







































 

 

 
85 

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Assessing grain yield of quality protein maize under low soil nitrogen through associated 
agronomic traits   

 

 

 Qudrah Olaitan 
Oloyede-Kamiyo1+ 

 Richard Olutayo 
Akinwale2 

 Adedotun Daniel 
Adewumi3 

 Mayowa Segun 
Oladipo4 

 Adewole Taiwo 
Akintunde5 

 Abigail Oluremi 
Ojo6 

 Folake Bosede 
Anjorin7 

1,3,4,5,6,7Institute of Agricultural Research and Training, Obafemi Awolowo 
University, P.M.B. 5029, Moor Plantation, Apata, Ibadan, Nigeria. 
1Email: qudratkamiyo@gmail.com  
3Email: adewumiadedotun66@gmail.com  
4Email: oladipoms@gmail.com  
5Email: akintundeadewole@gmail.com  
6Email: oluremiojo7@gmail.com  
7Email: folakeawoeyo@gmail.com  
2Faculty of Agriculture, Obafemi Awolowo University, Ile-Ife, Osun State, 
Nigeria. 
2Email: akinrichie2002@yahoo.com  

 

 
(+ Corresponding author) 

 ABSTRACT 
 
Article History 
Received: 30 September 2024 
Revised: 13 November 2024 
Accepted: 28 November 2024 
Published: 19 December 2024 
 

Keywords 
Correlation 
Crop improvement 
Grain yield 
Low nitrogen 
Quality protein maize 
Regression. 

 
The study was conducted to improve a quality protein maize (QPM) population, 
ART/98/ILE 1-OB, for tolerance to low soil nitrogen, and to investigate the agronomic 
characters that are linked to grain yield of QPM in low soil nitrogen environments. S1 
lines were selected in the maize population at cycle one (C1) in a recurrent selection 
programme, for evaluation to move to cycle 2 (C2). Data were collected on agronomic 
traits, stay-green ability (SGR) and grain yield (GY) and analysed using SAS. SGR 
rating at 8 weeks after planting (8WAP) was moderate under low nitrogen (3.09). GY 
was slightly higher under low nitrogen (LN) (2.19 tons/ha) than under high nitrogen 
(HN) condition (1.98 tons/ha). There were notable negative phenotypic and genotypic 
correlations between grain yield (GY) and traits such as days to 50% anthesis and 
silking, stay green rating (SGR), ear aspect (EA), and plant aspect (PA). In contrast, 
positive correlations were observed with plant height (PH) and number of ears per plant 
(EPP). In stepwise regression, EPP emerged as the most significant character  under LN 
(R2 = 45%), with EA, SGR at 8WAP (SGR8), and PH following closely. EPP showed the 
highest positive direct effect on grain yield, followed by SGR8. EA had the highest 
negative direct effect. PC1 alone, which was mostly linked to PH, accounted for 96.5% of 
the overall variation. These findings underscore the importance of EPP, EA, SGR8 and 
PH as selection criteria in enhancing QPM productivity under LN conditions.  

Contribution/Originality: This study is novel in that it provides an insight into the key traits to be considered 

during selection in the improvement of quality protein maize for tolerance to low soil nitrogen. Most of the studies 

on low soil nitrogen have focused on normal maize. 

 

 

 

Current Research in Agricultural Sciences 
2024 Vol. 11, No. 2, pp. 85-99 
ISSN(e): 2312-6418 
ISSN(p): 2313-3716 
DOI: 10.18488/cras.v11i2.4006 
© 2024 Conscientia Beam. All Rights Reserved. 

 
 
 

 
 
 
 

 

 
 
 
 

https://orcid.org/0000-0002-9409-0259
https://orcid.org/0000-0001-9480-0794
https://orcid.org/0009-0002-3632-5176
https://orcid.org/0009-0001-2035-8531
https://orcid.org/0000-0002-3862-2476
https://orcid.org/0000-0001-8908-1879
https://orcid.org/0000-0002-7948-5850
mailto:qudratkamiyo@gmail.com
mailto:adewumiadedotun66@gmail.com
mailto:oladipoms@gmail.com
mailto:akintundeadewole@gmail.com
mailto:oluremiojo7@gmail.com
mailto:folakeawoeyo@gmail.com
mailto:akinrichie2002@yahoo.com
https://www.doi.org/10.18488/cras.v11i2.4006


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1. INTRODUCTION 

The livelihoods and food security of millions of resource-limited individuals are at risk due to factors such as 

population growth, climate change, resource depletion, and recurring food price crises. Maize accounts for up to 

51% of calories consumed and is the main crop in many parts of sub-Saharan Africa (SSA) [1]. Maize accounts for 

around 15% of the total energy consumed in rural populations in West and Central Africa [2]. 

