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Time Journals of Agriculture and Veterinary Sciences
Vol. 1 (4): 47-54 November, 2013
www.timejournals.org/tjavs
© 2013 Time Journals
ISSN:2360-736X
Genetic Diversity Analysis of Some Ethiopian Specialty
Coffee (Coffea arabica L.) Germplasm Accessions
Based on Morphological Traits
*Getachew WeldeMichael1, Sentayehu Alamerew2 , Taye Kufa1 and Tadesse Benti1
1 Jimma Agricultural Research Center, P.O. Box, 192, Jimma, Ethiopia
2 Jimma University, College of Agriculture and Veterinary Medicine, P.O. Box, 307, Jimma, Ethiopia
* Corresponding author
Email- getachewweldemichael@gmail.com
Accepted 20 November,2013
ABSTRACT
Information on genetic variability is a prerequisite for further improvement of the yield and quality of coffee.
However, lack of information on genetic variability for specialty coffee accessions has been one of the major
problems in coffee improvement program. Forty nine coffee (Coffea arabica L.) germplasm accessions, which
were collected from Gomma Wereda, were evaluated at Agaro research station with the objective of estimating
the genetic diversity. The experiment was conducted in simple lattice design with two replications during
2011/12 cropping season by superimposing on six years old coffee trees which were planted in July, 2006 and
grown under uniform coffee shade tree (Sesbania sesban) conditions. Data on 26 quantitative characters were
recorded. The analysis of variance showed significant (P<0.05) variation among the accessions for all
morphological traits except percentage bearing primary branches, leaf area, bean thickness and rust incidence.
This indicated the existence of variability among the tested materials. Cluster analysis of quantitative
characters grouped the 49 coffee germplasm accessions into five clusters. This makes the germplasm
accessions to be moderately divergent. The distances between most of these clusters were highly significant at
(P<0.01), suggesting the possibility of getting suitable accessions for hybridization program among the tested
materials. Principal component analysis showed the variation in the first two principal components, which
explained the lion’s share of the observed variation, (42%), was mainly due to inter node length of main stem
and primary branches, leaf length, hundred bean weight, plant height, number of main stem nodes, number of
primary branches, length of primary branches, number of secondary branches and canopy diameter. So, these
traits were identified as a source variation among Gomma wereda coffee accessions and can be used for
selecting diverse parents in future coffee hybridization program.
Keywords: Coffea arabica , cluster analysis, genetic diversity , principal component, specialty coffee
INTRODUCTION
The southwestern highlands of Ethiopia are the birth
place and home to Arabica coffee (Coffea arabica L.)
(Kassahun et al., 2008). Coffee is at the centre of
Ethiopian culture and economy and contributes to about
35% of the country’s foreign currency earnings (Gole and
Senebeta, 2008). It accounts for 10% of the gross
domestic product, and supports the livelihoods of around
25% of the population of Ethiopia (Gole and Senebeta,
2008). The estimated area of land covered by coffee is
about 600,000 hectares, whereas the estimated annual
national production of clean coffee is about 350,000 tons
(Alemayehu et al, 2008). Ethiopia is currently producing
an estimated 9.8 million bags that would rank the country
as the third largest coffee producer in the world after
Brazil and Vietnam, beating out Colombia (ICO, 2012).
Coffea arabica L. is originated in Ethiopia and there is a
Time J.Agr.Vet.Sci. 48
great genetic diversity in the country and the existence of
such genetic diversity provides immense opportunity for
coffee improvement (Fikadu et al., 2008). However,
despite the vast area of cultivation, wealth of tremendous
genetic diversity and importance to the national economy,
the productivity of coffee is very low (about 0.71 t/ha)
(Alemayehu et al., 2008).
Although many factors hampered production and yield
per unit area, the major factors contributing to such low
coffee yield include predominant use of unimproved local
coffee landraces, as well as conventional husbandry and
processing practices, which in turn seriously hampers the
overall national coffee production and productivity of the
smallholder coffee farmers in the country (Kufa, 2010).
Furthermore, coffee genetic resources are under serious
threats of extinction, mainly due to deforestation,
replacement of traditionally grown landrace by improved
varieties, environmental degradation and change in land
use (Gole and Teketay, 2001). Thus, it is pertinent to
collect and conserve coffee accessions from different
coffee growing regions of the country to reduce the loss
of coffee genetic resources and improve the productivity
of the crop by developing high productive coffee varieties.
