Nitrogen Responsiveness of Maize Hybrids Under Dryland Conditions

Abstract

Nitrogen (N) plays a decisive role in the growth and yield of crops. Hence, a high maize grain yield depends upon substantial N inputs. In the present study, morphological traits and yield components, grain yield, rain use efficiency (RUE), and N partial factor productivity (NPFP) were analyzed in two maize hybrids (ZP666 and NS6030) for 2 yr using four N rates (0 (N0), 60 (N60), 120 (N120), and 180 (N180) kg N ha⁻¹). In a climatically more favorable year (2022), the studied traits and NPFP were higher, while RUE was lower. Hybrid ZP666 had higher values of morphological traits and yield component traits, except 1000-grain weight, grain yield, RUE, and NPFP, than hybrid NS6030. The highest values for morphological traits, yield components, grain yield (9383 and 9456 kg ha⁻¹), and RUE (27.1 and 27.2 kg ha⁻¹ mm⁻¹) were obtained at 120 and 180 kg N ha⁻¹. The NPFP decreased significantly with increasing N input, from 137.6 (control) to 52.5 kg grain per kg fertilizer N (180 kg N ha⁻¹). A suitable hybrid selection and the application of a moderate N fertilizer rate of 120 kg N ha⁻¹ could contribute to high yields and lower nitrogen losses to the environment and promote sustainable agriculture.

1. Introduction

Maize (Zea mays L.) is one of the world’s most important sources of food for humans and animal feed. It is also used for various industrial purposes where different parts of a plant are used. It is adaptable to different environments and is cultivated between 58° north latitude and 40° south latitude. In 2023, global maize grain production was about 1.24 billion tons on an area of 208 million hectares with an average yield of 5.9 t ha⁻¹ [1]. The United States, China, and Brazil were the largest producers of maize, accounting for 48.8% of the area under cultivation [1]. In the same year, maize was grown on 922,980 ha (27.2% of the total cultivated area) in Serbia, with an average yield of 7.2 t ha⁻¹ and a production of 6.6 million tons [1]. Average maize yields have increased over time. The factors that have contributed to the achievement of high maize yields are based on the improvement of agronomic traits and adaptation to different agroclimatic and ecological conditions [2,3,4], including soil and crop management [5,6]. A recent study reported that improvements in climate, agronomy, and genetics increased maize grain yield by 48, 39, and 13%, respectively [7]. These findings highlight the predominant role of environmental and management factors over genetic gains in recent decades. Therefore, understanding the interaction between nitrogen input and genotype performance remains a key priority for sustainable yield improvements. The dominant strategy in maize breeding is to develop genotypes with wide adaptation to agroecological conditions and high and stable yields [8]. According to Egli [9], new genotypes were developed through breeding that quadrupled maize yields in terms of agronomic traits between 1930 and 2014. Apart from breeding, the maize production is based mainly on mineral N fertilizers, considering that N is a key factor determining crop yield and quality. Therefore, selecting the appropriate N fertilizer is one of the most important aspects needed to maximize maize yield [10] and prevent N losses in the environment through denitrification, leaching, and volatilization [11,12]. Many researchers showed that N fertilization increases morphological and productive traits of maize. Galindo et al. [10] observed that increasing N levels from 50 to 200 kg ha⁻¹ led to increased soil N availability, plant height, ear diameter, the number of grains per ear, 100-grain weight, and grain yield of maize. Grain yield and its attributing traits of maize hybrids increased with the increasing N rate from 160 to 220 kg ha⁻¹ [13]. Authors have indicated that this increase was particularly pronounced in the 10V10 genotype compared to Rajkumar F1 and NMH-731. According to Delibaltova [14], Marković et al. [15], and Gheith et al. [16], yield components and grain yield increased significantly with increasing N fertilization up to 240 kg ha⁻¹, 200 kg ha⁻¹, and 336 kg ha⁻¹, respectively. The authors also suggested that hybrids of maize respond differently to N rates under the same environmental conditions, emphasizing that the choice of hybrid and appropriate N rate are key factors for maximizing maize yield.

The aims of this study were to determine differences in maize agronomic traits and grain yields as a function of N fertilization and the choice of hybrids with greater efficiency in order to indicate an effective field strategy for improving grain yields. N fertilization represents an important agronomic input for improving quantitative traits in maize hybrids, particularly during variable meteorological conditions for growth.