Nitrogen (N) is an essential nutrient for the growth of plants, playing a key role in improving crop yield and 

productivity [3, 4]. It is the primary nutrient required by maize for optimal growth and grain yield [5, 6]. To 

boost maize yield in nitrogen-deficient soils, [7] suggested utilizing populations with a tolerance for low N to 

develop low N cultivars. 

Maize grain yield is a multifaceted quantitative trait, affected by a variety of factors such as environmental 

influences and different growth and physiological processes during the plant’s life cycle. Gaining insight into the 

relationship between yield and its contributing factors is crucial for identifying selection criteria that can improve 

the effectiveness of a breeding programs [8]. Direct yield selection can be misleading due to significant 

environmental influences [9]. Correlation coefficient analysis provides insight into traits that can be selected 

concurrently for grain yield improvement [10]. Correlation analyses assess the associations between yield and 

other characteristics. Indirect selection in breeding programs is possible through both genotypic and phenotypic 

association [11]. To determine the cause and impact of a correlation, path analysis [12] breaks it down into direct 

and indirect effects. 

Partial regression analysis has also been employed to predict agronomic traits that could influence yield. Sellam 

and Poovammal [13] found that Partial Least Square Regression (PLSR) analysis had limited predictive accuracy 

for maize grain yield, which could be enhanced by including more physiological traits and evaluating in more 

environments. Accurate phenotypic data is crucial for developing prediction models, making phenotyping a 

cornerstone of predictive breeding [14]. Selecting multiple traits simultaneously can be difficult, as the weakness of 

one trait may negatively impact the strength of another, resulting in inconsistent outcomes. Finding the essential 

traits that most influence yield is crucial for increasing selection accuracy. Grain yield and secondary traits must 

have high heritability, substantial genetic correlations with yield, and simplicity of measurement in order to be 

selected for efficiently in low nitrogen conditions. 

There is inconsistent evidence about the key agronomic traits that affect grain yield in low nitrogen soil 

conditions. Traits such as the Anthesis-Silking Interval (ASI) and the number of ears per plant are considered vital 

in low nitrogen and drought situations, forming the basis for selection criteria. Bänziger, et al. [15]; Edmeades, et 

al. [16]; Badu‐Apraku, et al. [17]; Ajala, et al. [18] and Badu‐Apraku, et al. [19]. Ajala, et al. [20] highlighted 

stay green ability, plant height, and ear aspect, while [21] reported kernel number per ear as crucial for grain yield 

under low nitrogen. This suggests that the contribution of associated traits may vary between populations. 

However, all these studies focused on normal maize. For breeding efforts on improvement of quality protein maize 

(QPM) for low soil nitrogen tolerance, research on agronomic traits influencing QPM grain yield is necessary. 

The objectives of this study are to: (i) increase the tolerance of a quality protein maize to low soil nitrogen; and 

(ii) identify the agronomic features that are predictive of quality protein maize grain yield in low soil nitrogen 

conditions. 

 

2. MATERIALS AND METHODS 

2.1. Test Population 

The open-pollinated ART/98/ILE 1-OB maize variety was developed primarily for its excellent protein 

characteristics by the Institute of Agricultural Research and Training (IAR&T), Nigeria. It is an intermediate-

maturing white-kernel maize that is well suited to Nigeria's southwest environment. 

 



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2.2. Development of Cycles of Recurrent Selection 

To increase the population's resistance to low soil nitrogen, two rounds of recurrent selection were applied to 

the QPM maize population. In 2018, at low nitrogen screening sites in Mokwa and Zaria, two hundred and fifty 

(250) S1 lines were generated from the original population for evaluation with six checks under low nitrogen (LN) 

and high nitrogen (HN) conditions. The LN block received N at the rate of 30 kgN/ha, while the HN received N at 

90 kgN/ha. The top-performing S1 lines were selected using 20% selection intensity. The chosen lines were 

screened under a lightbox to eliminate lines/kernels without the opaque genes before recombination to cycle 1 (C1). 

The recombination was done twice in 2019 to bring the population to C1F2.  