Having mandated to coordinate coffee research in
Ethiopia, Jimma Agricultural Research Center (JARC)
has been collecting coffee germplasm from different
coffee growing region of the country and so far about
5960 accessions have been conserved at JARC and its
sub-centers (Kufa, 2010). However, coffee genetic
diversity study did not get the attention that it deserves
and only few researchers have conducted genetic
diversity analysis on coffee in Ethiopia. Ermias (2005)
reported genetic variability among 81 west Wellega
coffee germplasm accessions for most of the characters
considered. In another work, Yigzaw (2005) reported high
genetic variability among 16 coffee germplasm
accessions of Northwest and Southwest Ethiopia for
morphological characters. Similarly, Mesfin (2008) also
reported the presence of wide genetic diversity among
141 coffee germplasm accessions collected from South
and Southeast Ethiopia. Olika et al. (2011) also
characterized 49 coffee germplam accessions collected
from Limu Kossa wereda for morphological characters
and reported the presence of wide genetic variability.
Information about genetic diversity within and among
genotypes of any crop is fundamental to estimate the
potential of genetic gain in a breeding program and for
effective conservation of available genetic resources
(Sakiyama, 2000). It may also be important for selecting
promising parental lines in hybrid variety development
(Barbosa et al., 2003). Such information could also serve
as a bench mark for future assessment of genetic erosion
(Hammer et al. 1996).
Gomma is one of the major coffee producing weredas
of Jimma Zone and coffee from this area is well known by
the name of ‘Limu Coffee’ and fetches very high price on
the world market for its peculiar winy flavor (Desse,
2008). However, systematic diversity analysis was not
conducted for specialty coffee accessions collected from
this wereda. The limited success in variety development
program for specialty coffee could partly be attributed to
lack of well characterized and distinctly variable breeding
materials that are readily available for use. Thus, the
present study was carried out to estimate the genetic
diversity of Gomma wereda specialty coffee germplasm
accessions using morphological traits.
MATERIALS AND METHODS
Description of the Study Site
The experiment was conducted at Agaro station of the
Jimma Agricultural Research Center. The center was
established in 1973 on land area of 27 ha near Agaro
town, 45 km far from Jimma and 397 km from Addis
Ababa. Agaro is located at 7’’50’35- 7’’ 51’ 00’’ N latitude
and 36’’35’30’’E longitude and at an altitude of 1650
meters above sea level. The mean annual rainfall of the
area is 1616 mm with an average maximum and
minimum air temperatures of 28.4 0C and 12.40C,
respectively. The major soil type is Mollic Nitisols with
pH of 6.2, organic matter 7.07%, nitrogen 0.42%,
phosphorus 11.9 ppm,CEC (cation exchange capacity)
39.40 cmol (+)/kg (Zebene and Wondwosen, 2008).
Experimental Materials
Forty seven C. arabica L. germplasm accessions which
have been collected in the year 2005 from the Gomma
wereda of Jimma Zone and two standard checks that are
maintained in the ex- situ field gene bank of Agaro station
were used for this study (Table 1). The experiment was
superimposed during the 2011/12 cropping seasons on
six years old coffee trees of the 49 accessions which
were planted in July, 2006 and grown under uniform
coffee shade tree (Sesbania sesban) conditions.
Methods of Data Collection
During the course of this study, data on 26 quantitative
characteristics, namely : Height up to first primary branch
(cm) , total plant height (cm) , number of main stem
nodes (no) , average inter node length of main stem (cm)
, main stem diameter (cm) , angle of primary branches(
deg) , number of primary branches (no), average length
of primary branches (cm) , number of nodes of primary
branches (no) , average Inter node length of primary
branches (cm), percentage of bearing primary branches
(%), number of secondary branches (no) , canopy
diameter (cm) , leaf length (cm) , leaf width (cm), leaf
area (cm2), fruit length (mm) , fruit width (mm), fruit
thickness (mm), bean length (mm), bean width (mm),
bean thickness (mm), hundred bean weight (gm), yield
per tree (kg), coffee berry disease (%) and rust incidence
WeldeMichael et al 49
Table 1. Geographical origin of the studied coffee ( Coffea ararbca L.) germplasm accessions at Agaro research station
*=Standard check variety
No.
Accession
No.
Farmers’ association
Specific
location
Altitude
No.
