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Research Article | | Peer-Reviewed

Agronomic and Physiological Efficiency of Maize (Zea mays L.) Hybrids as Influence by Nitrogen Fertilization in Semi-Arid Areas of Ethiopia

Jemal Bekere*,  Yaya Tesfa
Published in Agriculture, Forestry and Fisheries (Volume 13, Issue 6)
Received: 3 December 2024     Accepted: 16 December 2024     Published: 30 December 2024
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Abstract

Maize is one of the major food crops in semi-arid areas of Ethiopia. Efficient application of N fertilizer on maize crop enables smallholder farmers have a synergic effect through enhancing yield productivity, reducing cost of production and nitrous oxide emission to the atmosphere exacerbating the challenges of changing climate. This experiment was conducted to determine the effect of nitrogen fertilizer on yield and yield related traits and assess the relationship between yield and nitrogen use efficiency indices. Eight maize hybrids were evaluated at three rates of N fertilizer (0, 32.5 and 65 kg N/ha) using split-plot design with three replications at two locations (Dera and Melkassa) in 2020 main cropping season. The results from analysis of variance (ANOVA) at each location indicated that majority of yield and yield related traits, agronomic and physiological efficiency were significantly influenced either by one or two of the factors (nitrogen and genotype) and/or the interaction effect of the two at both locations. The results of combined ANOVA over locations revealed that the interaction of the three factors (location, nitrogen and genotype) had significant effect on agronomic and physiological efficiency. The hybrids WE7201 and WE8206 had obtained the highest agronomic (27.67 kg kg-1) and physiological efficiency (43.52 kg kg-1) due to the application of 32.5 kg N ha-1 respectively. Thus, WE7201 and WE8206 could be recommended for production in the study areas.

Published in Agriculture, Forestry and Fisheries (Volume 13, Issue 6)
DOI 10.11648/j.aff.20241306.20
Page(s) 308-319
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group
Previous article
Keywords

Agronomic Efficiency, Grain Yield, Nitrogen Fertilization, Physiological Efficiency

1. Introduction
Maize (Zea mays L.) is one of the members of the grass family, Gramineae. Its center of origin is accepted to be in Mesoamerica, primarily Mexico and the Caribbean though there is some controversy on the origin of the crop
 [32]
. It is cultivated globally being one of the most important cereal crops worldwide. In 2018, the three cereals (wheat, rice and maize) were cultivated on more than 672 million hectares of which maize accounted 41.6% land, and it had the widest distribution than the two cereal crops
 [16]
. Maize was cultivated in 166 countries which were more than by 49 and 44% than rice and wheat, growing countries respectively
 [11]
. Its high environmental adaptability to diverse climatic conditions and it is grown from sea level to higher than 3000 m.a.s.l. and in areas receiving annual rain fall of 250 to 5000 mm
 [13]
. The crop is being directly consumed as food, used as feed and for the production of fructose/glucose, flour, oils and ethanol. As a result of this versatility, adaptability and productivity, maize has become the most abundant crop globally
 [11]
.
In 2018/19 Meher season, maize is produced by 9,863,145 smallholder farmers on 2,367,797.39 hectares of land and produced 9,492,770.834 tonnes of grain yield with average yield of 3.99 t/ha
 [12]
. The average national maize yield was lower than 5.5 t/ha of the world’s average yield
 [16]
. The predominant constraints of maize production in Ethiopia are related to frequent occurrence of drought, low soil fertility, poor agronomic practice, limited use of input, insufficient technologies, lack of credit facilities, poor seed quality, diseases, insects and weeds
[10, 29]
.
Climate change and variability pose a serious threat to food production in sub-Saharan Africa
 [18]
. Climate change contributed significantly to the water scarcity problem
 [42]
. The changes in temperature and precipitation affect crop photosynthesis, crop development rates, as well as water and nutrient availability to crops
 [38]
. It was indicated that an increase in temperature of 2°C or more in the late 20th century was expected to negatively affect major crops (i.e. wheat, rice, and maize) on both temperate and tropical regions
 [23]
.
Nitrogen is the main limiting nutrient after carbon, hydrogen and oxygen for photosynthetic process, growth-development of plants and other changes to complete its lifecycle. Excessive use of N fertilizer results in enhanced crop production costs and atmospheric pollution; thus there is an urgent need to up-grade nitrogen use efficiency in agricultural farming system
 [30]
. Therefore, the water scarcity and temperature increase as constraints of maize production in moisture stress areas might not overcome unless the tolerant varieties to moisture stress are also efficient for N use. One of the major goals of crop research program is reducing fertilizer input while maintaining the environment or even increasing crop yield
[25, 40]
. However, genetic selection for improved nitrogen use efficiency (NUE) is often ignored and the genetic improvement of NUE in maize breeding program is mainly achieved through indirect selection for increased hybrid yield performance
[28, 34]
. In Ethiopia, 100 kg Urea and 100 kg NPS (65 kg N/ha) fertilizers are recommended for maize production for all the six major maize agro-ecology zones. However, the overall Ethiopia`s average fertilizer use is low and stands at approximately 21 kg/ha
 [4]
. Particularly, the small-scale farmers in moisture stress areas often do not invest in yield enhancing inputs like nitrogen fertilizer, because it contributes to lower crop productivity
 [9]
.
Evaluation and identification of inbred lines and QPM hybrids tolerant to low N were reported
[2, 8]
. Limited research were conducted on fertilizers rates determination for maize production in central rift valley but it was not on maize genotypes developed to tolerant to low N and moisture stresses
[36, 22]
. Melkassa Agriculture Research Center identified three way cross hybrids for moisture stress areas after evaluation for many years and over locations under managed drought stress and rain-fed conditions. However, these promising maize hybrids were not evaluated to N use efficiency, reducing the cost of production, enhance productivity of maize while maintaining environmental quality. Thus, the determination of NUE of these hybrids helps breeders in making decision and recommendation of better varieties which are efficient to N uptake and utilization that satisfies the interest of resource poor farmers to produce higher yield of maize with low input and cost in dry lowlands of the country. Therefore, the objectives of this study was to determine the genetic variability of maize hybrids for yield, yield related traits and agronomic and physiological efficiency under varying levels of N in semi-arid areas of Ethiopia.
2. Materials and Methods
2.1. Description of Experimental Sites
The field experiment was conducted during 2020 main cropping season at two locations (Dera and Melkassa) in the Central Rift Valley of Ethiopia representing semi-arid maize growing environments (drought prone areas) in Ethiopia is presented in (Table 1).
Table 1. Description of experimental sites.