 

2.3. Field Evaluation to Move to Cycle 2  

The C1 population was planted, and about 300 plants were self-pollinated in 2020. Out of these, only 131 S1s 

were got with a reasonable quantity of kernels due to the erratic rainfall during the period, which affected the grain 

filling of some of the selfed plants. During the 2021 cropping season, the 131 S1s with a check were assessed under 

low (LN) and high (HN) soil nitrogen conditions at the low N screening locations in Ilora and Ile-Ife, Nigeria. Ile-

Ife is in the agro-ecological zone of the rainforest, whereas Ilora is in the derived savanna. The fields at the two 

sites have been mopped up on their nitrogen for years by continuously planting maize without organic or inorganic 

fertilizer. After every harvest, the plants were often completely pulled out of the field. Prior to the experiment, soil 

samples were collected from various areas of the field and bulked for physio-chemical analysis at both sites. 

According to the results of the soil study, the soil at Ilora has 0.23 cmol/kg K, 5.96 mg/kg P, and 0.05% N. Ile-Ife's 

soil has 0.25 cmol/kg K, 11.98 mg/kg P, and 0.05% N. 

A 12x11 lattice design with two replicates was used in the experiment. To prevent any nitrogen seepage, the 

LN and HN blocks were spaced 5 meters apart. Every S1 was planted in a 3 m long single-row plot with 0.75 m 

between rows and 0.25 m inside rows of each other. To achieve a population of 53,333 plants/ha, thinning was 

carried out two weeks after planting (WAP) one plant per hill. Two and four WAP, a divided dosage of urea 

fertilizer was administered. Fertilizer was applied at a rate of 30 kgN/ha to LN plots and 90 kgN/ha to HN plots. 

At planting, 60 kg P2O5/ha P was applied as a single superphosphate to the LN and HN fields. Throughout the 

trials, weeds were kept out of the fields. 

 

2.4. Data Collection 

The number of days to 50% anthesis (DTA) and silking (DTS) were recorded in each plot as the number of 

days from sowing to when half of the plants shed pollen and emerge silks, respectively. Anthesis-silking interval 

(ASI) is computed as the difference in days between silking and anthesis. Stay green ability (SGR) was scored only 

on LN plots at 8 (SGR8) and 10 (SGR10)  weeks after planting (WAP) on a scale of 1 to 9, where 1 = less than 10 % 

senesced leaf and 9 = more than 80 % senesced leaf area below the ear. Plant height (PH) was measured in 

centimetres at maturity, the distance from the ground to the base of the tassel. Plant aspect (PA) was rated on a 

scale of 1 to 9, where 1 = excellent overall phenotypic appeal of the plants in a plot, and 9 = poor overall phenotypic 

appeal. Ear aspect (EA) was also rated on a scale of 1-9. One represents clean and well-filled cobs, while 9 

represents cobs without kernels or with very few kernels. The number of ears per plant (EPP) was estimated as the 

proportion of the ears divided by the number of harvested plants. A few ears were shelled from each plot to 

determine the moisture percentage. Grain yield (GY) adjusted to 14 % moisture was estimated from field weight at 

80 % shelling percentage. 

 

2.5. Statistical Analyses 

Mean values, coefficients of variation (CV), and ranges were calculated for the data. Separate combined analyses 

of variance (ANOVA) were conducted for LN and HN conditions using a random model in SAS version 9.0 [22] 



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from which heritability estimates were derived. Phenotypic and genotypic correlation analyses were performed to 

explore the relationships among different traits. Additionally, stepwise multiple regression analysis was carried out 

for each nitrogen (N) level, taking grain yield as the dependent variable. Path coefficient analysis was employed to 

break down significant phenotypic correlation coefficients into their direct and indirect effects, also using grain 

yield as the dependent variable [12]. The total correlation was determined by summing both direct and indirect 

impacts. Furthermore, principal component analysis was executed, considering components with Eigenvalues 

greater than 1.0, and characters with principal component (PC) values exceeding 0.6 were identified as significant 

contributors to the principal components [23]. 

 

3. RESULTS AND DISCUSSION 

3.1. Mean Performance of the Maize Population 

Means, ranges, CVs, and broad-sense heritability estimates of traits under LN and HN conditions are presented 

in Table 1. Stay green ability ranged between 3.09 at 8 WAP to 3.60 at 10 WAP under low N condition with a 

heritability estimate of 36 %. For the majority of the traits, heritability ranged from moderate to high, with the 

exception of ASI, days to 50% anthesis and ears per plant, under low N. 