Accession
No
Farmers’ association
Specific location
Altitude
1
L01/05
Chadero Suse
Chedaro
1540
26
L27/05
Bako Kuju
Arfeti
1750
2
L02/05
Chadero Suse
Chedaro
1540
27
L28/05
Bako Kuju
Jida
1750
3
L03/05
Chadero Suse
Chesech
1540
28
L29/05
Bako Kuju
Jida
1750
4
L04/05
Chadero Suse
Chesech
1540
29
L30/05
Bako Kuju
Jida
1750
5
L05/05
Gabena Abo
Kefemo
1540
30
L31/05
Bako Kuju
Jida
1750
6
L06/05
Gabena Abo
Kochele
1540
31
L32/05
Debi Kechamo
Eno
1660
7
L07/05
Gabena Abo
Kochele
1540
32
L33/05
Debi Kechamo
Eno
1660
8
L08/05
Gabena Abo
Kochele
1540
33
L34/05
Debi Kechamo
Eno
1660
9
L09/05
Gabena Abo
Kochele
1530
34
L35/05
Debi Kechamo
Eno
1670
10
L10/05
Gabena Abo
Kochele
1530
35
L36/05
Debi Kechamo
Edio
1630
11
L11/05
Gabena Abo
Kochele
1530
36
L37/05
Limu Sapa
Baole Kilfadi
1680
12
L12/05
Gabena Abo
Gabeni
1600
37
L38/05
Limu Sapa
Baole Kilfadi
1680
13
L13/05
Omo-Boko
Chore
1740
38
L39/05
Limu Sapa
Baole Kilfadi
1680
14
L14/05
Omo-Boko
Chore
1750
39
L40/05
Limu Sapa
Baole Kilfadi
1680
15
L15/05
Omo-Boko
Chemaro
1770
40
L41/05
Limu Sapa
Kiefa Adi
1700
16
L16/05
Omo-Boko
Chemaro
1770
41
L42/05
Omo Gobo
Malgobu
1720
17
L17/05
Omo-Boko
Chemaro
1770
42
L43/05
Omo Gobo
Malgobu
1720
18
L18/05
Omo-Boko
Chemaro
1700
43
L44/05
Omo Gobo
Malgobu
1720
19
L19/05
Omo-Boko
Chemaro
1710
44
L45/05
Omo Gobo
Dargoba
1740
20
L20/05
Goja Kemisse
Balcho
1660
45
L46/05
Omo Gobo
Dargoba
1740
21
L21/05
Goja Kemisse
Balcho
1660
46
L47/05
Omo Gobo
Siliko
1690
22
L23/05
Goja Kemisse
Kemisse
1640
47
L48/05
Omo Gobo
Siliko
1690
23
L24/05
Goja Kemisse
Kemisse
1640
48
744
-
-
-
24
L25/05
Goja Kemisse
Kemisse
1620
49
Dessu
-
-
-
25
L26/05
Bako Kuju
Arfeti
1750
Time J.Agr.Vet.Sci. 50
(%) , were collected from each accession using the
standard procedures of IPGRI (1996).
Statistical Analysis
Data were subjected to analysis of variance (ANOVA)
using SAS version 9.2 (SAS, 2008) to examine the
presence of statistically significant differences among
accessions for the characters studied. The relative
efficiency of simple lattice design over RCBD
(randomized complete block design) was estimated and
simple lattice design was found to be efficient. Hence, the
data were analyzed using simple lattice design. Least
Significant Difference (LSD at P = 0.05 and 0.01) was
employed to identify accessions that are significantly
different from each other.
In this study, 22 morphological characters that showed
statistically significant variations among the accessions
were used for clustering and principal component
analysis. The data were subjected to cluster analysis so
as to determine the variability among the accessions.
Hierarchical clustering was employed using the similarity
coefficients among the 49 coffee accessions. Clustering
was performed using the proc cluster procedure of SAS
version 9.2 (SAS, 2008) by employing the method of
average linkage clustering strategy of the observation.
The numbers of clusters were determined by following
the approach suggested by Copper and Miligan (1988) by
looking into three stastics namely Pseudo F, Pseudo t2
and cubic clustering criteria.
Genetic divergence between clusters was determined
using the generalized Mahalanobis's D2 statistics
(Mahalanobis, 1936) using the equation: D²p =
(Xi XjS1(Xi Xj).
Where: D2p= the distance between any two groups i
and j;
Xi and Xj = the p mean vectors of accessions i
and j, respectively.
S-1 = the inverse of the pooled covariance
matrix.
