Gene Effect of Morphophysiological Traits in Popcorn (Zea mays L. var. everta) Grown Under Contrasting Water Regimes

Abstract

To propose breeding strategies for drought conditions, we investigated gene expression associated with morphophysiological traits in four S7 popcorn (Zea mays var. everta) inbred lines using a partial diallel cross design with two testers. We evaluated morphological traits (plant height; the dry mass of stems, leaves, and reproductive organs; and root weight density (RWD) across five soil sections), water status indicators (leaf water content, cumulative evapotranspiration, agronomic water use efficiency, and carbon isotope signatures), anatomical traits (stomatal number and index), and leaf pigments. Significant variations were observed between lines and hybrids for plant height, shoot biomass traits, water status indicators, and RWD across all soil sections, particularly under water deficit conditions. Overall, the inbred lines were more adversely affected by drought than the hybrids. Dominance gene effects played a significant role in increasing anthocyanin content, cumulative evapotranspiration, stable carbon isotope signatures, and RWD in most soil sections. The superior water utilization observed in hybrids compared to inbred lines suggests that exploiting heterosis is likely the most effective strategy for developing drought-resilient popcorn plants.

1. Introduction

Drought is a phenomenon that adversely impacts global food security, contributing to malnutrition and hunger [1,2]. It generally arises from insufficient rainfall and disturbances in the hydrological cycle, impacting various crops, including popcorn [3,4,5]. The situation has been aggravated by global warming [6] and increasing food demands due to population growth [7].

In efforts to mitigate the adverse effects of drought, research focusing on popcorn—a crop that contributes approximately 1 billion dollars annually to the market in the USA—has been undertaken. This research aims to understand the mechanisms that confer tolerance to water deficits, identify traits suitable for indirect selection, and indicate superior genotypes that are less impacted by soil water scarcity [3,4,8,9,10,11,12]. Generally, a water deficit occurs when the soil water content diminishes to a level that hampers water absorption by the roots, leading to a disparity between water conservation by the plant and the high evaporative demand, thereby inducing changes in plant behavior. The irreversibility of water deficit effects is dependent upon the duration and intensity of occurrence, the phenological stage of the crop at the onset of stress, and, most importantly, the genetic potential for responding to this abiotic factor [13,14,15,16].

In maize cultivation, the critical period for water deficit spans from the pre-flowering phase until the grain-filling stage [1]. During this phase, soil water scarcity can compromise pollen viability and the initiation of grain filling, resulting in diminished productivity, particularly in terms of the number of grains per ear [10,13]. However, certain plants can activate mechanisms that enable adaptive responses, enhancing internal water transport capacity and storage, thus rendering them more tolerant or efficient in water usage. Such adaptive responses may include stomatal closure, which reduces transpiration and water loss [14,17,18], and modifications in root architecture, such as increased lateral roots and root length, to facilitate the capture of water and nutrients from deeper soil layers [19,20].

Understanding the genetic mechanisms associated with traits that enhance productivity under drought conditions presents opportunities for increasing production potential, with the goal of developing cultivars that are more tolerant and/or efficient in water usage. In this context, knowledge of gene actions and their estimates of combining ability is invaluable for devising breeding programs that more effectively attain gains through selection [21,22]. One method for estimating combining ability involves the use of the partial diallel system, which entails crossing two groups of parents with complementary traits of interest [22,23,24,25].

Therefore, this study performed a partial diallel system among popcorn lines pre-selected for popping expansion and grain yield under drought conditions. The aim is to investigate growth, water status, stable carbon isotope composition, leaf pigments, and root density differences to understand the genetic mechanisms controlling these traits under contrasting water conditions and to propose breeding strategies to develop cultivars with drought resilience.

2. Materials and Methods

2.1. Genotypes and Experimental Conditions

Four S₇ inbred lines of popcorn (Zea mays L. var. everta), derived from the cultivar UENF 14 (open-pollinated variety), were selected as female parents for crosses in a partial diallel scheme aimed at evaluating performance under contrasting water regimes. These lines, namely L220, L292, L383, and L688, were chosen from a pool of 50 lines tested in field conditions under low water availability, exhibiting popping expansion greater than 30 g mL⁻¹ [26]. Two S₇ lines, L61 from the “BRS-Ângela” population and L76 from the “Viçosa” population, served as the male parents. L61 is characterized by its low general combining ability for grain yield under water stress conditions, while L76 is recognized for its high combining ability for the same trait under similar conditions [27]. The resulting hybrids included L220 × L61, L220 × L76, L292 × L61, L292 × L76, L383 × L61, L383 × L76, L688 × L61, and L688 × L76, following the female (♀) × male (♂) parentage pattern.

The study was conducted in a greenhouse at the Research Support Unit (UAP) of the Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF) in a completely randomized block design with three replicates per water regime (WR). The WRs were defined as follows: the first WR, termed WW (well-watered), was maintained at 100% field capacity, and the second WR, termed WS (water-stressed), was maintained at 45% field capacity.