2. Materials and Methods

2.1. Field Experiment

A field experiment was conducted under dryland conditions at an experimental station of the Institute for Animal Husbandry, Belgrade-Zemun (latitude: 44° 85′ N, longitude: 20° 29′ E, altitude: 88 m), in 2021 and 2022. The two dent maize hybrids NS6030 and ZP666 (FAO600 maturity group) were tested. These hybrids widespread cultivated in the region and are very popular with Serbian farmers due to their high genetic yield potential, remarkable phenotypic plasticity, and good adaptation to the environment. They are suitable for both grain and forage production. They are also drought tolerant due to their delayed leaf senescence (stay-green trait). Four N rates were examined: 0 (control), 60, 120, and 180 kg N ha⁻¹, denoted as N0, N60, N120, and N180, respectively. The preceding crop was winter wheat (Triticum aestivum L.). Planting was performed on 12 April 2021 and 8 April 2022. The maize was planted in 4 rows, 6 m long, with an inter-row distance of 0.7 m (64,900 plants ha⁻¹). A standard cultivation practice was uniformly applied in all experimental plots. Basic fertilization with NPK fertilizer (10-30-20) was applied each autumn at a rate of 200 kg ha⁻¹. The N fertilizer CAN (calcium ammonium nitrate with 27% of N and 8% of Ca; HIP—Azotara Pančevo, Serbia) was applied in both years in May at the V3 to V5 stage in quantities of 0, 222.2, 444.4, and 666.6 kg ha⁻¹, respectively. Accordingly, the N treatments were 0, 60, 120, and 180 kg N ha⁻¹. The harvest was performed on 3 October 2021 and 1 October 2022.

2.2. Meteorological Conditions

For the long-term reference period of 1981–2010, the total rainfall amount and average annual temperature were 391.9 mm and 19.3 °C; for 2021, 272.4 mm and 19.8 °C; and for 2022, 447.0 mm and 20.4 °C (Figure 1). Therefore, the total seasonal rainfall of 447 mm for 2022 was 14.1% above the long-term period average of 391.9 mm and 64.1% above the 2021 average of 272.4 mm. In contrast, the total seasonal rainfall of 272.4 mm in 2021 was 31% lower than in the long-term reference period. In 2021, there were dry periods in June (intensive stem growth), August, and September (dough stage (R4) and physiological maturity (R6)). In 2022, the meteorological conditions were favorable for maize growth.

2.3. Soil Properties

The CaCO₃ content, organic matter, total N, and available P and K were determined using the Scheibler calcimeter [17], Kotzmann [18], Kjeldahl [19], and Egner–Riehm Al [20] methods, respectively. The pH of the soil was determined in a 1:2.5 suspension (soil:1 mol dm⁻³ KCl) using a digital pH meter (Hanna Instruments HI 83141, Italy). The results showed that the topsoil layer of 0—30 cm contained 0—30 cm contains 4.24% CaCO₃, 5.1% organic matter, 0.27% total N, 13.6 mg P₂O₅ 100 g soil⁻¹, and 17.8 mg K₂O 100 g soil⁻¹. The pH in KCl was 7.24.

2.4. Data Collection

Immediately after July silking in both years, ten plants in the central rows of each subplot were taken for measuring plant height, ear height, and the number of leaves per plant. At full maturity, on 6 October 2021 and 10 October 2022, the trial was manually harvested. Grain yield was determined using the two central rows of each plot to avoid edge effects, adjusted to 14% moisture content, and converted on a per-hectare basis. Ten ears from the bulk were taken to measure ear length, the number of rows per ear, the number of grains per ear, grain weight per ear, and 1000-grain weight. Rain use efficiency (RUE, kg ha⁻¹ mm⁻¹) was calculated by the following formula: grain yield/total seasonal rainfall. N partial factor productivity (NPFP, kg grain kg fertilizer N⁻¹) was calculated according to Cheng et al. [21] using the formula grain yield/N input. The experiment was carried out in four replications.

2.5. Statistical Analysis

A field experiment was analyzed using a three-factor random block system design with four replications. STATISTICA version 20 (StatSoft, Tulsa, OK, USA) was used for data analysis. The Tukey test at p ≤ 0.05 was used to detect the difference between the means of the parameter, whereas the p-value (p ≤ 0.05 and p ≤ 0.01) was used to determine the significance level. Pearson correlation coefficients (p ≤ 0.05 and p ≤ 0.01) were used for the interdependence between studied parameters. In addition, the principal component analysis (PCA) of investigated traits and parameters based on different N rates was applied using RStudio version 2024.12.1, Build 563. Determination of stability in the observed agronomic traits was carried out using AMMI analysis. Evaluation of genotype x environment interactions and determination of stability in the observed agronomic traits were carried out using AMMI (Additive Main Effects and Multiplicative Interaction) analysis. AMMI analysis combines analysis of variance for the additive main effects (genotypes and environments) with principal component analysis for the multiplicative interaction effects [22]. The combination of nitrogen doses and the years in which the experiments were conducted (N0, N60, N120, and N180 × 2 observed years) was considered as the environment. The analysis was performed using free RStudio software, version 2024.12.1, Build 563. In order to rank the observed characteristics in terms of stability, the AMMI stability value (ASV) was calculated [23].

$$\mathrm{A}\mathrm{S}\mathrm{V}=\sqrt{{\left[{\displaystyle \frac{{\mathrm{S}\mathrm{S}}_{\mathrm{P}\mathrm{C}1}}{{\mathrm{S}\mathrm{S}}_{\mathrm{P}\mathrm{C}2}}}\left(\mathrm{P}\mathrm{C}1\right)\right]}^2+{\mathrm{P}\mathrm{C}2}^2}$$

SS = sum of squares; PC1 = first principal component; PC2 = second principal component.

