Genetic diversity of rosewood (Dalbergia latifolia) in Yogyakarta, Indonesia for plus trees selection

Abstract

Riastiwi I, Witjaksono, Ratnadewi D, Siregar UJ. 2022. Genetic diversity of rosewood (Dalbergia latifolia) in Yogyakarta, Indonesia for plus trees selection. Biodiversitas 23: 2630-2639. Rosewood (Dalbergia latifolia Roxb.) or sonokeling is an important woody plant species with a high selling value. However, due to overexploitation, this species has been listed in Appendix II of CITES and its trade is strictly regulated. Therefore, the cultivation of this plant needs encouragement, and superior planting materials from selected plus trees are needed. This study aimed to examine the genetic diversity of the rosewood population and select plus trees in Yogyakarta Province, Indonesia. The plus tree selection was performed by comparing plus tree candidates with five other trees nearby in four districts, i.e. Bantul, Gunungkidul, Kulon Progo, and Sleman. As many as 61 plus tree candidates have been identified. Genetic diversity was assessed using 10 selected ISSR primers, resulting in 101 ISSR loci with average Polymorphic Loci values ??of 64.71% and Nei Heterozygosity of 0.23. The highest gene diversity (He=0.29) was found in the Kulon Progo population, and the lowest He=0.17 was in the Bantul population. The dendogram and PCA analysis put Gunungkidul and Bantul populations into one group, separated from the Sleman and Kulon Progo populations. Based on morphological and molecular analysis, six superior plus trees were obtained.

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B I O D I V E R S I T A S
ISSN: 1412-033X
Volume 23, Number 5, May 2022 E-ISSN: 2085-4722
Pages: 2630-2639 DOI: 10.13057/biodiv/d230546
Genetic diversity of rosewood (Dalbergia latifolia) in Yogyakarta,
Indonesia for plus trees selection
INDIRA RIASTIWI1,2, WITJAKSONO1, DIAH RATNADEWI2, ULFAH JUNIARTI SIREGAR3,♥
1Research Center for Genetic Engineering, Research Organization for Life Sciences and Environment, National Research and Innovation Agency. Jl.
Raya Jakarta-Bogor Km 46, Cibinong, Bogor 16911, West Java, Indonesia
2Department of Biology, Faculty of Mathematics and Natural Sciences, Institut Pertanian Bogor. Jl. Meranti, IPB University Campus Dramaga, Bogor
16680, West Java, Indonesia
3Department of Silviculture, Faculty of Forestry and Environment, Institut Pertanian Bogor. Jl. Agatis, IPB University Campus Dramaga, Bogor 16680,
West Java, Indonesia. Tel.: +62-251-8626806, Fax.: +62-251-8626886, ♥ email: ulfahjs@apps.ipb.ac.id
Manuscript received: 29 March 2022. Revision accepted: 27 April 2022.
Abstract. Riastiwi I, Witjaksono, Ratnadewi D, Siregar UJ. 2022. Genetic diversity of rosewood (Dalbergia latifolia) in Yogyakarta,
Indonesia for plus trees selection. Biodiversitas 23: 2630-2639. Rosewood (Dalbergia latifolia Roxb.) or sonokeling is an important
woody plant species with a high selling value. However, due to overexploitation, this species has been listed in Appendix II of CITES
and its trade is strictly regulated. Therefore, the cultivation of this plant needs encouragement, and superior planting materials from
selected plus trees are needed. This study aimed to examine the genetic diversity of the rosewood population and select plus trees in
Yogyakarta Province, Indonesia. The plus tree selection was performed by comparing plus tree candidates with five other trees nearby in
four districts, i.e. Bantul, Gunungkidul, Kulon Progo, and Sleman. As many as 61 plus tree candidates have been identified. Genetic
diversity was assessed using 10 selected ISSR primers, resulting in 101 ISSR loci with average Polymorphic Loci values of 64.71% and
Nei Heterozygosity of 0.23. The highest gene diversity (He=0.29) was found in the Kulon Progo population, and the lowest He=0.17
was in the Bantul population. The dendogram and PCA analysis put Gunungkidul and Bantul populations into one group, separated from
the Sleman and Kulon Progo populations. Based on morphological and molecular analysis, six superior plus trees were obtained.
