INTRODUCTION
Maize (Zea
mays L.) is the most widely grown cereal in the world, and the third most
important cereal crop after wheat and rice. It serves as a primary staple food
in most developing countries and provides ~60% of
all human calories alongside with rice and wheat (Cassman et al.,
2003; Khalil et al., 2011). In Africa maize is staple food and source of
income for small holder farmers and the need will be doubled in 2050 worldwide
especially in developing countries including Ethiopia (FAO, 2017). Therefore,
to feed the ever increasing human population especially in developing countries
more maize grain production is demanded.
In Ethiopia, maize is
one of the most important and major strategic food crop among cereal, ranking second
after teff in area coverage and first in production
and productivity with national average yield of 3.73 t/ha (CSA, 2017; FAO 2017).
Ethiopia has wide agro ecologies suitable for maize production from which Benshangul Gumuz region is one of
the highest potential maize production area (Gemechu et
al., 2016). In Benshangul Gumuz
region maize is the second most cultivated crops and the first in production
with average yield of about 3.84 t/ha (CSA, 2017). Even though, the region have
the highest potential maize growing environment average yield is far from the
world average 5.75 t/ha (FAO, 2017). And it needs to be increased by using
appropriate maize variety for the area. From the day maize research started in
Ethiopia in 1950 several OPVs and hybrid maize varieties have been released.
However, after 1995, as commercial maize production shifts to hybrid seeds, the
average yield increased significantly and creates more job opportunity to the
people (Worku et
al., 2012).
Yield is complex
trait governed by many genes and influenced directly as well as indirectly by
its various components. Hence, it’s important to quantify the observed and true
association through simple phenotypic and genotypic correlation coefficients.
For all crop breeders understanding the association between yield and other
contributing phenotypic trait is important for joint selection of two or more
traits for yield improvement (Sonnad 2005; Wolie and Dessalegn 2011).
Generally, yield improvement through selection of two or more traits
simultaneously and identifying the most adapted and high yielder hybrid maize
varieties for commercial utilization could help to boost maize productivity in
the study area. Hence, the objectives of the study were to determine the correlation between grain yield
and other agronomic parameters and to identify high yielding adapted hybrid
maize varieties
MATERIALS AND METHODS
Experimental Material, Design and Management
The experiment was conducted on two locations
Assosa (10°2ˈ24.2"N, 34°34ˈ19.2"
E, 1553 m altitude) and Kamash (09031’21.0”N,
350 53'09.4E”, 1217 m altitude) in Benshangul
Gumuz region of western Ethiopia in 2016 main
cropping season. Nineteen released hybrid maize varieties were evaluated using
randomized complete block design in three replications. Hybrid maize varieties MH130,
MH138, AMH760Q, Gibat, Wenchi,
BH140, BH540, BHQP542, BHQPY545, BH546, BH547, BH660, BH661, BH670 and BH543
(standard check) are released by Ethiopian institute of Agricultural Research (Bako National Maize, Melkasa and
Ambo Agricultural research centers) Whereas, Limu and
Shone released by Pioneer Hi-Bred Seeds Ethiopia, and the rest Abarya and SCDUA43 released
by Seed co company. Each genotype was planted by using a plot size of two rows
with a 5.1m length and 0.75m x 0.15m inter and intra row spacing, respectively.
Two border rows were used in each direction to reduce the border effect. Each
variety was planted two seeds per hill and recommended planting density were
achieved through thinning after two weeks of emergence. The experimental field preparation,
seed rate and other agronomic activities were done following recommended
agronomic practice for the area. Inorganic fertilizer UREA (180 kg/ha) and DAP (100
kg/ha) were used as a source of N and P as per the recommended rate and time
for the area.
Data Collection and
Analysis
Data were collected on plant and plot basis
for ten quantitative traits. Plant height (cm), ear height (cm) and number of
ears per plant were taken from five randomly selected plants. Whereas the rest
on plot basis. Phonological data like days to anthesis
(DA), days to silking (DS) and days to maturity (DM)
were collected as the number of days from sowing to 50% of the plot reaches.
