Radial variation of wood properties of sengon (Paraserianthes falcataria) and Jabon (Anthocephalus cadamba).

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ESI FAJRIANI

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

BOGOR


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STATEMENT

I declare that this thesis entitled Radial Variation of Wood Properties of Sengon (Paraserianthes falcataria) and Jabon (Anthocephalus cadamba) is my own work with the direction of the supervising committee and has not been submitted in any form for any college except in AgroParisTech ENGREF, France (required by Double Degree Program). Information and quotes from journals and books have been acknowledge and mentioned in the thesis where they appear. All complete references are given at the end of the paper.

I understand that my thesis will become part of the collection of Bogor Agricultural University. My signature below gives the copyright of my thesis to Bogor Agricultural University.

Bogor, December 2013

Esi Fajriani


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SUMMARY

ESI FAJRIANI. Radial Variation of Wood Properties of Sengon (Paraserianthes falcataria) and Jabon (Anthocephalus cadamba). Supervised by YUSUF SUDO HADI and MERIEM FOURNIER.

Seven years old Sengon (Paraserianthes falcataria) and Jabon (Anthocephalus cadamba) trees were harvested from plantation forest in West Java, Indonesia aiming to characterize radial pattern of selected physical and anatomical properties.

One disk from log section in length of 2m (bottom part) and 6m (upper part) was taken from each tree of the tree stem, the sample from pith to bark (2.6cm x 2.0cm) was prepared from disk. Each sample was divided in 1cm wide segments (segmented ring) numbered from pith to bark. Anatomical parameters and density were measured for each segmented ring to investigate the juvenile and mature pattern of radial variation for each property. Observed patterns were described using three different models: I linearly increase or decrease, II exponential, III lineary equal to intercept. By using measured profiles, a typology of variations was defined from statistical modeling.

The pattern of radial variation showed in both species, all properties in vessel elements (vessel frequency and vessel area), fiber length and density in Jabon had model II. Lumen diameter, cell wall thickness and density in Jabon had model I and also for fiber diameter of bottom part in both of species, diameter lumen of upper part Sengon and cell wall thickness of bottom part Sengon. Model III had found in fiber diameter of upper part in both species and lumen diameter of bottom part Sengon.

Key words:

Sengon, Jabon, juvenile and mature transition, density, vessel element, fiber element


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RINGKASAN

ESI FAJRIANI. Variasi Radial dari Sifat Kayu Sengon (Paraserianthes falcataria) dan Jabon (Anthocephalus cadamba). Dibimbing oleh YUSUF SUDO HADI and MERIEM FOURNIER

Sengon (Paraserianthes falcataria) dan Jabon (Anthocephalus cadamba) berumur 7 tahun yang ditanam di Hutan Tanaman yang berlokasi di Jawa barat Indonesia diambil sebagai contoh uji untuk mengkarakterisasi variasi radial pada beberapa sifat fisik dan anatomi kayu tersebut.

Contoh uji berupa disk diambil dari ketinggian 2m (bottom part) and 6m (upper part) pada masing-masing kayu bulat (log). Contoh uji kayu (2,6cm x 2,0cm) dari empulur ke kulit disiapkan dari masing-masing ketinggian dan jenis kayu. Setiap contoh uji dari empulur ke kulit dibagi dalam beberapa segmen (1 cm) dari empulur ke kulit. Parameter anatomi dan kerapatan diukur pada tiap segmen contoh uji untuk menentukan pola transisi variasi radial pada kayu remaja dan dewasa. Pola kayu remaja dan kayu dewasa pada masing-masing sifat kayu yang diukur di kelompokkan ke dalam tiga model yang berbeda: I linear meningkat atau menurun, II exponensial, III linear equal to intercept. Tipe variasi radial ditentukan berdasarkan model statistika yang digunakan.

Pola variasi radial terlihat dari kedua spesies yang diuji, diantaranya pada sel pembuluh (jumlah sel pumbuluh per mm2 dan luas permukaan sel pembuluh), panjang serat dan kerapatan pada kayu jabon masuk ke dalam model II. Diameter lumen, tebal dinding sel dan kerapatan pada kayu jabon masuk ke dalam model I dan juga pada diameter fiber bagian bawah pada kedua spesies, diameter lumen bagian atas sengon dan tebal dinding sel bagian bawah sengon. Model III ditemukan pada diameter serat bagian atas dari kedua spesies dan diameter lumen bagian bawah sengon.

Kata kunci:

Sengon, Jabon, transisi kayu muda dan kayu dewasa, kerapatan, elemen sel pembuluh, elemen serat

 

 

 


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RADIAL VARIATION OF WOOD PROPERTIES OF SENGON

(

Paraserianthes falcataria

) AND JABON (

Anthocephalus cadamba

)

ESI FAJRIANI

Thesis

In partial fulfillment of the requirements for the degree of Master of Science

At

Bogor Agricultural University

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

BOGOR


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SHEET APPROVAL

Title : Radial Variation of Wood Properties of Sengon (Paraserianthes falcataria) and Jabon (Anthocephalus cadamba)

Name : Esi Fajriani

NIM : E251110091

Approved, Co-Major Professors,

Prof Dr Ir Yusuf Sudo Hadi, MAgr Prof Meriem Fournier, PhD

Head of the Department of Forest Products Technology

Prof Dr Ir I Wayan Darmawan, MSc

Presented : 03 December 2013

Dean of the Graduate School

Dr Ir Dahrul Syah, MScAgr

Date of Graduation : Known by,


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FOREWORD

All praise and gratitude to Allah SWT so that the author could finish this scientific work entitled Radial Variation of Wood Properties of Sengon (Paraserianthes falcataria) and Jabon (Anthocephalus cadamba). The study is expected to provide scientific information on the juvenile and mature pattern in Sengon and Jabon.

The special thank goes to my helpful supervisor Prof. Yusuf Sudo Hadi, Prof. Meriem Fournier and Dr. Julien Ruelle. The supervision, advice and support that they gave truly help the progression and smoothness of my study.

My grateful thanks also go to Dr. Jana Dlouha for a big contribution and advice many times during my research, Marylin Harroué for helping me to work in laboratory and for all member of laboratory of wood quality INRA Champenoux, Nancy, France.

Thanks also to my beloved parents, Mr. Amlis and Mrs. Nurhayati, my sisters and brother, Irna Efida, Efa Fitria, Esa Wahyuni and Eka Ardian, my fiancé Heru Septiawan and the whole family, for all the prayers and love. And also thanks to all master student of Forest Products Technology especially to Abigael Kabe’, Nengsie Khaulany, Merry Sabed, Ammar Afif, Reinardus Cabuy, Fakhruzy and Ana Agustina.

Finally, I thank to Indonesian Ministry of Education “Beasiswa Unggulan programme” for its financial support. Without the support I simply could not come to study the Master program.

The author recognizes that this research is still far from perfect. Therefore, suggestions and constructive criticism are expected to improve this work.

