistry of Weathering and Protection. In
“The Chemistry of Solid Wood” (R. Rowell, ed.), pp. 401-451. American
Chemical Society, Washington DC.

Hon, D.N.S. 1991. Weathering and Phytochemistry of Wood. Pp 513-546 In
“Wood and Cellulosic Chemistry”. D.N.S. Hon and N. Shiraishi eds. M. Dekker.
New York. 1120 pp.

Hon, D.N.S., and Chang, S. T. 1984. Surface Degradation of Wood by Ultraviolet
Light. J. of Poly. Sci. 22: 2227-2241.

Hon, D. N. S. and W. C. Feist 1992. Hydroperoxidation in photoirradiated wood
surfaces. Wood and Fiber Sci. 32(2): 196-202.

Hon, D. N. S., and N. Minemura 2000. Color and Discoloration. Pp 385-442 in Hon
D.N.S nd N. Shirashi eds. Wood and Cellulosic Chemistry. Zed. Marcel Dekker,
Inc. New York, NY. 914pp.

Kalnins A. M. and Tarkow, H. 1966. Light-Induced Free Radicals in Wood. US.
Forest Service Research Paper FPL 58. US Dept of Agric. Forest Prod. Lab.

Kuo, M-L., and Hu, Ninghe. 1991. Ultrastructural Changes of Photodegradation
of Wood Surfaces Exposed to UV. Holzforschung 45(5): 347-353.

Maldas, D. C., & Kamdem, D. P. 1999. Wettability of extracted southern pine.
Forest Products Journal 49 (1 1/12), 91-93.

Nzokou, P. and Kamdem, D. P. 2002. Weathering of two hardwood species: African

padauk: Pterocarpus soyauxii, and Red maple: Acer rubrum. Journal of Tropical
Forest Products 8(2): 1-10.

143

CHAPTER 7
CONCLUSIONS AND RECOMMENDATIONS

Based on observations made in this study, extractives removed by ethanol and
ethanol-toluene from red oak, black cherry, and red pine were made up of fatty acids,
saturated esters, and cyclic polyphenolic compounds. The water extracts were mainly
coloriﬁc matter, condensed tannins, and low molecular weight carbohydrates. FTIR and
XPS analysis of wood surfaces showed that extraction results in hemicelluloses and
cellulose becoming more exposed on the wood surface.

Further investigations showed that these wood extractives lowered the
equilibrium moisture content of wood at a high relative humidity. Application of the
Hailwood-Homobin Sorption Theory to our data demonstrated that extracted wood had
more adsorption sites available and needed lower energy to absorb water.

The contact angle of extracted wood surface and distilled water decreased with
increased extraction, suggesting increased ability of wood surfaces to absorb water due to
the removal of extractive. This could lead to increased dimensional instability and
eventually lead to more severe physical damages on extracted wood.

However, monitoring of the physical degradation of specimens showed no
speciﬁc inﬂuence of wood extractives on the roughening, weight loss and microscopic
degradation of red pine, red oak, and black cherry following exposure to artiﬁcial
weathering. This observation suggests that the structure of wood, its density and internal
stresses developed during drying, and wetting are, as largely published in the literature,
the main factors of the erosion, weight loss and cracking of wood during weathering, with

extractives having only a limited and undetectable effect.

144

Investigation of the discoloration behavior of specimens showed that the rate of
whitening and the total discoloration rate of wood specimens were signiﬁcantly affected
by the removal of water extractable compounds from wood. This conﬁrms that
extractives, which are known to be polyphenolic in nature, act as anti-oxidants, and
provide some level of protection to wood against photodegradation.

However, more work is required to understand the chemistry of photo-protection
of wood surface by extractives, before any practical and economically viable use of this
property could be developed.

Recommendations for further study can be summed up as the followings:

(1) These results need to be conﬁrmed by conducting a similar study with ﬁeld test

exposure.

(2) More studies are needed on the chemical nature of extractives and their mechanism of

interaction with wood components.