3. Results

3.1. Descriptive Statistics and Variations in Parameters

Descriptive statistics and variations for the investigated parameters are shown in

Table 1. Descriptive statistics of morphological traits, yield component traits, grain yield, RUE, and NPFP of maize hybrids at different N rates.

Parameters	Mean	Minimum	Maximum	SD	CV, %
Plant height (cm)	244.7	220.0	285.0	12.7	5.2
Eer height (cm)	97.1	60.5	118.8	13.9	14.3
Number of leaves per plant	12.8	11.0	14.5	1.0	7.8
Ear length (cm)	20.3	16.4	27.1	2.3	11.3
Number of rows per ear	14.1	12.0	16.7	1.1	7.8
Number of grains per ear	581.9	407.1	816.1	98.1	16.9
Grain weight per ear (g)	184.5	118.5	245.1	26.6	19.8
1000-grain weight (g)	278.3	197.5	396.0	53.9	19.4
Grain yield (kg ha−1)	8634.7	4315.5	12,561.5	1734.5	20.1
Rain use efficiency(kg ha−1 mm−1)	24.8	15.8	46.1	5.6	22.6
N partial factor productivity(kg grain kg fertilizer N−1)	89.4	39.0	161.2	38.6	43.2

SD—standard deviation; CV—coefficient of variation.

. Plant height varied little, ranging from 220.0 cm to 285.0 cm, with an average of 244.7 cm. Ear height followed a similar trend, spanning from 60.5 cm to 118.8 cm (mean 97.1 cm), while the number of leaves per plant ranged between 11.0 and 14.5, averaging 12.8. Ear length showed medium variability and ranged from 16.4 cm to 27.1 cm (mean 20.3 cm), with the number of rows per ear ranging from 12.0 to 16.7 (mean 14.1). The number of grains per ear varied from 407.1 to 816.1, with a mean of 581.9 grains. Grain weight per ear ranged from 118.5 g to 245.1 g, with a mean of 184.5 g, while 1000-grain weight ranged from 197.5 g to 396.0 g (mean 278.3 g). Grain yield exhibited a wide range, from 4315.5 to 12561.5 kg ha⁻¹, averaging 8634.7 kg ha⁻¹. RUE varied between 15.8 and 46.1 kg ha⁻¹ mm⁻¹ (mean 24.8 kg ha⁻¹ mm⁻¹), and NPFP ranged from 39.0 to 161.2 kg grain per kg fertilizer N⁻¹, with a mean of 89.4 kg grain per kg fertilizer N⁻¹. The coefficient of variation for the traits ranged from 5.2% (plant height) to 20.1% (grain yield); for RUE and NPFP, it was 22.6% and 43.2% respectively.

3.2. Morphological Plant Traits

We have analyzed morphological traits of the two maize hybrids under different weather conditions and N rates. Under favorable weather conditions, present in the second year, plant height was greater by 2.7%, ear height by 25.2%, and the number of leaves by 15.1% than in the first year (241.5 cm, 86.2 cm, and 11.9, respectively), as shown in

Table 2. Effects of year, hybrid, and N rate on morphological traits of maize.

Trait	Year (Y)		Hybrid (H)		N Rate, kg ha−1
	2021	2022	NS6030	ZP666	0	60	120	180
PH (cm)	241.5 b	247.9 a	238.0 b	251.3 a	236.5 b	243.1 ab	247.8 a	251.2 a
EH (cm)	86.2 b	107.9 a	97.9 a	96.2 a	92.0 b	95.7 ab	98.5 ab	102.1 a
NLP	11.9 b	13.7 a	12.8 a	12.8 a	12.5 b	12.7 ab	13.0 a	13.0 a
F test	Y	H	N	Y × H	Y × N	H × N	Y × H × N
PH	**	**	**	ns	ns	ns	ns
EH	**	ns	*	ns	ns	ns	ns
NLP	**	ns	**	ns	ns	ns	ns

PH—plant height (cm); EH—ear height (cm); NLP—number of leaves per plant; means with different superscript letters in a row are significantly different by Tukey’s test at the 5% level; ** significant at 1%; * significant at 5%; ns—not significant.