Bogor, December 2013


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TABLE OF CONTENTS

TABLE OF CONTENTS x

LIST OF TABLES xi

LIST OF FIGURES xi

LIST OF APPENDIXS xii

1. INTRODUCTION 1

Background 2 Formulation 2 Objective 2 Benefits 2

2. STUDY LITERATURES 3

Juvenile Wood 3

Sengon and Jabon: two fast growth species widely planted in Indonesia for wood industry

4

3. MATERIALS AND METHODS 6

Location and Period of Research 6

Tools and Materials 6

Data Analyzing 11

4. RESULTS AND DISCUSSION 13

Results 13 Discussion 18

5. CONCLUSION 23

REFERENCES 24 APPENDIXES 26


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LIST OF TABLES

1. The mean value of all the properties with standard deviation 13

2. Typology of radial patterns 15

3. Predicting of transition location using t=3τ+1 for type II models 16

4. Amplitude of variations 17

5. Fiber quality 21

LIST OF FIGURES

1. Mechanistic hypotheses for the location of the core wood/outer wood transition

4

2. a) Sengon tree; b) Jabon tree 6

3. Sample preparation 7

4. Sample of density measurement 8

5. Sliding microtome with tungsten blade 8

6. One segment sample for anatomical analysis 9

7. a) ImageJ software; b) Vessel frequency measurement; c) Fiber diameter, lumen diameter and cell wall thickness measurement

10

8. Fiber length measurement 11

9. Types of models used to determine transition location 11 10.Radial variation of density for Sengon (left figure) and Jabon (right

figure)

14 11.Radial variation of cell wall thickness for Sengon 14


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LIST OF APPENDIXES

1. Graph 26

2. Modelisation graph 29


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1 INTRODUCTION

Background

The development of human civilization has caused many problems. One of many problems is an increase the concentration of carbon dioxide (CO2) in the atmosphere. Planting fast-growing species is one alternative that can be used to reduce this problem. Moreover, the availability of wood as raw materials for industry is also a problem that can be solved by planting fast-growing wood species to meet production needs.

In the 70's, 100% wood industries in Indonesia only rely on natural forests as a source of supply (Mansur and Surahman 2011). The rate of degradation natural forests continues to increase causing sharply reduced timber supply. The raw materials have changed from natural forests to plantations forest, providing a great challenge for wood science to find out how much portion of juvenile wood and mature wood contained in fast-growing species in a particular age cut. Short rotation in the fast-growing species is feared can lead a large portion of juvenile wood in the tree (Bao et al. 2001).

Sengon (Paraserianthes falcataria) and Jabon (Anthocephalus cadamba) are two kind of superior wood that can be developed through Industrial Plantation Forest and the Community Forest. In meeting the wood demand for companies, industries and individuals, Indonesia has been using Sengon and Jabon wood from plantations forest which is generally harvested in short rotations and small diameter. In this case, Sengon and Jabon, generally harvested in cutting age 5 to 7 years (Darmawan et al. 2013).

The high amount of juvenile wood portion in tree may limit its use, because the characteristics of juvenile wood are inversely proportional to the mature wood. Uses wood from short rotation plantations which have a high potential to produce a large portion of juvenile wood give effect on the final product of wood processing.


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Formulation

Sengon (Paraserianthes falcataria) and Jabon (Anthocepalus cadamba) are fast growth species where radial variations of wood properties associated to juvenile and mature pattern are suspected to be a potential limit for industrial use. Characterizing how the pattern juvenile/mature always pronounced? Are some properties stabilized earlier? What is the range of variations observed in harvestable trees (diameter 40 cm and age 7 years old) and what are the consequences for industrial uses? Are the two species similar?

Objective

This study aims to characterizing how different properties (density and anatomy) in seven years old Sengon and Jabon change along a radius.

Benefits

The study is expected to provide scientific information on the juvenile and mature pattern in Sengon and Jabon. In this condition, processing of wood with a high portion of juveniles should be able to do well so that the final product has a good quality.


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2 STUDY LITERATURES

Juvenile Wood  

Juvenile wood is woody stems displays large progressive changes in cell features and wood properties from the pith outwards (Lachenbruch et al. 2011). This empirically observed pattern of radial variations is called juvenile/mature wood pattern (Panshin and de Zeeuw 1980). This pattern is characterized by progressive changes. The juvenile core is anatomically made of smaller and shorter fibers with thinner walls and larger micro fibril angles, with a higher lignin content (and a lower cellulose content). Concerning wood properties, juvenile core is reported to be of lower density, lower stiffness (MOE) and strength (MOR), higher grain angle, higher longitudinal shrink age, higher incidence of reaction wood. (Evans et al. 2000; Koubaa et al. 2005; Clark et al. 2006; Adamopoulus et al. 2007; Gryc et al. 2011; Lachenbruch et al. 2011).

The biology of such radial patterns is not simple and well known. Therefore there is no simple way to determine a transition between juvenile and mature wood (as the radial variations differ among species and wood properties) or to define silvicultural criteria to limit the magnitude of radial variations (as optimal combinations of harvestability age and annual increment, etc). Actually, the juvenile and mature pattern could be explained by i) the distance between the cambium and the living crown, ii) the cambial age, iii) the distance between the cambium and the pith (Figure 1). All of them predict radial variations but in i) the transition is determined by age and in ii) it is determined by diameter.

The juvenile and mature pattern depends on both species and properties. As emphasized by Lachenbruch et al. (2011), juvenile and mature pattern has been widely studied in commercial species and especially conifers. Moreover radial patterns never reveals a single nature of juvenile and mature wood but the kinetics of the transition depends on properties as well on individual trees and sites (Grezkowiak 1997; Lachenbruch et al. 2011).


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Figure 1 Mechanistic hypotheses for the location of the core wood/outer wood transition. Core

wood is white, and outer wood is gray. (a) Location determined by the position of the livecrown.

(b) Location determined by cambial age. Shown schematically for transition age of9 years, with

each sheath of the tree representing 3 years growth. At any stage of tree growth,core wood is

produced at cambial age of ≤ 9 years and outer wood is produced at cambial age of > 9 years

(arrow). (c) Location determined by cambial age. Shown schematically for transition age of 9

years for a slow-grown and a fast-grown tree. (d) Location determined by diameter  

The juvenile and mature pattern limits industrial uses. When the transition juvenile and mature occupies a large portion of processed wood, such heterogeneity may limit its use, because heterogeneity is by itself undesired by industry. Two reasons make the heterogeneity due to juvenile and mature pattern undesired: on one hand, it will produce sawings, pulp or veneers of non-constant quality, on the other hand as a single sawing or veneer could include both juvenile and mature wood with a strong gradient of longitudinal shrinkage and mechanical properties, such a gradient induces a greater propensity to distortion when wood is dried. Moreover, the characteristics of the juvenile core are usually weaker.

Also in the pulp industry, the presence of juvenile wood is not desired because juvenile wood has a short fiber, so the quality of the pulp produced is not good. In addition, the presence of a high amount of juvenile wood limits its lumber uses because it is considered to be less favorable due to lower wood density and higher shrinkage.