Disease data like gray leaf spot (GLS) and Turcicum leaf blight (TLB) were collected on 1-5 scale as
described by Badu-Apraku et al. (2012). Ear weight was
recorded from total plot and converted to kilogram per hectare. Grain yield was
calculated using formula adopted by MacRobert et al.
(2014).
Grain yield (kg/ha) = 
Where, MC = harvest time moisture
content in grains (%), 0.8 = standard shelling co-efficient, 12.5 = standard
moisture content, and 7.65 = area harvested (m2)
Data were
subjected to analysis of variance (ANOVA) procedure using a general linear
model (GLM). Phenotypic and genotypic correlation analysis between grain yield
and other traits was done using the formula adopted by Singh and Chaudhary (1985). The correlation value was tested for
their significance using t-test as described by Sharma, (1998). Data analysis
was carried out using SAS software version 9.2 (SAS, 2009).
RESULTS AND DISCUSSION
F-test indicates the homogeneity of error
variance violates the assumption of ANOVA for all tested traits, therefore
analysis were done separately for each locations. Analysis of variance revealed highly significant
difference (p≤ 0.01) among genotypes for most of tested traits at both Kamash and Assosa locations (Table
1 and 2, respectively). These indicated presence of sufficient amount of
variability among genotypes for the tested traits. The days to maturity ranged
from 111-152 and 140-169 days after sowing with mean value of 140 and 159 for Kamash and Assosa location,
respectively. Genotypes showed relatively shorter phenology at kamash and it may be due to its lower altitude. Similarly, Xue-jun et al. (2013) reported the positive association of
altitude with growing period on maize. Phenological
traits showed highly significant difference among genotypes in which MH130 and
BH670 showed the shortest and the longest days to maturity, respectively at kamash. Whereas, BH661 and BH670 recorded the longest days
to maturity while SCDUA43 found to be early maturing in Assosa
condition. The mean value for plant and ear height were 262 cm and 139 cm for Kamash whereas 256 cm and 146 cm for Assosa,
respectively. Under both locations, varieties MH130 and BH661 recorded the
lowest and the highest plant and ear height, respectively. The highest fresh
ear weight were recorded from Limu, Shone and BH546
varieties while the lowest value were from MH138, MH130, BHQPY545 and Jibat varieties at Kamash
location. At Assosa Shone, BH546, Abarya
and BH547 recorded highest fresh ear weight while MH130 was the least. Similarly,
several authors observed significant genotypic difference in maize for
phonological and agronomic traits (Yusuf, 2010; Reddy et al., 2012; Musvosvi and Wali 2017; Debela et al., 2017).
Several biotic and abiotic stresses resulted in
considerable yield loss in maize. Among these turcicum
leaf blight and gray leaf spot are the most economically important maize
diseases in western Ethiopia (Wende et al., 2013).
Accordingly, hybrid maize varieties evaluated for both disease reactions and
showed highly significant difference among genotypes. Resistance and
susceptible phenotype for gray leaf spot disease reaction observed from BH546
and MH130 at Kamash, and from Limu
and SCDUA43 at Assosa, respectively. At kamash condition, low disease severity was observed from
AMH760Q for tircicum leaf blight. Comparable result
was reported by Debela et al. (2017).
Highly significant differences (p≤ 0.01) were observed
in grain yield under both locations with the mean values of 7856 kg/ha and 6831
kg/ha at Kamash and Assosa,
respectively. This result is in conformity with the findings of Reddy et al.
(2012) and Kinfe et al. (2015) in maize. Hybrid maize varieties Limu, Shone and BH546 showed the highest grain yield and
significantly different from the standard check BH543 at Kamash
location. At Assosa maize hybrids showed
non-significant yield difference from the check. Although, best agronomic
performance and greater than 13% yield advantage over the check were recorded
from varieties Abarya, Shone, BH546 and BH547. Therefore,
demonstration and creating awareness about these high yielding and adaptable maize
varieties to maize growers could boost maize production in the area. Least grain
yield and other agronomic performance were observed from MH130,
BHQPY545 and Jibat varieties under both locations
while MH138 at Kamash. Hence, cultivating these
released hybrid maize varieties were not recommended for the study area.
