Advances in Crop Science and Technology
Open Access

Agronomic efficiency; Grain yield; Nitrogen use efficiency; Physiological efficiency

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 (Purseglove, 1976). 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 (FAO STAT, 2020). Maize was cultivated in 166 countries which were more than by 49 and 44 % than rice and wheat, growing countries respectively (CONABIO, 2017). 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 (Downsell et al., 1996). 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 (CONABIO, 2017) [1,2].

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 (CSA, 2019). The average national maize yield was lower than 5.5 t/ha of the world’s average yield (FAO, 2019). 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 (CIMMYT, 2004; Mosisa et al., 2012) [3].

Climate change and variability pose a serious threat to food production in sub-Saharan Africa (Fosu-Mensah et al., 2019). Climate change contributed significantly to the water scarcity problem (WHO, 2009). The changes in temperature and precipitation affect crop photosynthesis, crop development rates, as well as water and nutrient availability to crops (Steve and Paul, 1991). It was indicated that an increase in temperature of 2º 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 (IPCC, 2012) [4].

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 (Muhammad et al., 2020). 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 (Matson et al., 1997; Tilman et al., 2002). 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 (Moll et al., 1982; Below et al., 2013) [5]. 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 (Aweke, 2018). 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 (CIMMYT and IITA, 2010) [6].

Evaluation and identification of inbred lines and QPM hybrids tolerant to low N were reported (Addisalem, et al., 2019; Buchaillot et al., 2019). 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 (Sime and Aune, 2014; Hawi, et al., 2015). 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 [7]. 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 nitrogen use efficiency under varying levels of N in moisture stress areas of Ethiopia [8].

Materials and Methods

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 (Table 1).

Table 1: Description of experimental sites.

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 (Table 2) [9].

Table 2: Description of Experimental Materials .

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 9m2 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 1m and 1.5 m apart, respectively [10].

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 [11]. 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 [12].

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 (AACC, 2000). The laboratory analysis was done at Melkassa Agricultural Research Center, Soil Laboratory [13].

Data collection

Phenology, growth, yield and yield components data were collected. Crop growth rate was suggested by Watson (1956). The CGR explains the dry matter accumulated per unit land area per unit time (gm-2 day-1).

CGR= (W2-W1) p(t2-t1)

Where, W1 and W2 are whole plant dry weight at time t1 – t2 respectively.

ρ is the ground area on which W1 and W2 are recorded.

CGR of a species are usually closely related to interception of solar radiation

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 (Fageria and Baligar, 2005) as below [14].

Agronomic efficiency (AE) = Gf¬- Gu= kg grain/kg N-fertilizer

Na

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 - Yu = kg kg-1

Nf - Nu

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) [15].

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 (Gomez and Gomez, 1984). 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 [16].

Results and Discussions

Soil physico-chemical properties of the experimental sites

The results of physical and chemical analyses of the soil sample for each location. 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 (Tekalign, 1991) [17]. According to (FAO, 2008), 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).

Table 3: Physicochemical properties of soil at Dera and Melkassa sites before planting maize in 2020 main cropping season .

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, 1980; Tekalign, 1991 and FAO, 2006). According to the rating suggested by Olsen et al. (1954), the soil for the two sites had medium available P content (Dera, 5.02 ppm and Melkassa, 6.12ppm) but slightly saline soil at Dera site. As suggested by (EthioSIS, 2016), 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 [18].

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. 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 (Botta, 2015). According to (Aweke, et al., 2014), 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 (Kumar et al., 2015) [19].

Weather conditions of the experimental sites

The weather condition of the experimental sites in 2020 cropping season are presented in (Figure 1 & 2). The two sites received rainfall every month starting from March 2020 in which the Dera and Melkassa sites received the maximum 165.9 and 248.5 mm rainfall respectively. The lowest precipitation for Dera site was 2.1mm received during October 2020 while, Melkassa site received the lowest rainfall during November (1.1mm). The total rainfall received during 2020 cropping season was 764.4 and 832.8mm at Dera and Melkassa sites respectively. The average monthly maximum and minimum rainfall distribution and relative humidity of the sites were suitable for maize production at both sites [20].

Figure 1: Monthly precipitation, maximum and minimum temperature at Dera site during 2020 main cropping season.

Figure 2: Monthly precipitation, maximum and minimum temperature at Mekassa site during 2020 main cropping season.

Dera and Melkassa sites had the maximum temperature during the month of May (30.90C) and February (32.20C), respectively. The minimum temperature for Dera (8.80C) and Melkassa (9.40C) sites were registered during November 2020. Dera site had 27.4 and 14.20C average maximum and minimum temperature, respectively, while at Melkassa site had 28.6 and 14.30C average maximum and minimum temperature, respectively [21].

Analysis of variance for yield and yield related traits

The results from analysis of variance (ANOVA) for 13 yield and yield related traits of eight maize hybrids at individual location. 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 [22].

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 [23]. 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 (Tolera, et al., 2019). Gizaw (2018) 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 [24].

The results of combined analysis of variance over locations. 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 [25].

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 [26]. 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. Seyoum et al. (2019) 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 (Tadesse and Kim, 2015) 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 [27].