Sengon and Jabon: two fast growth species widely planted in Indonesia for wood industry

 

Sengon (Paraserianthes falcataria) and Jabon (Anthocephalus cadamba) are two kind of superior wood that can be developed through Industrial Plantation Forest and the Community Forest. In meeting the wood demand for companies,


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industries and individuals, Indonesia has been using Sengon and Jabon wood from plantations forest which are generally harvested in short rotations and small diameter.

Sengon (Paraserianthes falcataria L. Nielsen) also known with Sengon is one of pioneer species important in Indonesia. This type selected as one type of industrial plantation because the growth is very fast, adaptable in different soil type, etc. Sengon has annual increment about 4-5 cm until 6 years old and will decrease about 3-4 cm/year at 8-9 years old and decrease slightly. According National Statistic Biro (2004), 60% of total number of Sengon trees planted in West Java and Central Java.

Jabon (Anthocephalus cadamba Roxb. Miq.) is one kind of industrial tree species that grows fast (fast growing species), as a producers of wood to meet the demands of Indonesian timber which continues to increase (Mansur and Surahman 2011). According Eichhorn and Slik (2006), Jabon has planted in Indonesia on a large scale since 1930s. Jabon consider has a relatively high annual increment about 7cm/years until 6-8 years old and will decrease to 3cm/years at age 20 years old (Pratiwi 2003).

Sengon and Jabon are a fast-growing species that have been widely planted and used in Java (Indonesia) and widely used by the pulp industry, and also for lightweight construction, furniture and wood composite materials (plywood and laminated veneer lumber (LVL)). In this condition, processing of wood with a high portion of juveniles should be able to do well so that the final product has a good quality.


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After felling the trees, one disk from log section in length of 2m (bottom part) and 6m (upper part) was taken from each tree of the tree stem. The juvenility sample disks (Figure 3) were cross cut from the middle part of the sample logs and prepared from pith to bark through using a band saw. The sample were also resawed in 2mm thick from pith to bark for specimens of density with microtomography method (specimen A) and 20mm for specimen of anatomical measurements (specimen B). Considering that distinct growth rings are absent both in Jabon and Sengon trees, segmented ring was considered to be practically useful for characterizing variation and patterns of variation along the tree radius. A specified width of segmented rings (1cm) was made from pith to bark and numbered consecutively (Figure 3).

Figure 3 Sample Preparation  

2. Density Measurement (Microtomography Method)

Density profiles from pith to bark were measured using X-ray densitometer from the Xylosciences platform of the INRA-Lorraine center in Champenoux, France. The specimen A (Figure 4) were air-dried (±12%) and scanned to estimate the air-dried wood density for each segmented ring from the pith to bark. Each segmented ring (1cm from pith to bark) was determined based on the intra-ring microdensitometric profiles. In this study, wood density is expressed in g/cm3.


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Figure 4 Sample of density measurement

3. Anatomical Measurements Preparation of thin sections

Thin sections (25µm in thickness) were prepared by using a sliding microtome equipped with a tungsten blade (Figure 5). The juvenility test specimens were inserted into microtome holder, and were sliced to produce undamaged thin slices. An undamaged thin slice was then transferred onto a slide of 7.5cm x 2.5cm that has a few drops of distilled water by using drawing brush. Safranin 1% and Blue Astra 1% were used in order to easily study the cell structure.

Figure 5 Sliding microtome with Tungsten blade

Quantitative anatomy on thin sections

Digital images of transverse sections were captured with a digital camera mounted on photonic microscope and analyzed with the ImageJ 1.47s software (http://rsb.info.nih.gov/ij/) to determine the vessel area, vessel frequency (vessel number per unit area), fiber diameter, lumen diameter and cell wall thickness for each segmented ring. Figure 6 is the picture of 1cm (one segment) sample for anatomical analysis which was captured from digital camera mounted on photonic microscope.


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a)

b). c).

Figure 7 a) ImageJ software. b) Vessel frequency measurement. c) Fiber diameter, lumen diameter and cell wall thickness measurement

Measurement of fiber length

To measure fiber length, small pieces were prepared from the test specimens by using cutter, for maceration based on FRANKLIN method with Acetic acid and Hydrogen peroxide during 48 hours in oven at 60°C. Macerated fiber suspension was placed on a standard slide of 7.5cm x 2.5cm. Safranin 1% was used for staining. Ninety fibers from macerated samples were prepared from each segmented ring and the fiber length was determined by using digital images of transverse sections captured with a digital camera mounted on photonic microscope and analyzed with the ImageJ 1.47s software (Figure 8) (http://rsb.info.nih.gov/ij/). All results were averaged for each segmented rings to comprehensively record the radial variation from pith to bark.


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Figure 8 Fiber length measurement

Data Analyzing  

Radial variation profiles of studied parameters were graphically represented from pith to bark at two different heights for each tree. Graphs representing the radial variation profile were used to check the typology of radial variation for each property. To evaluate transition location, 3 types of model were used. These models are graphically described in Figure 9.

I II III

Figure 9 Types of models used to determine transition location

 

Type I, linearly increase or decrease the pattern of properties from pith to bark showed a linear increase or decrease. Model regression linear with form:

0 20 40 60 80 100 120 140

1 2 3 4 5 6

Properties

Segmented ring

0 10 20 30 40 50 60 70 80 90

1 2 3 4 5 6 7 8

Properties

Segmented ring

0 5 10 15 20 25 30

1 2 3 4 5 6 7 8 9

Proprietes


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Y = Yi + Pi T

Type II, the pattern exhibits quick evolution in properties in the beginning followed by stabilization that can be described by an exponential form:

Y = Ym – (Ym- Yi) exp (-T/τ) Where,

Yi = the valeur of properties in first ring segment Ym = the final value of the variation curve

T = n-1, where t is number of ring segment near pith; n is number the first ring segment.

Pi = initial slope

τ = the parameter characteristic of the kinetics of the transition from juvenile wood to mature wood

To determine the transition location in sample (t), we assumed that 95% of the total varability due to age was accomplised:

(Y-Yi) = 0.95 (Ym-Yi), which gives T = 3τ and thus t = 3τ +1.

The type II model (Grezkowiak 1997) described classically juvenile-mature transition as a first order kinetics (the rate is proportional to the quantity) where increasing age acts as a dashpot. Because of this mechanistic meaning, such a model was tested as an alternative to polynomial or two segments models sometimes used (Darmawan et al. 2013).

Type III, linearly equal to intercept, the models are no adapted as the simplest model Y = Yi + Pi T (where Pi ≈ 0) fits better to data. In this last case, the pattern of properties can be assumed to be stable from pith to bark with no change.

The best fitting model is selected based on R2 adjusted criterion taking into account varying number of model parameters. The parameters of the model (fitted by minimizing the sum of squared differences) and values of R2 and R2 adjusted were calculated using the origin software.

