A study to characterize and determine the magnitude of genetic variation among 60 open-pollinated maize varieties was conducted at two contrasting locations in Sierra Leone during the 2015 wet cropping season. Results revealed that traits such as grain moisture content, anthesis-silking interval, plant and ear heights, number of ears harvested, field weight and grain yield showed moderate to high values of the components of genetic variation while days to 50% anthesis and silking revealed low values of the components of genetic variation. The first two PCA axes explained 54% of the total variation, of which the first principal component (PC1) accounted for 35% and PC2 contributed 19% of the total variation. The cluster diagram grouped the genotypes into seven main clusters and results suggest that crosses involving clusters I and V with any other clusters would produce segregants with low grain yields while the crosses between clusters IV, VI and VII would be expected to manifest higher heterosis and could result in segregants with higher grain yields. There was significant genetic variability observed among the genotypes evaluated thereby suggest the scope to bring about traits improvement of genotypes through direct selection and hybridization.

1. Genetic Variability and Morphological Diversity among Open-Pollinated Maize (Zea mays L.) Varieties
IJPBCS
Genetic Variability and Morphological Diversity among
Open-Pollinated Maize (Zea mays L.) Varieties
1Sayo Sesay*, 2Alpha Bellah Jalloh and 3Nabieu Kamara
1,2,3
Crop Improvement Programme, Rokupr Agricultural Research Center, Rokupr - Sierra Leone Agricultural
Research Institute, PMB 1313, Tower Hill, Freetown, Sierra Leone
A study to characterize and determine the magnitude of genetic variation among 60 open-
pollinated maize varieties was conducted at two contrasting locations in Sierra Leone during the
2015 wet cropping season. Results revealed that traits such as grain moisture content, anthesis-
silking interval, plant and ear heights, number of ears harvested, field weight and grain yield
showed moderate to high values of the components of genetic variation while days to 50%
anthesis and silking revealed low values of the components of genetic variation. The first two
PCA axes explained 54% of the total variation, of which the first principal component (PC1)
accounted for 35% and PC2 contributed 19% of the total variation. The cluster diagram grouped
the genotypes into seven main clusters and results suggest that crosses involving clusters I and
V with any other clusters would produce segregants with low grain yields while the crosses
between clusters IV, VI and VII would be expected to manifest higher heterosis and could result
in segregants with higher grain yields. There was significant genetic variability observed among
the genotypes evaluated thereby suggest the scope to bring about traits improvement of
genotypes through direct selection and hybridization.
Keywords: Diversity, genetic variability, open-pollinated maize, principal component, correlation.
INTRODUCTION
Maize (Zea mays L.) is the second most important cereal
crop grown in Sierra Leone after rice, the country’s staple.
The crop is cherished by Sierra Leoneans and is grown in
homesteads in the uplands during the raining season and
inland valley swamps in the dry season (MAFFS, 2005). It
has a very high commercial value when compared with
other food crops grown in the country contributing to
poverty alleviation. Maize grain yields are generally low
with national average of 2t/ha (USDA, 2015). The low grain
yields may be attributed to inadaptable maize varieties,
varietal mixtures in the hands of farmers, low reactions to
insect pests and diseases and abiotic factors. The demand
for maize in Sierra Leone is rising as the human and
livestock population increases. This rise means
developing new cultivars that will meet the growing
demand of the Sierra Leone population.
However, genetic resources are the most valuable and
essential basic raw material to meet the current and future
needs for genetic improvement of any crop (Kaur et al.,
2017). The choice of germplasm is fundamental and
decisive in any plant breeding program, which is aimed at
the development of open pollinated varieties or obtains
pure lines for use in hybridization (Baretta et al., 2016).
Open populations contain a gene pool with high value and
represent important source of genetic variability that can
be explored in the search for genes of tolerance and/or
resistance to biotic and abiotic factors (Araújo and Nass,
2002).
*Corresponding Author: Sayo Sesay, Crop
Improvement Programme, Rokupr Agricultural Research
Center, Rokupr - Sierra Leone Agricultural Research
Institute, PMB 1313, Tower Hill, Freetown, Sierra Leone.
Tel: +23278084923 Email: osaiosesay@yahoo.com.