Keywords: Genetic diversity, ISSR, plus trees, rosewood
Abbreviations: ISSR: Inter Simple Sequence Repeat, He: Expected Heterozygosity, PPL: Percentage of Polymorphic Loci, KL: Kulon
Progo, BL: Bantul, SL: Sleman, GK: Gunungkidul, CITES: Convention of International Trade of Endangered Species
INTRODUCTION
Rosewood (Dalbergia latifolia Roxb.) or sonokeling of
Fabaceae (Papilionoideae) was introduced to Indonesia,
originating from India (Adema et al. 2016). Rosewood is
distributed in Java, West Nusa Tenggara, South Sumatra,
Sulawesi, Timor Island (Yulita et al. 2020). One of the
rosewood production centers in Indonesia is D. I.
Yogyakarta (DIY), where trees are cultivated by local
communities on a small scale in their yard and field as
community forests. However, large trees are hardly found
in Java (Dwianto et al. 2019). The global rosewood
population is currently facing the threat of extinction due to
overharvesting (Hanifah 2022), that since 2015 the tree
species have been listed in Appendix II of CITES
(Convention on International Trade in Endangered Species).
In nature, rosewood reproduces by seed or by
adventitious shoots growing from roots. Rosewood seeds
have a low germination rate, only around 30-40% (Prawirohatmodjo
et al. 1994). In Yogyakarta, Central Java-Indonesia,
rosewood trees were reported to flower but not produce
fruits and seeds. In those areas, people propagate rosewood
using root cuttings. Rosewood roots of 5-20 cm in length
were used as cuttings materials (Vasudevan et al. 2020).
This reproductive system would affect the distribution
pattern of the genetic diversity of a population.
Knowledge of the genetic diversity of a plant
population is needed for tree breeding, especially to select
the parent trees or plus trees. The selection of plus trees is
vital for seed and clonal seed sources and as parents in
plant breeding. The plus trees were selected based on their
best phenotypic appearance compared to surrounding trees,
while considering their diverse genetic background.
Therefore greater genetic diversity of the population is
preferable in order to include as many as possible different
genetic background in the selected plus trees. This is
important aspect as monoculture systems with narrow
genetic diversity made trees more susceptible to pests and
diseases (Liu et al. 2018; Crowther et al. 2020). Research
on plus trees has previously been carried out in
Paraserianthes falcataria resulting from mutation by
gamma irradiation (Zakiyah et al. 2017).
The genetic diversity of a plant population can be
studied using molecular markers. The molecular marker
Inter Simple Sequence Repeat (ISSR) has become a
popular tool in the study of plant population genetics
(Abdelaziz et al. 2020; Li et al. 2020, Sheikh et al. 2021;
Shakoor et al. 2022; Samarina et al. 2022). The genetic
diversity of Dalbergia was studied using several molecular
markers, for example ISSR (Hien and Phong 2012; Javaid

RIASTIWI et al. – Genetic diversity of rosewood in Yogyakarta, Indonesia
2631
et al. 2014; Fatima et al. 2018a; Fatima et al. 2018b; Bal
and Panda 2018; Ijaz et al. 2019; Junior et al. 2020),
Random Amplified Polymorphic DNA (RAPD) (Bal and
Panda 2018; Dobhal et al. 2019; Tewari et al. 2022), and
Sequence Related Amplified Polymorphism (SRAP)
(Yulita et al. 2020). This research aimed to study genetic
diversity of four rosewood population in Yogyakarta using
ISSR marker, and identify plus trees based on their
morphological traits as sources of propagation and for their
breeding program.
MATERIALS AND METHODS
This research was carried out in 2 stages. Firstly, the
exploration and identification of plus tree candidates.
Secondly, the genetic diversity analysis among the
populations of plus tree candidates using ISSR to determine
the best plus trees with high genetic diversity.
Plus tree selection
Exploration of plus trees was carried out in four
districts in Yogyakarta Province, Indonesia, i.e., Bantul,
Gunungkidul, Kulon Progo, and Sleman (Figure 1), by
walking along the roads in the villages and visiting the
community forests where rosewood trees were planted
among the other trees (Figure 2). When a rosewood tree
was identified, the tree was marked. After finding six or
more trees, the one that visually has the best morphology
was identified as a plus tree candidate and was compared
with five other surrounding rosewood trees. Plus tree
candidate was determined through an assessment using a
scoring system modified from the method developed by
Hidayat (2010) for Toona sinensis.