. Further analysis indicated that, averaged across years and N rates, the hybrid ZP666 had a higher value of plant height by 5.6% than hybrid NS6030 (238.0 cm). The average values of investigated traits across two years and two hybrids increased with increasing N rate. Compared to the control, significantly higher plant height and the number of leaves per plant were observed at 120 and 180 kg N ha⁻¹, while a significantly greater ear height was recorded at 180 kg N ha⁻¹. Interactions among factors were not significant for these morphological traits.

3.3. Grain Yield and Yield Component Traits

According to the variance analyses, the effects of year, hybrid, and N rate have a significant influence on the characteristics of the yield components and grain yield, as shown in

Table 3. Effects of year, hybrid, and N rate on yield components traits, grain yield, RUE, and NPFP of maize.

Trait	Year (Y)		Hybrid (H)		N Rate, kg ha−1
	2021	2022	NS6030	ZP666	0	60	120	180
EL	18.8 b	21.7 a	19.4 b	21.2 a	19.2 b	20.3 ab	20.6 a	21.0 a
NRE	13.5 b	14.7 a	13.9 b	14.3 a	13.4 b	13.6 b	14.4 a	14.9 a
NGE	518.0 b	645.9 a	556.4 b	607.5 a	529.0 b	585.5 a	624.8 a	588.4 a
GWE	168.8 b	202.2 a	180.1 b	188.9 a	167.4 b	178.7 b	195.9 a	196.1 a
TGW	239.2 b	317.4 a	275.6	281.0	247.4 b	280.4 a	285.6 a	299.8 a
GY	7631 b	9639 a	8324 b	8945 a	7446 b	8255 b	9383 a	9456 a
RUE	28.0 a	21.6 b	23.7 b	25.9 a	21.0 b	23.9 ab	27.1 a	27.2 a
NPFP	81.0 b	97.8 a	85.7 b	93.2 a	—	137.6 a	78.2 b	52.5 c
F test	Y	H	N	Y × H	Y × N	H × N	Y × H × N
EL	**	**	**	ns	*	*	*
NRE	**	**	**	*	**	ns	*
NGE	**	**	**	*	*	*	ns
GWE	**	*	**	*	ns	ns	ns
TGW	**	ns	**	*	**	*	ns
GY	**	*	**	*	ns	ns	ns
RUE	**	*	**	*	*	ns	ns
NPFP	**	*	**	*	ns	ns	ns

EL—ear length (cm); NRE—number of rows per ear; NGE—number of grains per ear; GWE—grain weight per ear (g); TGW—1000-grain weight (g); GY—grain yield (kg ha⁻¹); RUE—rain use efficiency (kg ha⁻¹ mm⁻¹); NPFP—N partial factor productivity (kg grain kg fertilizer N⁻¹). Distinct letters in the row indicate significant differences according to Tukey’s test (p ≤ 0.05); **—significant at 1% level of probability; *—significant at 5% level of probability; and ns—not significant.

.

As for the two hybrids and four N rates, the values of the investigated parameters were higher in 2022 than in 2021 on average. The ear length was higher by 15.4%, the number of rows per ear by 8.9%, the number of grains per ear by 24.7%, grain weight per ear by 19.8%, 1000-grain weight by 32.7%, and grain yield by 26.3% than in 2021 (18.8 cm, 13.5, 518.0, 168.8 g, 239.2 g, and 7631 kg ha⁻¹, respectively). Averaged over years and N rates, the hybrid ZP666 had a higher value of investigated traits, except for 1000-grain weight, compared to the hybrid NS6030. Higher N inputs (120 and 180 kg ha⁻¹) significantly increased the yield component traits and grain yield compared to the control. The lowest N rate of 60 kg ha⁻¹ significantly increased the number of grains per ear by 10.7% and 1000-grain weight by 13.3% compared to the control (529.0 and 247.4 g). The interaction of year × hybrid was not significant for ear length only; the interaction of year × N rate was not significant for grain weight per ear and grain yield, while the interaction of hybrid × N rate was not significant for the number of rows per ear, grain weight per ear, and grain yield. The interaction of year × hybrid × N rate was significant for ear length (p ≤ 0.05) and the number of rows per ear (p ≤ 0.05).

3.4. Rain Use Efficiency (RUE) and N Partial Factor Productivity (NPFP)

As expected, the RUE (21.6 kg ha⁻¹ mm⁻¹) was lower while NPFP (97.8 kg grain kg fertilizer N⁻¹) was higher in 2022, the year with a favorable growing season (Table 2). The hybrid ZP666 had higher RUE (25.9 kg ha⁻¹ mm⁻¹) and NPFP (93.2 kg grain kg fertilizer N⁻¹) than the hybrid NS6030 (23.7 kg ha⁻¹ mm⁻¹ and 85.7 kg grain kg fertilizer N⁻¹, respectively). The N rates of 120 and 180 kg ha⁻¹ significantly increased the RUE compared to the control. On the contrary, NPFP decreased significantly with increasing N rates, and the lowest NPFP (52.5 kg grain kg fertilizer N⁻¹) was recorded at 180 kg N ha⁻¹. The interaction of year × hybrid was significant for RUE (p ≤ 0.05) and NPFP (p ≤ 0.05), and the interaction of year × N rate was significant for RUE (p ≤ 0.05).