The plants were grown in PVC tubes 10 cm in diameter and 150 cm in length, split longitudinally into two halves, and sealed with adhesive tape along the vertical and horizontal axes. To manage excess water percolation during the maintenance of the WRs and to prevent substrate loss, a 10 cm-diameter vessel with perforations was placed at the base of each tube. The vessel was attached to the tube using wires threaded through holes at both ends. Six seeds from each genotype were initially sown per tube, with thinning performed after 21 days to leave three plants per tube and a second thinning 10 days later to leave one plant per tube. The spacing was set at 25 cm within rows and 94 cm between rows, yielding a density of approximately 42,553 plants ha⁻¹, mirroring field conditions. Plants were grown under shelter from the rain to regulate water availability.

Water capacity for each tube was determined pre-sowing by weighing the tube, then adding a substrate mix of 80% perlite and 20% peat, followed by thorough irrigation. After draining the excess water for 72 h, the tubes were reweighed to calculate their total capacity (TC—100%), defined by the weight difference between the tube holding a wet substrate (post-drainage) and the tube with a dry substrate (pre-saturation). The average amount of water added to each tube was 2.27 L.

For the WW regime, the tubes were kept at full capacity until the final assessments. The tubes were weighed every 2–3 days before irrigation, and water was added to restore them to full capacity. In the WS regime, irrigation was reduced 15 days post-emergence, allowing water levels in the tubes to decrease gradually based on plant consumption until reaching 45% capacity, where it was maintained until harvest. This approach ensured a uniform decrease in water capacity across genotypes, as plants with higher water consumption were irrigated precisely to match the capacity of those consuming less water.

Nutrient provision was managed through irrigation with the Hoagland and Arnon [28] solution, adjusted according to plant needs and the imposed water regime throughout the experiment.

2.2. Morphological Traits

Plant height (PH) was measured in centimeters (cm) from the tube’s surface to the last fully developed leaf using a tape measure. Soon after, the plants were dissected into leaves, stems, and reproductive organs, which were then enclosed in paper envelopes and dried in an oven at 70 °C until a constant weight was achieved. This process allowed for the determination of the dry weight of leaves (LDMs), stems (SDMs), and reproductive organs (i.e., ears and tassels; ODM), measured in grams.

2.3. Leaf Pigments

Leaf pigments were measured one day prior to harvest. The concentrations of chlorophyll (CHL), flavonoids (FLAVs), and anthocyanins (ANTHs) were quantified on the middle section of the last fully developed leaf using a portable Dualex^® meter (FORCE-A, Orsay, France).

2.4. Stomatal Density and Index

Stomatal density and index were evaluated on the adaxial and abaxial surfaces of the middle third of the last fully developed leaf, between the central vein and the leaf edge. The area was coated with nail polish and left to dry for 10 min, and the resulting film was peeled off using adhesive tape and placed on a glass coverslip. Stomata (s) and epidermal cells (e) were counted under a microscope at 40× magnification in three distinct fields per leaf replicate (adaxial and abaxial). This method was adapted from the technique described by Radoglou and Jarvis [29].

2.5. Plant Cumulative Evapotranspiration and Agronomic Water Use Efficiency

The total water transpired by each plant, or cumulative transpiration (ET, in dm³ plant⁻¹), was monitored throughout the growth cycle. Prior to irrigation, each tube was weighed, and the top surface was covered with plastic to prevent direct evaporation from the substrate surface. Additionally, the agronomic water use efficiency (WUE, in g kg⁻¹) was determined based on the total shoot biomass (TSB) (leaves, stems, and reproductive organs) and ET, using the following formula: ${WUE}_{ Agro}={\displaystyle \frac{TSB}{ET}}$.

2.6. Leaf Relative Water Content

Before harvest, fresh leaf discs (1.65 cm in diameter) were taken from the most recently developed leaf of each plant and immediately weighed to obtain fresh weight (FW). The discs were then soaked in distilled water for 12 h in a refrigerator at 4 °C in a dark environment. Post-soaking, the discs were gently dried with a paper towel, reweighed to ascertain the turgid weight (TW), and subsequently dried in an oven at 70 °C for 72 h to determine the dry weight (DW). The relative water content (RWC, %) was calculated as follows: $RWC=100\times {\displaystyle \frac{(FW-DW)}{(TW-DW)}}$.

Using the same leaf discs, with a leaf area (LA) of 2.1282 cm², the specific leaf area (SLA, cm² g⁻¹) was estimated with the following equation: $SLA={\displaystyle \frac{LA}{DW}}$.

