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Article

Plant Growth Regulators Enhance Maize (Zea mays L.) Yield under High Density by Optimizing Canopy Structure and Delaying Leaf Senescence

1
Jilin Agricultural University, Changchun 130118, China
2
Institute of Agricultural Resources and Environment, Jilin Academy of Agricultural Sciences/Key Laboratory of Crop Eco-Physiology and Farming System in the Northeastern, Ministry of Agriculture and Rural Affairs, Changchun 130033, China
*
Authors to whom correspondence should be addressed.
Agronomy 2024, 14(6), 1262; https://doi.org/10.3390/agronomy14061262
Submission received: 10 May 2024 / Revised: 2 June 2024 / Accepted: 7 June 2024 / Published: 11 June 2024

Abstract

:
Shaping the canopy architecture and delaying leaf senescence in maize are pivotal strategies for extending the crop’s photosynthetic period and improving yield. The application of plant growth regulators (PGRs) is a critical cultivation measure, with the timing of application being of paramount importance. To explore the effects of PGR application time on maize canopy structure, leaf senescence characteristics and yield, a comparative two-year field study was undertaken during the 2019–2020 growing seasons at the Gongzhuling Experimental Station of the Jilin Academy of Agricultural Sciences, utilizing a PGR containing ethephon as the active ingredient. The experiment was structured with two plant densities of 60,000 and 90,000 plants ha−1, and three distinct PGR application protocols: T10 (application of PGR at the 10th leaf stage), T15 (application at the 15th leaf stage), and CK (control group sprayed with water). The result indicated that the yield increased by 5.62% following T15 treatment compared to the CK under high density (90,000 plants ha−1). Furthermore, the kernel per ear and the 1000-kernel weight increased by 3.93% and 5.62% respectively, while the abortion rate decreased. Correlation analysis showed that yield and yield components were correlated with plant morphology, physiology, and aging characteristics under 90,000 plants ha−1. Pollen density was also positively correlated with the top leaf area and the top leaf angle (p < 0.01). Furthermore, relative green leaf area at maturity (RGLAM) showed positive correlations with chlorophyll b, superoxide dismutase activity (SOD), peroxidase activity (POD), catalase activity (CAT), and soluble protein content (p < 0.01), while displaying a negative correlation with malondialdehyde content (MDA) (p < 0.01). Spraying plant growth regulators at the 15-leaf stage under high density can effectively enhance the top canopy structure of the maize and reduce the upper leaf area and angle, increase pollen density, and boost the number of grains. Furthermore, it delayed the senescence of leaves, prolonged the functional period of the leaves, increased kernel weight, optimized light resource utilization, and ultimately enhanced the maize yield.