145

APPENDIXES

146

Appendix 1: One Way Analysis of Variance of the contact angle
values for wood specimens

Black Cherry

Normality Test: Passed (P = 0.019)

Equal Variance Test: Passed (P = 0.271)

Source of Variation DF SS MS F P
Between Groups 11 30539.204 2776.291 58.203 <0.001
Residual 84 4006.817 47.700

Total 95 34546.02]

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000
All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P P<0.050
Control vs. Eth-Tol+Water 46.788 12 19.161 <0.001 Yes
Control vs. Eth-T01 39.078 12 16.003 <0.001 Yes
Control vs. Eth+W 34.612 12 14.175 <0.001 Yes
Control vs. Eth 31.613 12 12.946 <0.001 Yes
Red Oak

Normality Test: Passed (P > 0.200)

Equal Variance Test: Passed (P = 0.805)

Source of Variation DF SS MS F P
Between Groups 4 8994.801 2248.700 31.321 <0.001
Residual 35 2512.826 71.795

Total 39 1 1507.628

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000

147

All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison

Control vs. Eth-Tol+W
Control vs. Eth-T01
Control vs. Eth+W
Control vs. Eth

Diff of Means p
39.737 5
38.612 5
37.287 5
25.950 5

One Way Analysis of Variance

13.265
12.889
12.447
8.662

P

<0.001
<0.001
<0.001
<0.001

Saturday, March 06, 2004, 16:09:02

P<0.050

Yes
Yes
Yes
Yes

Red Pine
Normality Test: Passed (P > 0.200)

Equal Variance Test: Passed (P = 0.021)

Source of Variation DF SS MS F P
Between Groups 4 30068.394 7517.099 76.317 <0.001
Residual 35 3447.442 98.498

Total 39 33515.836

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000

All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P P<0.050
Control vs. Eth-Tol+W 70.632 5 20.130 <0.001 Yes
Control vs. Eth+W 63.1 14 5 17.987 <0.001 Yes
Control vs. Eth 35.796 5 10.202 <0.001 Yes
Control vs. Eth-T01 12.995 5 3.703 0.089 No

148

Appendix 2:

One-Way ANOVA Analysis of the change in contact over time

SEM
0.289
0.0661
0.253
0.0907
0.342

F P
23.060 <0.001

Black Cherry

Normality Test: Passed (P = 0.011)
Equal Variance Test: Passed (P = 0.206)
Group Name N Missing Mean Std Dev
Control 8 0 1.622 0.816
Eth-T01 8 0 0.827 0.187
Eth-Tol+W 8 0 2.823 0.717
Eth 8 0 0.692 0.257
Eth+W 8 0 3. 164 0.967
Source of Variation DF SS MS
Between Groups 4 40.885 10.221
Residual 35 15.513 0.443
Total 39 56.398

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000

All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

 

Comparison Diff of Means p P P<0.050
Eth+W vs. Eth 2.472 5 10.503 <0.001 Yes
Eth+W vs. Eth-T01 2.337 5 9.928 <0.001 Yes
Eth+W vs. Control 1.542 5 6.551 <0.001 Yes
Eth+W vs. Eth-Tol+W 0.341 5 1.448 0.843 No
Eth-Tol+W vs. Eth 2.131 5 9.055 <0.001 Yes
Eth-Tol+W vs. Eth-T01 1.996 5 8.481 <0.001 Yes
Eth-Tol+W vs. Control 1.201 5 5.103 0.008 Yes
Control vs. Eth 0.930 5 3.952 0.060 No
Control vs. Eth-T01 0.795 5 3.377 0.143 Do Not Test
Eth-To] vs. Eth 0.135 5 0.575 0.994 Do Not Test
Red Oak

Normality Test: Passed (P > 0.200)

149

 

Equal Variance Test:

Passed (P = 0.213)

Group Name N Missing Mean Std Dev SEM
Control 8 0 2.758 0.649 0.230
Eth-T01 8 0 1.449 0.384 0.136
Eth-Tol+W 8 0 2.347 0.751 0.265

Eth 8 0 2.543 0.658 0.233
Eth+W 8 0 2.771 0.847 0.300
Source of Variation DF SS MS F P
Between Groups 4 9.515 2.379 5.212 0.002
Residual 35 15.975 0.456

Total 39 25.490

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = 0.002).