The complete scoring system is shown in Table 1. The
score of a plus tree for height and diameter was calculated
from the average score of the five comparison trees. The
total score of a plus tree was the numerical sum of tree
growth variables which included tree height, branch-free
plant height (TBBC), trunk diameter at breast height, tree
height score, trunk diameter score, straightness score,
canopy condition score, and tree health score. The
candidate plus trees frequency distribution was calculated
using Phyton Software (Liu et al. 2021).
Table 1. The complete plus tree candidate scoring system
developed for rosewood tree*
Morphological characters
and tree health
Evaluation system
Score
Tree height
<105%
4
105%-110%
5
111-115%
12
116-120%
16
>121%
20
Diameter at chest height
<105%
5
105%-110%
7
111-115%
17
116-120%
23
>121%
30
Stand straightness
Not straight
0
Straightness < 20%
1
Straightness 25%
2
Straightness 50%
3
Straightness 75 %
4
Straightness
5
Canopy condition
Damage >80%)
0
Damage >60%
1
Damage <50%
2
Damage <40%
3
Damage <30%
4
Damage<20%
(healthy and balance)
5
Tree health
Damage >80%)
0
Damage >60%
1
Damage <50%
2
Damage <40%
3
Damage <30%
4
Damage <20%
(healthy and balance)
5
Note: *modified from Hidayat (2010)
Figure 1. Location map of the study areas in Yogyakarta Province, Indonesia for plus trees selection and genetic diversity of rosewood

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Figure 2. The habitat of the sampling tree of rosewood. A. Dryfield, B. Homegarden
Molecular work
Leaf samples were taken for molecular analysis from
the selected plus tree candidates. Samples of 3-5 young
leaves were stored in a tightly closed plastic box containing
silica gel. Genomic DNA was isolated by grinding the 0.2 g
leaf sample in a sterilized mortar using liquid nitrogen and
Genomic DNA Mini Kit (Plant, Gene Aid) according to
protocol from Geneaid, 2022. For ISSR analysis, out of 23
ISSR primers examined, only 10 primers gave polymorphic
amplifications. Those 10 primers (Table 2) were
subsequently used for genetic diversity analyzing of the
tree populations studied. The PCR reaction mixture
consisted of 1 x PCR master mix (Promega), 10 ng
template DNA, 1 µL for each primer to get a total volume
of 10 µL. The PCR reaction was run under the following
optimum conditions (Poerba and Ahmad 2013): 94°C for 5
min, 94°C for 1 min, 50°C, for 45 seconds and 72°C for 2
min. The reaction was stopped by extension at 72°C for 5
min. PCR products (amplicons) were stained with GelRed
(Biotium). Then the stained samples were electrophoresed
on 1.5% agarose gel (Vivatis) in 1x TBE buffer and were
run at 100 Volts for 120 min. The electrophoresis results
were then photographed using a gel documentation system
(Atto Bioinstrument).
Data analysis
The ISSR band profile of each ISSR primer was
observed from the electrophoresis gel photographs. The
clear and observable band patterns were scored according
to the presence or absence of the bands in the existing band
rows. Score 1 was for the presence of a band and 0 for the
absence of a band. The score data matrix was compiled in
Excel software and used for further analysis.
Percentage of polymorphic loci (PPL), Nei gene
diversity index (H), and Shannon information index (I) are
the key parameters to measure genetic diversity. The
Shannon index can vary from 0 to 1, and lower genetic
diversity is represented by values close to zero (Silva et al.
2015). The assessment of genetic diversity was based
mainly on the polymorphisms found at loci, which were
represented by PPL values. The molecular variance (AMOVA)
and population genetics analysis were performed using the
AIEx 6.3 Gene software (Peakall and Smouse 2006) with
an individual binary model. Cluster analyses were executed
using PAUP software (Zhang et al. 2019). Principal
Component Analysis (PCA) was executed using the
Metaboanalyst 5.0 software (Xia and Wishart 2016).
The plus tree was then selected based on the high score
and genetic diversity within the population and between the
populations according to the results of molecular marker
analysis, namely genetic distance.