Co-Author 2
Tel: +23276661369; Email:
2
alphabjalloh@yahoo.co.uk; 3Tel: +23288069592
3kamara.nabieu@yahoo.com
International Journal of Plant Breeding and Crop Science
Vol. 5(3), pp. 421-428, November, 2018. © www.premierpublishers.org. ISSN: 2167-0449
Research Article

2. Genetic Variability and Morphological Diversity among Open-Pollinated Maize (Zea mays L.) Varieties
Sesay et al. 422
Genetic variation among traits is important for breeding
and in selecting desirable types (Astereki et al., 2017).
Characterization studies allow pointing out the variability
pattern of the most significant variables and establishing
groups of accessions with similar traits. Assessment of
genetic diversity, relationships, and structure within a
given set of germplasm is useful in plant breeding. The
genetic improvement through hybridization and selection
depends upon the extent of genetic diversity between
parents. Assessment of germplasm diversity by
morphological descriptors still remains the only traditional
and legitimate marker type accepted by the International
Union for Protection of new Varieties (UPOV, 2009)
(Ghixari et al., 2014). The use of morphological descriptors
is unavoidable for DUS (Distinctness, Uniformity and
Stability) testing and in the procedures for protection of
varieties (Cupic et al., 2009).
However, there is inadequate information regarding the
amount of genetic variation in maize germplasm arrays to
make important consideration for effective and efficient
utilization of germplasm resources in Sierra Leone. This
study was therefore conducted in open-pollinated maize
varieties, with broad genetic base, to characterize
genotypes for desirable attributes and identify promising
sources of variability, which could be exploited in breeding
programmes.
MATERIALS AND METHODS
Description of test locations
Field experiments were conducted at two different
locations (Newton and Kalangba) during the wet cropping
season of 2015 in Sierra Leone. Location Newton
(8°20'6.6''N, 13°0'29.9''W, and 36m above sea level) is
situated in the Western Rural Area of Sierra Leone and
received an annual rainfall and temperature of 3392mm
and 26°C, respectively. On the other hand, Location
Kalangba (9°06'12.6''N, 12°37'21.2''W, 56masl) is in the
Kambia District, the northern part of Sierra Leone and
received an annual rainfall and temperature of 2988mm
and 26.8°C, respectively.
Experimental materials and design
Sixty genotypes of open-pollinated maize varieties which
were developed for drought tolerant and striga resistant by
the International Institute of Tropical Agriculture (IITA),
Ibadan, Nigeria were used in the study (Table 1).
Genotypes were planted in a two-row plot, 5m long in a 10
x 6 Alpha lattice design with three replications. Total area
covered was 45m x 35m, with 1m between blocks. Three
seeds per hill were planted and later thinned to two plants
per hill using plant spacing of 75cm between and 50cm
within rows. Nitrogen, Phosphorus and Potassium
fertilizers in the forms of NPK 15:15:15 and urea were
applied at the rate of 120 kg N/ha, 60 kg P2O5/ha and 60
kg K2O/ha. The nitrogen fertilizer was applied in two splits
- two and six weeks after planting. Two hand weeding was
done at two and six weeks after planting at the two
locations.
Data collection of morphological traits
Data were recorded on the following traits:
a. Days to 50% anthesis: Observations were recorded on
plot basis in days from sowing date to the date when
50% of the plants had started shedding pollens.
b. Days to 50% silking: Observations were recorded on
plot basis in days from sowing date to the date when
50% of the plants had emerged silks.
c. Anthesis and silking intervals: Observations were
recorded on plot basis in days as the difference
between days to anthesis and silking.
d. Plant height: Average height of ten randomly selected
plants measured in centimetres (cm) from the base of
the plant to where tassel branching began.
e. Ear height: Average height of ten randomly selected
plants measured in cm from the base of the plant to the
node bearing the upper ear.
f. Number of ears harvested: Average number of ears
harvested per plot counted at harvest.
g. Grain moisture content - Was determined at harvest for
each plot, grains were shelled from ten randomly
selected ears and uniformly mixed to record the percent
grain moisture using a digital moisture tester.
h. Field weight: Was measured in kilogram (kg) per plot
for each entry at harvest of dehusked ears using a
measuring balance.
i. Grain yield: Grain yield in kgha-1 (later converted into
t/ha) was calculated for every entry from the data of field
weight per plot using the following formula (Rahman et
al., 2007):
Grain yield (kgha-1)=
𝐹𝑖𝑒𝑙𝑑 𝑤𝑒𝑖𝑔ℎ𝑡 (𝑘𝑔/𝑝𝑙𝑜𝑡)𝑋(100−𝑀𝐶)𝑋 0.8 𝑋 10,000
(1000.8)𝑋 7.5
Where: MC= moisture content in grains at harvest (%),
0.8= shelling co-efficient,
7.5 = Area harvested plot-1 (m2),
1 hectare = 10,000m2 and
12% = moisture content required in maize grain at storage.