T-test procedure has been used to give information about the different between upper part (6m) and bottom part (2m). Amplitude variation was comparison between the values of last segment and first segment.


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4 RESULTS AND DISCUSSION

RESULTS

Mean value of wood properties are given in Table 1.

Table 1 The mean value of all the properties with standard deviations

Part Sengon Jabon

Vessel

VF (n/mm2)

Upper 2.17 ± 0.489 6.13 ± 1.80 Bottom 1.80 ± 0.850 5.69 ± 1.58 VA (μm2)

Upper 35321 ±5962 18108 ± 3835 Bottom 30428 ± 11295 14960 ± 3704

Fiber

FL (µm)

Upper 1096 ± 154 1288 ± 199 Bottom 946 ± 158 1379 ± 186 FD (µm)

Upper 25.15 ± 0.97 23.19 ± 1,26 Bottom 25.58 ± 1.38 23.87 ± 1.26 LD (µm)

Upper 21.53 ± 1.06 18.63 ± 1.67 Bottom 21.67 ± 1.33 18.86 ± 1.64 CWT (µm)

Upper 1.81 ± 0.15 2.36 ± 0.35 Bottom 1.95 ± 0,14 2.50 ± 0.30 Density ρ12% (g cm-3)

Upper 0.314 ± 0.052 0.49 ± 0.080 Bottom 0.290 ± 0.038 0.50 ± 0.101 Properties are vessel features (VF vessel frequency, VA vessel area), fiber characteristics (FL fiber length, FD fiber diameter, LD lumen diameter, CWT cell wall thickness) and

ρ12 air dried density

All types of radial patterns are observed as showed in Figure 10 and Figure 11. A comprehensive presentation off all graphs obtained is given in Appendix.


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Figure 10 Radial variation of density for Sengon (left figure) and Jabon (right figure). Red corresponds to upper height and blue to bottom height. Points correspond to experimental values and dashed lines to fitted models.

Figure 11 Radial variation of cell wall thickness for Sengon. For details on legend see Figure 10.

 

Table 2 summarizes the different models selected for each property, in the two species and the two different heights. Table 3 gives the prediction of transition location when model of type II was selected. Table 4 gives the amplitude of variations.

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 2 4 6 8 10 12 14 16

Density   (g/cm3) Segmented ring Sengon 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 2 4 6 8 10 12 14 16

Density   (g/cm3) Segmented ring Jabon 0 0.5 1 1.5 2 2.5

0 2 4 6 8 10 12 14 16

Thickness

 

(µm)

Segmented ring


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Table 2 Typology of radial patterns

Sengon Jabon

Vessel

VF II U : R² = 0.70 II U : R² = 0.93 B : R² = 0.96 B : R² = 0.78 VA II U : R² = 0.90 II U : R² = 0.95 B : R² = 0.90 B : R² = 0.85

Fiber

FL II U : R² = 0.97 II U : R² = 0.99 B : R² = 0.94 B : R² = 0.98 DF III U: R² = 0.04 III U: R² = 0.06

I B : R² = 0.11 I B : R² = 0.41 DL I U : R² = 0.11 I U : R² = 0.43 III B : R2 = 0.06 I B : R² = 0.60 CWT II U : R² = 0.71 I U : R² = 0.60 I B : R² = 0.22 B : R² = 0.78 Density ρ12% II

U : R² = 0.58

I U : R² = 0.93 B : R² = 0.45 B : R² = 0.94

U = upper part; B = bottom part. I, II or III are the selected model (I: linearly increase or decrease, II exponential, III linearly equal to intercept), R² is the coefficient of determination (not adjusted), so the part of variance explained by models I or II. Only significant R² (p<0.01) are retained


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Table 3 Predicting transition location using t=3τ+1 for type II models Transition location (cm)

Sengon Jabon

Vessel

VF U 1.1 6.7

B 4.3 9.8

VA U 3.4 13.6

B 21.7 12.0

Fiber

FL U 37.3 165

B 18.3 40

DF U -- --

B -- --

DL U -- --

B -- --

CWT U 4.6 --

B -- --

Density ρ12%

U 14.1 --


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Table 4 Amplitude of variations

Amplitude of variation Sengon Jabon

Vessel

VF (n/mm2) U -1.4 -5.9

B -3.0 -4.6

VA (µm2) U 19506 11973

B 33709 11012

Fiber

FL (µm) U 463 617

B 486 576

DF (µm) U --* --*

B --* --*

DL (µm) U --* -3.4

B --* -4.0

CWT (µm) U 0.42 0.96

B --* 0.73

Density ρ12 (g cm-3)

U 0.15 0.24

B 0.10 0.31

Amplitude of variations within the range of radius when typical radial patterns are observed (models I or II). For all models, the amplitude is calculated as the difference between the property predicted for the last segmented ring and the one calculated for the first ring.


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DISCUSSION

The juvenile and mature patterns

According to literature, all the measured properties are expected to vary with typical radial patterns (Lachenbruch et al. 2011). For example, Wiemann and Williamson (1988) found that tropical pioneer angiosperm species can have very high radial variation in wood density.

Typical variations in both of species of Sengon and Jabon, for example the density near the pith is lower than the density near the bark as in many species. In the summary tables of radial trends in wood properties published in Zobel and van Buitjenen (1989), many species are noted as having radial increases, many fewer decreases. In this research, the results of density showed that the density varies linearly from each segment and has a tendency increased from pith to bark. The total surface vessel area for both of species Sengon and Jabon increased from pith to bark. This occurred because in the area near the bark, vessel cell larger with small quantity than area near bark, vessel cell smaller but higher quantity. If we calculated the total surface vessel area by number of vessel, we can obtain the larger area of vessel in mature wood. That related with Barcík et al. (2006), found out a smaller total surface area in the juvenile wood of Populus tremula than in the mature wood. The frequency of vessel cell for both of species decreased from pith to bark.

Surprisingly, we found a significant number of cases where no typical variations were observed (Type III model) especially in cell features as fiber diameter and lumen diameter.

Mature wood in such fast growth trees

In such fast growth species, it can be suspected that if transition is determined by age, mature wood (i.e. wood where property is stabilized after juvenile to mature variations) could not be observed at harvestable diameter, as 7 years old is very young. However, if it is determined by radius, it could be. To define when a significant stabilization is observed before the diameter of 40cm, a criterion is chosen as a transition location t < D°/2 (i.e. juvenile wood is only in the core of diameter D°) with the selection of a type II model.

Taking D°=30cm, according to table 2 and 3, mature wood is then observed: - For all vessels properties in both species, excepted the bottom VA

(vessel area) in Sengon - For density of Sengon,


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On the opposite, typical radial juvenile/mature patterns are observed but with a not yet reached stabilization (Type I model or Type II model with t > 15cm) in:

- Fiber length for all heights and species - Density of Jabon

- Fiber diameter of bottom logs, lumen diameter (except bottom log of Sengon), cell wall thickness except upper log of Sengon

In a similar study on fiber length and density at breast height, Darmawan

et al. (2013) concluded that all wood is juvenile in 7 years old Jabon and Sengon trees. This conclusion agrees with our results on fiber length but not on density as in our study, density reaches stabilization on Sengon. Moreover, our observations on vessel cells proved that juvenility ends early for these characteristics. Moreover, juvenile wood extent is larger in Jabon that in Sengon.