3.5. Principal Component Analysis and AMMI Analysis for Measured and Calculated Parameters

Principal component analysis (PCA) revealed that the first (PC1) and second (PC2) components contributed 97.1%, 92.48%, and 95.14% of the total variation for two hybrids (general, ZP666, and NS6030), respectively (Figure 2). All observed variables are positively correlated with the first principal component. The length of the vector of the observed traits differs between the two observed hybrids, and therefore their variance. The highest variability was found for NPFP in both observed hybrids. In the hybrid ZP666, a greater variability of traits was observed compared to NS6030.

Among the parameters tested for ZP666, RUE, grain yield, number of leaves per plant, number of grains per ear, and ear length are significantly correlated with each other, but the first three parameters are negatively correlated with PC2. Among the parameters tested for NS6030, RUE, ear height, grain yield, and grain weight per ear are significantly correlated with each other and positively correlated with the second axis (PC2). In both hybrids, NPFP is positively correlated with TGW.

In addition, it was established that an N rate of 120 kg ha⁻¹ contributed most to the variability in the seven observed parameters (ear length, 1000-grain weight, RUE, plant height, number of leaves per plant, grain yield, and grain weight per ear). When different hybrids are observed, for ZP666, 120 kg ha⁻¹ N rate in the greatest degree contributed to the variability in grain yield, 1000-grain weight, RUE, grain weight per ear, and the number of leaves per plant, while, for NS6030, 180 kg ha⁻¹ N rate contributed to the variability in the grain weight per ear, grain yield, ear height, and RUE. The 60 kg ha⁻¹ N rates slightly induced variability in NPFP in both genotypes.

According to the AMMI analysis, the stability of the agronomic traits differs in relation to the nitrogen dose used, which maize hybrid was used, and the growing conditions (Tables S1–S12, Figures S1–S11). NS6030 gave more stable and better results in both observed years, compared to ZP666. Regarding the plant height trait, ZP666 had more stable results in conditions with less rainfall during the season, while NS6030 was more stable in more optimal corn growing conditions. Rain use efficiency was more stable in drier conditions, and better results were recorded with ZP666. The hybrid NS6030 had stable results for most of the observed traits at lower doses of nitrogen (control and 60 kg ha⁻¹) and at the highest applied dose (180 kg ha⁻¹). ZP666 gave the best (most stable) results with the application of a nitrogen dose of 120 kg ha⁻¹. All traits varied less during the second experimental year. Based on AMMI stability values (ASV), the highest variability (highest values of the stability coefficient) was determined for the traits the number of grain per ear, and grain yield, while the most stable traits (lowest variability) were plant height, number of leaves per plant, ear length, number of rows per ear, and RUE (

Table 4. AMMI stability values (ASV) for eleven parameters of two maize hybrids across two growing seasons and four N rates.

Trait	Hybrid + Year				N Rate, kg ha−1 (N)
	ZP666—21	ZP666—22	NS6030—21	NS6030—22	0	60	120	180
PH	2.66	1.50	4.35	2.44	3.54	0.71	4.14	2.02
EH	4.10	7.54	11.17	7.39	8.58	5.55	2.78	11.87
NL	4.68	3.14	0.46	1.15	4.78	0.49	2.67	1.76
EL	1.58	2.81	2.49	6.56	1.79	3.97	0.94	6.31
NRE	2.04	0.84	2.26	4.71	2.37	2.71	4.24	1.08
NGE	26.01	138.48	83.28	29.73	106.99	106.93	48.99	48.89
GWE	8.41	6.19	3.18	10.88	8.40	3.29	12.19	2.74
TGW	11.37	5.73	10.78	24.83	12.03	5.95	9.33	25.05
GY	64.59	47.28	25.13	81.72	61.42	25.63	93.00	25.31
RUE	6.40	1.42	1.28	5.96	6.66	1.19	5.77	1.01
NPFP	0.77	5.06	12.61	8.30	10.59	10.94	3.78	2.81

PH—plant height; EH—ear height; NL—number of leaves per plant; EL—ear length; NRE—number of rows per ear; NGE—number of grains per ear; GWE—grain weight per ear; TGW—1000-grain weight; GY—grain yield; RUE—rain use efficiency; NPFP—N partial factor productivity.

).