Ranges were high for all the traits under both LN and HN. Stay-green ability is crucial for crop resilience and 

yield stability, particularly under low nutrient conditions [24]. On a scale of 1 to 9, stay-green ability varied in this 

study in low nitrogen conditions, with a heritability estimate of 36%. It ranged from 3.09 at eight weeks after 

planting to 3.60 at ten weeks after planting. The relatively low stay-green ratings suggest that maize plants can 

sustain their photosynthetic capacity longer under low nitrogen conditions. The moderate heritability indicates 

potential for improvement through selective breeding [25]. 

In this cycle, grain yield was greater under low nitrogen conditions (2.19 tons/ha) compared to high nitrogen 

(1.98 tons/ha). In low nitrogen environments, the anthesis-silking interval (ASI) was longer while the days to 

anthesis and silking were shorter. The quantity of ears per plant and the scores for plant and ear aspect did not 

significantly change between the high and low nitrogen conditions. It is possible that adaptation processes, such as 

improved nitrogen use efficiency (NUE) in the studied maize population, are responsible for the higher grain 

production observed in low nitrogen environment in contrast to the high nitrogen environment. Some maize 

varieties are naturally adapted to low-input conditions, using available nutrients more efficiently. Varieties that 

perform better under low nitrogen stress are often better adapted to local conditions and allocate resources more 

effectively for grain production rather than vegetative growth, as excessive nitrogen can sometimes lead to 

luxuriant vegetative growth at the expense of reproductive development [26]. The plant expedited its reproductive 

period in low nitrogen conditions to ensure seed production before nutrient depletion, as seen by the shorter days to 

anthesis and silking. On the other hand, a prolonged Anthesis-Silking Interval (ASI) in low-nitrogen environments 

suggests stress since it slows down the growth of both male and female flowers, which affects grain set and 

pollination efficiency. 



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Table 1. Estimates of mean, range, coefficient of variation (CV), and broad sense heritability (H2) of traits from evaluation of the S1 lines of ART/98/ ILE 1-OB 
population at Cycle 2 under LN and HN conditions at Ile-Ife and Ilora in 2021. 

Traits Mean± S.E Range CV (%) H2 (%) 

LN HN LN HN LN HN LN HN 

Stay-green 8WAP (1-9) 3.09± 0.58 - 1-9 - 26.3 - 36.9 - 
Stay-green 10WAP (1-9) 3.60± 0.53 - 1-9 - 20.77 - 36.3 - 
Grain yield (t/ha) 2.19± 0.55 1.98± 0.58 0.04-6.15 0.06- 6.03 35.5 41.8 30.8 32.4 
Days to 50% silking 63.9± 1.49 66.17± 1.82 55-79 59-73.6 3.28 3.89 43.1 32.4 
Days to 50% anthesis 63.6± 2.1 65.53± 1.76 55-78 66-77 4.66 3.8 14.16 34.16 
Anthesis-silking interval (ASI) 3.9± 0.17 2.85± 1.21 1-5 -1-9 6.33 59.9 -7.23 -0.36 
Plant height (cm) 123.22± 6.5 110.8± 8.04 58.5-172 57-152 7.47 10.26 66.9 42.56 
Ears per plant 0.84± 0.31 0.74± 0.28 0.01-3.2 0.12-3.9 52.1 53.6 19.41 8.7 
Ear aspect (1-9) 3.87± 0.83 4.14± 0.89 1-9 1-9 30.22 30.29 23.21 30.29 
Plant aspect (1-9) 3.78± 0.62 4.3± 0.52 1-8 2-8 23.08 17.31 41.15 26.9 

Note: S.E: Standard error; (1-9): 1 for excellent, 9 for poor;  cm: centimeter,  LN: Low nitrogen;  HN: High nitrogen. 

 



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3.2. Relationship Between Grain Yield and Other Agronomic Traits  

Table 2 illustrates the relationships between various agronomic parameters and grain yield (GY). There was a 

strong negative phenotypic correlation between GY and stay green ratings at 8 weeks (SGR8) and 10 weeks 

(SGR10), with correlation coefficients of -0.37** and -0.38**, respectively. Additionally, GY was negatively 

associated with days to anthesis (DTA) and days to silking (DTS), with values of -0.36** and -0.26**, respectively, 

observed under low nitrogen (LN) conditions. Similarly, negative correlations were observed between grain yield 

(GY) and both ear (EA) and plant aspect (PA). In contrast, plant height and ears per plant (EPP) demonstrated 

markedly strong positive correlations with GY, with correlation coefficients of 0.38** and 0.71**, respectively. The 

anthesis-silking interval (ASI) did not exhibit a significant phenotypic correlation with GY under low nitrogen 

conditions. Among the traits measured, EPP had the strongest correlation with GY, followed by EA and PA. 