Table 2. Sequences of ISSR primer pairs used for genetic diversity analysis in this study
Primers pairs
Sequences
Primers pairs
Sequences
UBC807
AGAGAGAGAGAGAGAGT
UBC822
TCTCTCTCTCTCTCTCA
UBC825
ACACACACACACACACT
UBC826
ACACACACACACACACC
UBC817
CACACACACACACACAA
UBC819
CACACACACACACACAG
UBC809
AGAGAGAGAGAGAGAGG
UBC808
CTCTCTCTCTCTCTCTA
UBC811
GAGAGAGAGAGAGAGAC
UBC842
GAGAGAGAGAGAGAG AYG
A
B

RIASTIWI et al. – Genetic diversity of rosewood in Yogyakarta, Indonesia
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RESULTS AND DISCUSSION
Characterization and determination of the plus tree
candidates
The exploration and comparison of plus tree candidates
with five surrounding trees resulted in 61 plus tree
candidates. Those 61 identified candidates had been
compared with 305 other individual trees. All candidates
from the four regencies in Yogyakarta are distributed
unevenly and form several clusters (Figure 1). It can be
seen that there is one large cluster in the middle of
Yogyakarta covering Gunungkidul, Sleman, and Bantul
regencies (GSB cluster). One medium cluster is situated
around the border of Kulon Progo and Sleman (KLS
cluster), consisting of two small clusters in the middle of
Sleman district (cluster S) and one on the eastern edge of
Kulon Progo district cluster KL). However, those
geographical clusters required molecular genetic studies to
determine plus tree diversity.
The total scoring results of the 61 plus tree candidates
in the four districts in Yogyakarta range from 43-147 with
an average of 97.5 (median 96.5 and mode 97) (Figure 3).
The total scores for morphological traits have a normal
distribution, showing that 95% of the highest score falls on
a score of at least 131. There are three plus tree candidates
within that total score limit with a score of 132, 134.5, and
147, which are the accession no KL06, SL04, and GK05,
respectively. These plus tree candidates are located in three
districts, i.e., Kulon Progo, Sleman and Gunungkidul.
Referring to the geographical map of the study area (Figure
1), the plus tree candidates with the 5% highest score were
distributed in two different geographic clusters. The KL
cluster on the eastern edge of Yogyakarta for accession no
KL06, and the middle GSB cluster of Yogyakarta for the
accession SL04 and GK06.
If the plus tree were selected at a lower percentile, 90%,
then the limiting score drops to 124, and the plus tree
candidates that can be selected increase to eight trees, i.e.,
accession no GK05, GK12, KL01, KL02, KL06, BL10,
SL04, and SL12. These plus tree candidates are distributed
throughout the entire districts being explored. The ten plus
trees with the highest scores are presented in Table 3,
including the plus trees of the 95% and 90% percentiles.
Genetic diversity analysis
DNA amplification using ten pairs of ISSR primers of
the plus tree candidates from four rosewood populations
resulted in 101 amplicon fragments. Different primers
produced different polymorphism patterns. The UBC 825
primer was one of the primers that produced the most
abundant amplicons (Figure 4.A) while the UBC 811
primer produced the fewest amplicons (Figure 4.B).
Nevertheless, it can be said that all primer pairs produce
high polymorphism. The fragment size also showed a high
variation, ranging from 200-3000 base pairs (bp) (Table 4).
Figure 3. The frequency distribution of the plus tree candidate
measurements was calculated using Phyton software
Table 3. The top ten rosewood plus tree candidates in Yogyakarta based on scoring method
Population
Plus tree
accession
no.
Measured variable
Score value of the measured variables and other qualitative traits
Total
Height
(m)
Diameter
(cm)
Height of
branch free
trunk (m)
Height
Diameter
Canopy
Straightness
Tree
health
Gunungkidul
GK05
11
56
4
20
30
4
3
4
132**
GK12
20
41
5
20
30
4
4
4
128*
Kulon Progo
KL01
20
40
5
20
30
2
3
4
124*
KL02
20
40
6
20
30
2
2
4
124*
KL06
20
56
6.5
12
30
3
3
4
134.5**
KL07
20
32
7
20
30
2
4
4
119
Bantul
BL10
20
37
10
20
30
2
4
4
127*
Sleman
SL03
12
45
5
20
30
4
3
3
122
SL04
20
62
4
20
30
5
3
3
147**
SL12
20
35
10
20
30
4
4
4
127*
Note: *percentile 90%, **percentile 95%

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Figure 4. ISSR profile of 61 rosewood samples from four Yogyakarta populations using two different primers. A. primer UBC 825. B.