1. Introduction

Maize, being the cereal crop with the widest planting area and highest yield globally, holds a pivotal position in agricultural production [1,2]. However, due to the limited arable land, enhancing maize yield of the per unit area is crucial for increasing total yield, and increasing planting density serves as a significant approach towards achieving this goal [3,4]. Increased planting density can result in intensified interspecific competition for solar radiation within the maize population, resulting in reduced light interception in the middle canopy (the primary source organ for grain yield formation), unfavorable for enhancing the maize productivity of single plants. This can also impact light distribution and the efficiency of light energy utilization, leading to premature plant senescence, hindering the grain filling process, and potentially causing grain abortion, ultimately reducing the maize yield [5,6,7]. The later stage of maize growth is crucial for increasing yield, but it is often accompanied by leaf senescence, resulting in decreased photosynthetic capacity. This limitation severely hampers the accumulation of photosynthetic products, thus affecting yield. Research indicates that prolonging the effective photosynthetic period of leaves by just 2 days in the later growth stage can increase yield by 11.0%. Therefore, during the grain filling stage, delaying leaf senescence and extending the period of high photosynthetic rates are effective strategies to enhance the production potential of the maize [8,9].
Plant growth substances can be classified into two categories: plant hormones and plant growth regulators. Plant hormones are organic compounds synthesized by plants that have significant effects on the growth and development of plants [10,11]. Research on plant hormones originated in the 1930s with the study of auxin. In the 1950s, the action mechanisms of two more plant hormones, gibberellin and cytokinin, were identified. By the 1960s, abscisic acid and ethylene were also recognized as plant hormones. Presently, there are five established categories of plant hormones: auxins, gibberellins, cytokinins, ethylene, and abscisic acid [12]. Plant growth regulators, synthetic hormones that are as effective or even more effective than natural plant hormones, are rapidly advancing in the pesticide industry. They have the ability to alter plant morphology, improve plant stress resistance, and regulate various stages of plant growth and development. Since the 1970s, extensive research has been conducted in our country on four specific plant growth substances, gibberellins, ethephon, mediamine, and paclobutrazol, with significant success in field production [13,14]. Several reports had shown that jasmonates played an important role in signaling drought-induced antioxidant responses. Jasmonic acid can enhance the antioxidant system of soybean and photosynthesis to alleviate combined heat and drought stress effects [15,16]. Exogenous IAA sprayed on plants during drought or heat stresses mitigated the adverse stress effects on pollen viability, spikelet fertility, and yield components [17]. Foliar gibberellic acid (GA3) application also increased leaf area, leaf fresh weight, leaf dry weight, chlorophyll content, the level of chlorophyll a and b, individual fruit weight, and the number of fertile seeds of the blueberry [18]. A significantly improved ROS plant defense system was noted to increase enzymatic antioxidant activities and yield characteristics due to the exogenous application of ABA under drought stress [19].
Achieving an efficient yield increase is a crucial objective in maize research, and increasing planting density is one of the most direct and effective measures for increasing yield [20]. Maize population yield and leaf area index increase with the increase in planting density. However, when the planting density reaches a certain range, it can cause photosynthetic obstacles and early leaf senescence in maize. Intense competition occurs between plants, and the yield and leaf area index no longer increase [21,22]. Excessive accumulation of reactive oxygen species (ROS) and malondialdehyde (MDA) in the leaves, along with the gradual decrease in the activity of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), accelerates the aging of maize leaves, thereby affecting maize yield. Therefore, exploring agricultural measures that improve photosynthetic efficiency and leaf physiology under high-density planting is of great significance for establishing high-yielding and efficient maize populations and promoting intensive and sustainable agricultural production [23,24]. The recent studies have demonstrated that using plant growth regulators can effectively regulate plant endogenous hormones, enhance physiological metabolism, and improve morphological characteristics of plants [25,26]. By applying plant growth regulators, the canopy structure was optimized, ventilation and light transmittance increased, competition between plants was reduced, and overall photosynthesis improved, leading to higher final yield [27,28]. Different plant growth regulators, application amounts, and application periods can have varying effects on maize growth and development [29,30,31]. Ethephon, also known as 2-chloroethylphosphonic acid, remains stable at pH levels below 4 and can be absorbed by plant leaves. It functions by releasing ethylene within the plant, promoting endogenous ethylene biosynthesis [32,33]. Another plant growth promoter, Acetate (DA-6), discovered in the 1990s, is a substitute for regulators like gibberellins, nitro compounds, and adenine. It enhances crop stress resistance, improves crop quality, and has no toxicity or side effects [34,35,36,37]. EDAH, a plant growth regulator containing 27% ethephon and 3% DA-6, can reduce maize plant height, ear height, and center of gravity height while increasing the vascular bundle number and plant stem. Additionally, it enhances the content of structural compounds in basal internodes, ultimately improving maize quality and the tolerance of maize to density. Additionally, EDAH significantly increased grain yield by 14.3% by increasing kernel number. Different growth stages for applying plant growth regulators have varying effects on maize. Spraying during the jointing stage can increase light transmittance in the canopy, leading to higher yields and resistance to lodging [38]. Application at the seven-leaf stage strengthens stem mechanical properties, vascular bundles, and enhances photosynthetic rates, enzyme activity, and prolongs leaf greenness, ultimately increasing the maize yield [39,40,41]. However, some studies suggest that applying regulators at the 5–7 leaf stage may reduce ear number and negatively impact grain formation [42]. Conversely, spraying after the 12-leaf stage has shown to significantly increase the grains of the ear, thereby increasing maize yield by 5% [43]. Furthermore, research indicates a synergistic regulatory effect between maize ears and internode growth. For instance, uniconazole inhibits internode elongation but promotes ear size during the anthesis stage. Additionally, using ethephon in later growth stages can enhance the kernel number of the ear, leading to increasing the maize yield [44,45].
Based on previous research within the research group, different spraying periods of plant growth regulators (PGRs) were screened, revealing that applying ethephon at the 15-leaf stage can prevent damage to floret growth, reduce competition with stem growth, and expedite the distribution of photosynthetic products from leaves to ears, providing ample assimilates for grain growth and formation [28,45]. However, these studies lacked an analysis of the maize canopy structure and senescence processes, leading to the formulation of the following hypotheses: (i) Spraying plant growth regulators (PGRs) at different periods will affect the canopy structure of maize. (ii) Spraying plant growth regulators (PGRs) at different periods will result in diverse effects on maize pollen density. (iii) Spraying plant growth regulators (PGRs) at different periods will impact the senescence process of maize ear leaves. We expect the experiment to produce the following results: (1) Spraying plant growth regulators (PGRs) at the 15th leaf stage will optimize the canopy structure of maize and enhance the yield. (2) Spraying plant growth regulators (PGRs) at the 15th leaf stage will increase pollen density of the maize. (3) Spraying plant growth regulators (PGRs) at the 15th leaf stage will delay the senescence and prolong the functional period of the leaves.

2. Materials and Methods

2.1. Site Description

The study was conducted at the Gongzhuling Experimental Station of the Jilin Academy of Agricultural Sciences, Changchun, Jilin Province, China (43°52′ N, 124°81′ E; 206 m a.s.l.). The region is in temperate and cold-temperate zones with humid and semi-humid climates. Winters are cold and dry, and summers are warm and short. During the growth period of 2019–2020, the average sunlight duration was 1348.5 h, total solar radiation was 1679 MJ m−2, average temperature was 18.6 °C, and average precipitation was 633.5 mm. The climate and good soil quality explain why the north spring maize region is the main maize-producing area in China. Meteorological data during the study period are presented in Figure 1. The soil is a typic Hapludoll [46,47], which is known locally as “black soil”. Soil physiochemical properties in the 0 to 20 cm tillage layer were as follows: organic matter: 16.2 g kg−1; alkali hydrolyzable nitrogen (N): 183.4 mg kg−1; available phosphorus (P): 12.1 mg kg−1; available potassium (K): 283.4 mg kg−1; pH: 7.6.