The D2 values obtained for pairs of clusters were tested
for significance at 5% and 1 % level of significance
against the tabulated values of p degrees of freedom,
where p is the number of variables considered (Singh
and Chaudhary, 1987). Principal component analysis was
also performed by employing SAS version 9.2 (SAS,
2008 ).
RESULTS AND DISCUSSION
Mean squares for the 26 quantitative traits from analysis
of variance (ANOVA) are presented in Table 2.
Significant (P<0.05) differences among the coffee
germplasm accessions were observed for all traits
except for percent of bearing primary branches, leaf area,
bean thickness and rust incidence.
The significant variations observed for most of
morphological traits in a population is the result of
combination of the genotypic and environmental effects
(Welsh, 1990).The variability present for important traits
in the present study clearly proved the possibility to bring
considerable improvement mainly in coffee yield and
coffee berry disease resistance through selection and
hybridization. Bayetta (1997) reported high genetic
variability within the Arabica coffee population for yield,
CBD (coffee berry disease ) resistance and growth
characters. The existence of variability among Arabica
coffee accessions was further confirmed by many authors
who reported significant differences among coffee
germplasm accessions collected from major coffee
growing regions of the country (Ermias , 2005; Yigzaw,
2005 ; Olika et al., 2011). The D2 value based on the
mean of coffee germplasm accessions resulted in
classifying the 49 accessions into five groups (Table 3).
This indicates the tested coffee germplasm accessions
were moderately divergent. Cluster I and II were the
largest with nineteen germplasm accessions (39% each)
followed by cluster III and IV with 5 germplasm
accessions (10% of the total population, each ) and one
accession (2% ) into cluster V.
In the present study, accessions collected from
different kebeles /sub- districts/ clustered together, for
instance, accessions collected from the seven kebeles
clustered together in cluster I and II. In support of this,
Bayetta (2001) reported that morphological variation is
more important than variation in geographic origin as
indicator of genetic diversity in coffee. Seyoum (2003)
has also reported that accessions collected from
Gambella, Kullo, Keffa, Illubabor, Wello, Wellega, Maji,
Harar, and Sidamo were clustered together, despite the
fact that they were collected from different geographic
origins. In addition, in the present study, accessions
collected from same kebeles were clustered into different
clusters, suggesting the existence of high genetic
diversity within each collection sites. So, this diversity
could be exploited further in order to increase the genetic
base of specialty coffee varieties. Genetic divergence as
measured by Mahalanobis (1936) generalized distance
(D2) has been one of the important statistical tools to
provide a rational basis for selection of parents in
breeding programs. Mahalanobis distance (D2) of the five
clusters of 49 coffee germplasm accessions based on 22
quantitative traits is presented in Table 4. The chi-square
test for the five clusters indicates that there were highly
significant differences between clusters except cluster I
&II, I &III and II&IV. The maximum inter cluster distance
was between cluster III and IV (183.94) followed by IV
and V (165.72), I and IV (108.95), I and V (103.24). The
minimum being between II and IV (29.53) followed by I
and II (30.07) (Table 4). In general, this study revealed
that the germplasm accessions included in this study
were moderately divergent.
The importance of genetic diversity to maximum
heterosis has been reported by many investigators.
WeldeMichael et al 51
Table 2. Analysis of variance (Mean squares) for 26 quantitative characters of 49 coffee germplam accessions grown at Agaro
(2011/12).
* *=highly significant (p<0.01), *= significant (p<0.05), ns= non significant
HUP= height up to first primary branch. TPH= total plant height, NMSN= number of main stem nodes, AILMS= average inter node length of
main stem, SD= stem diameter, APB= angle of primary branches, NPB= number of primary branches, ALPB= average length of primary
branches, NNPB= number of nodes of primary branches, AILPB= average inter node length of primary branches, NSB=number of secondary
branches, CD= canopy diameter, LL= leaf length, LW= leaf width, FL= fruit length, FW= fruit width, FT= fruit thickness, BL= bean length, BW=
bean width, HBW= hundred bean weight, CBD =coffee berry disease, Yd/tr= yield per tree, RCBD= randomized complete block design, LSD=
least significant difference , CV= coefficient of variation.