3.6. Correlation Among Parameters

The simple correlation coefficients showed that grain yield had a significant and strongly positively correlation with the number of leaves per plant (r = 0.66 **), grain weight per ear (r = 0.91 **), and 1000—grain weight (r = 0.67 **); a significant and moderately positive correlation with plant height (r = 0.42 **), ear height (r = 0.52 **), ear length (r = 0.55 **), number of rows per ear (r = 0.58 **), and number of grains per ear (r = 0.59 **); and a significant and weakly positive correlation with RUE (r = 0.31 *) and NPFP (r = 0.30 *),

Table 5. Correlation matrix (Pearson) between studied parameters.

	EH	NL	EL	NRE	NGE	GWE	TGW	GY	RUE	NPFP
PH	0.40 **	0.39 **	0.41 **	0.45 **	0.40 **	0.41 *	0.38 *	0.42 **	−0.12 ns	0.19 ns
EH		0.85 **	0.53 **	0.54 **	0.58 **	0.52 **	0.62 **	0.52 **	−0.38 **	0.14 ns
NL			0.61 **	0.61 **	0.66 **	0.67 **	0.74 **	0.66 **	−0.39 **	0.18 ns
EL				0.59 **	0.77 **	0.54 **	0.65 **	0.55 **	−0.18 ns	0.24 ns
NRE					0.64 **	0.56 **	0.67 **	0.58 **	−0.09 ns	0.10 ns
NGE						0.59 **	0.63 **	0.59 **	−0.18 ns	0.33 **
GWE							0.66 **	0.91 **	0.30 *	0.29 *
TGW								0.67 **	−0.22 ns	0.29 *
GY									0.31*	0.30 *
RUE										0.17 ns

PH—plant height; EH—ear height; NL—number of leaves per plant; EL—ear length; NRE—number of rows per ear; NGE—number of grains per ear; GWE—grain weight per ear; TGW—1000-grain weight; GY—grain yield; RUE—rain use efficiency; NPFP—N partial factor productivity; **—significant at 1% level of probability; *—significant at 5% level of probability; and ns—not significant.

.

The number of leaves per plant showed a strong positive correlation with ear height (r = 0.85 **) and a high correlation with 1000-grain weight (r = 0.74 **). Similarly, ear length showed a high positive correlation with the number of grains per ear (r = 0.77 **). The NPFP showed a weak, significant positive correlation with the number of grains per ear (r = 0.33 **), the grain weight per ear (r = 0.29 *), and the 1000-grain weight (r = 0.29 **).

4. Discussion

4.1. Year Impact on Morphological and Yield Component Traits, Yield, Rain Use Efficiency, and N Partial Factor Productivity

Our results showed a low CV for plant height, number of leaves per plant, and number of rows per ear; a medium CV for ear height, ear length, number of grains per ear, grain weight per ear, and 1000-grain weight and a high CV for grain yield, rain use efficiency (RUE), and N partial factor productivity (NPFP), as indicated by Pimentel–Gomes [24]. A reasonable coefficient of variation for morphological traits, ear-related traits, and grain yield suggests the experiment’s high level of precision.

It is estimated that 80% of the maize of worldwide arable land is grown under rainfed conditions [25]. Its productivity is influenced by numerous factors such as genetics; temperature; rainfall; physical, chemical, and biological soil properties; and agronomic practices. Maize cultivation in Serbia and neighboring countries depends primarily on rainfall, which is often irregular or unevenly distributed. The present study revealed a significant influence of two contrasting years regarding climatic parameters on morphological and yield component traits, yield, RUE, and NPFP. The two years differed in the amount and distribution of monthly rainfall and temperatures during the maize growing season. Specifically, total seasonal rainfall was 1.6 times higher in the second year than in the first year, resulting in higher values of all parameters except RUE. In the first year, the main cause of yield losses was long-term drought stress during the stem elongation (June) and grain filling (August–September) stages. In the stem elongation phase (second half of June), high temperatures combined with water deficiency reduced stem cell elongation, resulting in shorter internode lengths and reduced plant height. Further, prolonged water stress in August and September negatively affected several yield-related traits, including the number of grains per ear, grain weight per ear, and 1000-grain weight, which ultimately led to lower grain yield. These traits are crucial for grain yield potential and exhibit a high correlation with final grain yield. In August of the same year, water stress during the grain filling stage shortened this stage and reduced grain weight. Drought stress at this stage leads to daily yield losses of 3–5.8%, while extreme drought stress leads to losses of 20–30% [26]. The lower grain weight after flowering can be attributed to a reduced transfer of photosynthetic assimilates to the grains. Similarly, Sah et al. [27] indicated that water deficit stress in the pre-flowering and grain-filling stages decreased morphological traits, ear length, ear width, number of ears per plant, number of grains per row, number of grain rows per ear, and grain yield. In our findings, RUE was higher, while NPFP was lower under unfavorable climatic conditions, aligning with results observed in previous research [28,29]. In drier climates, RUE tends to increase while NPFP decreases, indicating larger rainfall efficiency but lower nitrogen productivity.