2.2. Experiment Design

The experiments were arranged in a split-plot design in three replicates, with the plant growth regulator as the main plots and plant density as sub-plots. The plot size was 10 m × 6 m. The plant growth regulator that is commercially named “Jindele” in China with the main active ingredients of ethephon and cycocel (EC; w/w = 3:1) was used. Based on the product specification, the application dose was 450 mL ha−1 and the concentration was 2 mL EC/1 L H2O at each application timing. There were three EC application treatments included: T (10)—EC was sprayed at the 10-leaf stage, T (15)—EC was sprayed at the 15-leaf stage, and control—no EC application was performed during the entire growth period (CK). The maize cultivar was “Fumin985”, which is one of the main maize cultivars grown in the region. An appropriate plant density of 60,000 plants ha−1 (D1) and a high plant density of 90,000 plants ha−1 (D2) were used. Sowing dates were 28 April in 2019 and 28 April in 2020; harvest dates were 28 September in 2019 and 28 September in 2020, respectively. All treatments received the same levels of fertilizers (N, 63 kg ha−1; P2O5, 94 kg ha−1; K2O, 80 kg ha−1), with N, P, and K applied once as a base fertilizer before sowing. The nitrogen fertilizer (Resin-Coated urea) (Jilin Difu Fertilizer Technology Co., Changchun, China) has a slow availability effect and can support the nitrogen supply of maize throughout its reproductive period. During the whole growing period of maize, weeds, insects, and diseases were well controlled in two years.

2.3. Sampling and Measurements

2.3.1. Grain Yield and Its Components

At crop maturity, harvesting ears were sampled in two 10 m long rows in the middle of each plot. Kernel number per ear was determined from 30 randomly selected ears. To determine the 1000-kernel weight, kernels of the 30 ears were threshed by hand and oven-dried at 80 °C to a constant weight. Grain water content was adjusted to 14%. Maize yield was determined as follows [35]:
YG = δ × θ × WG × 10−6/(1 − 0.14)
where YG is the grain yield (kg ha−1), δ is the number of harvested ears (ears ha−1), θ is the number of kernels per ear (kernels ear−1), and WG is the 1000-kernel weight (g). The minimum standard of moisture content suggested in the literature for maize in storage is 14%.

2.3.2. Leaf Area and Leaf Angle

At vegetative tasseling stage (VT), three plants with consistent growth were selected from each plot, and the leaf layers were determined as follows: three leaves (the ear leaf and the immediately subsequent leaves) were used as the middle leaf layer (ML), and leaves above and below the middle leaf layer were the upper leaf layer (UL) and below leaf layer (BL), respectively. The stem-leaf angle was determined using a protractor, and the single-leaf area was computed from measuring the width and length of green leaves [36].
Single-leaf area (cm2) = leaf length (cm) × leaf width (cm) × 0.75

2.3.3. Pollen Density

From the initiation of maize tasseling, monitor the timing at which pollen shedding commences. In order to assess pollen density, a glass slide coated with petroleum jelly is placed in a collector with dimensions of 15 cm (length) × 15 cm (width) × 10 cm (height). This collector is positioned near the maize ear, with ventilation on all sides and in four vertical directions to capture dispersed pollen [48,49]. Five sampling locations were established in the southeast, northeast, southwest, and northwest corners and the center of each plot. Samples were collected at the central point at 4:00 PM daily to analyze fluctuations in pollen density under different treatments. Pollen grains were observed under a 10× microscope, with each collector examining 12 fields of view. The average value is the pollen density in this direction. The average pollen density in the five directions of the collector is the pollen density at that point. The unit of pollen density is per cm−2. After conversion, 1 cm2 = 39, with 3 views.

2.3.4. Canopy Radiation

At VT, canopy radiation measurements were taken using a canopy analyzer (Sunscan-UM-2.0, Delta-t, Cambridge, UK) with a linear quantum sensor in the middle of each lysimeter on a sunny and windless day from 09:00 to 15:00. The photosynthetically active radiation (PAR) was measured at four heights in the canopy: the bottom of the canopy (I1), the third leaf below the ear (I2), the ear (I3), and the third leaf above the ear (I4); each height per pool was measured four times in parallel. Each layer’s interception rate (Ii) was calculated. The formulas for performing the above calculations by the intercepted PAR (IPAR) of different heights and intercepted PAR at the top of the canopy (TPAR) are as follows [37]:
Ii = (1 − IPAR/TPAR) × 100%

2.3.5. Photosynthesis Rate of Ear Leaf

The net photosynthetic rate (Pn) of the ear leaf was measured by randomly selecting five plants from each plot at VT and at milk maturity stage (R3). The measurement point was at the middle of each ear leaf (excluding the main leaf veins). Plants were sampled between 1000 and 1200 using an LI-6400 portable photosynthetic instrument (LI-COR Inc., Lincoln, NE, USA). During the measurement period, the light intensity was kept stable at 1700 ± 50 μmol m−2 s−1, and the LED light system was used to maintain the light intensity.