2.7. Carbon Isotope Signature

To assess the stable carbon isotope (¹³C/¹²C ratio), together with total nitrogen content, samples were collected from the last developed leaf of all plants under both WRs. Approximately 10 mg of dry leaf matter from each plant, alongside the reference materials, was encapsulated in silver capsules [30]. The carbon isotope composition was measured at the Environmental Sciences Laboratory (LCA) of the Center for Biosciences and Biotechnology (CBB) at UENF, using a Flash 2000 Organic Elemental Analyzer (Thermo Scientific, Waltham, MA, EUA), connected to a Conflo IV interface and a Delta V Advantage Isotope Ratio Mass Spectrometer (Thermo Scientific). The stable carbon isotope was determined by an in-line system consisting of a double oven containing an oxidation column at 1020 °C and a reduction column at 650 °C. The isotopic ratio was calculated as follows: ${\delta }^{C}E ‰=[\left(Rsamples/Rstandard\left)\right]-1\right]\times 1000 (‰)$, where R represents the ratio of the heaviest to the lightest isotope (¹³C/¹²C). The standard for carbon is the Pee Dee Belemnite limestone (PDB), assigned an ${\delta }^{C}E$ value of 0‰. The precision of triplicate sample analyses was ±0.1‰. The samples were calibrated against analytical carbon dioxide 5.0 gasses supplied by White Martins and compared to urea isotopic standards from IVA-Meerbusch-Germany [30,31,32]. The total nitrogen content was simultaneously determined by the elemental analyzer coupled to the IRMS, which quantified the nitrogen present in the leaf samples based on combustion products, offering accurate results for both variables of interest.

2.8. Root Traits

At the time of harvest, the PVC tubes were opened, and roots were segmented into five equal parts from the top surface of the tubes to the lower end: 0–30 cm (a), 30–60 cm (b), 60–90 cm (c), 90–120 cm (d), and 120–150 cm (e). Each section was washed in running water, wrapped, packed in a paper bag, and dried at 60 °C, and the dry weight of the roots was recorded separately for each section. The root weight density for each soil layer (RWDsec, in g m⁻³) was calculated as per Elazab et al. [33]: ${RWD}_{sec}={RB}_{sec}/\pi \times R^2\times L$, where RB_sec is the dry root biomass per soil layer (g), R is the tube radius (0.07 m), and L is the length of the tube segment (0.30 m).

2.9. Statistical Analysis

Using GENES software version 1990.2023.66 [34], individual analysis of variance was conducted for each WR, along with a combined analysis to assess the genotype × WR interaction for each trait. The individual analysis was based on the genetic-statistical model: $Y_{ij}=\mu +G_i+B_j+{\epsilon }_{ij}$, where $Y_{ijk}$ represents the measurement of genotype i under the water regime j and block k; $\mu$ denotes the overall trait mean; $G_i$ is the fixed effect of genotype i; $B_j$ represents the random effect of block j; and ${\epsilon }_{ij}$ is the experimental error.

Subsequently, separate analyses were performed to evaluate the effects (contrasts) of lines, testers, and hybrids on each trait, utilizing the SAS software, version 9.0, Copyright 2002 SAS Institute Inc., Cary, NC 27513, USA. ALL Rights Reserved [35]. The contrasts examined included the following: I, representing differences between lines; II, differences between testers; III, differences between hybrids; and IV, the interaction between lines and hybrids. The combined analysis for WRs employed the following model: $Y_{ijk}=\mu +G_i+{B/E}_{jk}+E_j+{GE}_{ij}+{\epsilon }_{ijk}$, where $Y_{ijk}$ is the value observed for genotype i in water regime j and block k; $\mu$ is the overall mean; $G_i$ is the fixed effect of genotype i; ${B/E}_{jk}$ is the random effect of block k within water regime j; $E_j$ is the fixed effect of water regime j; ${GE}_{ij}$ is the fixed interaction effect between genotype i and water regime j; and ${\epsilon }_{ijk}$ represents the random error, associated with observation $Y_{ijk},$ with the NID distribution (0, σ²).

2.10. Statistical Analysis of the Partial Diallel

For the statistical analysis of the partial diallel, the method proposed by Griffing (1956) [36] and adapted by Miranda Filho et al. (1987) [37] was followed. This involved conducting variance analyses for the partial diallel arrangement under each WR using GENES software. The following model was employed: $Y_{ij}=\mu +g_i+g_j+s_{ij}+{\varepsilon }_{ij}$, where $Y_{ij}$ is the mean value of the hybrid combination between tester i from group 1 and S₇ line j from group 2; $\mu$ is the overall mean; $g_i$ is the general combining ability effect of parent i in group 1; $g_j$ is the general combining ability effect of parent j in group 2; $s_{ij}$ is the specific combining ability effect of the hybrids formed; and ${\varepsilon }_{ij}$ is the experimental error mean.

3. Results

3.1. Impact of Water Restriction on Growth Traits and Leaf Pigments

In the combined analysis, all traits differed significantly in response to the ‘genotype’ (G) as the source of variation. For the source variation ‘water regime’ (WR), all traits except flavonoid content (FLAV) were significant. The genotype × water regime (GWR) interaction showed significance only for specific leaf areas (SLAs). In the individual analysis, irrespective of WR, growth traits and leaf pigments displayed statistical differences in the IV contrast, particularly between lines and hybrids, with exceptions noted for FLAV and SLA under WW conditions (

Table 1. Combined and individual analyses of variance displaying mean values and standard deviations of growth measurements and leaf pigments in popcorn lines, testers, and hybrids evaluated in contrasting environments regarding water availability.