Effects of location, nitrogen and genotype on yield and yield related traits

Interaction effect of nitrogen x genotype on ear length

Ear length was significantly influenced by the interaction effect of nitrogen and genotype. The genotype WE8206 with the application of 65 N kg/ha had significantly produced a longer ear length (24.31cm) and, followed by the genotype WE7210 with the application of 32.5 N kg/ha obtained the longer ear length (22.04cm) as compared to other genotypes. The standard check variety, MH138Q was registered a shorter ear length (15.19) at the control plot; however, it had statistically non-significant difference with ear length of other two genotypes obtained from control plots. Ear length of this hybrid (MH138Q) in the control plot had statistically nonsignificant with the application of 32.5 N kg/ha. The results showed that the hybrids had genetic variation on ear length and had differential response to the rates of N for ear length. The result is in line with (Ahmad et al., 2018) reported that ear length was significantly influenced due to varieties [28]. This result is also supported by (Anjorin and Ogunniyan, 2014) who reported that the increase in nitrogen levels positively influence ear length of maize (Table 4).

Table 4: Interaction effect of Genotype x Nitrogen on ear length of eight maize hybrids at two locations during 2020 cropping season .

Interaction effect of location x nitrogen x genotype on number of kernels per ear

Number of kernels per ear was significantly influenced by the three way interactions of location, genotype and nitrogen. The two hybrids (WE8206 and WE7210) recorded significantly highest number of kernels per ear (517.33) and (503.73) at Melkassa site with the application of 65 N kg/ha) respectively. The hybrids at both locations (Dera and Melkassa) due to the application of 65 N kg/ha had statistically nonsignificant number of kernels per ear. The lowest (111.83) number of kernels per ear was recorded for standard check variety of MH138Q at Dera on plots that did not receive fertilizer (control plot). However, the number of kernels per ear of this hybrid had nonsignificant difference with WE5202 and MH140 at Dera site at control plot. The results of the research indicated that as N rates increased the number of kernels per ear of maize hybrids also increased at two locations, but some of the hybrids had higher number of kernels per ear than others in response of the rates of nitrogen at both locations [29].

Maize cultivars having longer ear length (more number of kernels per row) could produce more number of kernels per ear because number of kernels per ear is the result of number of rows per ear x number of kernels per row (Belay and Adare, 2020). The result is in accordance with report of (Hejazi and Soleyman, 2014) who reported that the number of kernels per ear was significantly affected by variety (Table 5) [30].

Table 5: Interaction effect of Location x Genotype x Nitrogen on number of kernels per ear of eight maize hybrids at two locations during 2020 main cropping season.

Interaction effect of genotype x nitrogen and genotype x location thousand kernels weight

Statistical data analysis of variance indicated that two-way interaction of nitrogen and genotype had a significant effect on thousand kernel weight. The highest thousand kernel weight (395.28g) was obtained from WE8206 at plots that were treated with 65 N kg/ha. The lowest (206.67g) thousand kernel weight was measured for WE5202 from the control treatment; however, it had statistically nonsignificant difference with thousand kernel weight of other four hybrids obtained from control plots. Thousand kernel weight of this hybrid (WE5202) increased by 49.76 and 49.72% than control plot due to the application of 32.5 and 65 N kg/ha, respectively, that had statistically nonsignificant difference with thousand kernel weight of that had statistically nonsignificant difference with WE6205 and WE8203 (65 N kg/ha), WE7210 (0, 32.5 and 65 N kg/ha) and WE8206 (32.5 N kg/ha). The hybrid, WE7210 had higher thousand kernel weight at three levels of N (0, 32.5 and 65 kg/ha) as compared to other genotypes. The results showed that the hybrids had a genetic variation for thousand kernel weights and had differential response to the rates of N for kernel weight. This result is in line with (Belay, 2020) who reported that the maximum thousand kernel weight was obtained from Bate maize variety where plants were fertilized with 150 kg NPS and 87 kg N/ha at Babile. (Ahmad et al., 2018) also reported that 1000-grain weight was significantly affected by the interaction effect of genotype by nitrogen [31].

Thousand kernel weight was significantly influenced by the interaction effect of location and genotype. The highest thousand kernel weight (371.08g) was obtained from the hybrid WE7210 at Melkassa site. The lowest (177.22g) thousand kernel weight was measured from the standard check variety MH138Q at Dera site; but, it had statistically nonsignificant difference with thousand kernel weight of other two genotypes obtained from control plots. Thousand kernel weight of (WE7210) was highest at both locations as compared to other genotypes, and also at Melkassa site the highest thousand kernel weight was recorded as compared to Dera site; however three genotypes were statistically nonsignificant. The research results showed that the hybrids had genetic variation across locations for thousand kernel weight. This result was in harmony with (Abera and Adinew, 2020) who reported that the maximum thousand kernel weight was obtained from maize hybrids (Table 6).

Table 6: Interaction effect of Genotype x Nitrogen and Genotype x Location on thousand kernels weight of eight maize hybrids at two locations during 2020 cropping season .