Power of performed test with alpha = 0.050: 0.892

All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P P<0.050
Eth+W vs. Eth-T01 1.322 5 5.533 0.004 Yes
Eth+W vs. Eth-Tol+W 0.424 5 1.773 0.720 No
Eth+W vs. Eth 0.227 5 0.952 0.961 Do Not Test
Eth+W vs. Control 0.0130 5 0.0544 1.000 Do Not Test
Control vs. Eth-T01 1.309 5 5.479 0.004 Yes
Control vs. Eth-Tol+W 0.411 5 1.719 0.743 Do Not Test
Control vs. Eth 0.214 5 0.897 0.968 Do Not Test
Eth vs. Eth-T01 1.094 5 4.581 0.021 Yes
Eth vs. Eth-T01+W 0.196 5 0.821 0.977 Do Not Test
Eth-Tol+W vs. Eth-T01 0.898 5 3.760 0.081

Red Pine

Normality Test: Passed (P > 0.200)

Equal Variance Test: Passed (P = 0.226)

Group Name N Missing Mean Std Dev SEM

Control 8 0 5.199 0.915 0.324
Eth-T01 8 0 6.950 1.457 0.515

150

Eth-Tol+W 8 0 3.660 1.024 0.362

Eth 8 0 2.790 0.735 0.260

Eth+W 8 0 3.319 0.860 0.304

Source of Variation DF SS MS F P
Between Groups 4 91.595 22.899 21.642 <0.001
Residual 35 37.032 1.058

Total 39 128.628

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000

All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P P<0.050

Eth-T01 vs. Eth 4.160 5 1 1.440 <0.001 Yes
Eth—T01 vs. Eth+W 3.632 5 9.986 <0.001 Yes
Eth-T01 vs. Eth-Tol+W 3.290 5 9.046 <0.001 Yes
Eth-T01 vs. Control 1.752 5 4.816 0.014 Yes
Control vs. Eth 2.409 5 6.623 <0.001 Yes
Control vs. Eth+W 1.880 5 5.170 0.007 Yes
Control vs. Eth-T01+W 1.538 5 4.230 0.038 Yes
Eth-Tol+W vs. Eth 0.870 5 2.393 0.452 No
Eth-Tol+W vs. Eth+W 0.342 5 0.940 0.963 Do Not Test
Eth+W vs. Eth 0.529 5 1.453 0.841 Do Not Test

A result of "Do Not Test" occurs for a comparison when no signiﬁcant difference is
found between two means that enclose that comparison. For example, if you had four
means sorted in order, and found no difference between means 4 vs. 2, then you would
not test 4 vs. 3 and 3 vs. 2, but still test 4 vs. 1 and 3 vs. 1 (4 vs. 3 and 3 vs. 2 are
enclosed by 4 vs. 2: 4 3 2 1). Note that not testing the enclosed means is a procedural
rule, and a result of Do Not Test should be treated as if there is no signiﬁcant difference
between the means, even though one may appear to exist.

151

Appendix 3: One-Way ANOVA Analysis of the Roughness Index
(RI)

Red Pine
Normality Test: Passed (P = <0.001)
Equal Variance Test: Failed (P = <0.001)

Group Name N Missing Mean Std Dev SEM

Control 25 0 39.857 7.757 1.551

Eth-T01 25 0 8.106 1.032 0.206
Eth-Tol-1-Water25 0 5 .465 2.095 0.419

Eth 25 0 9.964 3.697 0.739

Eth+Water 25 0 4.284 0.934 0.187

Source of Variation DF SS MS F P
Between Groups 4 22144.615 5536.154 345.308 <0.001
Residual 120 1923.903 16.033

Total 124 24068.517

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000
All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P P<0.050
Control vs. Eth+Water 35.573 5 44.421 <0.001 Yes
Control vs. Eth-Tol+Water 34.392 5 42.946 <0.001 Yes
Control vs. Eth-T01 31.752 5 39.649 <0.001 Yes
Control vs. Eth 29.893 5 37.329 <0.001 Yes
Red Oak

Normality Test: Passed (P = 0.075)
Equal Variance Test: Failed (P = <0.001)
Group Name N Missing Mean Std Dev SEM

Control 25 0 5.708 1.857 0.371
Eth-To] 25 0 4.332 1.212 0.242
Eth-Tol+Water25 0 3.3 16 1.397 0.279
Eth 25 0 5.179 1.475 0.295
Eth+Water 25 0 2.61 1 0.498 0.0996

152

Source of Variation ' DF SS MS F P

Between Groups 4 163.785 40.946 22.028 <0.001
Residual 120 223.055 1.859
Total 124 386.840

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000

All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P P<0.050
Control vs. Eth+Water 3.096 5 1 1.356 <0.001 Yes
Control vs. Eth-T01+Water 2.392 5 8.772 <0.001 Yes
Control vs. Eth-T01 1.375 5 5.044 0.005 Yes
Control vs. Eth 0.528 5 1.937 0.648 No
Black Cherﬂ