STATISTICAL ANALYSIS
Data of traits combined for the two locations were
subjected to analysis of variance to determine the effects
of genotypes, locations and genotype x environment
interaction. The form of ANOVA used is presented in Table
2. Fixed effects influence mean and random effects
influence variance (Francis et al., 2012). This work
therefore considered both genotypes and locations as
random effects as it focused on estimation of variance
components of traits.

3. Genetic Variability and Morphological Diversity among Open-Pollinated Maize (Zea mays L.) Varieties
Int. J. Plant Breed. Crop Sci. 423
Table 1: List of maize genotypes used in the study
Code Genotype Code Genotype
1 2004 TZE-W Pop DT STR C4 31 2014 TZE-W DT STR
2 2004 TZE-Y Pop DT STR C4 32 2014 TZE-Y DT STR
3 2004 TZEE-W Pop STR C4 33 Check 1 (Western Yellow)
4 2004 TZEE-Y Pop STR C4 34 Check 2 (DMR-ERS-Yellow)
5 2008 Syn EE-W DT STR 35 DTE STR-W Syn Pop C2
6 2008 Syn EE-Y DT STR 36 DTE STR-W Syn Pop C3
7 2008 TZEE-W STR 37 DTE STR-Y Syn Pop C2
8 2008 TZEE-Y STR 38 DTE STR-Y Syn Pop C3
9 2009 DTE-W STR Syn 39 EV DT-W 2008 STR
10 2009 TZE-OR1 DT STR 40 TZE-W Pop DT C3 STR C5
11 2009 TZE-OR1 DT STR QPM 41 TZE-W Pop DT C4 STR C5
12 2009 TZE-OR2 DT STR 42 TZE-W Pop DT C5 STR C5
13 2009 TZE-OR2 DT STR QPM 43 TZE-Y Pop DT C3 STR C5
14 2009 TZE-W DT STR 44 TZE-Y Pop DT C4 STR C5
15 2009 TZE-W Pop DT STR 45 TZE-Y Pop DT C5 STR C5
16 2009 TZE-Y Pop DT STR 46 TZE Comp 3 DT C2 F2 (RE)
17 2010 TZE-W DT STR 47 TZEE-W Pop DT C0 STR C5
18 2010 TZE-Y DT STR 48 TZEE-W Pop DT C1 STR C5
19 2011 DTE STR-Y Synthetic 49 TZEE-W Pop STR C4
20 2011 TZE-W DT STR Synthetic 50 TZEE-W Pop STR C5
21 2011 TZE-Y DT STR 51 TZEE-W Pop STR x Z105
22 2012 TZE-W DT C4 STR C5 52 TZEE-W Pop STR x Z107
23 2012 TZE-W Pop DT C4 STR C5 53 TZEE-W STR 104 BC2
24 2012 TZE-Y Pop DT C4 STR C5 54 TZEE-W STR 105 BC2
25 2012 TZEE-W DT STR C5 55 TZEE-W STR 107 BC2
26 2012 TZEE-Y DT STR C5 56 TZEE-W STR 108 BC2
27 2013 DTE STR-W Syn 57 TZEE-Y Pop DT C0 STR C5
28 2013 DTE STR-Y Syn 58 TZEE-Y Pop DT C1 STR C5
29 2013 TZEE-W Pop DT STR 59 TZEE-Y Pop STR C5
30 2013 TZEE-Y Pop DT STR 60 TZEE-Y STR 106 BC2
Table 2: Form of ANOVA for the combined location data used in the study
Source of variation Df Mean squares Variance component F: ratio
Location (L) l – 1 M1 (M1 + M5)/(M2+M4)
Replication (Location) (r-1) l M2
Genotype (G) g – 1 M3 (M3 – M4)/ rl M3/M4
Genotype x Location Interaction (G x L) (g-1)(l-1) M4 (M4 – M5)/r M4/M5
Pooled error (r-1)(g-1)l M5 M5
Source: Mclntosh (1983)
The genotypic and phenotypic coefficients of variation
(PCV and GCV) to compare the variation among traits
were estimated for each location according to the
procedure outlined by Johnson et al. (1955). PCV and
GCV values were categorized as low when less than 10%,
moderate, 10-20% and high, greater than 20% as
indicated by Deshmukh et al. (1986). Broad-sense
heritability was estimated according to the procedure
suggested by Singh and Chaudhary (1985). Heritability
percentage was categorized as low when less than 30%,
moderate, 30-60% and high, greater than 60%. Genetic
advance values were determined by the formula illustrated
by Johnson et al. (1955). Genetic advance was expressed
as a percentage of the genotypes mean. This was
categorized as high when it is above 20%, moderate, 10-
20% and low when it is less than 10%.