Traits	Combined Analysis			Water Deficit (45%)							Full Irrigation (100%)
				Lines		Testers		Hybrids		C	Lines		Testers		Hybrids		C
	G	WR	G × WR	$\overline{\mathit{x}}$ I		$\overline{\mathit{x}}$ II		$\overline{\mathit{x}}$ III		IV	$\overline{\mathit{x}}$ I		$\overline{\mathit{x}}$ II		$\overline{\mathit{x}}$ III		IV
PH	**	**	ns	0.70	±0.33 **	0.35	±0.23 ns	1.01	±0.39 ns	**	1.31	±0.37 **	0.84	±0.35 ns	1.39	±0.29 **	**
LDM	**	**	ns	5.12	±0.73 **	2.52	±0.91 ns	8.57	±1.15 **	**	8.98	±1.28 *	5.65	±0.54 ns	11.20	±1.32 ns	**
SDM	**	**	ns	5.51	±0.86 **	1.43	±0.31 **	9.06	±1.43 **	**	12.76	±1.45 **	5.94	±0.69 ns	14.73	±1.77 ns	**
ODM	**	**	ns	5.86	±1.67 **	0.07	±0.42 ns	13.71	±2.03 ns	**	16.06	±1.91 *	7.80	±1.16 ns	24.10	±2.40 ns	**
CHL	**	*	ns	25.85	±1.82 **	23.63	±1.27 ns	41.37	±1.97 *	**	41.57	±1.50 **	37.04	±1.66 ns	46.45	±1.98 ns	**
FLAV	**	ns	ns	0.57	±0.32 ns	0.62	±0.26 ns	0.63	±0.21 **	*	0.63	±0.26 *	0.66	±0.20 ns	0.65	±0.22 **	ns
ANTH	**	*	ns	0.20	±0.17 **	0.22	±0.10 *	0.14	±0.21 ns	**	0.15	±0.08 **	0.17	±0.14 ns	0.13	±0.14 ns	**
SLA	**	*	**	211.74	±4.07 **	226.87	±5.04 ns	183.41	±3.78 ns	**	172.95	±3.32 *	184.26	±4.61 ns	176.18	±0.56 *	ns

Values in the $\overline{\mathrm{x}}$ columns represent the means ± standard deviations of the evaluated genotypes. Statistical differences are represented by I = between lines, II = between testers, and III = between hybrids within each water regime (WR). IV = The mean contrast between lines and hybrids. Combined analysis refers to the interaction between the genotype (G), water regime (WR), and genotype × water regime (G × WR) under water deficit (WS = 45% of tube capacity) and full irrigation (WW = 100% of tube capacity). PH: plant height (cm); LDM: leaf dry matter (g); SDM: stem dry matter (g); ODM: reproductive organs dry matter (g); CHL: chlorophyll content (µg/cm²); FLAV: flavonoid content (μmol g⁻¹); ANTH: anthocyanin content (μmol g⁻¹); SLA: specific leaf area (cm² g⁻¹). According to the decomposition of the effects of lines, testers, and hybrids separately, ns = not significant; * = significant at p < 0.05; and ** = significant at p < 0.01.

).

Water stress led to notable reductions (>20%) in plant height (PH) and the dry matter content in the leaves (LDMs), stems (SDMs), and reproductive organs (ODMs) for both lines and hybrids. The impact was more pronounced in lines, with reductions of 49.40%, 46.00%, 60.40%, and 70.50% for these traits, respectively. In hybrids, the reductions were 27.50%, 23.50%, 38.50%, and 43.10%, in the same order. Only lines experienced a significant decrease in the chlorophyll index (CHL), exceeding 37.30%. Significant increases (> 20%) were observed predominantly in lines for anthocyanin content (ANTH) and SLA, with increases of 40.00% and 22.70%, respectively (Figure 1).

3.2. Impact of Water Restriction on Stomatal Index and Density, Cumulative Evapotranspiration, Agronomic Water Use Efficiency, and Stable Carbon Isotope Signatures

Significant effects due to G as a source of variation were noted for most traits, except for the adaxial (DSI) and abaxial (BSI) stomatal indices. The water regime significantly affected cumulative evapotranspiration (ET), agronomic water use efficiency (WUE), carbon isotopic signature (δ¹³C), and total nitrogen (N_Total). Significant alterations were also detected in WUE and N_Total in response to the G × WR interaction. In the WS regime, except for BSI, statistical differences were observed for the IV contrast concerning DSI, adaxial (DSD) and abaxial (BSD) stomatal density, ET, the leaf relative water content (RWC), WUE, δ¹³C, and N_Total. Under WW conditions, the ET, WUE, and δ¹³C traits showed statistical differences for the IV contrast (

Table 2. Combined and individual analysis of variance displaying mean values and standard deviation for stomatal index and density, cumulative evapotranspiration, agronomic water use efficiency, and stable carbon isotope signatures of popcorn testers and hybrids evaluated in contrasting environments in terms of water availability.