Character
Mean square of treatment
(48)
Mean square of error
LSD
Efficiency
relative to
RCBD (%)
CV (%)
Unadjusted
Adjusted
Intra block
(36)
RCBD
(48)
0.05
0.01
HUP
41.46
38.86**
7.79
9.71
6.00
8.05
110.83
8.84
TPH
802.79
757.11**
272.62
318.85
35.14
47.12
106.22
7.03
NMSN
20.40
19.51*
9.32
13.31
6.66
8.93
123.39
8.93
AILMS
0.48
0.41*
0.17
0.24
0.89
1.20
126.26
7.44
SD
0.59
0.56**
0.11
0.21
0.72
0.97
167.38
8.44
APB
44.11
42.89**
13.06
16.12
7.76
10.41
110.13
5.70
NPB
124.47
121.37**
52.76
57.99
14.60
19.48
102.62
12.06
ALPB
61.56
49.48*
22.80
33.94
10.45
14.02
127.72
6.18
NNPB
7.5
7.79**
1.49
2.39
2.63
3.60
136.65
6.69
AILPB
0.21
0.19**
0.05
0.07
0.47
0.63
131.06
5.96
PBPB
30.54
28.24ns
27.55
28.10
10.55
14.08
100.15
6.91
NSB
2541.41
1933.00*
905.65
1147.9
64.86
86.97
112.25
24.79
CD
486.17
375.06**
118.6
184.27
23.91
32.06
132.54
5.70
LL
2.19
1.54*
0.64
0.97
1.75
2.35
130.11
14.50
LW
0.32
0.26**
0.08
0.12
0.64
0.85
123.61
5.70
LA
101.71
73.28 ns
32.53
50.75
12.53
16.80
133.02
11.94
FL
0.75
0.77**
0.27
0.34
1.12
1.50
111.73
3.24
FW
0.50
0.48*
0.23
0.32
1.05
1.41
118.24
3.94
FT
0.50
0.56*
0.27
0.36
1.12
1.51
117.32
5.29
BL
0.74
0.7**
0.16
0.17
0.8
1.06
100.94
4.35
BW
0.19
0.18**
0.043
0.037
0.42
0.56
86.10
2.89
BT
0.06
0.054 ns
0.033
0.035
0.36
0.49
101.92
4.30
HBW
8.1
7.83**
0.86
1.01
1.98
2.65
106.74
5.46
CBD
462.52
452.11**
162.37
279.75
28.14
37.73
145.37
70.2
Rust
159.50
134.65ns
90.43
115.69
20.51
27.51
113.02
15.29
Yd/tr
0.098
0.08*
0.045
0.05
0.43
0.57
101.03
35.20
Time J.Agr.Vet.Sci. 52
Table 3. The distribution of germplasm accessions into five clusters based on D2 analysis for 49 coffee germplasm accessions tested at
Agaro (2011/12).
Table 4. Average inter-cluster divergence (D2) values obtained based on 22 quantitative characters of 49 coffee germplasm
accessions tested at Agaro (2011/12).
**=Highly significant P<0.01(χ 2) =40.29
Bayetta et al. (2008) reported the requirement of genetic
divergence among parents with respect to geographic
origin and/or morphological traits for maximum heterosis
to occur in certain hybrid characters like yield and stem
diameter. Wassu et al.(2008) also reported maximum
heterosis in crosses involving diverse parents with
respect to geographic origin compared to crosses having
parent’s from similar geographic origin.
Principal component analysis revealed the first six
principal components with eigenvalues greater than one
accounted for 70 % of the total variation among the
accessions for 22 quantitative traits (Table 5).
The first principal component which accounted for 25 %
of the variability among coffee germplasm accessions
were attributed to discriminatory traits such as inter node
length of main stem and primary branches, leaf length
and hundred bean weight. Likewise, 17% of the total
variability among the tested coffee accessions accounted
for the second principal component originated from
variation in plant height, number of main stem nodes,
number of primary and secondary branches, average
length of primary branches and canopy diameter. So,
these traits played major role in classifying coffee
accessions into different clusters and should be
considered in selecting diverse parents in crossing
program. This finding is partly in agreement with the
finding of Olika et al. (2011) who have reported bean
length, hundred bean weight, leaf length and leaf width
contributed to the variation among Limmu coffee
accessions.
CONCLUSION
The analysis of variance revealed the presence of
significant differences for most of the traits, indicating the
presence of variability which can be exploited through
selection and hybridization. The cluster analysis for 22
quantitative characters classified 49 coffee germplasm
accessions into five clusters and most of inter-cluster
distances were significantly different. So, crossing coffee
accession from these divergent clusters will result in
heterosis and recombinant in segregating generation.