Principal component and cluster analysis were performed
for combined locations data to establish the importance of
agro-morphological traits in explaining multivariate
polymorphism and group sets of genotypes into
homogenous cluster. Pearson’s correlation coefficient was
also performed for each of the two locations tested to
determine traits association with grain yield. The Statistical
Tool for Agricultural Research (STAR, 2014), version 2.0.1
was used for the analysis.

4. Genetic Variability and Morphological Diversity among Open-Pollinated Maize (Zea mays L.) Varieties
Sesay et al. 424
Table 3: Analysis of variance showing mean squares of nine traits for 60 open-pollinated maize varieties evaluated at
Newton and Kalangba, 2015.
Source of variation df Anthesis Silking
Anthesis
- Silking
Interval
Plant
Height
Ear
Height
No. of
Ears
Harvested
Grain
Moisture
Field
weight
Grain
yield
Location (L) 1 2265.03**2305.34**0.18 32680.3** 49679** 9912** 10886.7** 465.58** 37.96**
Replication(Location) 4 2.79* 2.46* 0.04 16.5* 1.6 0.82 0.2 0.014 0.012
Genotype (G) 59 16.53 17.1 0.42 557.6 127.2 22.76 23.5 0.28 0.31
Genotype x Location
Interaction (G x L) 59 15.32** 14.84** 0.40** 602.8** 174.5** 44.38** 23.6** 0.403** 0.48**
Error 236 0.96 0.92 0.06 5.70 2.10 1.02 1.20 0.01 0.01
Total 359
*, ** significant at probability level of 0.05 and 0.01, respectively.
Table 4: Components of variation of 60 open-pollinated maize varieties for nine traits evaluated at Newton and Kalangba,
2015.
Trait Min. Max. Mean
Std.
Dev. PCV GCV H (%) GAM (%)
Location Newton
Anthesis 40 52 47.5 1.8 3.8 3.2 69.2 5.5
Silking 44 55 50.7 1.7 3.4 2.8 67.1 4.7
ASI 2 4 3.2 0.4 12.5 10.4 56.8 14.6
Plant Height 172 186 180.2 3.1 1.7 1.3 55.8 1.9
Ear Height 73 88 83.5 3.1 3.7 3.4 86.2 6.5
No. of Ears Harvested 32 43 37.0 2.3 6.3 5.7 81.9 10.6
Grain Moisture 20.8 39.4 30.7 4.1 13.6 12.6 85.9 24.0
Field weight 4.4 5.5 4.9 0.2 4.4 3.8 77.1 7.0
Grain yield 2.4 4 3.1 0.3 9.5 8.7 83.3 16.3
Location Kalangba
Anthesis 46 63 52.5 2.9 5.6 5.3 89.6 9.9
Silking 50 67 55.7 3.0 5.2 5.0 90.3 9.7
ASI 2 4 3.2 0.5 14.1 11.8 70.2 20.4
Plant Height 105 200 161.1 19.5 12.2 12.1 98.1 24.6
Ear Height 35 83 60.0 9.6 16.2 15.9 97.0 32.3
No. of Ears Harvested 13 37 26.5 4.3 16.1 15.7 94.2 31.3
Grain Moisture 19.5 19.9 19.7 0.1 0.5 0.4 67.9 0.7
Field weight 1.1 3.6 2.6 0.4 17.2 16.6 93.4 33.1
Grain yield 1.1 3.5 2.5 0.4 17.7 17.1 93.3 34.0
PCV = phenotypic coefficient of variation, GCV = genotypic coefficient of variation, H (%) = broad sense heritability, GAM
(%) = genetic advance as percent of mean.