Traits	Combined Analysis			Water Deficit (45%)							Full Irrigation (100%)
				Line		Testers		Hybrids		C	Line		Testers		Hybrids		C
	G	WR	G × WR	$\overline{\mathit{x}}$	I	$\overline{\mathit{x}}$	II	$\overline{\mathit{x}}$	III	IV	$\overline{\mathit{x}}$	I	$\overline{\mathit{x}}$	II	$\overline{\mathit{x}}$	III	IV
DSD	**	ns	ns	76.02	±3.87 ns	84.61	±4.52 ns	62.87	±3.33 ns	**	62.04	±3.46 ns	68.35	±1.97 *	59.30	±3.21 ns	ns
BSD	**	ns	ns	103.07	±4.18 ns	99.42	±4.47 ns	86.21	±3.35 ns	**	87.54	±4.04 ns	94.30	±1.54 ns	32.45	±3.80 ns	ns
DSI	ns	ns	ns	22.81	±2.23 ns	23.86	±1.18 ns	19.71	±1.85 ns	**	19.88	±1.92 ns	20.86	±0.84 *	35.87	±2.54 ns	ns
BSI	ns	ns	ns	28.14	±1.93 ns	27.76	±2.17 ns	26.05	±1.81 ns	ns	26.55	±1.83*	26.06	±1.00 ns	41.49	±2.77 ns	ns
ET	**	**	ns	3.33	±0.70 **	1.96	±0.93 ns	6.03	±1.14 ns	**	9.58	±0.85**	6.73	±0.85 ns	45.83	±1.25 ns	**
RWC	**	ns	ns	85.76	±2.35 ns	86.91	±1.26 ns	89.56	±2.03 ns	*	85.82	±1.83 ns	87.89	±1.39 ns	25.44	±2.11 ns	ns
WUE	**	**	**	4.54	±0.83 **	2.33	±1.24 ns	5.18	±0.58 ns	**	3.87	±0.71 ns	2.86	±0.54 ns	36.88	±0.14 ns	**
δ13C	**	**	ns	−14.24	±0.49 ns	−14.66	±0.59 ns	−14.13	±0.47 ns	**	−14.00	±0.58 ns	−13.83	±0.30 ns	23.16	±0.45 ns	*
Ntotal dm (%)	**	**	**	2.59	±0.46 *	2.48	±0.42 ns	3.18	±0.51 **	**	3.23	±0.52 ns	3.58	±0.21 *	3.45	±0.67 *	ns

Values in the $\overline{x}$ columns represent the means ± standard deviations of the evaluated genotypes. Statistical differences are represented by I = between lines, II = between testers, and III = between hybrids within each water regime (WR). IV = The mean contrast between lines and hybrids. Combined analysis refers to the interaction between the genotype (G), water regime (WR), and genotype × water regime (G × WR) under water deficit (WS = 45% of tube capacity) and full irrigation (WW = 100% of tube capacity). DSD: adaxial stomatal density (mm⁻²); BSD: abaxial stomatal density (mm⁻²); DSI: adaxial stomatal index (%); BSI: abaxial stomatal index (%); ET: cumulative evapotranspiration (dm³ plant⁻¹); RWC: leaf relative water content (%); WUE: agronomic water use efficiency (g kg⁻¹); δ¹³C: stable carbon isotope signature (‰); N_Total: total nitrogen content (_dm %). According to the decomposition of the effects of lines, testers, and hybrids separately, ns = not significant; * = significant at p < 0.05; and ** = significant at p < 0.01.

).

Compared to hybrids, lines exhibited greater reductions in ET and N_Total, with decreases of 66.70% and 23.70%, respectively. An increase in ET was more pronounced in hybrids, reaching 51.90% (Figure 2).

3.3. Impact of Water Restriction on Root Traits

In the combined analysis, significant differences were observed for all root weight density (RWD) sections in response to G as a source of variation. For WR variations, significant differences were noted in RWD (a, b, c, and e). However, no significant differences were found for the G × WR interaction. Independent of WR, RWD decreased with increasing soil depth. Water restriction had a more pronounced effect on RWD in lines compared to hybrids. In both WW and WS regimes, RWD exhibited statistical differences in all soil sections (a, b, c, d, and e) for contrast IV (Table 3).

Table 3. Combined and individual analysis of variance displaying mean values and standard deviation for root weight density; a-b-c-d-e refers to the depth of each soil section, i.e., 0–30 cm (a); 30–60 cm (b); 60–90 cm (c); 90–120 cm (d); and 120–150 cm (e) in popcorn testers and hybrids evaluated in contrasting environments in terms of water availability.

Traits	Combined Analysis			Water Deficit (45%)						Full Irrigation (100%)
				Line		Testers		Hybrids		C	Line		Testers		Hybrids		C
	G	WR	G × WR	$\overline{\mathit{x}}$	I	$\overline{\mathit{x}}$	II	$\overline{\mathit{x}}$	III	IV	$\overline{\mathit{x}}$	I	$\overline{\mathit{x}}$	II	$\overline{\mathit{x}}$	III	IV
RWDa	**	*	ns	713.13	±14.75 *	491.44	±11.38 ns	1110.60	±16.70 ns	**	968.01	±10.42 **	871.27	±14.47 *	1262.33	±18.92 ns	**
RWDb	**	*	ns	212.42	±8.24 **	66.07	±4.11 ns	483.54	±11.09 *	**	330.84	±9.59 ns	224.63	±10.03 ns	502.18	±11.82 ns	**
RWDc	**	*	ns	106.72	±7.54 ns	27.00	±2.76 ns	244.30	±7.50 **	**	134.61	±9.46 ns	44.23	±4.46 ns	303.27	±9.06 *	**
RWDd	**	ns	ns	57.33	±7.68 ns	4.39	±3.28 ns	125.44	±8.18 ns	**	53.75	±7.38 *	6.44	±3.97 ns	125.21	±8.67 *	**
RWDe	*	**	ns	32.17	±5.59 ns	0.00	±0.00 ns	67.15	±7.34 ns	**	0.89	±1.75 ns	0.00	±0.00 ns	29.74	±6.57 *	**