2.3.6. Chlorophyll Content

Three plants were randomly obtained from each plot during the tasseling stage, as well as 15, 30, 45, and 60 days after the tasseling stage, plants with uniform growth were selected, and ear leaves were cut with scissors. The main vein was removed, wrapped in tin foil paper, and placed in liquid nitrogen for preservation until the analyses of the chlorophyll content, antioxidant defense enzyme, MDA content, and soluble protein concentration of leaves. The chlorophyll content was determined by 95% ethanol. For the experiments, a hole punch with a diameter of 0.6 cm was used to punch out 15 leaf discs. The discs were submerged in 15 mL of 95% ethanol, ensuring that they were completely covered. The mixture was placed on a thermostatic shaker (110 rpm) protected from light for 18 h. Chlorophyll pigment extract was poured into a cuvette with an optical path of 1 cm, and 95% ethanol was used as a blank. Absorbance was measured at wavelengths of 665 nm, 649 nm, and 470 nm. Chlorophyll a (Chla), chlorophyll b (Chlb), and carotenoid (Car) concentrations were calculated using Equations (4)–(6), and the content of each pigment was calculated according to the volume of extract, dilution factor, and area of the sample [38].
Chla = 13.95 × A665 − 6.88 × A649
Chlb = 24.96 × A649 − 7.32 × A665
Pigment content (mg dm−2) = Pigment concentration × volume of extract × dilution factor/area of sample

2.3.7. Leaf Senescence Process

Starting from the VT stage of maize, three plants were marked in each plot, and the leaf area was measured every 15 d using the length–width method. The green leaf area (GLA) was calculated using Equations (7)–(12), and the leaf senescence rate was fitted by a senescence model [39]:
GLA = leaf length × leaf width × 0.75
Leaf senescence model: y =a e b−cx/(1 + e b−cx)
RGLAM at full maturity (%) = GLA at full maturity/GLA at tasseling stage
Average aging rate (Vm) = (RGLAs − RGLAM)/time interval
Maximum senescence rate of relative green leaf area: Vmax = c/4
Time of occurrence of maximum green leaf decay rate: Tmax = b/c
where y is the relative green leaf area (RGLA, %) at a certain time, x is the number of days after tasseling, a is the theoretical initial value of RGLA (RGLAs), b is related to the start of leaf senescence, c is related to the rate of leaf senescence, and TS is the start time of leaf senescence, which refers to the initial time when RCLA reaches 95%.

2.3.8. Antioxidant Enzymes’ Activities, MDA Content, and Soluble Protein Content

SOD activity was determined according to Giannopolitis [40]. An amount of 20 μL enzyme solution was drawn and mixed with 3 mL SOD reaction solution (pH 7.8 phosphate buffer 1.5 mL, 750 mol L−1 NBT 0.3 mL, 130 mmol L−1 Met 0.3 mL, 20 mol L−1 FD 0.3 mL, 100 mol L−1 EDTA-Na2 0.3 mL, and distilled water 0.3 mL). Control and enzyme solutions were placed for 30 min in 4000 lux light. The blank was placed in dark for zero, compared in 560 nm.
POD activity was determined according to Hernandez [41]. An amount of 20 μL enzyme solution was drawn and mixed with 3 mL POD reaction solution (1.4 μL guaiacol, 0.85 μL 30% H2O2, and 0.1 mol L−1 pH 6.0 phosphate buffer). The absorbance values were recorded once every 30 s at 470 nm.
CAT activity was assayed as a decrease in absorbance at 240 nm for 1 min following the decomposition of H2O2 according to Change and Maehly [42]. The reaction mixture contained 50 mM phosphate buffer (pH 7.0) and 15 mM H2O2.
MDA content was measured as follows: 2 mL enzyme solution was drawn and mixed with 0.67% TBA 2 mL, then it was heated in a water bath for 30 min in 100 °C, and centrifuged after cooling down. The supernatant was determined at 450 nm, 532 nm, and 600 nm. The H2O2 content was measured using the method of Xie and others [43].
Soluble protein concentration was measured with coomassie brilliant blue G-250 staining.

2.3.9. Soil Physiochemical Properties

Soil organic carbon (SOC) content was measured by oxidation with potassium dichromate. Soil alkali-hydrolyzable nitrogen (AN) content was determined by the alkali diffusion method. Available phosphorus (AP) was measured by the molybdenum blue method using an ultraviolet spectrophotometer. Available potassium (AK) was measured by the flame photometry method. Soil pH was measured in soil–water (1:2.5) with a glass electrode meter [50].

2.4. Statistical Analyses

Raw data were analyzed utilizing Microsoft Excel 2019 software (Microsoft, Redmond, WA, USA). The main effects of the variables year, plant density, timing of regulator application, and their interactions were tested for the grain yield, ear characteristics, and canopy characteristics, using SPSS19.0 (IBM, Inc., Armonk, NY, USA). The comparisons of pollen density, light interception rate, Pn, chlorophyll content, antioxidant enzymes activities, MDA content, and soluble protein content among groups were tested by one-way ANOVA and Duncan’s multiple range test. Significantly different means that samples were separated at the 0.05 probability level by the least significant difference test. A combination graph of a correlation heat map of yield components and plant parameters and a mantel test line was drawn using the R package (“ggcor”) with R 4.1.2.