Besides, the traits with the largest values in the first two
principal components played major role in clustering the
accessions and should be considered for selection
program.
AKNOWLEDGEMENTS
The authors would like to acknowledge Jimma
Agricultural Research Center for allocating the required
budget for the research.
Cluster
No.
No. acc.
Percent
(%)
Accessions
1
19
39
L23/05 L08/05, L11/05, L40/05, L19/05, L15/05, L32/05, L31/05 L25/05, L36/05, L48
/05, L17/05, L35/05 , L20 /05, L12/05 ,L37/05, L39/05, L42/05 and F-59
2
19
39
L07/05, L33/05, L43/05 , L44/05 , L26/05, L45/05, L18/05, L47/05, L41/05, L05/05,
L03/05, L13/05, L28/05, L34/05, L14/05, L09/05, L16/05, and L27/05 and 744
3
5
10
L10/05, L06/05, L01/05, , L21/05 and L46/05
4
5
10
L24/05, L04/05, L30/ 05 L38/05 and L29/05
5
1
2
L02/05
Cluster
I
II
III
IV
V
I
30.07
32.36
108.95**.
103.24**
II
83.87**
29.53
96.33**
III
183.94**
70.14**
IV
165.72**
WeldeMichael et al 53
Table 5. Eigenvectors and eigenvalues of the first six principal components for 22 morphological characters of 49 Arabica coffee
germplasm accessions
HUP= height up to first primary branch. TPH= total plant height, NMSN= number of main stem nodes, AILMS= average inter node length of main stem,
SD= stem diameter, APB= angle of primary branches, NPB= number of primary branches, ALPB= average length of primary branches, NNPB= number of
nodes of primary branches, AILPB= average inter node length of primary branches, NSB=number of secondary branches, CD= canopy diameter, LL= leaf
length, LW= leaf width, FL= fruit length, FW= fruit width, FT= fruit thickness, BL= bean length, BW= bean width, HBW= hundred bean weight, CBD
=coffee berry disease, Yd/tr= yield per tree, PC= principal component.
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Characters
Eigen vectors
PC1
PC2
PC3
PC4
PC5
PC6
HUP
0.14
0.09
-0.28
-0.10
0.28
-0.5
TPH
0.15
0.42
-0.1
-0.01
0.17
0.06
NMSN
-0.18
0.36
-0.16
0.13
0.19
0.03
AILMS
0.35
0.05
0.13
-0.14
-0.08
0.16
SD
0.14
0.29
-0.12
0.01
0.23
-0.35
APB
0.13
0.14
-0.34
-0.22
0.19
0.35
NPB
-0.17
0.39
-0.01
0.15
-0.05
0.10
ALPB
0.12
0.30
0.44
-0.12
-0.06
0.12
NNPB
-0.19
0.21
0.41
0.1
0.1
0.01
AILPB
0.32
-0.01
-0.11
-0.22
-0.15
0.1
NSB
-0.01
0.32
-0.15
0.23
-0.38
-0.001
CD
0.03
0.32
-0.38
-0.18
0.1
-0.13
LL
0.30
0.02
0.05
-0.27
0.04
0.04
LW
0.29
0.07
0.06
-0.23
-0.02
-0.05
FL
0.29
0.01
-0.05
0.24
0.02
0.19
FW
0.27
-0.11
0.17
0.1
0.06
-0.19
FT
0.10
-0.14
0.13
0.03
0.49
0.40
BL
0.09
0.01
0.11
0.42
0.05
0.26
BW
0.25
-0.11
0.1
0.41
0.1
-0.22
HBW
0.32
-0.04
0.1
0.37
0.1
-0.16
CBD
-0.2
-0.06
-0.02
-0.01
0.57
0.04
Yd/tr
0.17
0.15
-0.33
0.20
-0.1
0.24
Eigen values
5.59
3.67
2.12
1.64
1.38
1.14
Percent variation
0.25
0.17
0.10
0.07
0.06
0.05
Cumulative variation
0.25
0.42
0.52
0.59
0.65
0.70
Time J.Agr.Vet.Sci. 54
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Ethiopia, 14-17 August 2007, Addis Ababa, Ethiopia. pp. 58-63.
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quantitative Traits in Limu Coffee (Coffea arabica L.) in Ethiopia.Int.
J. Agric. Res. 6: 482-493.
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Cary, NC.USA
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