Normality Test: Passed (P = 0.003)

Equal Variance Test: Passed (P = <0.001)

Group Name N Missing Mean Std Dev SEM

Control 24 0 2.814 0.439 0.0896

Eth-To] 25 0 0.945 0.198 0.0396
Eth-Tol+Water25 0 0.7 l 7 0.306 0.0612

Eth 25 0 1.084 0.688 0.138
Eth+Water 25 0 0.644 0.289 0.0578

Source of Variation DF SS MS F P
Between Groups 4 77.907 19.477 110.476 <0.001
Residual 1 19 20.979 0.176

Total 123 98.886

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000

153

A11 Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P

Control vs. Eth+Water 2.169 5 25.569 <0.001
Control vs. Eth-Tol+Water 2.096 5 24.707 <0.001
Control vs. Eth-To] 1.869 5 22.029 <0.001
Control vs. Eth 1.729 5 20.382 <0.001

154

P<0.050

Yes
Yes
Yes
Yes

Appendix 4: One-Way ANOVA Analysis of Microcracking index
(MCI)

Red Pine
Normality Test: Passed (P = 0.024)
Equal Variance Test: Failed (P 2 <0.001)

Group Name N Missing Mean Std Dev SEM
Control 25 0 17.175 4.013 0.803

Eth-T01 25 0 5.246 1.482 0.296
Eth-Tol+Water25 0 3.236 1.773 0.355

Eth 25 0 6.064 2.708 0.542

Eth+Water 25 0 2.897 0.915 0.183

Source of Variation DF SS MS F P
Between Groups 4 3461.287 865.322 146.093 <0.001
Residual 120 710.771 5.923

Total 124 4172.058

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000
All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P P<0.050
Control vs. Eth+Water 14.278 5 29.334 <0.001 Yes
Control vs. Eth-Tol+Water 13.938 5 28.636 <0.001 Yes
Control vs. Eth-T01 1 1.929 5 24.508 <0.001 Yes
Control vs. Eth 1 1.1 10 5 22.826 <0.001 Yes
Red Oak

Normality Test: Passed (P > 0.200)
Equal Variance Test: Passed (P = 0.078)

Group Name N Missing Mean Std Dev SEM

Control 25 0 1.616 0.768 0.154
Eth-T01 25 0 2.455 0.997 0.199
Eth-Tol+Water25 0 1.732 0.581 0.1 16
Eth 25 0 2.213 0.839 0.168
Eth+Water 25 0 1.809 0.559 0.1 12

155

Source of Variation DF SS MS F P

Between Groups 4 12.535 3.134 5.330 <0.001
Residual 120 70.552 0.588
Total 124 83.087

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 0.932

All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P P<0.050

Eth-To] vs. Control 0.839 5 5.468 0.002 Yes
Eth-T01 vs. Eth-Tol+Water 0.722 5 4.710 0.010 Yes
Eth-T01 vs. Eth+Water 0.645 5 4.209 0.029 Yes
Eth-To] vs. Eth 0.242 5 1.575 0.799 No
Eth vs. Control 0.597 5 3.893 0.052 No
Eth vs. Eth-Tol+Water 0.481 5 3.134 0.181 Do Not Test
Eth vs. Eth+Water 0.404 5 2.634 0.343 Do Not Test
Eth+Water vs. Control 0.193 5 1.259 0.900 Do Not Test
Eth+Water vs. Eth-Tol+Water 0.0768 5 0.501 0.997 Do Not Test
Eth-Tol+Water vs. Control 0.116 5 0.759 0.983 Do Not Test

A result of "Do Not Test" occurs for a comparison when no signiﬁcant difference is
found between two means that enclose that comparison. For example, if you had four
means sorted in order, and found no difference between means 4 vs. 2, then you would
not test 4 vs. 3 and 3 vs. 2, but still test 4 vs. 1 and 3 vs. 1 (4 vs. 3 and 3 vs. 2 are
enclosed by 4 vs. 2: 4 3 2 1). Note that not testing the enclosed means is a procedural
rule, and a result of Do Not Test should be treated as if there is no signiﬁcant difference
between the means, even though one may appear to exist.