  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



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Table 2. Phenotypic (above diagonal) and genotypic (below diagonal) correlation coefficients obtained from the evaluation of the S1 lines of ART/98/ ILE 1-OB population at Cycle 2 under low N condition at Ile-Ife and Ilora in 2021. 

Traits Stay green ability 
at 8WAP (SGR8) 

Stay green ability at 
10WAP (SGR10) 

Grain yield 
(GY) 

Days to 50% 
silking (DTS) 

Plant 
height (PH) 

Ears per 
plant (EPP) 

Ear aspect 
(EA) 

Anthesis-Silking 
Interval (ASI) 

Plant 
aspect (PA) 

Days to 50% 
anthesis (DTA) 

SGR8  0.68** -0.37** 0.39** -0.38** -0.50** 0.41** -0.03 0.41** 0.33** 
SGR10 1.0**  -0.38** 0.24** -0.31** -0.47** 0.32** 0.01 0.40** 0.08 
GY -0.48** -0.57**  -0.36** 0.38** 0.71** -0.53** 0.07 -0.47** -0.26** 
DTS 0.63** 0.40** -0.51**  -0.38** -0.32** 0.34** 0.06 0.19* 0.63** 
PH -0.68** -0.55** 0.70** -0.58**  0.41** -0.26** 0.05 -0.40** -0.21* 
EPP -0.62** -0.73** 1.00** -0.43** 0.80**  -0.40** 0.11 -0.32** -0.14* 
EA 0.52** 0.71** -0.87** 0.55** -0.65** -0.89**  0.02 0.34** 0.13* 
ASI NaN NaN NaN NaN NaN NaN NaN  0.07 -0.37** 
PA 0.51** 0.63** -0.73** 0.39** -0.59** -0.52** 0.67** NaN  0.16* 
DTA 0.31** 0.49** -0.25* 1.00** -0.61** -0.34** 0.15 NaN 0.24*  
Note: NaN: due to negative genotypic variances for one or more traits. 

*, ** significant at P= 0.05, 0.01 respectively. 



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In the light of the intricate nature of grain yield, a trait marked by its elusive heritability in the face of 

environmental stresses, it becomes apparent that an exclusive reliance on yield as the sole criterion for selection 

may prove to be rather inefficient [27]. Thus, selecting for grain yield under low nitrogen conditions along with 

secondary traits can enhance selection efficiency, provided the secondary traits are easy to measure, have high 

heritability and significant genetic correlation with grain yield [28, 29]. Yield is influenced by numerous 

interacting factors throughout the plant's life cycle [30]. There are differing views on which agronomic traits are 

most critical for maize yield under low nitrogen conditions. Correlation studies play an essential role in 

understanding the relationships among traits. A notable negative relationship between grain yield and stay-green 

ability suggests that maize plants that can maintain photosynthesis for a longer period in low nitrogen 

environments are likely to produce higher yields [31]. The impressive grain yield achieved in low nitrogen 

condition, coupled with an extended green leaf duration, demonstrates the capacity of the maize genotype to 

effectively re-mobilize nitrogen and manage the distribution of assimilates. Prior investigations by Chen, et al. [32] 

and Liu, et al. [33] have noted variations in nitrogen allocation and remobilization in response to low nitrogen 

stress among contemporary stay-green hybrids. 

A similar pattern was seen in the genotypic relationships (Table 2). The genotypic association between GY and 

SGR8 (-0.48**) and SGR10 (-0.57**) was found to be strong and negative. Furthermore, there were very strong 

negative relationship between GY and DTA (-0.25*) and DTS (-0.51**). Positive and highly significant 

correlations were noted between PH and EPP, with values of 0.70** and 1.00**, respectively. Both plant and ear 

aspect showed significant negative correlations with GY (-0.73** and -0.87**, respectively). EPP exhibited the 

highest genotypic correlation with GY, followed by EA and PA. The strong negative relationship between grain 

yield and days to 50% anthesis suggest that earlier-flowering plants under low nitrogen conditions tend to produce 

higher yields. The contrasting significant correlations between ASI and grain yield (GY), as well as between GY 

and stay-green rating (SGR), suggest that hybrids combining early flowering with enhanced stay-green capacity 

post-grain filling can achieve greater yields. Early flowering proves beneficial under low nitrogen conditions as it 

allows the plant to complete its reproductive stage before experiencing severe nutrient stress, thereby improving 

grain yield [34]. 