RESULTS AND DISCUSSION
Analysis of variance
Table 3 presents the analysis of variance showing mean
squares of nine traits for 60 open-pollinated maize
varieties evaluated at two locations. Effects due to
locations and genotype x location interaction were
statistically different for all the traits assessed, except
anthesis-silking interval which showed none significant
difference in location main effect. Significant effect due to
genotype x environment interaction indicates that some
genotypes had consistent mean traits performance
whereas some performed differently in the two locations
tested. Results also revealed that the magnitude of
genotype x environment interaction contributed to the total
treatment sum of squares was larger than that of
genotypes.
This showed a negative effect on the heritability of most
traits (plant height, ear height, number of ears harvested,
grain moisture, field weight and grain yield) evaluated, and
according to Yan and Kang (2003), the larger the sum of
squares of the genotype x environment interaction when
compared with that of the genotypes, the more negative
effects would manifest on the traits under consideration.
Consequently, data of genotypes for genetic variation
components were analysed separately for the two
locations tested.
Genetic variation of traits
Components of variation of 60 open-pollinated maize
varieties for nine traits are shown in Table 4. The reliability
of a parameter to be selected for breeding programme
among other factors is dependent on the magnitude of its
coefficient of variations (CV) especially the genotypic

5. Genetic Variability and Morphological Diversity among Open-Pollinated Maize (Zea mays L.) Varieties
Int. J. Plant Breed. Crop Sci. 425
coefficient of variation (GCV) (Bello et al., 2012). Results
revealed considerable range of variation for all the traits
evaluated in each of the two locations, indicating enough
scope for bringing about genetic improvement of the traits.
There were slight differences observed between
phenotypic and genotypic coefficient of variation values for
all of the traits in each of the locations, suggesting that the
environments had minimal influence in the expression of
the traits. Similar results have been reported by Bello et al.
(2012) and Nelson and Somers (1992). Generally,
phenotypic and genotypic coefficient of variation and
genetic advance values were observed to be low in most
of the traits measured in location Newton and high in
location Kalangba. Heritability values were observed to be
high in most traits in the two different locations. Anthesis-
silking interval measured in location Newton showed
moderate values for phenotypic and genotypic coefficient
of variation, heritability and genetic advance. This
indicates that the trait is controlled by both additive and
non-additive gene effects, and that phenotypic
performance of this trait can be achieved through careful
selection. Grain moisture content measured in location
Newton; anthesis-silking interval, plant and ear heights,
number of ears harvested, field weight and grain yield in
location Kalangba showed moderate phenotypic and
genotypic coefficient of variation, and high heritability and
genetic advance values. This suggests that these traits
were mainly governed by additive gene actions and direct
phenotypic selection for these traits will be effective
(Ibrahim and Hussein, 2006; Nwangburuka et al., 2012).
This result is in line with Raut et al. (2017) who reported
moderate PCV and GCV, and high heritability and genetic
advance values for ear height and grain yield.
The low phenotypic and genotypic coefficient of variation
and genetic advance, and high heritability values observed
in days to 50% anthesis and silking in both locations
suggest that direct selection for these traits may not be
possible because the traits were governed by non-
addictive gene effect and most of the variation is attributed
to environmental effects. Such traits require management
practices than selection to improve the traits performance
(Wondimu et al., 2014). This result is in corroboration with
the findings of Sesay et al. (2016) who observed low
phenotypic and genotypic coefficient of variation,
heritability and genetic advance values in days to 50%
anthesis and silking in both top-cross and three-way cross
hybrids. Vashistha et al. (2013) also observed low genetic
variability for days to 50% anthesis and silking in maize
cultivars.
Principal component analysis
Table 5 presents the principal component analysis of 60
open-pollinated maize varieties for nine traits evaluated at
two locations. Results showed that the four principal
components had Eigen values greater than one,
contributing to 84% of the total variation among the 60
maize genotypes. The first principal component (PC1)
contributed 35% whereas PC2, PC3 and PC4 contributed
19%, 18% and 12%, respectively of the total variation. The
traits which contributed more positively to PC1 are number
of ears harvested, field weight and grain yield. Traits such
as anthesis, silking, anthesis-silking interval, plant and ear
heights, and grain moisture contributed more positively to
PC2. Anthesis-silking interval, plant and ear heights
contributed more positively to PC3 whereas plant and ear
heights and grain yield contributed more positively to PC4.