The prediction of transition location in each properties of Sengon and Jabon has been calculated (Table 3). The transition location of tree could be predicted with the mean value of the prediction of transition location in all properties that had type II. For Sengon, the mean value of the transition location all properties was 12.42 segments. For Jabon, the mean value of the transition location in all properties was 41.18 segments. The different annual increament of Sengon and Jabon in early grow and late grow was different and it can be difficult to determine the age of transition of the tree.

 

The heterogeneity of juvenile/mature

Beyond the transition kinetics, the range of variations between juvenile and mature wood is of great important for end uses. The lower the radial variations, the higher wood quality will be, whatever the transition length. For both species, the amplitude of variations ranges between 0.1 to 0.3 for air dried density, and between 460 to 620 µm for fiber length (Table 4). Lachenbruch et al. (2011) reported that juvenile wood density is commonly 10-20% lower than mature wood, whereas in some pine species (mostly hard pines), the specific gravity of outerwood can be as much as double that of corewood. Indeed, in our species, the amplitude of variations of density is large and a further question should be to test whether it is due to sylviculture and fast growth, or to specific characters of Sengon and Jabon. For fast growing and planted poplars (Populus euramericana cv I214 40cm at 22 years old), Greskowiak (1997) mentioned an amplitude of 670µm for fiber length variations. Honjo et al. (2005) mentioned variations of 500 µm for fast growing Acacia mangium. Our results are thus similar to those observed in planted and fast growth trees. However fiber length variations between 150 µm and 260 µm have been observed by Hosseini (2006) for oriental beech (Fagus orientalis) in natural forests. A further question would be to understand why fiber length variations are enhanced by fast growth.


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Comparison of transitions in bottom and upper logs

If juvenile and mature transition is determined by radius then results of the too heights will be superimposed, whereas the transition should be at a different radius if juvenile and mature transition is determined by age or distance to the crown. For vessel properties, the location t was higher in bottom logs whereas it is lower for fiber length. From these results, it can be concluded that the ageing of vessel and fiber characteristics is not governed simply by the radius, and are not controlled by the same physiological processes. The nature of juvenile and mature pattern is not unique.

Comparison of technological properties of Jabon and Sengon

From our measurements, the wood quality of the two species could be valued from i) criteria of mean values and ii) criteria of variations along the radius and between heights. Obviously, a lower quality is given by both weak properties and great variations. Industrial uses could require trade-off between mean values but variations. For example, for LVL or plywood processing, a density in the range 0.4 – 0.5 is allowed but above all, homogeneous veneers are necessary.

Procedure t-test on SPSS 16.0 has been used to give us information about the different between upper part and bottom part in all properties. The results showed that there is no significant difference between upper part and bottom part of each kind properties for both of species.

Concerning the mean values of density, Jabon had higher density and basic density than Sengon (Table 1). Martawijaya et al. (2005) found out the density of Sengon wood range from 0.24 – 0.49 g/cm3 in the average of 0.33 g/cm3, and the density of Jabon wood range from 0.29 – 0.56 g/cm3 in the average of 0.42 g/cm3. Our own samples are of lower value for Sengon, that could be explained by more juvenile trees. However, our Jabon tree is on the average. Such values classify Jabon and Sengon as very light wood, similar to poplar (Populus sp. as a french species).

Density is a basic industrial property which variations could be explained anatomically: density decreases when the fiber lumen diameter as well as the product of mean vessel area x vessel frequency increase, or when cell wall thickness decrease. In Sengon of lower density, surface vessel area and fiber lumen diameter are higher but vessel frequency as well as cell wall thickness is lower.

The fiber length of Jabon was 31% longer than Sengon. Additional properties of interests for pulp are cell wall thickness which is 28% lower in Sengon, and fiber diameter, which are quite similar.


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Criteria of fiber quality for pulp uses have been calculated (Table 5) according to Rachman and Siagian (1976). Sengon fibers rank at the highest grade I whereas Jabon is grade II.

Table 5 Fiber quality

Sengon Jabon Mean first ring bottom last ring bottom first ring upper log last ring upper log Mean first ring bottom last ring bottom first ring upper log last ring upper log

FL 1015 522 1100 766 1269 1333 974 1596 915 1543

FD 25.38 25.38 25.38 25.38 25.38 23.53 23.53 23.53 23.53 23.53 LD 21.61 21.61 21.61 21.61 21.61 18.75 21.19 17.27 18.75 18.75 CWT 1.89 1.89 1.89 0.90 1.87 2.43 2.07 2.81 1.70 2.73

Grade FL 50 25 50 25 50 50 25 50 25 50

Runkle

Ratio 0.17 0.17 0.17 0.08 0.17 0.26 0.20 0.33 0.18 0.29

Grade 100 100 100 100 100 50 100 50 100 50

Felting

Power 40.0 20.6 43.3 30.2 50.0 56.7 41.4 67.8 38.9 65.6

Grade 25 25 25 25 25 50 25 50 25 50

Flexibility

ratio 0.85 0.85 0.85 0.85 0.85 0.80 0.90 0.73 0.80 0.80

Grade 100 100 100 100 100 50 100 50 50 50

Coeff

Rigidity 0.074 0.074 0.074 0.036 0.074 0.103 0.088 0.119 0.072 0.116

Grade 100 100 100 100 100 50 100 50 100 50

Muhlstep

ratio 27.5 27.5 27.5 27.5 27.5 36.5 18.9 46.2 36.5 36.5

Grade 100 100 100 100 100 50 100 50 50 50

Total grade 475 450 475 450 475 300 450 300 350 300 Quality I II I II I II II II II II Values of fiber quality indices for Sengon and Jabon. The first columns represent mean properties,

other present the variations of quality, for the first and the last ring, and for bottom and upper logs. Fiber indices are Runkle ratio=2 CWT/LD, Felting power=FL/FD, Flexibility ratio= LD/FD, Coeff Rigidity=CWT/FD, Muhlstep ratio=100(FD²-LD²)/FD²; grades are calculated from indices; Total grade is the sum of grades for each indices and is used to determine quality (three classes I, II, III) (Rachman and Siagian, 1976). Models have been used to assess variations of properties FL, FD, LD, and CWT.


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Variations along the radius (juvenile and mature range)

Radial variations of properties have been widely discussed above. For fiber length and density which are technologically important, Jabon is more variable than Sengon (see Table 4). Concerning fiber quality for pulp uses, in Sengon, because fiber length decreases, juvenile wood is ranked in quality II, even if other criteria are not changed. In Jabon, several criteria change in juvenile wood but the total fiber quality remains always II. Concerning air dried density, juvenile wood of Sengon is below 0.2 g/cm3 which similar to the lightest commercial woods as Balsa. In Jabon, density changes from 0.33 g/cm3 which in under minimal density required for structural uses, to 0.60 g/cm3. Then, for both species, the weaker properties of the juvenile core really depreciate wood quality as Sengon is mainly produced for pulp and Jabon mainly for light structural uses.