Locations

Geographical position

Soil types

Altitude (m.a.s.l)

Rain fall (mm)

Temperature (°C)

Latitude

longitude

Min

Max

Dera

80 04` N

390 00` E

Andosols

1660

616.86

6.6

26.19

Melkassa

80 26` N

390 22` E

Andosols

1550

763

14

28
Source: Melkassa Agricultural Research Center
2.2. Experimental Materials
Eight maize hybrids including two standard checks were used at a test crop at two locations (Dera and Melkassa. The six QPM (Quality Protein Maize), a three way cross hybrids were developed for moisture stress areas and selected as better performing hybrids in yield, drought tolerance, rust and TLB diseases from national variety trials. The two check varieties viz. MH 138Q and MH 140 are medium maturing QPM and non-QPM hybrid, respectively, and both varieties were released by Melkassa Agricultural Research Centre. The quality protein maize, MH 138Q is a three way cross hybrid released in 2012, whereas as MH 140 (non-QPM) is also a three way cross hybrid released in 2013. All these hybrids are categorized under a medium physiological maturity group. The list and description of eight maize hybrids are presented in (Table 2).
Table 2. Description of Experimental Materials.

S.N

Genotypes

Pedigree

Year of released

Original source

G1

WE5202

WMA2101/WMC8801//CML539

-

MONSATO -South Africa

G2

WE6205

WMA3104/WMA2001//CML539

-

MONSATO -South Africa

G3

WE7201

WMC5813/WMC8801//CML539

-

MONSATO -South Africa

G4

WE7210

CML539/WMB0001//WMA2002

-

MONSATO -South Africa

G5

WE8203

WMB3002/WMB4810//WMA2502

-

MONSATO -South Africa

G6

WE8206

WMB3002/WMB4810//WMA2230

-

MONSATO -South Africa

G7

MH138Q

CML144/CML159//POLL15#SR538

2012

CIMMYT

G8

MH140

CML444/CML547//ZL0814

2013

CIMMYT
Seed source: Melkassa Agricultural Research Center (MARC).
2.3. Treatments and Experimental Design
The treatments consisted of factorial combinations of eight maize hybrids and three N levels (0, 32.5 and 65 kg N/ha) laid out in a split plot design with three replications. Nitrogen rate was assigned as main plot and the genotypes were assigned as sub plot. The plot size for planting was 4 m × 4.5 m (18 m2) accommodating 6 rows of 0.75 m and 0.25 m inter-and intra-row spacing, respectively. The data was collected from the net plot size of 9 m2 of four middle/central rows of each plot leaving the outside rows and a distance of 50 cm at the ends of each middle row to serve as borders. The distance between the plots and blocks were kept at 1 m and 1.5 m apart, respectively.
2.4. Experimental Procedures
The experimental plots were prepared by tractor plowing and harrowing. In accordance with the specifications of the design, a field layout was prepared and each treatment was assigned randomly to experimental plots within each block independently. The treatments of N soil nutrient were arranged based on the fertilizers recommendation for maize viz. 100 kg/ha Urea (46% N) and 100 kg/ha NPS/Nitrogen, Phosphorus and Sulfur (19% N, 38% P2O5 and 7% S). Therefore, The recommended rate of NPS was placed together with the seeds (two seeds per holes) during planting on June 26/2020 and July 14/2020 main cropping season at Melkassa and Dera sites respectively, while N was applied in a split application when plants was at jointing with approximately a 60-cm plant height or knee height and at flowering/anthesis as top dressing. The fertilizer after application was covered with the soil immediately to avoid its loss to the air through volatilization. Two seeds was planted per holes at a spacing of 25 cm intra raw and thinned to 1 plant per stand. Hand weeding was undertaken using a local hand hoe after three weeks of planting.
2.5. Plant Tissue Sampling and Analysis
At crop maturity, a sub-sample from each net plot was harvested at ground level and dried at 70°C until constant weight was reached for dry weight determination and partitioned into straw and grain. The dried samples were milled, and the grain and straw N content of the plant samples were determined using the micro-Kjeldahl method as stated by American Association of Cereal Chemists
 [3]
. The laboratory analysis was done at Melkassa Agricultural Research Center, Soil Laboratory.
2.6. Data Collection
Nitrogen use efficiency (NUE) evaluated in terms of agronomic efficiency and physiological efficiency. Agronomic efficiency was determined as kg grain produced per kg of nitrogen applied, whereas physiological efficiency was determined as kg grain produced per kg of nutrient uptake. It was calculated using the equation established as agronomic efficiency and physiological efficiency by
 [15]
as below.
Agronomic efficiency AE=Gf-GuNa=kg grain/kg N-fertilizer
Where Gf is the grain yield in the fertilized plot (kg), Gu is the grain yield in the unfertilized plot (kg), and Na is the quantity of nutrient applied (kg).
Physiological efficiency (PE)=Yf-YuNf-Nu=kg kg-1
Where Yf is the total biological yield (grain plus straw) of the fertilized plot (kg), Yu is the total biological yield in the unfertilized plot (kg), Nf is the nutrient accumulation in the fertilized plot (kg), and Nu is the nutrient accumulation in the unfertilized plot (kg).
2.7. Data Analysis
Data collected from each location was subjected to analysis of variance (ANOVA) for individual location and combined ANOVA over location was also done using the procedure of SAS version 9.2 (SAS Institute, 2008). F-ratio homogeneity test was conducted to error variances as outlined in
 [21]
. Following the presence of significant difference among hybrids for parameters, the mean values of maize hybrids was compared using least significant test (LSD) at 5% probability level.
3. Results and Discussions
3.1. Soil Physico-chemical Properties of the Experimental Sites
The results of physical and chemical analyses of the soil sample for each location have been presented in (Table 3). The textural class of the soils was sandy loam and sandy-clay loam at Dera and Melkassa sites respectively. The soil pH was neutral for Melkassa site and moderately alkaline for Dera as per the rating suggested by
 [39]
. According to
 [17]
, suitable pH range for most crops is between 6.5 and 7.5 in which N availability is optimum. Thus the results of soil test indicated the suitability of the soil reaction in the experimental sites for optimum crop growth and yield.
Table 3. Physicochemical properties of soil at Dera and Melkassa sites before planting maize in 2020 main cropping season.