Black Cher_ry

Normality Test: Passed (P = 0.001)

Equal Variance Test: Failed (P = <0.001)
Group Name N Missing Mean Std Dev SEM
Control 25 0 1.864 0.623 0.125
Eth-T01 25 0 0.915 0.289 0.0579
Eth-T01+Water25 0 0.640 0.328 0.0655
Eth 25 0 1.260 0.527 0.105
Eth+Water 25 0 0.393 0.211 0.0422

156

Source of Variation DF SS MS F P

Between Groups 4 32.967 8.242 45.754 <0.001
Residual 120 21.615 0.180
Total 124 54.582

The differences in the mean values among the treatment groups are greater than would be
expected by chance; there is a statistically signiﬁcant difference (P = <0.001).

Power of performed test with alpha = 0.050: 1.000

All Pairwise Multiple Comparison Procedures (Tukey Test):

Comparisons for factor:

Comparison Diff of Means p q P P<0.050
Control vs. Eth+Water 1.471 5 17.334 <0.001 Yes
Control vs. Eth-Tol+Water 1.224 5 14.423 <0.001 Yes
Control vs. Eth-T01 0.949 5 1 1.178 <0.001 Yes
Control vs. Eth 0.605 5 7.122 <0.001 Yes

157

Appendix 5:

Lightness data (L)

Red Pine

Dependent Variable: y

Source
Model
Error
Uncorrected Total

Contrast

slope
slope
slope
slope
slope

of Control vs Eth-T01
of Control vs Eth-Tol+w
of Control vs Eth

of Control vs Eth-w

of Control vs water

Red Oak

Source
Model
Error
Uncorrected Total

Contrast

slope
slope
slope
slope
slope

of Control vs Eth-T01
of Control vs Eth-Tol+w
of Control vs Eth

of Control vs Eth-w

of Control vs water

Black cherry

Source
Model
Error
Uncorrected Total

Contrast

slope
slope
slope
slope
slope

of Control vs Eth-Tel
of Control vs Eth—Tol+w
of Control vs Eth

of Control vs Eth-w

of Control vs water

Number of observations

Sum of
BF Squares
12 368388.7713
48 1348.6016
60 369737.3729

DF Contrast SS

0.72598477
0.00924161
14.23527164
14.23527164
14.07350123

u—A—b-L—b—L

Sum of
BF Squares
12 339659.9699
48 660.9003
60 340320.8702

DF Contrast SS

.08948435
.71459606
.30646772
.30646772
.62354435

d-A-L—L-A

Sum of
BF Squares
12 282297.1321
48 2843.5121
60 285140.6442

DF Contrast SS

1 0.26361542
1 59.11629405
1 58.89795477
1 58.89795477
1 57.97243644

158

Results of SAS Statistical GLM analysis of the

60

Mean Square F Value
30699.0643 1092.65
28.0959
Mean Square F Value
0.7259847? 0.03
0.00924161 0.00
14.23527164 0.51
14.23527164 0.51
14.07350123 0.50
Mean Square F Value
28304.9975 2055.74
13.7688
Mean Square F Value
2.08948435 0.15
1.71459606 0.12
1.30646772 0.09
1.30646772 0.09
0.62354435 0.05
Mean Square F Value
23524.7610 397.11
59.2398
Mean Square F Value
0.26361542 0.00
59.11629405 1.00
58.89795477 0.99
58.89795477 0.99
57.97243644 0.98

Pr > F
<.0001

Pr > F

0.8730
0.9856
0.4800
0.4800
0.4825

Pr > F
<.ooo1

Pr>F

0.6986
0.7257
0.7594
0.7594
0.8324

Pr > F
<.ooo1

 

Appendix 6:

une

Results of SAS Statistical GLM analysis of
the Lowering Rate of Whiteness Index Lightness

(LWI)