primer UBC 811. Each row shows the banding pattern of one sample with a particular primer. The band pattern from left to right shows
20 samples from Kulon Progo, 13 samples from Gunungkidul, 10 samples from Bantul and 18 samples from Sleman. Blue arrows:
polymorphic band
Table 4. Number of amplified and polymorphic fragments
generated by ten selected ISSR primer pairs on the samples of
four different populations of rosewood in Yogyakarta
Primers
pairs
Number of
amplified
fragments
Number of
polymorhic
fragments
Size range
(bp)
UBC 807
8
8
200-1500
UBC 825
14
14
500-3000
UBC 817
13
13
400-3000
UBC 809
8
8
400-3000
UBC 811
9
9
400-1400
UBC 822
8
8
200-1800
UBC 826
10
10
400-2500
UBC 819
9
9
400-2500
UBC 808
10
10
200-1800
UBC 842
12
12
300-2500
The genetic variation parameters (Table 5) show a
fairly significant variation for each population. The average
PPL value of 64.71% indicated that the ISSR molecular
marker could be relied upon to detect polymorphisms at
both individual and population levels. The value of each
population's genetic diversity (He) showed a significant
difference. The highest diversity was obtained in the Kulon
Progo population, followed by Sleman, Gunungkidul
population, and the lowest was Bantul population. The
difference in genetic diversity from the highest to the
lowest reached 7.91%, indicating a significant difference.
This value is higher than the previous study on rosewood
by SRAP, which obtained 56% on rosewood (Yulita et al.
2020). A population is considered to have a high genetic
diversity value if it has high polymorphisms and
heterozygosity levels. A low heterozygosity value indicates
an organism's lack of genetic variation in wild populations.
This parameter is vital in determining strategies for certain
plant conservation (Siburian et al. 2017).
Several studies of natural populations have
demonstrated the percentage of polymorphic loci as a vital
measure of genetic diversity. However, despite the
commonly used, variation in these values is also observed
(Soares et al. 2016). According to (Nei 1987), the
proportion of polymorphic loci is not a significant measure
of genetic variation; therefore, the parameter of genetic
diversity (He) is still required because it can add more
accurate data.
The genetic diversity level of plus tree candidates in
Kulon Progo, represented by the value of He=0.29, showed
the highest diversity compared to plus tree candidates in
other districts studied. Kulon Progo is known to have a
protected forest in which the rosewood population exists.
There may be less human intervention in this rosewood
population than populations in other areas, such as
Gunungkidul. Farmers in their yards and fields manage the
rosewood population in Gunungkidul. The regeneration of
rosewood stands in the Kulon Progo protected forest can
occur more naturally, leading to higher genetic diversity
(Yulita et al. 2020). However, Sleman and Gunungkidul
A
B

RIASTIWI et al. – Genetic diversity of rosewood in Yogyakarta, Indonesia
2635
were found to have slightly lower genetic diversity than
Kulon Progo, with He=0.27 and He=0.21, respectively.
The average genetic diversity (H) of rosewood
candidate trees plus in Yogyakarta is high compared to
Adesmia bijuga with a value of 0.22 and a Shannon
Information Index of 0.36 (Guerra et al. 2018). The
diversity level of the plus tree in Kulon Progo with
He=0.29 is comparable to that of Pityrocarpa moniliformis
with He values of He=0.24 (Felix et al. 2020) and D. sissoo
with He=0.21 (Dobhal et al. 2019) and Caragana
microphylla (He=0.16 and I=0.24) (Huang et al. 2016).
That level of genetic diversity is still higher than those of
Hedysarum sangilense with He=0.105 (Selyutina et al.
2021), Parkia biglobosa with He=0.18 (Lompo et al.
2017). The genetic diversity level of rosewood in Kulon
Progo was also higher than that of Oxytropis exserta with
He=0.156, O. kamtschatica with He=0.108, O. revoluta
with He=0.089 (Kholina et al. 2013).
Genetic distance among rosewood population and
individuals in Yogyakarta
Genetic distance among populations from the four, i.e.,
Sleman, Gunungkidul, Kulon Progo, and Bantul, and the
individuals within these populations are measured using
genetic distance and then demonstrated by clustering. The
genetic identity and diversity parameters of four rosewood
populations in Yogyakarta are summarized in Table 6. The
similarity among individual mother trees is presented in a
dendrogram (Figure 5). The highest genetic identity (0.985)
and the lowest genetic distance (0.015) were observed
between Gunungkidul and Bantul, indicating very high
similarities between these populations. Those values
explain Gunungkidul and Bantul on the dendrogram and
PCA (Figure 5 and Figure 6), which are grouped into one
population. The genetic identity between Kulon Progo and
Sleman is 0.921, indicating that the populations' differences
are pretty far.