Location

Soil property

Dera

Melkassa

Reference

Physical properties

Value

Rating

Value

Rating

Sand (%)

58

52

Silt (%)

26

18

Clay (%)

16

30

Textural class

Sandy loam

Sandy-clay loam

Tekalign

 [39]

Chemical properties

pH

7.41

Moderately alkaline

7.3

Neutral

Tekalign

 [39]

Total N (%)

0.09

Low

0.12

low

Tekalign

 [39]

Av. P (ppm)

5.02

Medium

6.12

Medium

Olsen et al.

 [31]

OC (%)

0.91

Low

1.23

Low

Tekalign

 [39]

OM (%)

1.56

Low

2.10

Low

Berhanu

 [6]

CEC (cmol(+) kg

0.3

Low

1.0

Low

FAO

 [17]
N (%) = percentage of total Nitrogen, P=Phosphorus, OC (%)= Percent Organic Carbon, OM (%)=Percent Organic Matter and CEC (cmol(+) kg = Cation Exchange Capacity.
The soil organic matter content (OM) (1.56 and 2.10%), total nitrogen (TN) (0.09 and 0.12%), organic carbon (OC) (0.91 and 1.23%) and cation exchange capacity (CEC) (0.3 and 1.0 cmol kg-1 soil) were low at Dera and Melkassa sites respectively, as suggested by (Berhanu,
 [6]
; Tekalign,
 [39]
and FAO,
 [17]
. According to the rating suggested by
 [31]
, the soil for the two sites had medium available P content (Dera, 5.02 ppm and Melkassa, 6.12 ppm) but slightly saline soil at Dera site. As suggested by
 [14]
, the N nutrient of the soils at both sites were low; hence, amending the soils of the sites with fertilizer was important for enhancing crop yield as well as soil health.
The soils of the study sites had higher sand to clay ratio at (Dera, the sand to clay ratio is 3.63:1. and at Melkassa the sand to clay ratio is 1.73:1), low organic matter and low organic carbon (Table 3). This indicated that the soil fertility of the two sites was low. If the CEC is low, it is necessary to consider the increasing inputs of organic matter through additional inputs of organic materials
 [7]
. According to
 [5]
, loss of soil organic matter due to topsoil erosion along with poor physicochemical properties is the prominent causes for the deterioration of soil fertility and productivity. Balanced and careful use of external inputs together with eco-friendly and environmentally sounds soil management practices are essential issues for sustainable agriculture production
 [24]
.
3.2. Analysis of Variance for Yield and Yield Component Traits
The results from analysis of variance (ANOVA) for yield and yield related traits of eight maize hybrids at individual location are presented in (Table 4). Ear length, number of kernel per ear, thousand kernel weight, grain yield, biomass yield and harvest index were significantly influenced by N and genotype at both locations. In addition, these traits except number of kernel per ear and biomass yield were significantly influenced by the interaction of N x genotype at both locations. The application of Nitrogen had significant effect on plant height and leaf area index at both locations while a day to maturity was significantly influenced by N and genotype at Dera and Melkassa, respectively. Neither Nitrogen nor genotype had significant effect on days to emergence, days to 50% tasselling, days to 50% silking and number of ear per plant. at both locations.
The results indicated that the eight maize hybrids had significant variations for yield and yield components, and nitrogen fertilizer had significant effect on the performances of hybrids on plant height, leaf area index, yield, and yield components at both locations. Grain yield, ear length, thousand kernel weight and harvest index) were significantly influenced by the interaction of genotype and nitrogen fertilizer rates indicated that the hybrids had differential response to the applied rates of nitrogen fertilizer on the performances of these traits. The effects of nitrogen fertilizer rates on maize hybrids on phenology, growth traits, yield and yield components at different sites and years were reported by many authors, which was in agreement of the current study results. There was a significant difference among five maize genotypes for grain yield, thousand seed weight and harvest index evaluated at Bako Tibe in 2013 and 2014 cropping season
 [41]
.
 [20]
who also reported that significant variation between two maize varieties for grain yield, ear length and thousand kernel weights and the effect of genotype x nitrogen fertilizer interaction on these traits.
The results of combined analysis of variance over locations are presented in (Table 5). Nitrogen had revealed a significant effect on all traits and genotypes also showed significant differences for all traits except plant height and leaf area index. Location had significant effect on all traits except days to physiological maturity, ear length and biomass yield. The interaction between nitrogen and genotype had a significant effect on all traits except days to physiological maturity and plant height. The interactions between location x nitrogen and location x genotype had significant effect on days to maturity and number of kernel per ear. Besides, thousand kernels weight was significantly influenced by the interaction of location x genotype. The interaction of the three factors (location, nitrogen and genotype) had significant effect on only leaf area index and number of kernel per ear.
The result of combined ANOVA suggested that the maize hybrids had significant differences to the utilization (uptake) of nitrogen and produce grain yield in response to the rates of nitrogen fertilizer. The significant effect of nitrogen x genotype interaction on all yield and yield related traits except phenology (days to maturity) and plant height indicated the effort of increasing the maize yield and yield related traits should be towards the identification of the responsive maize hybrids to nitrogen fertilizer and produce high yield. The presence of significant differences for genotypes x nitrogen interaction, and three way interaction (location x genotype x nitrogen) for maize hybrids were reported by many authors.
 [37]
, who reported that significant differences among ten maize hybrids for grain yield, thousand kernels weight, leaf area index and harvest index evaluated at four sites (Bako, Hawassa, Melkassa and Adamitulu) in 2013 and 2014 cropping season. The result was in agreement with the finding of
 [1]
, who reported that significant variation on maize variety for grain yield, leaf area index, 1000 kernels weight, above ground biomass and harvest index and the interaction of genotype x nitrogen fertilizer effects on these traits evaluated at two sites (Melkassa and Adamitulu) in 2014 main cropping season.
Table 4. Mean squares from analysis of variance for 13 yield and yield related traits of eight maize hybrids as influenced by Nitrogen fertilizer rates at Dera and Melkassa during 2020 main cropping season.