Variations between upper and bottom parts

For both Jabon and Sengon, the value of density does not vary between upper part and bottom part. Jabon and Sengon are kind of diffuse-porous species. Based on Okkonen et al. (1972) for most diffuse porous species, specific gravity does not change with height.

Fiber length varies differently in the two species: in Sengon wood, the fiber length in up part was higher than the bottom part. Whereas in Jabon wood, the fiber length bottom part was higher than the up part. As we known, within the tree fiber properties gradually increased from base to top to certain height and finally decreased at the top. Bhat et al. (1990) reported that fiber length of

Eucalyptus grandis increased from stump level to 25% of tree height level and then decreased toward to the top. Other fiber criteria do not vary with height.


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5 CONCLUSIONS

Density, vessel area and fiber length increase from pith to bark for both species. On the contrary, vessel frequency decreases, and the variable more stable are fiber diameter, lumen diameter and thickness cell wall. Stabilization was observed in vessel area, vessel frequency and in density, but not in fiber length which continued to increase quite linearly. Moreover, juvenile and mature patterns at different heights depend on species and properties, so that it could not be concluded that juvenile mature transition is governed by age or distance to crown. Based on fiber quality, Sengon is the highest quality for pulp. In both case, juvenile core depreciates strongly quality class.

Further research would be conducted to determine whether wood quality could be control by sylviculture, for instance by tree breeding programs or fertilization. Moreover, studies of larger tree samples according to climate or soil will be useful to know what conditions would be more favorable. Other solutions in wood industries would be to promote sorting of veneers or chips into different categories according to position (core or outer wood). Then homogeneous quality could be produced. The lower core quality could be improved by treatments, such as impregnation.


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References

Adamopoulos S, Passialis C, Voulgaridis E. 2007. Strength properties of juvenile and mature wood in black locust (Robinia pseudoacacia). Wood and Fiber Science 39 (2): 241-249.

Bao FC, Jiang ZH, Jiang XM, Lu XX, Luo XQ, Zhang SY. 2001. Differences in wood properties between juvenile wood and mature wood in 10 species grown in China. Wood Science and Technology 35 (4): 363-375.

Barcík Š, Kotlínová M, Pivolusková E, Ma. Kovická-Paulínyová J. 2006. Vplyv f yzikálno-mechanických vlastností juvenilného topolového dreva na energetickú náročnosť pri rovinnom frézovaní. In: rieskové a beztrieskové obrábanie dreva 2006. Starý Smokovec-Tatry, Zvolen, Vydavateľstvo TU vo Zvolene: 37–42.

Bath KM, Bath KV, Dharmodaran TK. 1990. Wood density and fiber length of

Eucalyptus grandis grown in Kerala, India. Wood and Fibre Science (22): 54-61.

Clark A, Richard F, Daniels, Jordan L. 2006. Juvenile mature wood transition in loblolly pine as defined by annual ring specific gravity, proportion of latewood, and microfibril angle. Wood and Fiber Science 38 (2): 292-299. Darmawan W, Nandika D, Rahayu I, Fournier M, Marchal R. 2013.

Determination of juvenile and mature transition ring for fast growing sengon and jabon wood. Journal the Indian of Academy of Wood Science

2013: 1-9.

Eichhorn KAO, Slik JWF. 2006. The plant community of Sungai Wain, East Kalimantan, Indonesia: Phytogeographical status and local variation.

Blumea Supplement 18: 15-35.

Evans J, Senft JF, Green DW. 2000. Juvenile wood effect in red alder: Analysis of physical and mechanical data to delineate juvenile and mature wood zones, Forest Products Journal (50): 75–87.

Greskowiak V. 1997. Le bois juvenile de deux Angiospermes à pores diffus (Populus euramericana cv I214, Dicorynia guianensis): Variations radiales et avec la hauteur des caractéres anatomiques, de l’infradensité et du retrait axial. Ecole Nationale du Genie Rural, des Eaux et Forets Centre de Montpellier [disertation]. ENGREF (France): AgroParisTech.

Gryc V, Vavrcik H, Horn K. 2011. Density of juvenile and mature wood of selected coniferous species. Journal of Forest Science 57 (3): 123–130. Honjo K, Furukawa I, Sahri MH. 2005. Radial Variation of Fibre Length


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Hosseini SZ. 2006. The effect of altitude on juvenile wood formation and fiber length, a case study in Iranian beech wood (Fagus orientalis L.). Agric. Science Technology (8): 221-231.

Koubaa A, Isabel N, Shu YZ, Beaulieu J, Bousquet J. 2005. Transition from juvenile to mature wood in black spruce (Picea Mariana (MILL.). Wood and Fiber Science 37 (3): 445-455.

Lachenbruch B, Moore J, Evans R. 2011. Radial variation in wood structure and function in woody plants and hypotheses for its occurence p.121-164 in FC Meinzer, B. Lachenbruch, TE Dawson, Eds, Size and age related changes in tree structure and function, Springer, Dordrecht.

Mansur I, Surahman. 2011. The growth of jabon (Anthocephalus cadamba Roxb. Miq.) in less optimum environment and its respons to fertilizer application.

Silvikultur Tropika 3 (1): 71-77.

Martawijya A, Kartasujana I, Kadir K, Prawira S. 2005. Atlas kayu Indonesia. Forest Products Research Institute, Bogor

National Statistic Biro. 2004. Potensi hutan rakyat Indonesia 2003. Pusat inventarisasi dan statistika kehutanan. Departemen Kehutanan dan Direktorat Statistika Pertanian Badan Statistika Nasional, Jakarta. Indonesia. Okkonen EA, Wahlgren HE, Maeglin RR. 1972. Relationships of specific gravity to tree height in commercially important species. Forest Product Journal 22 (7): 37-41.

Panshin AJ, De Zeeuw C. 1980. Textbook of wood technology: Structure, identification, properties and uses of the commercial woods of the United States and Canada, 4rd ed. McGraw-Hill, New York. NY.

Pratiwi. 2003. Prospek pohon jabon untuk pengembangan hutan tanaman. Bogor:

Buletin Penelitian dan Pengembangan Kehutanan 4 (1): 61-66.

Rachman AN, Siagian RM. 1976. Dimensi Serat Jenis Kayu Indonesia Bagian III (Fiber dimension in Indonesian wood species) III. Bogor. Laporan LPHH No 75.

Wiemann MC, Williamson GB. 1988. Extreme radial changes in wood specific gravity in some tropical pioneers. Wood and Fibre Science 20: 344-349. Zobel BJ, Van Buijtenen JP. 1989. Wood variation: its causes and control.


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Appendixes

1.