3. Results

3.1. Yield and Yield Components

During the two-year duration of the study from 2019 to 2020, the maize grain yield was significantly enhanced by 5.0% in D2 as compared to D1 (Table 1). The application of plant growth regulators did not exert a significant impact on yield when applied at D1 density. Conversely, in D2, there was a reduction in the number of kernels per ear by 5.6% and a decrease in the thousand-grain weight by 6.4% in the treatment designated as T10, when compared to the CK. Notably, in T15, there was a marked increase in yield, amounting to a 5.8% improvement over CK. Additionally, the kernels per ear increased by 3.9% and the thousand-grain weight increased by 2.3% in T15.

3.2. Ear Characteristics

With the increase in maize plant density from 60,000 to 90,000 plants ha−1, the ear length of the maize decreased by 12.3%, the number of total florets decreased by 7.4%, and the total abortive rate increased by 25.4%. The application of plant growth regulators did not exert a significant influence on the ear traits of the maize under condition D1. However, in D2, the ear length increased by 6.7% and the grain abortion rate decreased by 10.4% compared with the CK in T15 (Table 2).

3.3. Pollen Density

As plant densities escalated from 60,000 to 90,000 plants ha−1, the pollen density also increased. When plant growth regulators were sprayed, the effect on pollen density was not significant in D1. However, in D2, the average pollen density decreased by 21.0% for the T10 compared with the CK, while T15 increased by 20% (Figure 2).

3.4. Canopy Characteristics

3.4.1. Leaf Area and Leaf Angle

With increased plant densities from 60,000 to 90,000 plants ha−1, the leaf area decreased significantly. In comparison with the D1, the upper, middle, and lower leaf areas in D2 decreased by 17.9%, 6.6%, and 13.4%, respectively. The impact of spraying plant growth regulators on leaf area was not significant in D1. However, in D2, compared with the CK, the upper leaves’ area decreased by 10.5% in T10 and decreased by 20.1% in T15 (Table 3).
With increased plant densities from 60,000 to 90,000 plants ha−1, there was a significant reduction in leaf angle. Compared with D1, the upper, middle, and lower leaf angles decreased by 17.0%, 9.2%, and 11.1%, respectively, in D2. Following the application of plant growth regulators in D1, there was no significant effect on leaf angle. However, in D2, the upper leaf angle in the T15 treatment was notably reduced by 14.3% compared with the CK (Table 3).

3.4.2. Canopy Radiation Interception

With an increase in plant density from 60,000 to 90,000 plants ha−1, there was a significant reduction in the radiation interception rate. Compared with D1, the light energy interception rate of the upper leaves in D2 increased by 15.2% and the middle increased by 5.7%. In D1, spraying plant growth regulators did not significantly affect the radiation interception rate; however, in D2, after spraying plant growth regulators, the radiation interception rate of the upper leaves decreased by 15.2%, while the middle leaves increased by 5.2% in T15 (Figure 3).

3.5. Leaf Photosynthetic Traits

3.5.1. Photosynthetic Rate

The net photosynthetic rate of leaves decreased as the growth period advanced, with a corresponding decrease in net photosynthetic rate as density increased. Specifically, at the VT stage, the T15 showed a 22.6% increase compared to CK after the application of plant growth regulators in D1. Similarly, in D2, the T10 demonstrated a 16.7% improvement over the CK following the application of plant growth regulators, while the T15 showed a significant increase of 31.7% (Figure 4).

3.5.2. Chlorophyll Content

The chlorophyll content of the leaves showed a decline over the days after tasseling, with increased plant densities from 60,000 to 90,000 plants ha−1, and the chlorophyll content decreased significantly. Following the application of plant growth regulators under D1, there was a notable decrease in chlorophyll a by 11.9% and chlorophyll b by 1.1% in T10 when compared to the CK. In contrast, under the same condition, T15 demonstrated an increase in chlorophyll a by 7.3% and a more pronounced rise in chlorophyll b by 16.8%. In D2, compared with the CK, chlorophyll a and chlorophyll b decreased by 10.8% and 17.1% in T10, while in T15, chlorophyll a and chlorophyll b increased by 12.5% and 26.3%, respectively (Figure 5).

3.6. Leaf Senescence

3.6.1. Relative Green Leaf Area

Figure 6 illustrates the dynamic changes in the RGLA under different treatments after maize tasseling. The figure visually represents the senescence of maize leaves. Based on the change law, the model y = aeb–cx/(1 + eb−cx) better simulated (R2 = 0.976–0.998) the senescence of maize leaves. The relative green leaf area demonstrates a decreasing trend as the growth period advances. In D1, post application of plant growth regulators, the relative green leaf area increased 5.2% in T10 and increased 3.2% in T15 compared with the CK at 50 days after tasseling (Figure 6).