Values in the $\overline{x}$ columns represent the means ± standard deviations of the evaluated genotypes. Statistical differences are represented by I = between lines, II = between testers, and III = between hybrids within each water regime (WR). IV = The mean contrast between lines and hybrids. Combined analysis refers to the interaction between genotype (G), water regime (WR), and genotype × water regime (G × WR) under water deficit (WS = 45% of tube capacity) and full irrigation (WW = 100% of tube capacity). RWD: root weight density; a-b-c-d-e refers to the depth of each soil section, i.e., 0–30 cm (a); 30–60 cm (b); 60–90 cm (c); 90–120 cm (d); and 120–150 cm (e). According to the decomposition of the effects of lines, testers, and hybrids separately, ns = not significant; * = p < 0.05; and ** = p < 0.01. Compared to hybrids, lines experienced more substantial reductions in RWDa, RWDb, and RWDc, with decreases of 68.00%, 45.00%, and 23.00%, respectively (Figure 3).

Table 3. Combined and individual analysis of variance displaying mean values and standard deviation for root weight density; a-b-c-d-e refers to the depth of each soil section, i.e., 0–30 cm (a); 30–60 cm (b); 60–90 cm (c); 90–120 cm (d); and 120–150 cm (e) in popcorn testers and hybrids evaluated in contrasting environments in terms of water availability.

Traits	Combined Analysis			Water Deficit (45%)						Full Irrigation (100%)
				Line		Testers		Hybrids		C	Line		Testers		Hybrids		C
	G	WR	G × WR	$\overline{\mathit{x}}$	I	$\overline{\mathit{x}}$	II	$\overline{\mathit{x}}$	III	IV	$\overline{\mathit{x}}$	I	$\overline{\mathit{x}}$	II	$\overline{\mathit{x}}$	III	IV
RWDa	**	*	ns	713.13	±14.75 *	491.44	±11.38 ns	1110.60	±16.70 ns	**	968.01	±10.42 **	871.27	±14.47 *	1262.33	±18.92 ns	**
RWDb	**	*	ns	212.42	±8.24 **	66.07	±4.11 ns	483.54	±11.09 *	**	330.84	±9.59 ns	224.63	±10.03 ns	502.18	±11.82 ns	**
RWDc	**	*	ns	106.72	±7.54 ns	27.00	±2.76 ns	244.30	±7.50 **	**	134.61	±9.46 ns	44.23	±4.46 ns	303.27	±9.06 *	**
RWDd	**	ns	ns	57.33	±7.68 ns	4.39	±3.28 ns	125.44	±8.18 ns	**	53.75	±7.38 *	6.44	±3.97 ns	125.21	±8.67 *	**
RWDe	*	**	ns	32.17	±5.59 ns	0.00	±0.00 ns	67.15	±7.34 ns	**	0.89	±1.75 ns	0.00	±0.00 ns	29.74	±6.57 *	**

Values in the $\overline{x}$ columns represent the means ± standard deviations of the evaluated genotypes. Statistical differences are represented by I = between lines, II = between testers, and III = between hybrids within each water regime (WR). IV = The mean contrast between lines and hybrids. Combined analysis refers to the interaction between genotype (G), water regime (WR), and genotype × water regime (G × WR) under water deficit (WS = 45% of tube capacity) and full irrigation (WW = 100% of tube capacity). RWD: root weight density; a-b-c-d-e refers to the depth of each soil section, i.e., 0–30 cm (a); 30–60 cm (b); 60–90 cm (c); 90–120 cm (d); and 120–150 cm (e). According to the decomposition of the effects of lines, testers, and hybrids separately, ns = not significant; * = p < 0.05; and ** = p < 0.01. Compared to hybrids, lines experienced more substantial reductions in RWDa, RWDb, and RWDc, with decreases of 68.00%, 45.00%, and 23.00%, respectively (Figure 3).

Figure 3. Reductions observed in popcorn lines and hybrids grown under different water regimes (WS: water-stressed; WW: well-watered) for RWD: root weight density. a-b-c-d-e refers to the depth of each soil section, i.e., 0–30 cm (a); 30–60 cm (b); 60–90 cm (c); 90–120 cm (d); and 120–150 cm (e).

Figure 3. Reductions observed in popcorn lines and hybrids grown under different water regimes (WS: water-stressed; WW: well-watered) for RWD: root weight density. a-b-c-d-e refers to the depth of each soil section, i.e., 0–30 cm (a); 30–60 cm (b); 60–90 cm (c); 90–120 cm (d); and 120–150 cm (e).