The AMOVA calculated to examine genetic variations
between and within geographic populations was
statistically significant (p<0.001). The results of the
AMOVA analysis (Table 7) showed that the highest
genetic variation within the population was 70%, rather
than among the populations that were only 30%. This
means there is not much genetic difference among the four
geographical populations of rosewood in Yogyakarta,
presumably due to the propagation history of rosewood in
Yogyakarta by root cuttings. This analysis firmly indicates
the low genetic differences among the populations.
Since among populations does not vastly different, it
might be possible that the origin of vegetatively propagated
rosewood populations studied here is similar. More
significant genetic variation within the population (88.2%)
was also observed in Prosopis cineraria compared to the
variance between populations (11.8%) (Sharma et al.
2011). Similar results were also observed in the
Pseudotsuga menziesii population, with diversity values of
72,2% within and 27.8% between populations (Castelan et
al. 2019).
Table 5. Comparison of genetic variation of rosewood plus tree candidates from Kulon Progo, Gunungkidul, Bantul, Sleman in
Yogyakarta, based on Nei's
Population area
N
PPL (%)
Na
Ne
He
I
Kulon Progo
20
75.49%
1.54
1.52
0.29
0.42
Gunungkidul
13
58.82%
1.32
1.38
0.21
0.32
Bantul
10
45.10%
1.09
1.30
0.17
0.25
Sleman
18
79.41%
1.58
1.48
0.27
0.40
Mean ± SD for all loci
15.25 (0.19)
64.71% (7.91%)
1.39 (0.043)
1.42 (0.020)
0.23 (0.011)
0.34 (0.015)
Note: N: number of individuals. PPL: percentage of polymorphic loci. Na: Observed number of alleles. Ne: Effective number of alleles.
He: Nei’s gene diversity (Nei 1973). I: Shannon's Information index
Table 6. Genetic identity (above diagonal) and genetic distance (below diagonal) based on Unbiased Measures Nei
Populations
Kulon Progo
Gunungkidul
Bantul
Sleman
Kulon Progo
0.880
0.866
0.921
Gunungkidul
0.127
0.985
0.864
Bantul
0.144
0.015
0.850
Sleman
0.082
0.146
0.163
Table 7. AMOVA based on ISSR data for four rosewood populations in Yogyakarta
Source
Degree of
freedom
Sum of
square
Mean sum
of square
Estimated variance
Proportion of
total variance %
Among populations
3
270.464
90.155
5.245
30%
Within populations
57
682.257
11.969
11.969
70%
Total
60
952.721
17.214
100%

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In contrast, in Tecomella undulata the diversity within
populations was 64% and 36% among populations
(Chhajer et al. 2018). AMOVA results that show more
significant variation within the observed populations may
be due to the clustering of Gunungkidul and Bantul
populations into one group. This phenomenon also occurs
in Artocarpus annulatus, in which the variation within the
population is greater than between populations, with the
PCA distribution intersecting between populations
(Dickinson et al. 2020).
Cluster analysis using PCA supports the relatedness of
plus tree candidates by genetic distances, generating three
large clusters according to their geographic locations,
namely the Sleman cluster, Kulon Progo cluster, and the
Gunungkidul-Bantul cluster (Figure 6). This shows that the
genetic diversity of plus trees originating from the same
area or the same population cluster tends to be similar. The
clustering analysis of plus tree candidates based on Nei
genetic distance also showed the same clustering (Figure 5).
The dendrogram shows that the four rosewood
populations in Yogyakarta were separated into three main
groups (Figure 5). The first group is the Kulon Progo
population. The second group is the Sleman population
which is divided into four subgroups. The third group is the
Bantul population together with the Gunungkidul
population. The closeness of these two populations could
result from human facilitated dispersal, for example, root
cuttings exchange among farmers (personal
communication). PCA analysis was performed to
determine genetic relationships between individuals
(Figure 6). Analysis of dendrogram clustering based on the
genetic distance matrix among populations and PCA based
on the ISSR data showed that the Sleman population was
the most divergent compared to other populations (Figure
5). The three groups formed in this clustering clearly
showed more significant genotypic differentiation,
consistent with the dendrogram. Accession no SL 11 and
SL 02 are separated and quite different from the other
Sleman accessions, which indicated that SL 11 and SL 02
have different genetic constitutions than other samples.