Location

Dera

Melkassa

Trait

Rep (4)

Nitrogen (A) (2)

Error (a) (4)

CV (%)

Genotype (B) (7)

A x B (14)

Error(b) (42)

CV (%)

Rep(4)

Nitrogen (A) (2)

Error (a) (4)

CV (%)

Genotype (B) (7)

A x B (14)

Error (b)(42)

CV (%)

DE

1.91

1.08ns

2.16

15.4

1.084ns

0.799ns

1.1349

10.2

1.263

1.513ns

0.33

13.7

2.093ns

1.117ns

0.12

11.39

TS

0.53

12.86ns

3.15

7.84

4.183ns

1.923ns

2.0992

5.91

6.291

5.291ns

5.33

6.55

5.744ns

2.815ns

3.51

4.87

SK

0.92

10.24ns

4.96

16.2

7.229ns

2.443ns

2.073

8.13

7.49

6.543ns

0.93

8.55

4.876ns

2.981ns

0.67

2.88

DPM

2.43

175.68**

5.74

9.15

5.442ns

6.014ns

3.6706

8.38

3.7431

1.930ns

2.08

11.4

19.230**

4.819ns

1.84

10.97

PLH

161.3

4135.17*

200.97

14.7

134.98ns

232.55ns

168.38

10.2

200.97

3500.1*

229.97

13.7

193.42ns

202.7ns

191.35

6.83

LAI

0.18

12.774**

0.3

11.6

0.141ns

0.1436ns

0.013

5.88

0.297

19.087**

0.58

14.3

0.176ns

0.256*

0.31

6.2

NEPP

0.05

0.03ns

0.18

13.7

0.035ns

0.053ns

0.047

8.45

0.061

0.021ns

0.072

13

0.041ns

0.056ns

0.045

8.44

EL

2.02

47.75**

1.42

11.9

24.886**

4.849**

1.303

6.7

1.423

33.611**

1.67

11.4

45.121**

9.088**

0.16

6.87

NKPE

797.1

37156.4**

1490.7

8.91

4667.2*

2552.7ns

1078.4

7.8

1090.7

32856.5**

5621.47

9.25

5172**

2610.4ns

3280.4

7.4

TKW

321.2

37638.9**

300.5

10.3

8658**

3478.6*

160.9

8.68

300.5

36515.8**

1229.72

8.13

8744**

3658.6*

1085.7

6.46

GY

0.1

28.93**

0.14

9.45

3.0933**

1.152**

0.017

8.95

0.139

22.931**

2.22

10.7

4.5714**

0.994**

1.4

7.52

BY

5.92

121.62**

1.43

11.9

28.976*

13.72ns

0.732

9.46

1.431

137.597**

47.06

9.25

10.601**

4.994ns

10.83

7.13

HI

0.04

0.012**

5.43

12.1

0.020*

0.002**

3.272

10.2

0.003

0.093**

0.07

11.1

0.002**

0.013*

0.004

9.74
ns, * and **, nonsignificant, significant at P<0.05 and P<0.01, respectively. DE = Days to emergence, TS= Days to 50% tasselling, SK= Days to 50% silking, DPM = days to physiological maturity, PLH= Plant height, LAI= leave area index, NEPP= Number of ear per plant, EL =Ear length, NKPE=Number of kernels per ear, TKW=Thousand kernels weight, GY=Grain yield, BY=Biological yield, HI= Harvest index and CV (%)= percentage of coefficient of variance. Number in parenthesis in each source of variation is degree of freedom.
Table 5. Mean squares from combined analysis of variance for nine yield and yield related traits of eight maize hybrids as influenced by Nitrogen fertilizer rates at two sites (Dera and Melkassa) during 2020 main cropping season.