3.4. Significance and Importance of Mean Squares Associated with General (GCA) and Specific (SCA) Combining Abilities

In the WS regime, the mean square for the general combining ability (GCA) among lines (GCA I) showed significant differences for traits including PH, LDM, SDM, ODM, CHL, ANTH, SLA, ET, WUE, total N_Total, and RWD in sections b and e. For GCA among the testers (GCA II), significant differences were observed for ANTH, DSD, and DSI. The mean square for the specific combining ability (SCA) among hybrids was significant for CHL, ANTH, SLA, ET, WUE, δ¹³C, and RWD in sections b, c, and d. In the WW regime, GCA I was significant for FLAV, SLA, WUE, N_Total, and RWD in section d, while GCA II showed significance for DSD, WUE, and RWD in section a. The SCA I*II contrast revealed significant differences for LDM, SDM, ODM, ET, WUE, and RWD in sections b, c, and d (Figure 4).

4. Discussion

4.1. Impacts of Water Restriction on Growth Traits and Leaf Pigments

Hybrids showed higher dry biomass accumulation, reflected in increased LDM, SDM, ODM, and PH values. This may result from a larger photosynthetic area, enhancing carbon assimilation. Tollenaar et al. [38] suggested that increased dry matter accumulation prior to flowering is attributed to larger leaf sizes (represented by the leaf area), which correlate with higher photosynthetic rates across the entire plant canopy. Kamphorst et al. (2022) [4] reported that popcorn hybrids maintain higher photosynthetic rates under drought conditions, possibly due to fewer but larger epidermal cells in the F1 generation compared to parental lines.

The stem was the non-laminar structure most significantly impacted by water deficit in both lines and hybrids. As a key organ for structural support and water and nutrient transport [39], the stem also stored significant reserves of photoassimilates, vital for translocation to the ear during grain filling, which is a period of high photoassimilate demand. Water scarcity reduces photoassimilation, leading to thinner stems prone to lodging and possibly smaller leaves [39].

In general, the CHL content decreased in both hybrids and lines under reduced water availability, with hybrids consistently showing higher CHL levels than lines, irrespective of WR. Araus et al. [40] observed that chlorophyll content differences amplify during grain filling, with a steady decline from 20 to 25 days post-anthesis under water stress. Lines exhibited more marked reductions in leaf chlorophyll content under these conditions. In contrast, in adult corn plants in field conditions, on a dry-matter basis, it was not possible to detect heterosis effects for traits related to foliar N [40]. Chairi et al. [41] observed no heterosis effects on N absorption in corn seedlings, noting that the lines exhibited higher nutrient levels. This supports Sinha and Khanna’s [42] assertion that heterosis in nutrient absorption appears only in per-plant analyses.

Flavonoid levels were significantly elevated in hybrids under both WRs tested, yet ANTH levels did not differ significantly between lines and hybrids, regardless of WR. These phenolic compounds, produced by plant secondary metabolism, act as antioxidants, osmoregulators, and photoprotective agents, shielding plants from both biotic and abiotic stresses, including water deficit, by filtering ultraviolet rays [43,44,45]. Therefore, higher phenolic compound levels may confer an adaptive edge, particularly under WS conditions.

In the WS regime, SLA was higher regardless of the genotype category, with lines exhibiting the highest values. This suggests that leaves in lines were thinner or less dense [46,47], likely due to diminished cell expansion compared to hybrids. Studies on corn and popcorn by Chairi et al. (2016) [41] and Kamphorst et al. (2022) [4] suggest that growth traits in plants are influenced more by cell size than cell number since, despite higher SLA values in line, hybrids demonstrated superior photosynthetic rates.

4.2. Stomatal Index and Density, Cumulative Evapotranspiration, Agronomic Water Use Efficiency, and Stable Carbon Isotope Signature in an Environment Under Water Restriction and Full Irrigation

Water scarcity induces stomatal closure to mitigate transpiration and minimize water loss, adversely affecting the photosynthetic rate. Stomatal density and index are crucial for determining the maximum CO₂ diffusive conductance to the leaf [48]. Although stomatal traits are significant, this study did not find statistical differences between water treatments or genotype × WR interaction. However, under WS conditions, both adaxial and abaxial stomatal densities, along with the adaxial stomatal index, were lower in hybrids compared to their parental lines.

Under the WS regime, hybrids exhibited a higher leaf relative water content (RWC) compared to lines, indicating that drought-tolerant genotypes tend to maintain elevated RWC levels. This may result from a deeper root system capable of accessing water from lower soil layers or improved osmotic adjustment [49]. In the present study, no notable differences were found between hybrids and parental lines in the WW regime or in the combined analysis across water treatments. Kamphorst et al. (2022) [4] also reported reduced RWC under WS in popcorn genotypes but noted that it was not critical for distinguishing lines from hybrids.

