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.govij 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.
area, step
Figure 6 ImageJ 1
, fiber diam for using Im
One segme 1.47s softw
meter, lumen mageJ 1.47s
ent sample f ware has bee
n diameter a s software.
for anatomi en used to m
and cell wa cal analysis
measure ves all thickness
s ssel frequen
s. Figure 7 ncy, vessel
shown the
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.govij . All results were averaged for each segmented rings to
comprehensively record the radial variation from pith to bark.
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:
20 40
60 80
100 120
140
1 2
3 4
5 6
Properties
Segmented ring
10 20
30 40
50 60
70 80
90
1 2 3 4 5 6 7 8
Properties
Segmented ring
5 10
15 20
25 30
1 2 3 4 5 6 7 8 9
Proprietes
Segmented ring
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 = 3 τ 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 R
2
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 R
2
and R
2
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.
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 nmm
2
Upper 2.17 ± 0.489
6.13 ± 1.80 Bottom
1.80 ± 0.850 5.69 ± 1.58
VA μm
2
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
ρ
12
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
ρ
12
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.
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.
0.1 0.2
0.3 0.4
0.5 0.6
0.7
2 4
6 8
10 12
14 16
Density gcm3
Segmented ring
Sengon
0.1 0.2
0.3 0.4
0.5 0.6
0.7
2 4
6 8
10 12
14 16
Density gcm3
Segmented ring
Jabon
0.5 1
1.5 2
2.5
2 4
6 8
10 12
14 16
Thickness µm
Segmented ring
Sengon
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 : R
2
= 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 ρ
12
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 p0.01 are retained
Table 3 Predicting transition location using t=3 τ+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
ρ
12
U 14.1 --
B 7.0 --
Table 4 Amplitude of variations Amplitude of variation
Sengon Jabon
Vessel VF nmm
2
U -1.4 -5.9
B -3.0 -4.6
VA µm
2
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 ρ
12
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.
not calculated because type III
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,
- For CWT cell wall thickness in upper logs of Sengon
On the opposite, typical radial juvenilemature 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 juvenilemature 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.
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 gcm
3
in the average of 0.33 gcm
3
, and the density of Jabon wood range from 0.29 – 0.56 gcm
3
in the average of 0.42 gcm
3
. 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.
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 CWTLD, Felting power=FLFD, Flexibility ratio= LDFD, Coeff Rigidity=CWTFD, Muhlstep ratio=100FD²-LD²FD²; 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.
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 gcm
3
which similar to the lightest commercial woods as Balsa. In Jabon, density changes from 0.33 gcm
3
which in under minimal density required for structural uses, to 0.60 gcm
3
. 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.
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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Appendixes
1.
Graph
Density
Vessel area
0.1 0.2
0.3 0.4
0.5 0.6
0.7 0.8
2 4
6 8
10 12
14 16
Densi ty
g cm
3
Segmented Ring
Sengon
0.1 0.2
0.3 0.4
0.5 0.6
0.7 0.8
2 4
6 8
10 12
14 16
Den sity g
cm
3
Segmented Ring
Jabon
10000 20000
30000 40000
50000 60000
2 4
6 8
10 12
14 16
Area µm
2
Segmented Ring
Sengon
10000 20000
30000 40000
50000 60000
2 4
6 8
10 12 14 16 Area µm
2
Segmented Ring
Jabon
Vessel frequency
Cell wall thickness
Fiber diameter
2 4
6 8
10 12
2 4
6 8
10 12
14 16
Frequence n m
m
2
Segmented Ring
Sengon
2 4
6 8
10 12
2 4
6 8
10 12
14 16
Frequence n m
m
2
Segmented Ring
Jabon
0.5 1
1.5 2
2.5 3
3.5 4
2 4
6 8
10 12
14 16
Thi ckness µm
Segmented Ring
Sengon
0.5 1
1.5 2
2.5 3
3.5 4
2 4
6 8
10 12
14 16
Thi ckness µm
Segmented Ring
Jabon
5 10
15 20
25 30
35
2 4
6 8
10 12
14 16
Diam eter µm
Segmented Ring
Sengon
5 10
15 20
25 30
35
2 4
6 8
10 12
14 16
Diam ater µm
Segmented Ring
Jabon
Lumen diameter
Fiber length
5 10
15 20
25 30
35
2 4
6 8
10 12
14 16
Diam ater µm
Segmented Ring
Sengon
5 10
15 20
25 30
35
2 4
6 8
10 12
14 16
Diam eter µm
Segmented Ring
Jabon
200 400
600 800
1000 1200
1400 1600
1800 2000
2 4
6 8
10 12
14 16
Lengt h µm
Segmented Ring
Jabon
200 400
600 800
1000 1200
1400 1600
2 4
6 8
10 12
14 16
Lengt h µm
Segmented Ring
Sengon
2.
Modelisation Graph Density
Vessel area
Vessel frequency
0.1 0.2
0.3 0.4
0.5 0.6
0.7
2 4
6 8
10 12
14 16
Den sity g
cm
3
Segmented ring
Sengon
0.1 0.2
0.3 0.4
0.5 0.6
0.7
2 4
6 8
10 12
14 16
Den sity g
cm
3
Segmented ring
Jabon
5000 10000
15000 20000
25000 30000
35000 40000
45000 50000
2 4
6 8
10 12 14 16 area µm
2
Segmented ring
Sengon
5000 10000
15000 20000
25000 30000
35000 40000
45000 50000
2 4
6 8
10 12 14 16 area µm
2
Segmented ring
Jabon
2 4
6 8
10 12
2 4
6 8
10 12
14 16
Frequence n m
m
2
Segmented ring
Sengon
2 4
6 8
10 12
2 4
6 8
10 12
14 16
Frequence n m
m
2
Segmented ring
Jabon
Thickness cell wall
Fiber diameter
Lumen diameter
0.5 1
1.5 2
2.5 3
3.5
2 4
6 8
10 12
14 16
Thickness µm
Segmented ring
Sengon
0.5 1
1.5 2
2.5 3
3.5
2 4
6 8
10 12
14 16
Thickness µm
Segmented ring
Jabon
5 10
15 20
25 30
2 4
6 8
10 12
14 16
Diameter µm
Segmented ring
Sengon
5 10
15 20
25 30
2 4
6 8
10 12
14 16
Diameter µm
Segmented ring
Jabon
5 10
15 20
25 30
2 4
6 8
10 12
14 16
Diam eter µm
Segmented ring
Sengon
5 10
15 20
25 30
2 4
6 8
10 12
14 16
Diam eter µm
Segmented ring
Jabon
Fiber Length
200 400
600 800
1000 1200
1400 1600
1800
2 4
6 8
10 12
14 16
Lengt h µm
Segmented ring
Sengon
200 400
600 800
1000 1200
1400 1600
1800
2 4
6 8
10 12
14 16
Lengt h µm
Segmented ring
Jabon
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
Levenes 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
32
Independent Samples Test
Levenes 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
Levenes 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 Equal variances not assumed
-1,402 21,638
,175 -,62234
,44398 -1,54398
,29930 33
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
Levenes 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
34
Independent Samples Test
Levenes 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
Levenes 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 Equal variances not assumed
2,542 21,764
,019 3110,09804
1223,50318 571,11260 5649,08347
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
Levenes 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