It was observed that grain yield and yield-related traits
contributed more to the first principal component while the
other agronomic traits contributed more to the second
principal component.
Table 5: Principal component analysis of 60 open-
pollinated maize varieties for nine traits evaluated at
Newton and Kalangba, 2015.
Statistics PC1 PC2 PC3 PC4
Standard deviation 1.78 1.31 1.28 1.03
Proportion of Variance 0.35 0.19 0.18 0.12
Cumulative Proportion 0.35 0.54 0.72 0.84
Eigen Values 3.19 1.71 1.63 1.06
Eigen Vectors
Variables
Anthesis -0.33 0.35 -0.50 0.15
Silking -0.34 0.39 -0.44 0.13
ASI -0.08 0.36 0.40 -0.18
Plant Height 0.16 0.44 0.37 0.26
Ear Height -0.01 0.48 0.33 0.25
No. of Ears Harvested 0.50 0.13 -0.23 -0.08
Grain Moisture 0.11 0.34 -0.10 -0.81
Field weight 0.50 0.18 -0.23 -0.01
Grain yield 0.47 0.03 -0.21 0.37
Cluster analysis and correlation of traits
Cluster diagram using Ward’s method based on nine agro-
morphological traits of 60 maize genotypes is presented in
the Figure 1. Results showed that the cluster diagram
grouped the genotypes into seven main clusters. Clusters
I, II, V and VI each consisted of eight genotypes, cluster III
seventeen, cluster IV five and cluster VII six genotypes.
Each of the main clusters consisted of two sub-clusters.
The first sub-clusters in cluster I and II comprised of four
genotypes each, cluster IV and VII two genotypes, while
the first sub-clusters in cluster III, V and VI comprised of
eight, three and six genotypes, respectively. The second
sub-clusters in cluster I, II and VII consisted of four
genotypes each whereas cluster III, IV, V and VI
comprised of nine, three, five and two genotypes,
respectively in their second sub-clusters. Genotypes
included in the third cluster contributed the bulk (28.33%)
of the total genotypes. In this cluster, genotypes were
grouped based on their early flowering and anthesis-
silking interval, shortest plant and ear heights, and low
grain moisture content (Table 6). Genotypes in the first,
second, fifth and sixth clusters contributed 13.33% each of

6. Genetic Variability and Morphological Diversity among Open-Pollinated Maize (Zea mays L.) Varieties
Sesay et al. 426
Figure 1: Dendogram of Euclidean distance measure using Ward’s clustering method
Table 6: Cluster means of traits for 60 genotypes evaluated at Newton and Kalangba, 2015.
Cluster Anthesis Silking
Anthesis-
silking interval
Plant
height
Ear
height
Number of
ears harvested
Grain
moisture Field weight Grain yield
I 51 54 3 166.26 70.08 32 27.99 3.7 2.62
II 49.12 52.75 4 173.69 74.39 30.88 25.36 3.61 2.71
III 49.29 52.47 3.06 165.22 68.32 30.88 23.61 3.62 2.77
IV 50.88 53.88 3 165.07 70.96 33.25 24.96 3.91 3.02
V 53.4 56.6 3.4 170.94 75.56 29 24.32 3.44 2.54
VI 50 53.5 3.83 181.82 73.23 34.33 26.95 4.05 3.07
VII 49 52.12 3 180.35 75.1 33.38 25.09 3.86 2.99
the total genotypes - Genotypes in the first cluster had
early anthesis-silking interval, highest grain moisture
content and lowest grain yield whereas in cluster II early
flowering and late anthesis-silking interval were the
peculiar characteristics that discriminated the genotypes
from the rest of the other genotypes. The cluster mean of
genotypes grouped in cluster V revealed that genotypes
expressed late flowering and highest ear height, and
produced the lowest number of ears harvested, field
weight and grain yield. Genotypes in cluster VI expressed
late anthesis-silking interval and produced the highest
plant height, number of ears harvested, field weight and
grain yield. Genotypes in cluster IV and VII represented
8.33% and 10%, respectively of the total genotypes. In
cluster IV, genotypes had early anthesis-silking interval
and shortest plant height, and produced the highest
number of ears harvested, field weight and grain yield.