Dependent Variable: y

Source
Model
Error

Uncorrected Total

Contrast

slope
slope
slope
slope
slope

of Control
of Control
of Control
of Control
of Control

Red oak

Source
Model
Error

V5
V8
V8
V3
VS

Eth-T01
Eth-Tol+w
Eth

Eth-w
water

Uncorrected Total

Contrast

slope
slope
slope
slope
slope

of Control
of Control
of Control
of Control
of Control

Black cher_ry

Source
Model
Error

V3
V5
V5
VS
VS

Eth-T01
Eth-Tol+w
Eth

Eth-w

water

Uncorrected Total

Contrast

slope
slope
slope
slope
slope

of Control
of Control
of Control
of Control
of Control

V8
V8
V8
VS
VS

Eth-T01
Eth-Tol+w
Eth

Eth-w

water

DF
12
48
60

DF
12
48
60

DF
12
48
60

The GLM Procedure

DF

Add—AA

DF

.A—b—L—L-l

0F

._bc-L-h—l—L

Sun of
Squares
0.59187584
0.18934891
0.78122475

Contrast SS

0.00007150
0.00005865
0.00288025
0.00288025
0.00232179

Sun of
Squares
0.95722441
0.13286554
1.09008995

Contrast SS

0.00058550
0.00019489
0.00002084
0.00002084
0.00111741

Sum of
Squares
.64880151
.78095009
3.42975160

010

Contrast SS

0.00003600
0.02726865
0.02607045
0.02607045
0.03286963

159

Mean Square
0.04932299
0.00394477

Mean Square

0.00007150
0.00005865
0.00288025
0.00288025
0.00232179

Mean Square
0.07976870
0.00276803

Mean Square

0.00058550
0.00019489
0.00002084
0.00002084
0.00111741

Mean Square
0.22073346
0.01626979

Mean Square

0.00003600
0.02726865
0.02607045
0.02607045
0.03286963

F Value

12.50

Value

F Value

28.82

F Value

0.21
0.07
0.01
0.01
0.40

F Value

13.57

F Value

Pr > F
<.0001

Pr > F

.8935
.0903
.3971
.0497
.0446

00000

Pr>F
<.0001

Pr>F

0.6477
0.0799
0.9312
0.0932
0.0582

Pr > F
<.0001

Pr>F

0.9627
0.0201
0.2117
0.0217
0.0167

 

Appendix 7:

in Chromaticity Coordinate a (Aa)

 

Results of SAS Statistical GLM analysis of the change

Red plne
Dependent Variable: y
Sum of
Source DF Squares Mean Square F Value Pr > F
Model 12 519.7577623 43.3131469 14.52 <.0001
Error 48 143.2022155 2.9833795
Uncorrected Total 60 662.9599778
Contrast DF Contrast SS Mean Square F Value Pr > F
slope of Control vs Eth-T01 1 0.00111075 0.00111075 0.00 0.9847
slope of Control vs Eth-Tol+w 1 1.36353632 1.36353632 0.46 0.5023
slope of Control vs Eth 1 0.04781313 0.04781313 0.02 0.8998
slope of Control vs Eth-w 1 0.04781313 0.04781313 0.02 0.8998
slope of Control vs water 1 2.03163514 2.03163514 0.68 0.4133
Red Oak
Sum of
Source DF Squares Mean Square F Value Pr > F
Model 12 1913.940105 159.495009 18.10 <.0001
Error 48 423.022787 8.812975
Uncorrected Total 60 2336.962892
Contrast DF Contrast 88 Mean Square F Value Pr > F
slope of Control vs Eth-Tol 1 0.81851925 0.81851925 0.09 0.7619
slope of Control vs Eth-Tol+w 1 0.95674572 0.95674572 0.11 0.7432
slope of Control vs Eth 1 0.22863637 0.22863637 0.03 0.8727
slope of Control vs Eth-w 1 0.22863637 0.22863637 0.03 0.8727
slope of Control vs water 1 0.30915247 0.30915247 0.04 0.8522
Black Chem
Sum of
Source DF Squares Mean Square F Value Pr > F
Model 12 5085.368137 423.780678 25.82 <.0001
Error 48 787.708988 16.410604
Uncorrected Total 60 5873.077125
Contrast DF Contrast SS Mean Square F Value Pr > F
slope of Control vs Eth-Tol 1 0.89008210 0.89008210 0.05 0.8168
slope of Control vs Eth-Tol+w 1 0.53142585 0.53142585 1.03 0.8579
slope of Control vs Eth 1 0.26397577 0.26397577 0.02 0.8996
slope of Control vs Eth-w 1 0.26397577 0.26397577 1.02 0.8996
slope of Control vs water 1 0.29487884 0.29487884 1.02 0.8939

160

 

Appendix 8:

Results of SAS Statistical GLM analysis of the

Change in Chromaticity Coordinate b (Ab*)