Graph Density Vessel area 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 2 4 6 8 10 12 14 16

Densi ty ( g/ cm 3) Segmented Ring Sengon 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 2 4 6 8 10 12 14 16

Den sity (g /cm 3) Segmented Ring Jabon 0 10000 20000 30000 40000 50000 60000

0 2 4 6 8 10 12 14 16

Area (µm 2) Segmented Ring Sengon  0 10000 20000 30000 40000 50000 60000

0 2 4 6 8 10 12 14 16

Area (µm

2)

Segmented Ring


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Vessel frequency

Cell wall thickness

Fiber diameter 0 2 4 6 8 10 12

0 2 4 6 8 10 12 14 16

Frequence (n/ m m 2) Segmented Ring Sengon  0 2 4 6 8 10 12

0 2 4 6 8 10 12 14 16

Frequence (n/ m m 2) Segmented Ring Jabon  0 0.5 1 1.5 2 2.5 3 3.5 4

0 2 4 6 8 10 12 14 16

Thi ckness (µm ) Segmented Ring Sengon  0 0.5 1 1.5 2 2.5 3 3.5 4

0 2 4 6 8 10 12 14 16

Thi ckness (µm ) Segmented Ring Jabon 0 5 10 15 20 25 30 35

0 2 4 6 8 10 12 14 16

Diam eter (µm ) Segmented Ring Sengon  0 5 10 15 20 25 30 35

0 2 4 6 8 10 12 14 16

Diam

ater (µm

)

Segmented Ring


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Lumen diameter Fiber length 0 5 10 15 20 25 30 35

0 2 4 6 8 10 12 14 16

Diam ater (µm ) Segmented Ring Sengon  0 5 10 15 20 25 30 35

0 2 4 6 8 10 12 14 16

Diam eter (µm ) Segmented Ring Jabon  0 200 400 600 800 1000 1200 1400 1600 1800 2000

0 2 4 6 8 10 12 14 16

Lengt h (µm ) Segmented Ring Jabon 0 200 400 600 800 1000 1200 1400 1600

0 2 4 6 8 10 12 14 16

Lengt

h (µm

)

Segmented Ring Sengon


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2.

Modelisation Graph Density Vessel area Vessel frequency 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 2 4 6 8 10 12 14 16

Den sity (g /cm 3) Segmented ring Sengon 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 2 4 6 8 10 12 14 16

Den sity (g /cm 3) Segmented ring Jabon 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000

0 2 4 6 8 10 12 14 16

area (µm 2) Segmented ring Sengon 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000

0 2 4 6 8 10 12 14 16

area (µm 2) Segmented ring Jabon 0 2 4 6 8 10 12

0 2 4 6 8 10 12 14 16

Frequence (n/ m m 2) Segmented ring Sengon 0 2 4 6 8 10 12

0 2 4 6 8 10 12 14 16

Frequence (n/ m m 2) Segmented ring Jabon


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Thickness cell wall Fiber diameter Lumen diameter 0 0.5 1 1.5 2 2.5 3 3.5

0 2 4 6 8 10 12 14 16

Thickness   (µm) Segmented ring Sengon 0 0.5 1 1.5 2 2.5 3 3.5

0 2 4 6 8 10 12 14 16

Thickness   (µm) Segmented ring Jabon 0 5 10 15 20 25 30

0 2 4 6 8 10 12 14 16

Diameter   (µm) Segmented ring Sengon 0 5 10 15 20 25 30

0 2 4 6 8 10 12 14 16

Diameter   (µm) Segmented ring Jabon 0 5 10 15 20 25 30

0 2 4 6 8 10 12 14 16

Diam eter (µm ) Segmented ring Sengon 0 5 10 15 20 25 30

0 2 4 6 8 10 12 14 16

Diam

eter (µm

)

Segmented ring Jabon


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Fiber Length

0 200 400 600 800 1000 1200 1400 1600 1800

0 2 4 6 8 10 12 14 16

Lengt

h (µm

)

Segmented ring

Sengon

0 200 400 600 800 1000 1200 1400 1600 1800

0 2 4 6 8 10 12 14 16

Lengt

h (µm

)

Segmented ring


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3.

Statistical analyzing: T-test 1. Jabon

a. Cell wall thickness

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Cell_wall_thickness Upper part 12 2,3588 ,35573 ,10269

Bottom part 12 2,4743 ,29557 ,08532

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Cell_wall_thickness Equal variances assumed ,629 ,436 -,865 22 ,396 -,11547 ,13351 -,39235 ,16141

Equal variances not assumed -,865 21,286 ,397 -,11547 ,13351 -,39289 ,16195

b. Density

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Density Upper part 12 ,4824 ,06501 ,01877

Bottom part 12 ,4962 ,08511 ,02457


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Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Density Equal variances assumed 1,833 ,190 -,445 22 ,661 -,01375 ,03092 -,07787 ,05037

Equal variances not assumed -,445 20,577 ,661 -,01375 ,03092 -,07812 ,05062

c. Fiber diameter

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Fiber_diameter Upper part 12 23,4403 1,01477 ,29294

Bottom part 12 24,0626 1,15569 ,33362

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Fiber_diameter Equal variances assumed ,130 ,722 -1,402 22 ,175 -,62234 ,44398 -1,54309 ,29841


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d. Fiber length

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Fiber_length Upper part 12 1,2899E3 166,41153 48,03887

Bottom part 12 1,3880E3 161,73066 46,68762

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Fiber_length Equal variances assumed ,086 ,772 -1,464 22 ,157 -98,05433 66,98856 -236,98010 40,87144

Equal variances not assumed -1,464 21,982 ,157 -98,05433 66,98856 -236,98665 40,87799

e. Lumen diameter

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Lumen_diameter Upper part 12 18,8967 1,39946 ,40399

Bottom part 12 19,1140 1,46670 ,42340


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Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Lumen_diameter Equal variances assumed ,015 ,903 -,371 22 ,714 -,21729 ,58522 -1,43095 ,99638

Equal variances not assumed -,371 21,952 ,714 -,21729 ,58522 -1,43110 ,99653

f. Vessel area

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Vessel_area Upper part 12 1,8570E4 2836,68515 818,88047

Bottom part 12 1,5460E4 3149,08523 909,06260

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Mean_vessel_area Equal variances assumed ,167 ,686 2,542 22 ,019 3110,09804 1223,50318 572,70774 5647,48833


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g. Vessel frequency

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Vessel_frequency Upper part 12 5,7576 1,06257 ,30674

Bottom part 12 5,4646 1,44671 ,41763

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Vessel_frequency Equal variances assumed ,756 ,394 ,565 22 ,577 ,29300 ,51817 -,78162 1,36762

Equal variances not assumed ,565 20,193 ,578 ,29300 ,51817 -,78723 1,37323

2. Sengon

a. Cell wall thickness

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Cell_wall_thickness Upper part 12 1,8065 ,14985 ,04326

Bottom part 12 1,9593 ,12298 ,03550


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Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Cell_wall_thickness Equal variances assumed ,045 ,834 -2,731 22 ,012 -,15283 ,05596 -,26888 -,03677