The inverse relationships found between plant and ear characteristics and grain production implied that 

healthier plants with fewer disease symptoms,—generally yield more. In a similar vein, the results of Emmanuel, et 

al. [35] and Adewumi, et al. [36] are supported by the positive correlations observed between grain yield, plant 

height, and the number of ears on each plant. Taller plants with more ears provide higher yields. Larger leaf areas 

on taller plants probably enhance photosynthetic ability, and more ears per plant will translate into better grain 

production potential. Both under nitrogen-limited and ideal conditions, studies by Inamullah, et al. [37] and Al-

Naggar, et al. [38] revealed favourable relationships between grain yield (GY) and ears per plant (EPP). Udo, et al. 

[39] similarly observed a positive relationship between GY and plant height under low nitrogen. This correlation 

is significant for breeding programs focused on improving yields in low nitrogen environments [40]. However, 

caution is necessary with tall plants, as they may be more susceptible to lodging, so selecting for an optimal height 

range is important.  

Among the traits, EPP showed the strongest correlation with grain yield, followed by ear aspect (EA) and 

plant aspect (PA), underscoring their importance in low nitrogen conditions. The consistent genotypic and 

phenotypic correlations confirm the genetic linkage of these traits, indicating that selecting for them can directly 

improve grain yield under low nitrogen stress. The strong positive associations may arise from gene linkage or 

pleiotropic effects where the same genes influence multiple traits in the same direction Kearsey and Pooni [41]. 

Amegbor, et al. [42] also found significant negative phenotypic and genotypic correlations between GY and DTS, 

PA, EA, and SGR, while observing a positive correlation between GY and EPP in hybrid maize under low nitrogen 

conditions. 



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3.3. Regression of Yield on Other Agronomic Traits 

A stepwise multiple regression analysis examining the relationship between yield and different agronomic 

traits under low nitrogen conditions indicated that ears per plant (EPP) was the most significant factor influencing 

yield in the maize population (Table 3), accounting for 45% of the variation (R² = 0.45). Ear aspect (EA) accounted 

for an additional 8% of the variance. The contributions of SGR8 and PH, though significant, were only 1 % each 

under LN. Plant height was picked as the most essential trait contributing to GY under HN with an R2 value of 

21%. EPP and EA contributed an additional 8 % and 7 % respectively. Though significant, PA and DTS contributed 

only 2 % and 1 % under HN (Table 3). This result emphasizes how crucial EPP is in determining yield in nutrient-

stressed environments. Grain production is increased when there are more ears per plant since more ears equal 

more kernels [26]. Under low N conditions, ear aspect added an extra 8% to the variability in grain yield. The ear 

aspect typically refers to the appearance and health of the ears, which can impact the quantity and quality of the 

grains produced. Good ear aspect indicates better grain filling and less susceptibility to diseases and pests, leading 

to higher yields [43]. Stay-green ability and plant height, though significant, contributed minimally, adding only 

1% to yield variability under low nitrogen. 

 

Table 3. Partial regression coefficients from stepwise regression of grain yield on agronomic 
traits in S1 lines of ART/98/ILE 1-OB at Cycle 2 under low and high N conditions, Ile-Ife and 
Ilora, 2021. 

Trait b-value R2 ∆R2 Probability 

Low N 

Ears per plant 0.97 0.45 0.45 <.0001 
Ear aspect (1-9) -0.23 0.54 0.08 <.0001 
Stay green ability 8 WAP (1-9) 0.09 0.54 0.01 0.0193 
Plant height (cm) 0.01 0.55 0.01 0.0164 
High N 

Plant height (cm) 0.02 0.21 0.21 <.0001 
Ears per plant 0.72 0.28 0.08 <.0001 
Ear aspect (1-9) -0.17 0.35 0.07 <.0001 
Plant aspect (1-9) -0.16 0.37 0.02 0.0002 
Days to 50 % silking -0.04 0.38 0.01 0.0044 

 

 

Under high nitrogen, plant height was the most significant trait, explaining 21% of yield variability. Taller 

plants generally have greater leaf area, enhancing photosynthetic capacity and biomass accumulation, leading to 

higher yields. This highlights the importance of plant height under optimal nutrient conditions. EPP and EA 

contributed an additional 8 % and 7 %, respectively, to yield variability under high nitrogen, emphasizing their roles 

in yield determination. Plant aspect and days to 50 % silking contributed minimally, suggesting that under high 

nitrogen, flowering time has lesser impact on yield than plant height and ear characteristics. 