The relationship between yield and agronomic traits is important
to the plant breeders to find out the traits correlated with yield and also how
they are associated among themselves. The results of genotypic and phenotypic
correlation for the tested traits were presented in Table 3 and 4 for Kamash and Assosa locations, respectively. At Kamash
field condition, correlation analysis revealed highly significant (p≤
0.01) positive genotypic and phenotypic correlation of grain yield with fresh
ear weight. Grain yield showed highly significant (p≤ 0.01) genotypic and
phenotypic negative correlation with gray leaf spot. Also grain yield showed
significant (p≤ 0.05) positive correlation with days to maturity and
negative correlation with Turcicum leaf blight at
phenotypic level. This implies that selection high values for the positively
correlated traits could result simultaneous improvement of yield and vice
versa. Fresh ear weight showed significant negative correlation with gray leaf
spot and Turcicum leaf blight at phenotypic level
while with gray leaf spot at genotypic level. Days to
maturity showed highly significant (p≤ 0.01) genotypic and phenotypic correlation with days to anthesis, days to silking, plant
height and ear height. Similarly, correlations among phonological traits were reported
by Reddy et al. (2012) in maize.
At Assosa field condition, grain yield showed significant
positive genotypic correlation with plant height and fresh ear weight.
Phenotypic correlation of grain yield were significant and positive for plant
height, ear height and fresh ear weight while significant and negative with
grey leaf spot and Turcicum leaf blight disease reaction. The strong correlation between
fresh ear weight, ear height and plant height with grain yield suggested that improvement
of grain yield in maize hybrids through indirect selection of these traits
could be possible. Similar results were reported by Reddy
et al. (2012) and Ndebeh
et al. (2017) for correlation of grain yield with plant height and ear height. Significant
genotypic correlations of fresh ear weight were positive for days to maturity
and plant height and negative for gray leaf spot. Fresh ear weight revealed
significant phenotypic correlations with days to maturity, plant height and ear
height positively. Significant negative genotypic correlation was observed
between ears per plant and plant height. Days to maturity showed significant positive
genotypic and phenotypic correlation with days to anthesis,
days to silking, plant height and ear height.
Similarly, significant positive correlation were reported for fresh ear weight