Equal variances not assumed -2,731 21,193 ,012 -,15283 ,05596 -,26914 -,03652

b. Density

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Density Upper part 12 ,3138 ,05096 ,01471

Bottom part 12 ,2921 ,03488 ,01007

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Density Equal variances assumed 2,160 ,156 1,220 22 ,235 ,02175 ,01783 -,01522 ,05872


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c. Fiber diameter

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Fiber_diameter Upper part 12 25,1456 ,97171 ,28051

Bottom part 12 25,7088 1,43561 ,41442

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Fiber_diameter Equal variances assumed ,363 ,553 -1,125 22 ,273 -,56313 ,50043 -1,60096 ,47470

Equal variances not assumed -1,125 19,331 ,274 -,56313 ,50043 -1,60933 ,48308

d. Fiber length

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Fiber_length Upper part 12 1,0956E3 153,75922 44,38646

Bottom part 12 9,5436E2 122,87455 35,47083


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Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Fiber_length Equal variances assumed 1,151 ,295 2,486 22 ,021 141,26718 56,81846 23,43290 259,10146

Equal variances not assumed 2,486 20,980 ,021 141,26718 56,81846 23,09972 259,43464

e. Lumen diameter

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Lumen_diameter Upper part 12 21,5327 1,05605 ,30486

Bottom part 12 21,7901 1,40650 ,40602

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Lumen_diamete r

Equal variances assumed ,317 ,579 -,507 22 ,617 -,25747 ,50773 -1,31044 ,79550


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f. Vessel area

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Vessel_area Upper part 12 3,5321E4 5962,37399 1721,18911

Bottom part 12 3,1547E4 9845,02466 2842,01382

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Mean_vessel_area Equal variances assumed 6,262 ,020 1,136 22 ,268 3773,90794 3322,57950 -3116,70019 10664,51608

Equal variances not assumed 1,136 18,112 ,271 3773,90794 3322,57950 -3203,47037 10751,28626

g. Vessel frequency

Group Statistics

Part N Mean Std. Deviation Std. Error Mean

Vessel_frequency Upper part 12 2,1696 ,48933 ,14126

Bottom part 12 1,6340 ,34382 ,09925


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Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper

Vessel_frequency Equal variances assumed ,390 ,539 3,103 22 ,005 ,53563 ,17264 ,17760 ,89367


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CURRICULUM VITAE

Esi Fajriani was born on September 09, 1989 in Jambi, Indonesia. She is 4th

child from 5 children from Mr. Amlis and Mrs. Nurhayati. She attended high school at SMA Negeri 1 Kota Jambi, where she grew up. She received her Bachelor of Forestry in Forest Products Technology Department, Faculty of Forestry, Bogor Agricultural University in 2011. She gets a scholarship from Indonesian Ministry of Education “Beasiswa Unggulan” to continue her Master degree at Bogor Agricultural University and AgroParisTech ENGREF, Nancy, France in Double Degree Programme.

An article entitled Radial Variation of Wood Properties of Sengon

(Paraserianthes falcataria) and Jabon (Anthocephalus cadamba) has been

accepted in Journal of the Indian Academic of Wood science in 19 November 2013.


(1)

Independent Samples Test Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference Lower Upper Cell_wall_thickness Equal variances assumed ,045 ,834 -2,731 22 ,012 -,15283 ,05596 -,26888 -,03677

Equal variances not assumed -2,731 21,193 ,012 -,15283 ,05596 -,26914 -,03652

b.

Density

Group Statistics

Part N Mean Std. Deviation Std. Error Mean Density Upper part 12 ,3138 ,05096 ,01471

Bottom part 12 ,2921 ,03488 ,01007

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference Lower Upper Density Equal variances assumed 2,160 ,156 1,220 22 ,235 ,02175 ,01783 -,01522 ,05872 Equal variances not assumed 1,220 19,452 ,237 ,02175 ,01783 -,01550 ,05900


(2)

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference Lower Upper Fiber_diameter Equal variances assumed ,363 ,553 -1,125 22 ,273 -,56313 ,50043 -1,60096 ,47470 Equal variances not assumed -1,125 19,331 ,274 -,56313 ,50043 -1,60933 ,48308

d.

Fiber length

Group Statistics

Part N Mean Std. Deviation Std. Error Mean Fiber_length Upper part 12 1,0956E3 153,75922 44,38646

Bottom part 12 9,5436E2 122,87455 35,47083


(3)

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed) Mean Difference Std. Error Difference

95% Confidence Interval of the Difference Lower Upper Fiber_length Equal variances assumed 1,151 ,295 2,486 22 ,021 141,26718 56,81846 23,43290 259,10146

Equal variances not assumed 2,486 20,980 ,021 141,26718 56,81846 23,09972 259,43464

e.

Lumen diameter

Group Statistics

Part N Mean Std. Deviation Std. Error Mean Lumen_diameter Upper part 12 21,5327 1,05605 ,30486

Bottom part 12 21,7901 1,40650 ,40602

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed) Mean Difference Std. Error Difference

95% Confidence Interval of the Difference

Lower Upper Lumen_diamete

r

Equal variances assumed ,317 ,579 -,507 22 ,617 -,25747 ,50773 -1,31044 ,79550 Equal variances not assumed -,507 20,411 ,618 -,25747 ,50773 -1,31521 ,80027


(4)

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference Lower Upper Mean_vessel_area Equal variances assumed 6,262 ,020 1,136 22 ,268 3773,90794 3322,57950 -3116,70019 10664,51608

Equal variances not assumed 1,136 18,112 ,271 3773,90794 3322,57950 -3203,47037 10751,28626

g.

Vessel frequency

Group Statistics

Part N Mean Std. Deviation Std. Error Mean Vessel_frequency Upper part 12 2,1696 ,48933 ,14126

Bottom part 12 1,6340 ,34382 ,09925


(5)

Independent Samples Test

Levene's Test for

Equality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference Lower Upper Vessel_frequency Equal variances assumed ,390 ,539 3,103 22 ,005 ,53563 ,17264 ,17760 ,89367 Equal variances not assumed 3,103 19,733 ,006 ,53563 ,17264 ,17520 ,89607


(6)

Esi Fajriani was born on September 09, 1989 in Jambi, Indonesia. She is 4

th

child from 5 children from Mr. Amlis and Mrs. Nurhayati. She attended high

school at SMA Negeri 1 Kota Jambi, where she grew up. She received her

Bachelor of Forestry in Forest Products Technology Department, Faculty of

Forestry, Bogor Agricultural University in 2011. She gets a scholarship from

Indonesian Ministry of Education “Beasiswa Unggulan” to continue her Master

degree at Bogor Agricultural University and AgroParisTech ENGREF, Nancy,

France in Double Degree Programme.

An article entitled Radial Variation of Wood Properties of Sengon

(

Paraserianthes falcataria

) and Jabon (A

nthocephalus cadamba

) has been

accepted in Journal of the Indian Academic of Wood science in 19 November

2013.