Red pi e
Dependent Variable: y

Source
Model
Error
Uncorrected Total

Contrast

slope of Control vs Eth-Tol
slope of Control vs Eth-Tol+w
slope of Control vs Eth

slope of Control vs Eth-w
slope of Control vs water

Red Oak

Source
Model
Error
Uncorrected Total

Contrast

slope of Control vs Eth-T01
slope of Control vs Eth-Tol+w
slope of Control vs Eth

slope of Control vs Eth-w
slope of Control vs water

Black Cher_ry

Source
Model
Error
Uncorrected Total

Contrast

slope of Control vs Eth-T01
slope of Control vs Eth-Tol+w
slope of Control vs Eth

slope of Control vs Eth-w
slope of Control vs water

DF
12
48
60

DF

J—L—‘A-A

0F
12
48
60

DF

J—L—L-L—L

DF
12
48
60

OF

The GLM Procedure

Sum of
Squares
4949.193842
1563.557687
6512.751529

Contrast SS

1.06395061
3.43175696
3.06641410
3.06641410
1.25122533

Sun of
Squares
6360.880755
2260.211656
8621.092411

Contrast SS

0.74104811
1.64684247
0.10877803
0.10877803
0.95133962

Sun of
Squares
7245.018438
1823.600448
9068.618887

Contrast SS

1.02227032
2.80859845

10.13132736
10.13132736

6.07743459

161

Mean Square
412.432820
32.574118

Mean Square

1.06395061
3.43175696
3.06641410
3.06641410
1.25122533

Mean Square
530.073396
47.087743

Mean Square

0.74104811
1.64684247
0.10877803
0.10877803
0.95133962

Mean Square
603.751537
37.991676

Mean Square

1.02227032
2.80859845
10.13132736
10.13132736
6.07743459

F Value
12.66

Pr > F
<.0001

F Value Pr > F
0.8573
0.7469
0.7603
0.7603
0.8454

Pr > F
<.0001

F Value
11.26

F Value Pr > F
0.9007
0.8524
0.9619
0.9619
0.8876

Pr > F
<.0001

F Value
15.89

F Value Pr > F
0.8704
0.7869
0.6079
0.6079
0.6910

0.03
0.07
0.27
0.27
0.16

 

Appendix 9:

Results of SAS Statistical GLM analysis of

the Change overall color change (AE)

Dependent Variable: y

Source
Model
Error

Uncorrected Total

Contrast

slope
slope
slope
slope
slope

of Control
of Control
of Control
of Control
of Control

Red Oak

Source
Model
Error

V8
V8
V8
V3
V5

Eth-Tol
Eth-Tol+w
Eth

Eth-w
water

Uncorrected Total

Contrast

slope
slope
slope
slope
slope

of Control
of Control
of Control
of Control
of Control

Black Cher_ry

Source
Model
Error

V8
V8
V5

V8
V5

Eth-Tol
Eth-Tol+w
Eth

Eth-w
water

Uncorrected Total

Contrast

slope
slope
slope
slope
slope

of Control
of Control
of Control
of Control
of Control

V5
V5
V8
V5
V8

Eth-Tol
Eth—Tol+w
Eth

Eth-w
water

DF
12
48
60

DF

d‘d-‘d

DF
12
48
60

DF

AAA-ii

0F
12
48
60

DF

A—‘d—L—A

The GLM Procedure

Sun of
Squares
11165.90822
1460.18597
12626.09418

Contrast SS

0.73083593
22.09719696
17.59290517
17.59290517
63.49871865

Sun of
Squares
14490.51969
1676.09156
16166.61125

Contrast SS

0.03462916
7.22108860

24.57766428
24.57766428
40.36024841

Sun of
Squares
25084.68622
2192.24783
27276.93405

Contrast SS

0.76783701

67.81642312
50.37613456
50.37613456
91.81589769

162

Mean Square
930.49235
30.42054

Mean Square

0.73083593

22.09719696
17.59290517
17.59290517
63.49871865

Mean Square
1207.54331
34.91857

Mean Square

0.03462916
7.22108860
24.57766428
24.57766428
40.36024841

Mean Square
2090.39052
45.67183

Mean Square

0.76783701
67.81642312
50.37613456
50.37613456
91.81589769

F Value
30.59

F Value

F Value
34.58

F Value

F

0.00 0
0.21 0
0.70 0
0.70 0
1.16 0

F Value
45.77

Value

0.02 0
1.48 0
1.10 0
1.10 0
2.01 0

Pr > F
<.0001

PP > F

0.8775
0.0398
0.4507
0.0450
0.0155

Pr > F
<.0001

Pr > F

.9750
.6513
.4056
.0465
.0287

Pr > F
<.0001

Pr > F

.8974
.0290
.2989
.0298
.0162

   

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3 1293 02551 6646