and yield, days to anthesis with days to silking and days to maturity, ear height with plant height and
days to silking (Patil
et al., 2016; Reddy et al., 2012; Sadaiah et al., 2013).
Table
1. Analysis of variance
and mean performance of hybrid maize varieties for yield and other traits at Kamash.
|
No
|
Variety
|
DA
|
DS
|
DM
|
PH
|
EH
|
GLS
|
Blight
|
EPP
|
EW
|
GYLD
|
|
1
|
Shone
|
71.7
|
75.0
|
147.0
|
278.3
|
124.7
|
2.0
|
2.0
|
1.1
|
14598.4
|
10338.7
|
|
2
|
BH140
|
72.7
|
78.0
|
145.0
|
252.7
|
140.3
|
2.3
|
3.0
|
1.0
|
10711.6
|
7758.7
|
|
3
|
BH540
|
69.7
|
73.3
|
144.3
|
262.3
|
130.7
|
3.3
|
2.7
|
1.1
|
10070.1
|
7442.2
|
|
4
|
BH543
|
67.7
|
78.3
|
147.3
|
270.7
|
151.3
|
2.3
|
2.0
|
0.9
|
10263.6
|
7395.1
|
|
5
|
BH546
|
71.7
|
76.7
|
145.7
|
257.3
|
140.7
|
1.7
|
2.3
|
0.9
|
12803.7
|
9108.5
|
|
6
|
BH547
|
73.0
|
77.7
|
147.3
|
248.3
|
142.0
|
2.0
|
2.7
|
0.9
|
12195.2
|
8872.8
|
|
7
|
BH660
|
73.7
|
82.0
|
151.3
|
301.3
|
186.0
|
3.3
|
2.3
|
1.0
|
11119.7
|
7973.5
|
|
8
|
BH661
|
73.0
|
83.7
|
148.7
|
314.0
|
186.0
|
2.0
|
2.3
|
1.0
|
10750.5
|
7683.7
|
|
9
|
BH670
|
75.0
|
81.7
|
152.0
|
304.3
|
180.3
|
2.7
|
2.3
|
0.9
|
10225.7
|
7386.2
|
|
10
|
BHQP542
|
71.7
|
74.0
|
144.0
|
268.3
|
122.3
|
2.0
|
2.7
|
1.3
|
11349.0
|
8465.7
|
|
11
|
BHQPY545
|
74.0
|
77.3
|
143.7
|
251.3
|
123.3
|
3.0
|
3.3
|
1.3
|
8602.8
|
6201.3
|
|
12
|
MH130
|
60.3
|
66.3
|
110.7
|
213.7
|
95.0
|
4.0
|
3.3
|
0.9
|
8035.1
|
6050.5
|
|
13
|
MH138
|
72.0
|
73.7
|
114.0
|
245.7
|
109.7
|
2.3
|
2.3
|
0.9
|
7969.2
|
5903.7
|
|
14
|
Limu
|
71.7
|
75.0
|
146.7
|
267.0
|
124.3
|
2.0
|
2.0
|
1.2
|
14647.3
|
10751.0
|
|
15
|
SC DUA43
|
64.7
|
69.3
|
113.7
|
250.3
|
105.0
|
3.0
|
2.3
|
1.1
|
11463.7
|
8573.3
|
|
16
|
Abarya
|
69.0
|
73.0
|
146.0
|
253.7
|
130.3
|
3.0
|
2.7
|
1.0
|
10261.7
|
7798.7
|
|
17
|
AMH760Q
|
72.3
|
77.0
|
150.0
|
247.0
|
156.0
|
3.0
|
1.7
|
1.0
|
10182.6
|
7260.2
|
|
18
|
Gibat
|
68.0
|
71.7
|
145.0
|
266.0
|
130.0
|
3.7
|
2.3
|
1.0
|
8971.8
|
6699.7
|
|
19
|
Wenchi
|
68.3
|
74.3
|
115.0
|
230.3
|
108.7
|
3.3
|
3.3
|
1.1
|
10655.7
|
7595.0
|
|
Mean
|
70.5
|
75.7
|
139.9
|
262.2
|
136.1
|
2.7
|
2.5
|
1.0
|
10783.0
|
7855.7
|
|
CV
|
2.1
|
3.2
|
2.7
|
3.6
|
7.0
|
21.1
|
20.5
|
15.6
|
12.4
|
11.9
|
|
LSD (0.05)
|
2.4
|
4.0
|
6.2
|
15.8
|
15.8
|
0.9
|
0.9
|
0.3
|
2219.1
|
1553.9
|
|
F-test
|
**
|
**
|
**
|
**
|
**
|
**
|
**
|
*
|
**
|
**
|
Key: DA: Days
to anthesis, DS: Days to silking,
DM: Days to maturity, PH: Plant height (cm), EH: Ear height (cm), GLS: Gray
leaf spot, TLB: Tircicum leaf blight, EPP: Ears per
plant, EW: Fresh ear weight (kg/ha), GYLD: Grain Yield (KG/ha), CV: Coefficient
of Variation, LSD: Least Significant Difference.