 

3.4. Path Coefficient Analysis of the Significant Phenotypic Correlation Coefficients of Traits Studied 

Significant correlations were analyzed in greater detail through path analysis, with grain yield serving as the 

dependent variable. Ears per plant (EPP) showed the strongest positive direct effect (1.15), followed by SGR8 (0.23) 

(Table 4). Both days to silking (DTS) and plant height (PH) also exhibited positive direct effects, while other traits 

had negative direct effects. Ear aspect (EA) had the largest negative direct effect (-0.18), closely followed by plant 

aspect (PA) at -0.17. The most significant negative indirect effects for EA and EPP occurred through SGR8 (-0.076 

and -0.58, respectively). EPP's largest positive indirect effect was observed through PH (0.47).  

Prior research has consistently identified ASI and EPP as critical characters for enhancing grain production in 

low-nitrogen environments, however, ASI made a small contribution to yield of the QPM population utilized in this 

investigation. The high direct effects of EPP, SGR8 and EA, along with the positive indirect effect of EPP via plant 

Note: (1-9): 1 for excellent, 9 for poor; cm: centimeter; N: Nitrogen, R2 :Coefficient of Determination ∆R2 : 
change in R2 



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height, highlight these traits' importance under low nitrogen. The high negative indirect effects of EA and EPP 

through SGR8 further emphasizes the importance of SGR. Maize genotypes with strong stay-green traits are 

typically more resilient to post-silking environmental stresses, including reduced nitrogen uptake and extended leaf 

longevity [44]. This allows them to maintain photosynthesis during periods of high nitrogen demand [45]. 

Therefore, stay-green ability plays a crucial role in the maize's nitrogen use efficiency (NUE) [15]. However, plant 

height should be carefully managed when developing a selection index for low nitrogen conditions, as very tall 

plants are more prone to lodging in strong winds [20].  



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Table 4. Direct (bold on diagonal) and indirect effects (off diagonal) from path coefficient analysis of significant phenotypic correlation coefficients of traits obtained from S1 lines of ART/98/ ILE 1 -OB at Cycle 2 under low N 
condition at Ile-Ife and Ilora in 2021. 

Traits 

Stay green 
ability 8 WAP 

(SGR8) 

Stay green 
ability 10 WAP 

(SGR10) 

Days to 50 
% silking 

(DTS) 

Plant 
height 
(PH) 

Ears per 
plant (EPP) 

Ear aspect 
(EA) 

Anthesis-Silking 
Interval  (ASI) 

Plant 
aspect 
(PA) 

Days to 50 
% anthesis 

(DTA) 
Total 

correlation 
Total Indirect 

effects 

SGR8 0.232 0.159 0.087 -0.088 -0.117 0.097 -0.002 0.102 0.069 0.539 0.307 

SGR10 -0.050 -0.074 -0.016 0.022 0.035 -0.025 -0.003 -0.033 -0.003 -0.147 -0.073 

DTS 0.003 0.001 0.007 -0.003 -0.002 0.002 0.000 0.001 0.004 0.014 0.007 

PH 0.000 0.000 0.001 0.001 0.001 0.000 0.000 0.000 0.000 -0.001 -0.002 

EPP -0.583 -0.550 -0.350 0.468 1.157 -0.473 0.113 -0.393 -0.140 -0.751 -1.908 

EA -0.076 -0.062 -0.057 0.047 0.075 -0.183 -0.008 -0.067 -0.016 -0.348 -0.165 

ASI 0.000 -0.001 -0.002 -0.002 -0.003 -0.001 -0.031 -0.003 0.012 -0.031 0.001 

PA -0.075 -0.077 -0.028 0.067 0.058 -0.063 -0.015 -0.172 -0.022 -0.326 -0.155 

DTA -0.019 -0.003 -0.041 0.013 0.008 -0.006 0.024 -0.008 -0.065 -0.096 -0.032 
Note: WAP: Weeks after planting. 



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96 

© 2024 Conscientia Beam. All Rights Reserved. 

Traits like ear aspect (EA) and stay-green rating (SGR) at eight weeks are easily assessed and can be utilized 

for selecting maize genotypes with improved yield under low nitrogen. 