Trait

R(L)

Location

Nitrogen

L x N

Error(a)

CV

(%)

Genotypes

L x G

N x G

L x N x G

Error(b)

CV

(%)

(4)

(L) (1)

(N) (2)

(2)

(8)

(G) (7)

(7)

(14)

(14)

(84)

DPM

14.396

126.562ns

105.215**

72.396**

4.087

4.77

11.428**

13.245**

6.422ns

4.412ns

3.824

3.28

PLH

4.72

108.51*

7621.26**

14.01ns

181.15

8.99

139.55ns

188.86ns

185.8ns

249.45ns

168.96

6.11

LAI

0.0596

0.9983*

31.541**

0.3209ns

0.2367

13.59

0.1845ns

0.1327ns

0.2173*

0.1826*

0.0998

11.13

EL

0.7158

6.2834ns

80.7253**

0.6366

1.7233

9.65

68.245**

1.7617

13.3615**

0.5765

1.2123

5.21

NKPE

1973

6894384**

17694**

15210**

946

16.76

2874**

2323**

1316*

1299*

740

12.87

TKW

2193

469990**

73023**

649ns

1549

11.86

10068**

3343*

4047**

2164ns

1233

10.93

GY

0.1319

12.8403*

51.6458**

0.2153ns

1.1181

11.97

7.1895**

0.4752ns

1.9871**

0.1597ns

0.3085

7.21

BY

3.444

37.007ns

257.757**

1.465ns

3.674

13.4

34.618**

4.959ns

14.487*

4.227ns

2.456

11.64

HI

0.00026

0.00737*

0.022**

0.00019ns

0.00039

10.2

0.00388**

0.00056ns

0.00256**

0.00073ns

0.0006

8.63
ns, * and **, nonsignificant, significant at P<0.05 and P<0.01, respectively. R(L) = Replication by location, DPM = days to physiological maturity, PLH= Plant height, LAI= leave area index, EL =Ear length, NKPE=Number of kernels per ear, TKW=Thousand kernels weight, GY=Grain yield, BY=Biological yield, HI= Harvest index and CV (%)= percentage of coefficient of variance. Number in parenthesis in each source of variation is degree of freedom.
3.3. Interaction Effect of Nitrogen x Genotype on Biomass, Grain Yield and Harvest Index
3.3.1. Aboveground Biomass
The results of analysis of variance indicated that the two-way interaction of nitrogen and genotype had a significant effect on biomass yield (Table 6). The maximum biomass yield (28011 kg) was obtained from WE7210 at a plot that received 65 N kg/ha while, the lowest (19003 kg) biomass yield was obtained from the variety WE7201 at the control plot. Biomass yield of this hybrid (WE7201) increased by 25.24 and 26.43% than control plot due to the application of 32.5 and 65 N kg/ha, respectively, that had statistically nonsignificant difference with biomass yield of WE5202 (65 kg N/ha) and WE6205 (32.5 kg N/ha and at the control plot) and WE8203 (at the control plot). The hybrid, WE7210 had higher biomass at three levels of N (0, 32.5 and 65 kg/ha) as compared to other genotypes. The research result showed that the hybrids had genetic variation and had differential response to the rates of N for biomass yield. This result is in line with
 [26]
who reported that the maximum biomass yield was obtained from Bate maize variety where plants were fertilized with 150 kg NPS and 87 kg N/ha at Babile.
3.3.2. Grain Yield
The results of analysis of variance revealed that the interaction of nitrogen and genotype had a significant effect on grain yield (Table 6). The highest grain yield (8390 kg) was obtained from WE8206 at a plot that was treated with 65 N kg/ha while, the lowest (3489 kg) grain yield was obtained from the standard check variety of MH138Q at the control plot. Grain yield of this hybrid (WE8206) increased by 47.31% and 14.63% than control plot due to the application of 32.5 and 65 N kg/ha respectively, that had statistically nonsignificant difference with grain yield of the genotypes WE7210, WE7201 and WE8203 (65 N kg/ha). This hybrid, WE8206 also had higher grain yield at three levels of N (0, 32.5 and 65 kg/ha) as compared to other genotypes. The results of research revealed that the hybrids had genetic variation in grain yield and had differential response to the rates of N for grain yield. The result was in harmony with the finding of
 [27]
who reported that significant differences between maize varieties for grain yield, evaluated at Haramaya in 2018 and 2019 cropping season under rain-fed condition.
 [19]
, who also obtained significant difference among three wheat varieties for grain yield, evaluated at Enewari in 2014 and 2015 cropping season.
3.4. Harvest Index
The harvest index of a crop is an interaction of its physiological efficiency and its ability to convert the photosynthetic material into economic yield. Harvest index was significantly influenced by the interaction effect of nitrogen and genotype. As indicated in (Table 6), the maximum harvest index (39.61%)) was obtained from the variety WE8206 where plots was treated with 65 kg N/ha however, two genotypes (WE7210 and WE 7201) had statistically nonsignificant difference with the application of 65 kg N/ha for harvest index. The lowest (25.51%) harvest index was noted from the standard check variety MH138Q at a plot did not receive fertilizer application. The genotype, WE8206 had higher harvest index at the three levels of N (0, 32.5 and 65 kg/ha) and its overall mean of harvest index was significantly higher than other hybrids. The research results indicated that the hybrids had genetic variation and differential response to the rates of N for harvest index. Similarly
 [33]
, who reported that higher harvest index was found from variety R-2210.
 [26]
, also stated that harvest index was significantly affected by the interaction of genotype and N rate.
Table 6. Interaction effect of Genotype x Nitrogen on biomass yield, grain yield and harvest index of eight maize hybrids at two locations during 2020 cropping season.