4.2. Hybrid Impact on Morphological and Yield Components Traits, Yield, Rain Use Efficiency, and N Partial Factor Productivity

The choice of a proper maize hybrid is an important factor for high grain production and should be adapted to the respective cultivation area together with the application of adequate agricultural practices. Today, hybrids have a high genetic yield potential. Due to their remarkable phenotypic plasticity, the hybrids from the FAO600 group are the most productive and adapted to the production conditions, suitable for grain and forage production [30,31]. The two divergent late-maturing hybrids (NS 6030 and ZP 666) used in the present study are highly adaptive to the climate and soil conditions of southeastern Europe and are grown in lowland regions and river valleys at altitudes of up to 300 m above sea level [32]. The hybrids have delayed leaf senescence, stay-green traits, and are tolerant to drought. For the tested maize hybrids, most of the studied parameters displayed differences. The hybrid ZP 666 had significantly higher plant height, ear length, number of rows per ear, number of grains per ear, grain weight per ear, grain yield, RUE, and NPFP than the hybrid NS 6030. It indicated the existence of inter-varietal differences that can be attributed to genetic divergence, i.e., background [33]. On the other hand, ear height, number of leaves, and 1000-grain weight showed no significant differences between hybrids. In both hybrids, the ears were at approximately the same height within the crop. Regarding NPFP, it is necessary for hybrids to have a higher value, as it is associated with a greater photosynthetic capacity, which contributes to a higher accumulation of dry biomass and a higher grain yield [34]. In addition, genotypes with high NPFP achieve higher yields with low soil N content and lower N fertilizer application [35,36]. Both hybrids exhibit a higher NPFP compared to the average NPFP in China (35 kg grain kg fertilizer N⁻¹) and in agriculturally developed countries for maize production (58 kg grain kg fertilizer N⁻¹), as reported by Wang and Mi [37]. Moreover, the selection of hybrids with high NPFP is one of the ways to reduce the production costs of many crops [38].

4.3. N Rate Impact on Morphological and Yield Components Traits, Yield, Rain Use Efficiency, and N Partial Factor Productivity

An optimal nitrogen (N) fertilization rate maximizes crop production while conserving natural resources [39]. Consequently, it is essential to apply N at a rate that aligns with plant requirements, taking into account various factors that influence N utilization, such as soil properties, climatic conditions, and management practices. Our results showed that all investigated traits, except NPFP, increased with increasing N applications. However, the rate of 180 kg N ha⁻¹ did not significantly increase the observed traits compared to 120 kg N ha⁻¹. Hence, this study recommends applying 120 kg N ha⁻¹ for optimal grain yield. The increase in N rates resulted in enhanced values of morphological traits because N positively influences photosynthesis, cell division, and cell expansion, as established by Castro et al. [40] and Safari et al. [41]. The increase in the number of nodes and the length of internodes is associated with higher leaf production [42]. The yield components also increased with enhanced N rates, thereby causing yield improvement. Yield reduction was primarily driven by N reduction due to decreased yield components and NPFP. Interestingly, 1000-grain weight reached higher values at a rate of 60 kg N ha⁻¹ than in the control, suggesting that lower N rates may promote efficient transfer of assimilates from leaves to grains, although this did not translate into higher overall yield compared to higher N rates. The response of maize to the lowest N rate confirms the conclusion that 1000-grain weight is affected by climatic conditions and nutrient availability between the onset of flowering and the beginning of grain formation [43]. In addition, hybrids with delayed leaf senescence show a higher post-silking N accumulation in the grain, which is reflected in higher yields [44]. The present study indicates that increased N application can significantly increase the value of RUE, so the highest RUE was recorded at N rates of 120 and 180 kg ha⁻¹. Conversely, the lowest NPFP was recorded at 180 kg N ha⁻¹. Du et al. [45] and Rawal et al. [46] also found that NPFP declined with increasing N rates due to lower nitrogen utilization by maize. Furthermore, Galindo et al. [47] and Davies et al. [48] showed that the grain yield of maize increased with increasing N rates up to the optimum, supporting the results noticed in this study, while further N increase expressed no effect or was suppressive. This could be related to the increased N availability and accelerated photosynthetic rate leading to higher production of carbohydrates, resulting in better ear performance and consequently to the grain yield [49]. Additionally, several studies have indicated that the N rate is the most important factor affecting yield components and grain yield of maize. In particular, the studies by Imran et al. [50], Biswas and Ma [51], and Karki et al. [52] showed that application of nitrogen at rates of 210, 150–200, and 120 kg N ha⁻¹, respectively, resulted in maximum grain yield and yield components.