3.6.2. Leaf Senescence Characteristics

In D1, after applying plant growth regulators, the relative green leaf area (RGLAM) of the T10 treatment increased by 5.2% compared to the CK; additionally, Vm increased by 4.8%, Ts advanced by 5.6 days, Vmax decreased by 17.7%, and Tmax was delayed by 1.4 days. In T15, RGLAM increased by 3.2%, Vm decreased by 26.7%, Ts was delayed by 4.2 days, Vmax decreased by 4.1%, and Tmax was delayed by 6.6 days. In contrast, in D2, after applying plant growth regulators, the RGLAM of the T10 decreased by 3.9%, Vm increased by 7.0%, Ts advanced by 9.2 days, Vmax decreased by 20.5%, and Tmax advanced by 2.3 days. The RGLAM of the T15 increased by 32.8%, Vm decreased by 30.2%, Ts was delayed by 0.8 days, Vmax decreased by 21.1%, and Tmax was delayed by 8.3 days (Table 4).

3.6.3. Antioxidant Enzymes’ Activities, MDA Content, and Soluble Protein Content

With the growth process moving forward, the activity of SOD initially escalates and subsequently declines, achieving its zenith at 15 days after tasseling. With increased plant densities from 60,000 to 90,000 plants ha−1, there is a concomitant diminution in enzymatic activity. In D1, SOD activity exhibited a diminution of 1.4% in T10 relative to the CK, whereas it demonstrated an augmentation of 14.8% in T15. Conversely, in D2, SOD activity decreased by 23.1% in T10, yet it was observed to increase robustly by 25.5% in T15 (Figure 7).
With the growth process moving forward, the activity of POD initially rises and subsequently declines, achieving its peak around 30 days after tasseling. With increased plant densities from 60,000 to 90,000 plants ha−1, there is a concomitant reduction in enzyme activity. In D1, POD activity increased by 3.8% in T10 compared with the CK, while it increased by 7.4% in T15. Conversely, in D2, SOD activity decreased by 7.7% in T10 and increased by 19.1% in T15 (Figure 7).
With the growth process moving forward, there is a notable trend of declining activity in CAT. With increased plant densities from 60,000 to 90,000 plants ha−1, the activity of CAT exhibits a pattern of an initial increase followed by a subsequent decline. Specifically, In D1, CAT activity in T10 experienced a reduction of 10.3% relative to the CK, whereas in T15, there was a decrease of 3.7%. Conversely, in D2, CAT activity decreased by 19.8% in T10, while in T15, there was a notable increase of 19.1% (Figure 7).
The content of MDA increased with the growth process moving forward and the plant density increasing. In D1, MDA content decreased by 7.2% in T10 compared with the CK, while it increased by 0.3% in T15. In D2, the T10 experienced a modest increase of 3.2% in MDA content, while the T15 registered a more pronounced decrease of 11.1% (Figure 7).
With the growth process moving forward, the content of soluble protein initially rises and subsequently declines. With increased plant densities from 60,000 to 90,000 plants ha−1, there is a notable reduction in the content of soluble protein. In D1, T10 increased by 0.3% compared with CK, and it decreased by 10.0% in T15. In the D2 density, T10 showed a decrease of 17.8%, while T15 demonstrated a notable increase of 12.8% in soluble protein content (Figure 7).

3.7. Correlation

Correlation analysis has demonstrated that yield in D1 is significantly and positively associated with the total abortion rate, upper leaf area, and middle leaf area, as well as the middle leaf angle. However, it was not related to senescence characteristic parameters and physiological characteristics. On the other hand, in D2, yield and its components showed correlations with plant morphology, physiology, and senescence characteristics. Pollen density exhibited a significant positive correlation with both the upper leaf area and the upper leaf angle (p < 0.01). Additionally, RGLAM was correlated with chlorophyll b, SOD, POD, CAT activity, and soluble protein content, all of which showed a significant positive correlation (p < 0.01). Conversely, RGLAM displayed an extremely significant negative correlation with the content of MDA (p < 0.01) (Figure 8).

4. Discussion

4.1. Grain Yields and Yield Component

Increasing planting density is a crucial cultural practice for optimizing maize production potential, while the application of plant growth regulators serves as a technical method to enhance maize density tolerance [41]. In this study, it was found that spraying plant growth regulators under low planting density did not significantly alter plant morphology, improve canopy structure, or affect light conditions, resulting in minimal changes in maize yield and yield components. This can be attributed to the larger internal space within the plant group at low planting density, making maize plants less responsive to plant growth regulators [39]. The distribution of light energy to each leaf layer of the group remains relatively stable, allowing for steady growth. High light transmittance benefits the middle leaves, enhancing photosynthesis in later stages of maize growth. Conversely, at high density, poor light conditions within the plant population are observed. The application of plant growth regulators improves plant morphology and alters light conditions for middle leaves, impacting photosynthesis and ultimately leading to increased yield [40].
The optimization of maize (Zea mays L.) planting density is a crucial cultivation practice for improving the yield [4,51]. It is well established that within an optimal range, an elevated planting density can substantially augment the number of maize ears, thereby enhancing overall yield. However, beyond a certain point, the increased density can result in reduced access to essential resources like light and water, ultimately limiting the growth potential. This over-crowding can manifest in reduced kernel weight, shortened ear length, a diminished count of kernels per ear, and an escalated rate of grain abortion [5,52]. Research indicated that while a higher planting density can enhance maize yield by increasing the number of ears, it may also have negative impacts on ear length, number of ears, thousand-kernel weight, and grain abortion rate. Studies have shown that spraying plant growth regulators can enhance crops’ ability to withstand adverse conditions and decrease the yield losses under harsh environments [40,53,54] In this study, it was observed that spraying plant growth regulators at the 15-leaf stage in D2 led to an increase in ear length, number of kernels per ear, and thousand-grain weight, along with a decrease in grain abortion rate and an increase in yield. These outcomes are similar to previous research findings. In contrast, spraying plant growth regulators at the 10-leaf stage resulted in reduced ear length, ear number, and thousand-grain weight, while increasing grain abortion rate and effective ear number. Previous research has indicated that applying ethephon at the seven-to-nine-leaf stage can lead to decreased IAA content and increased ABA content in grains, hindering ear development, reducing grain storage capacity, and decreasing the number of kernels per ear, ultimately impacting grain filling and resulting in decreased thousand-grain weight and yield [55]. This differs from the results of spraying at the fifteen-leaf stage under high density in the current study. This finding contradicts the results of applying plant growth regulators at the fifteen-leaf stage but aligns with the results of applying plant growth regulators at the ten-leaf stage. Kernel number formation mainly depends on the potential kernel number that is established in the early vegetative growth period (i.e., floret initiation period), approximately the 8- to 13-leaf stages, depending on varieties [56]. Ethephon applied at this period suppressed or damaged floret initiation, thus reducing ear size and potential [57]. This was clearly confirmed by the literature and experimental results in the present study. This indicates that such practice could potentially impede ear development, leading to a decrease in the number of kernels per ear and the thousand-grain weight.