Cumulative evapotranspiration was consistently higher in hybrids than in inbred lines, regardless of WR. Research by Chairi et al. [41] and Kamphorst et al. [4] on the manifestation of heterosis in maize and popcorn hybrids under water deficit conditions also highlighted the superior performance of hybrids, attributed to greater water consumption, biomass accumulation, leaf area, and root system development compared to lines. It is important to note that ET estimation in our study did not account for the growing plant weight, leading to an underestimation of the water required to maintain 100% and 45% tube capacity. This likely impacted ET values for hybrids due to their larger size and weight, potentially influencing WUE measurements, which showed no significant differences between parental lines and hybrids or across WRs.

Regarding stable carbon isotopes (δ¹³C), parental lines exhibited slightly more negative values than their hybrids under water deficits, suggesting more extensive stomatal closure in response to reduced water availability in the tubes. Consistent with the findings from Cabrera-Bosquet et al. (2009) [50], Araus et al. (2010, 2013) [51,52], and Chairi et al. (2016) [41], δ¹³C measurements suggested higher water utilization in hybrids under water stress. Additionally, higher N_Total values in hybrids compared to parental lines support the notion that hybrids were less impacted by water stress and that the F₁ generation exhibited more efficient nitrogen uptake and metabolism in both WW and WS regimes [53,54].

4.3. Root Traits Under the Contrasting Water Regimes Applied

Regardless of the WR, root weight density (RWD) generally decreased with depth, with this reduction being more pronounced in lines compared to hybrids. This observation aligns with the findings by Kamphorst et al. (2022) [4], who studied popcorn parental lines and their hybrids under similar experimental conditions and found that RWD consistently diminished as the depth increased. Roots are crucial for adaptation in drought-affected areas, where a robust root system, particularly deeper roots, is associated with enhanced grain yields [55]. Hybrids exhibited higher RWD values across all soil sections (a, b, c, d, e), suggesting a more developed root system.

The development of the root system in deeper soil layers facilitates efficient water uptake from these lower profiles [56], as demonstrated in the popcorn hybrids of this study. Such a root system likely offers adaptive benefits under field water stress conditions. Ali et al. (2016) [55] proposed that a correlation exists between the biomass of deeper roots (beyond 45 cm) in corn and increased grain yield under field WS conditions, emphasizing the importance of deeper root development for drought resilience.

4.4. Mean Square Implications for Plant Breeding

Understanding how general combining ability (GCA) and specific combining ability (SCA) effects facilitate the development of more effective breeding strategies tailored to the target germplasm can drive genetic improvement in drought-prone environments. In this study, additive effects played a significant role in the evaluated growth and leaf pigment traits, except for CHL, ANTH, and SLA, where dominant gene action was more prominent (Figure 4). This contrasts with the findings for maize and popcorn by Tollenaar et al. (2004) [38] and Kamphorst et al. (2021) [27], respectively, who reported a stronger dominance effect on leaf biomass and pigment traits. Their studies highlighted increased dry matter accumulation before flowering in traits associated with leaf and stem biomass, as well as larger leaf sizes and higher leaf area indices in the F₁ generation, underscoring the potential of heterosis as a breeding strategy.

For traits such as ET, WUE, and δ¹³C, dominance effects were more pronounced (Figure 4). This dominance may account for the observed superior growth and weight of hybrids compared to their parental lines. Chairi et al. (2020) [57] noted that corn hybrids exhibited higher total ET compared to their parents, with a strong correlation to shoot biomass. Additionally, a significant SCA effect for δ¹³C in the WS regime suggested that hybrids were less adversely affected under WS compared to parental lines.

Root system traits have been identified as reliable indicators of agronomic performance in popcorn, showing better adaptation under both fully irrigated and water deficit conditions. Kamphorst et al. (2022) [4] recommend exploiting heterosis to enhance RWD across different water regimes. In the current study, RWD was generally influenced by dominance effects in both WS and WW regimes across most soil sections. Ali et al. (2016) [55] found strong positive correlations between grain yield and root biomass in maize hybrids under both WW and WS conditions. Gao and Lynch (2016) [49] reported that maize genotypes with fewer crown roots exhibited deeper rooting and a 57% yield increase under water deficit. Similarly, El Hassouni et al. (2018) [58] linked a higher wheat grain yield with deeper root systems. Therefore, a more extensive root system under water-limited conditions can help mitigate grain yield losses in crops.

Overall, the expression of mean squares between the evaluated water regimes did not indicate any changes that would alter the dominance of gene effects for the traits studied. This finding aligns with Lima et al. (2019) [10], who investigated the inheritance of economically important traits in popcorn and concluded that genetic effects remained consistent across different water regimes. This suggests that the same breeding strategies could be effective under varying water availability conditions.

5. Conclusions

Despite the challenges posed by water scarcity, hybrids generally exhibit superior performance in terms of shoot biomass accumulation, water status, and root system depth and density, offering them an adaptive edge over their parent lines. The enhanced root architecture of hybrids, characterized by greater density, facilitates more efficient water uptake, supporting improved plant growth, especially under water deficit conditions. This advantage was evident even under optimal irrigation, albeit to a lesser degree. Specifically, under drought stress, the analysis of stable carbon isotopes (δ¹³C) indicated that hybrids have a higher capacity for water utilization.

Given these advantages, incorporating hybrids into popcorn breeding programs emerges as a strategic approach to alleviate the impact of drought stress in the soil.