 

3.5. Principal Component Analysis of the Traits Studied Under Low N Condition 

The principal component analysis (PCA) results showed that the first three component axes had Eigenvalues 

exceeding one and accounted for 98.9% of the overall variation (Table 5). The Eigenvalues for PC1, PC2, and PC3 

were 218.41, 4.24, and 1.21, respectively, with corresponding contributions of 96.5%, 1.87%, and 0.53%. Plant 

height was the main variable that PC1 alone explained, accounting for 96.5% of the variance. All the three PCs had 

good loadings, with PC2 being related to days to 50% silking and PC3 being related to plant aspect. The PCA 

findings indicate that the main factors influencing the observed variation were plant aspect, days to 50% silking, 

and plant height, highlighting the significance of these factors in selection efforts. The dominant role of plant 

height in PC1 further highlights its significance in selection under low nitrogen conditions. 

Badu-Apraku, et al. [46] used genotype × trait biplot analysis  and identified days to anthesis and silking, stay-

green characteristic, ASI, plant height, EPP, and plant and ear aspects as traits strongly correlated with yield. . 

Their study highlighted ASI, EPP, and plant and ear aspects as the most reliable indicators for selecting early-

maturing maize inbred lines under low nitrogen conditions. Additionally, path-coefficient and GGE biplot analyses 

identified ear height, plant aspect, ear aspect, and stay-green traits as useful markers for selecting nitrogen-tolerant 

extra-early maize lines [47]. A stepwise regression by Talabi, et al. [48] further emphasized ear aspect, plant 

aspect, EPP, stay-green traits, days to silking, and stalk lodging as important factors for improving yield in low-

nitrogen environments. 

 

Table 5. Principal component, Eigenvalues, and percentage variation of the traits studied under low 
N conditions across the locations in 2021. 

Traits PC1 PC2 PC3 

Stay green ability 8WAP (1-9) -0.03 0.13 0.34 

Stay green ability 10WAP (1-9) -0.02 0.07 0.37 
Grain yield (t/ha) 0.02 -0.10 -0.28 
Anthesis-Silking Interval  (ASI) 0.01 0.10 0.52 
Days to 50% silking -0.07 0.97* -0.19 
Plant height (cm) 1.00* 0.08 0.03 
Ears per plant 0.01 -0.03 -0.09 
Plant aspect (1-9) -0.03 0.05 0.59* 
Ear aspect (1-9) 0.00 0.09 0.01 
Eigenvalue 218.41 4.24 1.21 
% variation 96.50 1.87 0.53 
Cumulative 96.50 98.37 98.90 

Note: *Component contributors; PC: Principal component. 
(1-9): 1 for excellent, 9 for poor; cm: centimeter. 

 

Bhadmus, et al. [49] found that plant and ear aspect significantly influenced grain yield, accounting for nearly 73% 

of the overall variation in their genetic study on 96 early white quality protein maize hybrids evaluated in low 

nitrogen environments. These results highlight the need to determine the most important qualities for different 

maize population, as the main attributes for yield prediction may differ with population. From the results presented 

in this study, it becomes evident that ear aspect, ear per plant (EPP), the capacity for stay-green, and plant height 

are important traits for selection in the improvement of QPM for tolerance to low soil nitrogen. These traits also 

exhibit high heritability in environments characterized by nitrogen scarcity.  

 

4. CONCLUSION 

The study discovered the key traits with moderate to high heritability that contribute to the QPM's grain 

production. These traits include the number of ears per plant, ear aspect, plant height, and stay-green ability at 8 



Current Research in Agricultural Sciences, 2024, 11(2): 85-99 

 

 
97 

© 2024 Conscientia Beam. All Rights Reserved. 

WAP. Thus, the traits may serve as selection criteria for enhancing Quality Protein Maize's resilience to low soil 

nitrogen conditions, thereby accelerating the pace of breeding advancements. However, plant height should be 

pegged to a certain level in the index because tall plants lodge easily under intense wind, and this could indirectly 

reduce yield. 

 

Funding: This study received no specific financial support.    
Institutional Review Board Statement: Not applicable. 
Transparency: The authors state that the manuscript is honest, truthful, and transparent, that no key 
aspects of the investigation have been omitted, and that any differences from the study as planned have been 
clarified. This study followed all writing ethics. 
Competing Interests: The authors declare that they have no competing interests. 
Authors’ Contributions: All authors contributed equally to the conception and design of the study. All 
authors have read and agreed to the published version of the manuscript. 

 

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