4.2. Pollen Density and Ear Traits

Maize, a unique monoecious and cross-pollinated crop, has evolved through long-term natural selection to develop a robust male inflorescence and abundant pollen. However, adverse environmental conditions can disrupt the process of pollen dispersal from the tassel, leading to grain abortion, a reduction in the number of grains per ear, and consequently, a decrease in overall yield [58,59,60]. The density of pollen is influenced primarily by two main factors: genetic factors, primarily plant type, and field environmental factors such as the climate, planting density, and cultivation practices. Pollen viability is also impacted by these factors, with high temperatures, high humidity, and moisture content during the pollen dispersal period affecting fertilization of the ear [61,62]. This study has identified a strong positive correlation between the number of kernels and pollen density, particularly under a planting density referred to as D2. Previous studies suggested that increasing planting density could result in smaller branches, fewer male ears of maize, degradation of florets, reduced total floret number, and pollen amount, ultimately affecting pollination and fruit setting, leading to a higher female ear abortion rate and lower yield [63]. This study also confirmed this point. However, following the application of plant growth regulators at the 15th leaf stage, changes in canopy structure resulted in an increase in pollen density. This led to a higher amount of the pollen scattered on the silk, enhanced the fertilization ability of silk, increased the grain yield per ear, and reduced the rate of abortion. The correlation heat map reveals a significant relationship between pollen density and the morphological structure of the upper part of the plant. Specifically, it has been observed that a reduction in the area of the upper leaves and the angle at which they are positioned can lead to an increase in pollen density. This increase in pollen density, in turn, results in a higher number of kernels and ultimately contributes to an enhancement in maize yield.

4.3. Canopy Characteristics

A well-structured canopy is paramount for the optimal growth and development of plants, as it enhances the absorption of light energy and augments photosynthetic capacity. This leads to increased transfer of dry matter to grains, ultimately improving yield [64,65,66]. While compact varieties perform better at higher planting densities, there are some drawbacks. It is crucial to further optimize plant types based on compact varieties to enhance maize pollination conditions and increase yield [4,67,68]. The application of plant growth regulators is a pivotal strategy for shaping an advantageous canopy structure in agricultural production. It plays a significant role in adjusting leaf angles and spacing, as well as optimizing canopy structure. In high-density planting scenarios, timely application of plant growth regulators can improve canopy structure, ensuring more uniform light distribution among different leaf layers and enhancing light energy utilization efficiency [40,41]. The findings from this experiment reveal that an increase in planting density can lead to a disorganized arrangement of leaves, resulting in diminished ventilation and light penetration between maize plants. However, spraying plant growth regulators, particularly at the 15-leaf stage, results in decreased upper leaf area and angle, lowering light interception in the upper part while increasing it in the middle part. This improvement in light transmittance within the canopy sets the stage for achieving high maize yields.