Table 2. Analysis of variance and mean performance of
hybrid maize varieties for yield and other traits at Assosa.
|
No
|
Variety
|
DA
|
DS
|
DM
|
PH
|
EH
|
GLS
|
TLB
|
EPP
|
EW
|
GYLD
|
|
1
|
Shone
|
79.3
|
83.3
|
160.0
|
266.0
|
140.7
|
2.0
|
2.0
|
1.0
|
12132.6
|
8354.7
|
|
2
|
BH140
|
84.7
|
88.7
|
162.0
|
249.3
|
143.3
|
2.3
|
3.0
|
1.1
|
8074.9
|
5713.8
|
|
3
|
BH540
|
85.0
|
86.7
|
161.7
|
236.0
|
128.3
|
2.7
|
2.3
|
1.0
|
8170.6
|
5764.4
|
|
4
|
BH543
|
80.7
|
83.3
|
161.0
|
264.3
|
158.3
|
2.0
|
3.0
|
1.1
|
10270.8
|
7134.6
|
|
5
|
BH546
|
82.7
|
86.0
|
163.3
|
257.7
|
142.0
|
2.0
|
2.3
|
1.1
|
12014.9
|
8072.5
|
|
6
|
BH547
|
83.7
|
86.3
|
161.7
|
242.0
|
145.3
|
2.0
|
2.7
|
1.0
|
11424.3
|
8062.2
|
|
7
|
BH660
|
86.3
|
87.3
|
167.3
|
307.3
|
201.0
|
2.3
|
2.3
|
1.1
|
10347.9
|
7161.7
|
|
8
|
BH661
|
87.3
|
90.0
|
169.0
|
274.7
|
163.0
|
2.0
|
2.3
|
1.1
|
10153.6
|
6791.4
|
|
9
|
BH670
|
86.3
|
88.7
|
169.0
|
293.3
|
186.0
|
2.0
|
2.0
|
1.1
|
11004.2
|
7597.8
|
|
10
|
BHQP542
|
82.3
|
84.7
|
155.3
|
268.0
|
144.0
|
2.0
|
3.7
|
1.2
|
9042.1
|
6534.3
|
|
11
|
BHQPY545
|
84.7
|
87.7
|
159.7
|
222.3
|
118.7
|
2.0
|
2.0
|
1.8
|
8225.0
|
5679.3
|
|
12
|
MH130
|
71.3
|
73.3
|
148.3
|
213.3
|
103.7
|
2.7
|
3.7
|
1.3
|
7680.4
|
5691.6
|
|
13
|
MH138
|
77.7
|
80.0
|
149.3
|
233.7
|
113.7
|
2.3
|
3.3
|
1.4
|
8879.6
|
6504.6
|
|
14
|
Limu
|
82.0
|
84.3
|
161.3
|
252.3
|
133.7
|
1.3
|
2.3
|
1.2
|
10903.8
|
7575.8
|
|
15
|
SC DUA43
|
72.0
|
73.7
|
140.3
|
251.7
|
120.7
|
3.7
|
2.7
|
1.3
|
8586.8
|
6361.9
|
|
16
|
Abarya
|
78.3
|
81.3
|
161.7
|
249.3
|
138.0
|
2.0
|
2.3
|
1.2
|
11755.7
|
8460.2
|
|
17
|
AMH760Q
|
81.0
|
85.3
|
167.3
|
279.0
|
176.0
|
2.0
|
2.7
|
1.3
|
9844.9
|
6676.2
|
|
18
|
Gibat
|
79.0
|
82.0
|
163.3
|
257.0
|
154.7
|
1.7
|
2.0
|
1.2
|
8130.8
|
5653.2
|
|
19
|
Wenchi
|
76.3
|
78.3
|
145.3
|
240.0
|
136.0
|
2.7
|
3.0
|
1.1
|
8278.9
|
5997.8
|
|
Mean
|
81.1
|
83.7
|
159.3
|
255.7
|
144.6
|
2.2
|
2.6
|
1.2
|
9732.7
|
6830.9
|
|
CV
|
3.4
|
3.3
|
2.2
|
6.1
|
9.7
|
21.0
|
19.9
|
10.9
|
15.4
|
15.1
|
|
LSD (0.05)
|
4.5
|
4.5
|
5.7
|
26.0
|
23.2
|
0.8
|
0.9
|
0.2
|
2485.4
|
1709.9
|
|
F-test
|
**
|
**
|
**
|
**
|
**
|
**
|
**
|
**
|
**
|
**
|
Key: DA: Days
to anthesis, DS: Days to silking,
DM: Days to maturity, PH: Plant height (cm), EH: Ear height (cm), GLS: Gray
leaf spot, TLB: Tircicum leaf blight, EPP: Ears per
plant, EW: Fresh ear weight (kg/ha), GYLD: Grain Yield (KG/ha), CV: Coefficient
of Variation, LSD: Least Significant Difference.