4.4. Interaction of Factors Affected Studied Parameters

The interactions of year × hybrid and year × N rate resulted in significant variation in yield component traits. This is of particular importance considering that stress periods occurring at later growth stages of maize can significantly affect these traits. Drought stress impairs the mineralization of N in the soil, the transport of N from the roots to the shoots, and the N metabolism in the plants, which impairs the uptake and utilization of N in the plants [53]. In our case, reduced soil water availability in August and September 2021, which coincided with the grain filling and maturity stages, hindered N mobility in the grains, contributing to lower grain yield, including NPFP, similar to Sinclair and Rufty [54]. In the wet year (2022), the availability of soil moisture promoted better mineralization and mobility of N, resulting in increased N uptake by plants and higher grain yields. Furthermore, the maize hybrids exhibited distinct responses to varying N rates for ear length, number of grains per ear, and 1000-grain weight. Consistent with our findings, Bello et al. [55] reported that the interaction between year and N rate significantly affected grain yield, while the interactions between hybrid and N rate particularly affected plant height, number of grains per ear, 1000-grain weight, and grain yield. Amanullah et al. [56] found a significant interaction between N rates and maize genotypes for the number of grains per ear. The three-way interaction between year, hybrid, and N rate was significant for ear length, number of rows per ear, and NPFP. These findings suggest that optimal N fertilization has the potential to enhance some quantitative traits, even under extreme climatic conditions such as drought. Dragičević et al. [57] also found that high N fertilization led to yield stability of maize under drought stress in a 20-year long-term experiment.

The maize hybrids differed in their drought tolerance depending on the N rate applied. In the dry year 2021, the hybrid ZP666 achieved the highest yield (9550.7 kg ha⁻¹) and RUE (35.1 kg ha⁻¹ mm⁻¹) at 120 kg N ha⁻¹. In contrast, the hybrid NS6030 exhibited greater yield stability at low (0 and 60 kg N ha⁻¹) and extreme N rates (180 kg N ha⁻¹), suggesting its potential suitability for both low-input and high-input of N. These findings suggest that certain hybrids, such as ZP666, can achieve higher yields under drought stress when provided with adequate nitrogen, emphasizing the importance of appropriate hybrid selection and N management under water-limited conditions, consistent with the observations of Zhang et al. [58]. In the wet year 2022, the hybrid ZP666 again achieved the highest yield (11,053.9 kg ha⁻¹) and RUE (24.7 kg ha⁻¹ mm⁻¹) at 120 kg N ha⁻¹, while the hybrid NS6030 (10,551.4 kg ha⁻¹) achieved the highest RUE (23.6 kg ha⁻¹ mm⁻¹) at the highest N rate. Overall, these results underline the importance of tailored hybrid choice and N management strategies to optimize maize productivity in different environmental scenarios.

4.5. PCA and Correlation Among Parameters

PCA may allow for greater flexibility in determining the N rates that are optimal for achieving high grain yield and, accordingly, the component traits that primarily contribute to higher yield potential. Correspondingly, the application of 120 kg N ha⁻¹ could significantly affect key maize traits, including the number of rows per ear, grain weight per ear, 1000-grain weight, and grain yield.

The correlation between the agronomic traits of maize showed a significant positive relationship between grain yield and yield-related traits. Grain weight per ear and 1000-grain weight had the greatest influence on grain yield compared to other yield components, which emphasizes the importance of sufficient grain filling and is consistent with the results of Ali et al. [59]. Therefore, the improvement of yield component traits is crucial for maximizing grain yield. In addition, morphological traits showed moderate correlation with grain yield, which is consistent with the observations of Mousavi and Nagy [60], suggesting that plant height is not a major determinant of productivity, as modern hybrids tend to have a shorter stature.

5. Conclusions

To enhance crop productivity, it is essential to implement effective soil and crop management practices. Genetic, environmental, and agronomic factors determine crop yield formation. So, maize production is significantly impacted by climatic conditions, particularly rainfall during the growing season, the selection of suitable hybrids, and the application of N fertilizer. Our results indicated that applying 120 kg N per hectare is optimal for enhancing maize yield in semi-arid regions. This nitrogen input improves key yield components, resulting in a notable increase in yield. However, NS6030 showed greater yield stability at low and high N inputs. This indicates a trade-off between the performance and adaptability of the hybrid. In general, the data show that the combination of an optimal N rate and the choice of a hybrid that is more efficient in N utilization can be useful tools to improve the agronomic parameters of maize grain yield while ensuring N savings and protection of the environment from N pollution. Therefore, recommendations should consider both the average performance and yield stability of maize hybrids, depending on the specific production context, including agroecological conditions, resource availability, technological level of the cropping system, and overall production objectives.