N rate (kg/ha)

Genotype

BY (kg/ha)

GY (kg/ha)

HI (%)

0

WE5202

20167fgh

3831h

28.81g

WE6205

19667hi

3777h

29.32ef

WE7201

19003i

3833h

27.21gh

WE7210

22167efg

4367g

29.59ef

WE8203

19509ghi

3809h

30.56de

WE8206

22500def

4421g

31.55cde

MH138Q

22164efg

3489i

25.51h

MH140

21161fgh

4001h

29.98ef

32.5

WE5202

25167a-d

6500ef

30.67de

WE6205

19333ghi

7310bc

31.22cde

WE7201

25419a-d

6330ef

32.66cde

WE7210

24667a-e

7333bc

30.74de

WE8203

26333ab

7159bcd

34.91b

WE8206

24500a-e

7162bcd

31.28cde

MH138Q

24333a-e

6166fg

32.01cde

MH140

22502def

6159fg

30.08de

65

WE5202

19833hi

6033ef

28.03g

WE6205

24830a-e

7533cde

33.44bc

WE7201

25833a-d

8103ab

36.01ab

WE7210

28011a

8159ab

37.84ab

WE8203

27000abc

8092ab

34.80b

WE8206

27167abc

8390a

39.61a

MH138Q

25167a-d

7959bcd

31.11cde

MH140

24332a-e

7364def

32.35cde

LSD (5%)

79.58

62.11

3.02
Mean values with similar letter(s) in column had nonsignificant difference at P<0.05. BY=Biomass yield (kg ha-1), GY = Grain yield (kg ha-1), HI =Harvest index (%) and LSD (5%) = least significant difference at 5% probability level
3.5. Interaction Effect of Location x Nitrogen x Genotype on Agronomic Efficiency
The hybrid WE7201 had significantly highest agronomic efficiency of 27.67 kg grain kg-1 nitrogen at plot received 32.5 kg N/ha at Melkassa, while WE 8203 had lowest agronomic efficiency (13.43 kg grain kg-1 nitrogen) at plot that received 65 kg N/ha at Dera. The hybrids except WE 8203 and WE 8203 had higher agronomic efficiency by about 4.74 kg grain kg-1 nitrogen at Melkassa due to the application of 32.5 kg N/ha than the application of 65 kg N/ha. There was variation among hybrids for the reduction of agronomic efficiency at plots that received 65 kg N/ha in which WE7201 hybrid had highest reduction of 13.67 kg grain kg-1 nitrogen followed by WE7210 hybrid with the reduction of 7.6 kg grain kg-1 nitrogen than AE at plots that received 32.5 kg N/ha. Whereas hybrids WE8203 and WE8203 showed lower agronomic efficiency reduction of 0.71 and 1.24 kg grain kg-1 nitrogen, respectively, at plots that received 65 kg N/ha than plots received 32.5 kg N/ha (Table 7). This showed that the agronomic efficiency of hybrids was significantly influenced by location and rates of nitrogen. The results suggested that the higher chance of identifying hybrids with higher agronomic efficiency in response of low rate of nitrogen at both locations and/or specific location than others as stable and/or fit to specific location. Maize crop had a genotypic variation in nitrate absorption and partitioning of N among plant parts. This result is in line with the reports of
 [35]
that significant differences for maize varieties for agronomic efficiency, evaluated at two sites (Addis Alem and Tepi) in 2016 cropping season.
Table 7. Interaction effect of Location x Genotype x Nitrogen on agronomic efficiency (kg grain kg-1 applied nutrients) of N of eight maize hybrids at two locations during 2020 main cropping season.

Genotype

Location

N rate (kg N/ha)

32.5

65

WE5202

Dera

22.22b-g

19.30d-k

WE6205

21.02c-h

17.23i-n

WE7201

20.08c-j

14.41mn

WE7210

23.31b-e

19.08e-l

WE8203

14.67lmn

13.43n

WE8206

20.02c-j

17.69h-n

MH138Q

19.56c-i

16.01j-n

MH140

19.33d-k

16.39j-n

WE5202

Melkassa

24.59b

19.00e-l

WE6205

24bc

17.33i-n

WE7201

27.67a

14mn

WE7210

22.60b-f

15k-n

WE8203

19.04e-l

18.33f-m

WE8206

23.33b-e

18g-n

MH138Q

23.05b-e

17.57h-n

MH140

20.06c-j

16j-n

LSD (5%)

6.42
Mean values with similar letter(s) in columns and rows had nonsignificant difference at P<0.05, and LSD (5%) = least significant difference at 5% probability level.
3.6. Interaction Effect of Location x Nitrogen x Genotype on Physiological Efficiency
Table 8. Interaction effect of Location x Genotype x Nitrogen on physiological efficiency (kg grain kg-1 nutrients uptake) of eight maize hybrids at two locations during 2020 main cropping season.