Table 3 Genotypic (above
diagonal) and phenotypic (below diagonal) correlations of ten quantitative traits
at Kamash.
|
Traits
|
DA
|
DS
|
DM
|
PH
|
EH
|
GLS
|
Blight
|
EPP
|
EBM
|
GYLD
|
|
DA
|
|
0.81**
|
0.68**
|
0.59**
|
0.63**
|
-0.55*
|
-0.26
|
0.03
|
0.27
|
0.22
|
|
DS
|
0.78**
|
|
0.68**
|
0.76**
|
0.90**
|
-0.45
|
-0.28
|
-0.23
|
0.20
|
0.13
|
|
DM
|
0.61**
|
0.60**
|
|
0.66**
|
0.74**
|
-0.38
|
-0.44
|
-0.08
|
0.38
|
0.35
|
|
PH
|
0.49**
|
0.56**
|
0.59**
|
|
0.82**
|
-0.35
|
-0.49*
|
-0.08
|
0.30
|
0.27
|
|
EH
|
0.51**
|
0.72**
|
0.65**
|
0.79**
|
|
-0.23
|
-0.42
|
-0.39
|
0.12
|
0.06
|
|
GLS
|
-0.40**
|
-0.33**
|
-0.30*
|
-0.29*
|
-0.20
|
|
0.40
|
0.02
|
-0.63**
|
-0.60**
|
|
Blight
|
-0.24
|
-0.15
|
-0.33*
|
-0.36**
|
-0.27*
|
0.25*
|
|
0.26
|
-0.43
|
-0.42
|
|
EPP
|
-0.03
|
-0.15
|
-0.03
|
-0.07
|
-0.22
|
-0.01
|
0.17
|
|
0.14
|
0.17
|
|
EBM
|
0.15
|
0.11
|
0.31*
|
0.24
|
0.13
|
-0.40**
|
-0.29*
|
0.29
|
|
0.99**
|
|
GYLD
|
0.09
|
0.03
|
0.29*
|
0.23
|
0.09
|
-0.38**
|
-0.28*
|
0.29
|
0.99**
|
|
Key: DA: Days
to anthesis, DS: Days to silking,
DM: Days to maturity, PH: Plant height, EH: Ear height, GLS: Gray leaf spot,
TLB: Tircicum leaf blight, EPP: Ears per plant, EW:
Fresh ear weight, GYLD: Grain Yield.
Table 4 Genotypic (above diagonal) and phenotypic
(below diagonal) correlations of ten quantitative traits at Assosa.
|
Traits
|
DA
|
DS
|
DM
|
PH
|
EH
|
GLS
|
TLB
|
EPP
|
EBM
|
GYLD
|
|
DA
|
|
0.95**
|
0.77**
|
0.53*
|
0.65**
|
-0.50*
|
-0.42
|
-0.28
|
0.34
|
0.22
|
|
DS
|
0.89**
|
|
0.77**
|
0.41
|
0.57*
|
-0.57*
|
-0.46
|
-0.12
|
0.34
|
0.22
|
|
DM
|
0.65**
|
0.63**
|
|
0.56*
|
0.70**
|
-0.68**
|
-0.50*
|
-0.24
|
0.44*
|
0.32
|
|
PH
|
0.08
|
0.02
|
0.34*
|
|
0.89**
|
-0.20
|
-0.32
|
-0.47*
|
0.54*
|
0.46*
|
|
EH
|
0.28*
|
0.25
|
0.51**
|
0.84**
|
|
-0.33
|
-0.41
|
-0.43
|
0.43
|
0.34
|
|
GLS
|
-0.27*
|
-0.33*
|
-0.37**
|
-0.22
|
-0.27*
|
|
0.32
|
0.04
|
-0.47*
|
-0.39
|
|
TLB
|
-0.22
|
-0.28*
|
-0.34**
|
-0.31*
|
-0.31*
|
0.40**
|
|
0.01
|
-0.43
|
-0.33
|
|
EPP
|
-0.31*
|
-0.24
|
-0.22
|
-0.08
|
-0.22
|
-0.11
|
-0.14
|
|
-0.41
|
-0.42
|
|
EBM
|
-0.01
|
-0.01
|
0.27*
|
0.58**
|
0.50**
|
-0.40**
|
-0.39**
|
-0.04
|
|
0.98**
|
|
GYLD
|
-0.11
|
-0.11
|
0.17
|
0.56**
|
0.45**
|
-0.35**
|
-0.33*
|
-0.01
|
0.99**
|
|
Key: DA: Days to anthesis, DS: Days to silking,
DM: Days to maturity, PH: Plant height, EH: Ear height, GLS: Gray leaf spot,
TLB: Tircicum leaf blight, EPP: Ears per plant, EW:
Fresh ear weight, GYLD: Grain Yield.