Whereas genotypes in cluster VII expressed early
flowering, highest plant and ear heights, and produced
highest number of ears harvested, high field weight and
grain yield. The distribution pattern of genotypes into
various clusters indicated the presence of considerable
genetic divergence among the genotypes for most of the
traits evaluated. Thus representative genotypes from a
particular group of cluster could be chosen for
hybridization programmes. For instance, clusters IV, VI
and VII that produced the highest grain yield and other
important traits were the most divergent from clusters I and
V, with the lowest mean grain yields and other traits.
However, the selection of parents for hybridization should
consider the special advantages of each cluster and each
genotype within a cluster depending on specific objectives
of hybridization (Singh, 2001; Chahal and Gosal, 2002).
Hence, crosses involving clusters I and V with any other
clusters would be meaningless because the chances of
producing segregants with high grain yields from crosses
with others are limited. On the other hand, crosses
involving cluster IV with clusters VI and VII would be
expected to manifest higher heterosis and could result in
segregants with higher grain yields.
Table 7 presents the correlation of nine traits in 60
genotypes evaluated at locations Newton and Kalangba.
Grain yield is a complex quantitative trait that depends on
other traits for selection (Fellahi et al., 2013). In this study,
plant and ear heights, number of ears harvested and field
weight evaluated at both locations exerted positive and
significant (p≤0.01) correlation with grain yield, indicating

7. Genetic Variability and Morphological Diversity among Open-Pollinated Maize (Zea mays L.) Varieties
Int. J. Plant Breed. Crop Sci. 427
Table 7: Simple correlation of nine traits in 60 genotypes for locations Newton (below diagonal) and Kalangba (above
diagonal)
Traits Anthesis Silking ASI
Plant
Height Ear Height
No. of Ears
Harvested
Grain
Moisture
Field
weight
Grain
yield
Anthesis 1 0.99** 0.06 -0.12 0.04 -0.28** 0.01 -0.26** -0.25**
Silking 0.98** 1 0.21** -0.08 0.08 -0.27** 0.03 -0.25** -0.24**
ASI -0.39** -0.18** 1 0.20** 0.25** 0.03 0.17* 0.01 0.01
Plant Height 0.02 0.03 0.03 1 0.55** 0.32** 0.15* 0.30** 0.30**
Ear Height 0.11 0.12 0.01 0.55** 1 0.20** 0.02 0.18** 0.19**
No. of Ears Harvested -0.03 -0.01 0.12 0.38** 0.30** 1 -0.05 0.96** 0.96**
Grain Moisture 0.03 0.02 -0.04 -0.02 0.11 -0.05 1 -0.02 -0.02
Field weight 0.03 0.05 0.07 0.40** 0.33** 0.78** 0.04 1 0.99**
Grain yield 0.01 0.03 0.08 0.27** 0.22** 0.55** -0.58** 0.56** 1
**, significant at probability level of 1%.
that the traits can be improved simultaneously with grain
yield in a selection programme and selection of these traits
may lead to a substantial improvement in grain yield.
Positive and significant correlation between grain yield and
both plant and ear heights was reported by Salami et al.
(2007). Traits such as grain moisture content evaluated at
Newton, and days to 50% anthesis and silking at Kalangba
showed negative and significant (p≤0.01) relationship with
grain yield. Raut et al. (2017) observed negative
correlation of days to 50% tasseling and days to 50%
silking with grain yield. Other traits revealed positive and
significant (p≤0.01) association with one another at each
location.
CONCLUSIONS
There was significant genetic variability observed among
the genotypes evaluated thereby suggest the scope to
bring about traits improvement of genotypes through direct
selection and hybridization. Plant and ear heights, number
of ears harvested and field weight that showed significant
genetic variation in location Kalangba and generally
associated with grain yield in the genotypes are identified
as important traits for grain yield selection and selection
would be effective in improving these traits in open-
pollinated maize breeding program.
CONFLICT OF INTERESTS
There is no conflict of interest for this paper
ACKNOWLEDGEMENTS
The authors acknowledged the Alliance for a Green
Revolution in Africa (AGRA) for financial support and the
International Institute of Tropical Agriculture (IITA), Ibadan,
Nigeria for providing the seeds of genotypes.
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Accepted 2 November 2018
Citation: Sesay S, Jalloh AB, Kamara N (2018). Genetic
Variability and Morphological Diversity among Open-
Pollinated Maize (Zea mays L.) Varieties. International
Journal of Plant Breeding and Crop Science 5(3): 421-428.
Copyright: © 2018 Sesay et al. This is an open-access
article distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium,
provided the original author and source are cited.