Genotype

Location

N rate (kg N/ha)

32.5

65

WE5202

Dera

21.56d-i

18e-i

WE6205

23.91c-g

14.29ghi

WE7201

27.51b-f

13.82ghi

WE7210

25.02b-h

12.34hi

WE8203

22.06c-i

15ghi

WE8206

27.03b-g

18e-i

MH138Q

22.66c-i

18.31e-i

MH140

23.30c-h

15.75f-i

WE5202

Melkassa

31.67b-e

21d-i

WE6205

31.67b-e

12.46hi

WE7201

34.74bcd

13.33ghi

WE7210

39.47ab

27.64b-g

WE8203

36.23bc

28.32b-f

WE8206

43.52a

35.04bc

MH138Q

30.03b-e

12i

MH140

28.67b-f

22.61c-i

LSD(5)

11.64
Mean values with similar letter(s) in columns and rows had nonsignificant difference at P<0.05, and LSD (5%) = least significant difference at 5% probability level.
The hybrid WE8206 had significantly highest physiological efficiency of 43.52 kg grain kg-1 nitrogen at plot received 32.5 kg N/ha, while the standard check variety MH138Q had lowest physiological efficiency (12.56 kg kg-1kg grain kg-1 nitrogen) at plot that received 65 kg N/ha at Melkassa site. Most of maize genotypes had significantly higher physiological efficiency with the application of 32.5 kg N/ha than the application of 65 kg N/ha at Melkassa site as compared to Dera. There was variation among hybrids for the reduction of physiological efficiency at plots that received 65 kg N/ha in which the standard check variety WE6205 hybrid had highest reduction of 19.21 kg grain kg-1 nitrogen followed by MH138Q hybrid with the reduction of 18.03 kg grain kg-1 nitrogen than PE at plots that received 32.5 kg N/ha. Whereas hybrid WE5202 showed lower physiological efficiency reduction of 3.56 kg grain kg-1 nitrogen, at plots that received 65 kg N/ha than plots received 32.5 kg N/ha (Table 8). The results of the research showed that the physiological efficiency of hybrids was significantly influenced by location and rates of nitrogen. The results suggested that the higher chance of identifying hybrids with higher physiological efficiency in response of low rates of nitrogen at locations and/or specific location than others as stable and/or fit to specific location. Similarly,
 [43]
reported that significant differences for maize variety on physiological efficiency, evaluated at three sites (Bako, Central rift valley and Jimma) in 2015 and 2016 cropping season.
4. Conclusions
Moisture stress in the central rift valley part of Ethiopia is one of the major factor that affect maize crop production in semi-arid areas of the country. The climate change and variability pose a serious threat to food production in this area contributed significantly to the water scarcity and with nutrient stress such as nitrogen. Thus the development of varieties to moisture stress areas is one of the strategies to withstand the maize production problems brought by water scarcity and temperature increase.
The results of analysis of variance for individual locations indicated that nitrogen and genotypes had a significant effect on leaf area index, ear length, number of kernel per ear, thousand kernel weight, grain yield, biomass yield and harvest index at both locations. In addition, days to physiological maturity and plant height at Dera site and plant height at Melkassa was significantly influenced by nitrogen levels. Genotype had also significantly influence days to physiological maturity at Melkassa site. Nitrogen and genotypes interacted to influence ear length, thousand kernel weight, grain yield and harvest index at both locations, but leaf area index was significantly influenced by the interaction of nitrogen and genotypes at Melkassa site. The results of combined analysis of variance across locations indicated that the interaction of the interaction of between nitrogen and genotype had significant effect on all traits except days to physiological maturity and plant height. The interactions between location x nitrogen and location x genotype had significant effect on days to maturity and number of kernel per ear. Besides, thousand kernels weight was significantly influenced by the interaction of location x genotype. The interaction of the three factors (location, nitrogen and genotype) had significant effect on only leaf area index and number of kernel per ear.
The genotypes also had significant differences for agronomic and physiological efficiency. These traits were significantly influenced by one or more than one of the possible two factors interactions (nitrogen x genotype, location x nitrogen, and location x genotype). The interaction of the three factors (location, nitrogen and genotype) had significant effect on leaf area index, number of kernel per ear, agronomic and physiological efficiency. This showed that the importance of identifying genotypes with high yield and nitrogen use efficiency to increase the productivity of the crop in the study areas.
The physiological maturity, most of the plant growth traits, yield components, agronomic and physiological efficiency were the function of genotype and nitrogen and/or the interaction of the two factors. Thus, the effort of enhancing nitrogen use efficiency of the maize genotypes in the study areas needs to be towards the identification of maize hybrids efficient to the utilization of available nitrogen nutrient at different locations. Hence, WE7201 and WE8206 hybrids could be recommended for production in the study areas.
However, further studies will be needed, because the two locations have received sufficient rainfall during the experimental year, and the response of the hybrids at both locations with low soil fertility conditions may not be sufficient to represent the semi-arid areas of Ethiopia.
Abbreviations