CONCLUSION
In Ethiopia, maize is one of the most
important and major strategic food crop among cereal. Significant yield
increments on yield have been observed as commercial maize production shifts to
hybrid seeds. To keep the change in the yield advances selection should be made
for yield and important yield components simultaneously. Moreover, newly
released maize hybrids should be testified for their adaptability and yield
performances there by selection should be made for further popularization of the
variety.
Analysis of variance
revealed sufficient amount of variability among genotypes for the tested
traits. Hybrid maize varieties Limu, Shone and BH546 are
showed significant yield advantage over the check at Kamash
areas. At Assosa maize hybrids Viz. Abarya, Shone, BH546 and BH547 revealed highest yield
performance. Therefore, demonstration and popularization of these varieties in
the respective areas could boost maize yield. Correlation analysis depicts
negative significant correlation of grain yield with gray leaf spot and Turcicum leaf blight diseases. Positive significant
correlation of grain yield were observed with days to maturity and fresh ear
weight at Kamash location and with plant height, ear
height and fresh ear weight at Assosa location. These
positive and significant associations between these traits suggested that they
can be selected simultaneously for yield improvement in maize breeding program.
However, since the study conducted for a year only, it is important to repeat
the experiment to confirm the result of the present study.
ACKNOWLEDGMENTS
I would like to thank Ethiopian institute of
agricultural research, Bako national maize program of
Ethiopia and Assosa agricultural research center for
financial and technical support provided. I also acknowledge Mr. Alemu Worku and Adugna Kumera for the support in
data collection.
REFERENCES
Abera, W.,
Hussein, S., Derera, J., Worku,
M. and Laing, M.D., 2013. Preferences and
constraints of maize farmers in the development and adoption of improved
varieties in the mid-altitude, sub-humid agro-ecology of western Ethiopia.
Afr. J. Agric. Res.,
8(14), pp.1245-1254.
Badu-Apraku, B. and Oyekunle, M. 2012. Genetic
Analysis of Grain Yield and other Traits of Extra-Early Yellow Maize Inbreeds
and Hybrid Performance Under Contrasting Environments. Field Crops Res., 129,
99–110.
Cassman, K.G., Dobermann, A., Walters,
D.T. and Yang, H., 2003. Meeting cereal demand while protecting natural
resources and improving environmental quality. Annu. Rev. Envir. Res., 28(1), pp.315-358.
Central Statically Agency. 2017.
Crop Area and Production of Major Crops Report, Private Peasant Holdings, and
Main season Volume I. Addis Ababa, Ethiopia.
Debela, M., Dejene, M. and Abera,
W., 2017. Management of Turcicum
leaf blight [Exserohilum turcicum
(Pass.) Leonard Suggs] of maize (Zea
mays L.) through integration of host resistance and fungicide at Bako, Western Ethiopia. Afr. J. Plant Sci.
11(1), pp.6-22.
FAO STAT.