Allegedly, the SL 11 and SL02 grew from seeds and not
from root cuttings that generated different properties.
Figure 5. Dendrogram of four rosewood populations in Yogyakarta, Indonesia based on Ne i’s genetic distance. Group 1 KL: Kulon
Progo, Group 2 SL: Sleman, Group 3 are BL: Bantul and GK: Gunungkidul

RIASTIWI et al. – Genetic diversity of rosewood in Yogyakarta, Indonesia
2637
Figure 6. Cluster analysis using PCA based on ISSR divided population into three groups. Analysis using the MetaboAnalyst 5 program
The selection of plus trees with a 95% percentile
resulted in three-plus trees, i.e., accession no GK05, KL06,
and SL04, which came from different genetic clusters and
thereby ensured their genetic diversity. A passing limit
value that is too high will result in fewer plus trees being
selected and eventually narrow genetic variation in the next
generation. Conversely, a score limit value that is too low
will give a low genetic gain (Zakiyah et al. 2017). Eight
plus trees could be selected at the 90% percentile, namely
the accession no GK05, GK 12, KL01, KL02, KL06,
BL10, SL04, and SL12, which represent the four
administrative regions of Gunungkidul, Kulon Progo,
Bantul, and Sleman.
However, it is necessary to see whether the plus trees
originating from the same administrative area show high
diversity or uniformity because they might originate from
clonal seedlings from the same parents. Comparison of plus
trees from the same area, for example, accession no KL01
and KL06 were clustered with a narrow genetic distance.
However, both were slightly different from accession no
KL2 with Nei's ecludian (Figure 5). Considering the
geographical proximity of the three trees of about 500
meters (Figure 1), the close relatedness of the three-plus
trees could be implied that those trees might come from the
same parent. In such a case, only one tree selected among
those three-plus trees is sufficient to represent the diversity
in that area. In the case of plus trees accession, no GK05
and GK12, both have genetic distances and geographical
locations far apart, so it can be concluded that they might
not come from the same parent. A similar case could be
applied for the plus tree accession no SL04 and SL12, with
large genetic distances and a far geographic location.
Therefore, out of eight-plus three candidates, it can be
selected six accessions with the highest genetic diversity
background, namely KL02, GK05, GK12, BL10, SL04,
and SL12. The selection of plus trees using growth criteria
with a scoring system combined with genetic distance
analysis has also been carried out on P. falcataria (Zakiyah
et al. 2017). In those plants, the main criteria in
determining the plus tree are height, diameter, TBBC,
straightness, permanent branches and trunk shape.
The selection of plus trees is an important step in any
tree improvement and breeding program. Selection based
on solely morphological characters, without considering
the genetic background of the selected plus trees could lead
to even more narrowing genetic diversity of the plus trees
selected, and further the tree plantations generated.
Unknown genetic background could lead to inter-bred of
plus trees with closely related genetic background, which
might be resulted in inbreeding. Inbreeding is
disadvantageous to most tree species breeding programs,
due to inbreeding depression. Therefore, this study which

B I O D I V E R S I T A S
23 (5): 2630-2639, May 2022
2638
incorporates both morphological characters with some
genetic distance analysis using genetic markers should
result in better improved tree plantations.
In conclusion, plus trees exploration in four d of
Yogyakarta has identified 61 candidates, each of which has
been compared with five other nearby trees. A modified
scoring system used for selecting plus trees resulted in
values that were normally distributed. Combination of
selection using 90% percentile highest scores with genetic
relatedness from genetic distance analysis and the
geographic location of each plus tree candidates, from the
eight selected plus trees from different administrative
regions can be narrowed down to six, i.e., the accession no
KL02, GK05, GK12, BL10, SL04, and SL12. They
represent both the genetic diversity of the populations and
their geographic locations. Thus, molecular genetic
analysis supports the morphological parameters in selecting
plus trees to ensure the genetic diversity of the selected
plus trees.
ACKNOWLEDGEMENTS
This research was funded by the By Research BRIN
program, No. 1457/H/2019 granted to the first author.
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