Interaction effect of nitrogen x genotype on biomass and grain yield

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. The maximum biomass yield (28011kg) was obtained from WE7210 at a plot that received 65 N kg/ha while, the lowest (19003kg) 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 (32.5kg 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 (Belay, 2020) 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.

Grain yield

The results of analysis of variance revealed that the interaction of nitrogen and genotype had a significant effect on grain yield. The highest grain yield (8390 kg) was obtained from WE8206 at a plot that was treated with 65 N kg/ha while, the lowest (3489kg) 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 (Belay and Adare, 2020) who reported that significant differences between maize varieties for grain yield, evaluated at Haramaya in 2018 and 2019 cropping season under rain-fed condition. Belete et al. (2018) also obtained significant difference among three wheat varieties for grain yield, evaluated at Enewari in 2014 and 2015 cropping season [32].

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. 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 65kg 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 65kg/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, (Qahar and Ahmad, 2016) who reported that higher harvest index was found from variety R-2210 and from the highest nitrogen fertilizer rate (350 kg N/ha). Belay (2020) also stated that harvest index was significantly affected by the interaction of genotype and N rate (Table 7) [33].

Table 7: 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 .

Yield response of maize hybrids to nitrogen fertilizer application

The combined mean values of eight maize hybrids for grain yield obtained from the application of two rates of nitrogen fertilizer (32.5 and 65 kg N/ha) as well as without nitrogen fertilizer application, N nutrient stress (0 kg N/ha) over two locations are presented in (Figure 3).

Figure 3: Combiled analysis of grain yield of eight maize hybrids in response to three levels of N evaluated at Dera and Melkassa sites during 2020 main cropping season.

The mean grain yield of the hybrids (WE8206 and WE7210) was obtained highest grain yield over the standard check variety without N fertilizer application while, the genotypes (WE7210 and WE6205), and WE8206 treated with 32.5 and 65 kg N/ha application had obtained highest grain yield than other hybrids, respectively. The application of 32.5 and 65 kg N/ha had yield advantages of.65.8 and 89.7%, respectively, over yield of maize hybrids obtained without nitrogen fertilizer application. The mean yield of hybrids obtained by application of 65 kg N/ha had yield advantage of 14.4% over the yield of maize hybrids obtained with the application 32.5 kg N/ha. The lowest mean grain yield was observed for the standard check variety (MH138Q) where the plot treated without N application whereas, the two standard check variety (MH 138Q and MH140), and WE5202 had registered the lowest mean grain yield due to the application of 32.5 and 65 kg N/ha, respectively, as compared to other hybrids. This result is in line with (Workneh et al., 2021) who reported that significant variation was obtained for maize variety, evaluated at three sites (Bako, Central rift valley and Jimma) in 2015 and 2016 cropping season [34].

Interaction effect of nitrogen x genotype on crop growth rate

The maximum and significantly highest crop growth rate (23.61g-2 day-1) was observed for hybrid WE8206 where it was treated with 65 kg N/ha. The hybrid, WE 7210 also had higher growth rate of 21.11 g-2 day-1due to the application of 65 kg N/ha though it had nonsignificant difference with other hybrids at different rates of N/ha including at control plot. The two hybrids, namely, WE 5202 and WE 7201 showed higher growth rate at control plot and plots received 32.5 kg N/ha, but had very low growth rate at plots received of 65 kg N/ha. In contrast, all the other hybrids showed higher growth rate at plots received of 65 kg N/ha and lower growth rate at control plot. The mean crop growth rate of hybrids was higher due to the application of 65 kg N/ha and WE 8206, WE 7201 and WE 5202 hybrids had high overall mean crop growth rate of 20.61, 19.53 and 19.47g-2 day-1, respectively, than other hybrids. The result indicated that the maize hybrids had genotypic variation and differential response to the rates of nitrogen application for crop growth rate. This suggested that the importance of identifying maize hybrids efficient in uptake of available nitrogen nutrient to accumulate high dry matter (crop growth rate) in moisture and nitrogen stress areas to obtain higher biomass yield. Similarly, (Tanveer et al., 2013) who reported that crop growth rate was significantly affected by nitrogen x genotype interaction (Table 8).

Table 8: Interaction effect of Nitrogen x Genotype on crop growth rate of (g-2 day-1) eight maize hybrids at two locations during 2020 cropping season .

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. 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 (Chevalier and Schrader. 1977). This result is in line with the reports of (Shiferaw, et al., 2018) that significant differences for maize varieties for agronomic efficiency, evaluated at two sites (Addis Alem and Tepi) in 2016 cropping season (Table 9).

Table 9: 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.

Interaction effect of location x nitrogen x genotype on physiological efficiency

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. 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, (Workneh, et al., 2021) 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. This result is in agreement with the reports of (Sadegh, 2017) that significant variation among three soybean cultivars for physiological efficiency, evaluated at Babol in 2012 and 2013 cropping season [35].

Conclusions

The central rift valley part of Ethiopia is one of the semi-arid areas in the country where the production of crops is suffering with moisture stress. 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 crop growth rate, 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, WE8206 and WE7210 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.

Acknowledges

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.

Conflict of Interest

The authors declare that there is no conflict of interest regarding the publishing of this work.

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