2017. Food and Agricultural Organization Statistical Data base: Production and
Trade. http://www.fao.org/faostat/en/#data/QC. Accessed on September 5, 2018.
Gemechu
Nedi, Sentayehu Alamerew and Leta Tulu. 2016.
Review on Quality Protein Maize Breeding for Ethiopia. J. of Bio., Agric.
and Health care, 6(15): 84-85.
Khalil AI,
Ur- Rahman H, Ur-Rehman N, Arif M, Khalil IH, Iqbal M, Hidayatullah, Afridi K, Sajjad M, Ishaq M (2011).
Evaluation of maize hybrids for grain yield stability in North-West of
Pakistan. Sarhad J. Agric. 27(2):213.
Kinfe H,Tsehaye Y, Redda A, Welegebriel R, Yalew D, et al.
(2017) Evaluating Adaptability and Yield Performance of Open Pollinated Maize
Varieties in North Western Tigray. Adv. Crop Sci. Tech. 5: 316.
MacRobert,
J. F., Setimela, P. S., Gethi,
J., & Worku, M. (2014). Maize Hybrid Seed Production Manual. Mexico, D.F.:CIMMYT.
Musvosvi, C. and Wali, M.C., 2017. Genotype by Trait Associations
among Drought Tolerant Maize Inbred Lines. J. of
Agric. Sci, 9(12), p.21.
Ndebeh, J., Akromah, R., Vah, E.G., Kolleh,
D.S. and Baysah, N.S., 2017. Correlation analysis for grain yield and other agronomic parameters
for 90 single crosses hybrid maize evaluated in three agrological zones in
Ghana. Afr. J.
Agric. Res, 12(51), pp.3529-3536.
Patil, S.M.,
Kumar, K., Jakhar, D.S., Rai,
A., Borle, U.M. and Singh, P. 2016. Studies on Variability, Heritability, Genetic Advance and
Correlation in Maize ('Zea mays L.).
Inter. J. of Agric., Env.
and Biotec, 9(6):
1103-1108.
Reddy, V.R., Jabeen, F., Sudarshan, M.R. and Rao, A.S.,
2012. Studies on genetic variability,
heritability, correlation and path analysis in maize (Zea mays L.) over locations. Int. J. Appl. Biol. Pharm. Technol., 4(1), pp.196-199.
SAS, S., 2009. STAT User's Guide, Version 9.2. Cary, NC, USA: SAS
Institute.
Sharma,
J.R., 1998. Statistical and Biometrical Techniques in Plant
Breeding. New Age International (P) Limited
Publishers, New Delhi.432p.
Singh,
R.K. and Chaudhary, B.D., 1985. Line
x Tester analysis. Biometrical Methods in Quantitative Genetic Analysis, Ed,
3, pp.215-223.
Sonnad SK. 2005.
Stability analysis in white ragi (Eleusine coracana Gaertn.)
genotypes. PhD Thesis, University of Agricultural Sciences, Dharwad, India.
Wolie A, Dessalegn T. 2011. Correlation and path coefficient
analyses of some yield related traits in finger millet (Eleusine
coracana (L.) Gaertn.) germplasm in northwest Ethiopia. Afr. J. Agric. Res., 6:5099-5105.
Worku, M., Twumasi-Afriyie, S., Wolde, L., Tadesse, B., Demisie G., Bogale, G., Wegary, D. and Prasanna, B.M. (Eds.) 2012. Meeting the Challenges of Global Climate
Change and Food Security through
Innovative Maize Research. Proceedings of
the Third National Maize Workshop of Ethiopia. Addis Ababa,
Ethiopia.
Xue-jun,
C., Guang-cai, C., Qun, S.,
Dong-bin, W., Jing, C., Ya-xiong, Y.U., Jie, L. and Wei, L., 2013. Altitude effects on
maize growth period and quality traits. Acta Ecologica Sinica,
33(4), pp.233-236.
Yusuf,
M., 2010. Genetic variability and correlation in
single cross hybrids of quality protein maize (Zea
mays L.). Afr. J. Food, Agric., Nutr. Dev.,
10(2).