AACC

American Association of Cereal Chemists

ANOVA

Analysis of Variance

FAO

Food and Agriculture Organization of the United Nations

MH

Melkassa Hybrid

NUE

Nitrogen Use Efficiency

TLB

Turcicum Leaf Blight

WHO

World Health Organization
Acknowledgments
The authors would like to acknowledge Africa Center of Excellence for Climate Smart Agriculture and Biodiversity Conservation-Haramaya University and, the World Bank Group and, also the Ethiopian Institute of Agricultural Research for providing financial support and laboratory facilities to carry out this study.
Author Contributions
Jemal Bekere: Conceptualization, Data curation, Formal Analysis, Methodology, Software, Validation, Writing – original draft, Writing – review & editing
Yaya Tesfa: Data curation, Formal Analysis, Resources, Software, Writing – original draft, Writing – review & editing
Conflicts of Interest
The authors declare no conflicts of interest.
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    Bekere, J., Tesfa, Y. (2024). Agronomic and Physiological Efficiency of Maize (Zea mays L.) Hybrids as Influence by Nitrogen Fertilization in Semi-Arid Areas of Ethiopia. Agriculture, Forestry and Fisheries, 13(6), 308-319. https://doi.org/10.11648/j.aff.20241306.20

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    Bekere, J.; Tesfa, Y. Agronomic and Physiological Efficiency of Maize (Zea mays L.) Hybrids as Influence by Nitrogen Fertilization in Semi-Arid Areas of Ethiopia. Agric. For. Fish. 2024, 13(6), 308-319. doi: 10.11648/j.aff.20241306.20

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    Bekere J, Tesfa Y. Agronomic and Physiological Efficiency of Maize (Zea mays L.) Hybrids as Influence by Nitrogen Fertilization in Semi-Arid Areas of Ethiopia. Agric For Fish. 2024;13(6):308-319. doi: 10.11648/j.aff.20241306.20

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  • @article{10.11648/j.aff.20241306.20,
  author = {Jemal Bekere and Yaya Tesfa},
  title = {Agronomic and Physiological Efficiency of Maize (Zea mays L.) Hybrids as Influence by Nitrogen Fertilization in Semi-Arid Areas of Ethiopia},
  journal = {Agriculture, Forestry and Fisheries},
  volume = {13},
  number = {6},
  pages = {308-319},
  doi = {10.11648/j.aff.20241306.20},
  url = {https://doi.org/10.11648/j.aff.20241306.20},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aff.20241306.20},
  abstract = {Maize is one of the major food crops in semi-arid areas of Ethiopia. Efficient application of N fertilizer on maize crop enables smallholder farmers have a synergic effect through enhancing yield productivity, reducing cost of production and nitrous oxide emission to the atmosphere exacerbating the challenges of changing climate. This experiment was conducted to determine the effect of nitrogen fertilizer on yield and yield related traits and assess the relationship between yield and nitrogen use efficiency indices. Eight maize hybrids were evaluated at three rates of N fertilizer (0, 32.5 and 65 kg N/ha) using split-plot design with three replications at two locations (Dera and Melkassa) in 2020 main cropping season. The results from analysis of variance (ANOVA) at each location indicated that majority of yield and yield related traits, agronomic and physiological efficiency were significantly influenced either by one or two of the factors (nitrogen and genotype) and/or the interaction effect of the two at both locations. The results of combined ANOVA over locations revealed that the interaction of the three factors (location, nitrogen and genotype) had significant effect on agronomic and physiological efficiency. The hybrids WE7201 and WE8206 had obtained the highest agronomic (27.67 kg kg-1) and physiological efficiency (43.52 kg kg-1) due to the application of 32.5 kg N ha-1 respectively. Thus, WE7201 and WE8206 could be recommended for production in the study areas.},
 year = {2024}
}

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  • TY  - JOUR
T1  - Agronomic and Physiological Efficiency of Maize (Zea mays L.) Hybrids as Influence by Nitrogen Fertilization in Semi-Arid Areas of Ethiopia
AU  - Jemal Bekere
AU  - Yaya Tesfa
Y1  - 2024/12/30
PY  - 2024
N1  - https://doi.org/10.11648/j.aff.20241306.20
DO  - 10.11648/j.aff.20241306.20
T2  - Agriculture, Forestry and Fisheries
JF  - Agriculture, Forestry and Fisheries
JO  - Agriculture, Forestry and Fisheries
SP  - 308
EP  - 319
PB  - Science Publishing Group
SN  - 2328-5648
UR  - https://doi.org/10.11648/j.aff.20241306.20
AB  - Maize is one of the major food crops in semi-arid areas of Ethiopia. Efficient application of N fertilizer on maize crop enables smallholder farmers have a synergic effect through enhancing yield productivity, reducing cost of production and nitrous oxide emission to the atmosphere exacerbating the challenges of changing climate. This experiment was conducted to determine the effect of nitrogen fertilizer on yield and yield related traits and assess the relationship between yield and nitrogen use efficiency indices. Eight maize hybrids were evaluated at three rates of N fertilizer (0, 32.5 and 65 kg N/ha) using split-plot design with three replications at two locations (Dera and Melkassa) in 2020 main cropping season. The results from analysis of variance (ANOVA) at each location indicated that majority of yield and yield related traits, agronomic and physiological efficiency were significantly influenced either by one or two of the factors (nitrogen and genotype) and/or the interaction effect of the two at both locations. The results of combined ANOVA over locations revealed that the interaction of the three factors (location, nitrogen and genotype) had significant effect on agronomic and physiological efficiency. The hybrids WE7201 and WE8206 had obtained the highest agronomic (27.67 kg kg-1) and physiological efficiency (43.52 kg kg-1) due to the application of 32.5 kg N ha-1 respectively. Thus, WE7201 and WE8206 could be recommended for production in the study areas.
VL  - 13
IS  - 6
ER  -

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