4.4. Leaf Photosynthetic Physiological Traits and Leaf Senescence Characteristics

The flowering stage is a crucial period for maize yield formation. As the grain filling process advances, leaf function gradually declines, leading to leaf senescence and reduced photosynthetic leaf area. Maintaining a high photosynthetic area during this stage is beneficial for increasing dry matter production and accumulation [23,69,70]. Leaf green duration and relative green leaf area serve as indicators to assess senescence progress. Leaf area changes directly reflect leaf growth, development, and senescence. Maintaining a larger leaf area during the latter growth phases can bolster the yield of photosynthetic products. Higher planting density can cause uneven light, temperature, and CO2 distribution, impacting leaf photosynthetic efficiency and material production, resulting in reduced effective photosynthetic area and premature leaf aging [71,72]. Research indicates that dense conditions accelerate lower leaf senescence, decreasing the leaf area per plant. However, applying plant growth regulators at the 15-leaf stage maintains a high relative green leaf area, increases photosynthetic pigment content, reduces the average senescence rate, delays leaf senescence onset, extends the leaf functional period, and enhances maize productivity by facilitating greater photosynthetic product production and transportation to the maize ear. Leaf senescence is influenced by more than just the levels of photosynthetic pigments; it is also affected by the antioxidant defense system [23,73]. Malondialdehyde (MDA) can bind with proteins on the cell membrane, rendering them inactive and disrupting membrane structure and function. Antioxidant enzymes such as Superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) play a protective role in combating lipid peroxidation in the membranes of plants. The activity of antioxidant enzymes decreases as maize plants mature. The buildup of reactive oxygen species and MDA can have detrimental effects on cells, including lipid peroxidation in plant cell membranes, protein denaturation, and interference with photosynthesis, ultimately accelerating leaf senescence [8,74,75]. This study validates the aforementioned perspective. Following the application of plant growth regulators on 15 leaves at a high density, MDA content decreased compared to the control group, while SOD, POD, and CAT activities increased, soluble protein content rose, and membrane lipid peroxidation decreased. This enhances crop stress resistance and delays leaf aging.

5. Conclusions

Under high planting density, spraying plant growth regulators at the 15-leaf stage can adjust the pollen density and increase the number of kernels per ear by optimizing the structure of the maize canopy. Additionally, it can enhance the photosynthetic ability of leaves, increase chlorophyll content, improve antioxidant enzyme activity, delay leaf senescence, and increase kernel weight; this is a direct consequence of the plant’s ability to allocate more resources towards kernel development, which is a key determinant of yield. In summary, the strategy of spraying plant growth regulator at the 15-leaf stage under high planting density conditions can lead to a cascade of positive effects that ultimately culminate in increased yield.

Author Contributions

Methodology, T.X.; data curation, T.X.; writing—original draft preparation, T.X.; investigation, T.X., D.W., Y.S., Y.K., Y.L. and Y.W.; formal analysis, D.W., Y.S., Y.K., X.S., Y.G. and Y.L.; software, D.W., Y.S. and Y.K.; resources, D.W., Y.S., Y.K., X.S. and Y.G.; visualization, D.W., X.S. and Y.G.; writing—review & editing, D.W., Y.S., Y.K., X.S., Y.G., Y.L. and Y.W.; supervision, X.S., Y.G., Y.L. and Y.W.; conceptualization, Y.W.; funding acquisition, Y.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Jilin Province Key Technology R&D Program (20220302004NC), the National Natural Science Foundation of China (U23A6001-01), and the China Agricultural Research System (CARS-02-19).

Data Availability Statement

Data are contained within the article.

Acknowledgments

The authors want to thank the staff of Gongzhuling Experimental Station for the excellent field management.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Daily temperature, sunshine duration, and precipitation during the 2019–2020 growing season.
Figure 1. Daily temperature, sunshine duration, and precipitation during the 2019–2020 growing season.
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Figure 2. Pollen density as an effect of plant growth regulator application at different growth stages (leaf age) under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying plant growth regulator during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages. ** represents significantly different at the 0.01 level; ns represents no significant difference.
Figure 2. Pollen density as an effect of plant growth regulator application at different growth stages (leaf age) under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying plant growth regulator during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages. ** represents significantly different at the 0.01 level; ns represents no significant difference.
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Figure 3. Light interception as effect of plant growth regulator application at different leaf layers under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying plant growth regulator during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages; Lower: lower leaf layer; Middle: middle leaf layer; Upper: upper leaf layer. ** represents significantly different at the 0.01 level; * represents significantly different at the 0.05 level; ns represents no significant difference.
Figure 3. Light interception as effect of plant growth regulator application at different leaf layers under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying plant growth regulator during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages; Lower: lower leaf layer; Middle: middle leaf layer; Upper: upper leaf layer. ** represents significantly different at the 0.01 level; * represents significantly different at the 0.05 level; ns represents no significant difference.
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Figure 4. Net photosynthetic rate as an effect of plant growth regulator application at different leaf positions under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying plant growth regulator during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages; VT: vegetative tasseling stage; R3, reproductive milk stage. Values followed by different small letters within a column are significantly different at p < 0.05 probability level.
Figure 4. Net photosynthetic rate as an effect of plant growth regulator application at different leaf positions under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying plant growth regulator during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages; VT: vegetative tasseling stage; R3, reproductive milk stage. Values followed by different small letters within a column are significantly different at p < 0.05 probability level.
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Figure 5. Chlorophyll content as an effect of plant growth regulator application at different leaf positions under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying ethephon during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages. ** represents significantly different at the 0.01 level; * represents significantly different at the 0.05 level; ns represents no significant difference.
Figure 5. Chlorophyll content as an effect of plant growth regulator application at different leaf positions under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying ethephon during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages. ** represents significantly different at the 0.01 level; * represents significantly different at the 0.05 level; ns represents no significant difference.
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Figure 6. Relative green area as an effect of plant growth regulator application at different leaf positions under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying ethephon during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages.
Figure 6. Relative green area as an effect of plant growth regulator application at different leaf positions under two plant densities in 2019 and 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying ethephon during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages.
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Figure 7. Antioxidant enzymes’ activities, MDA content, and soluble protein content as effects of plant growth regulator application at different leaf positions under two plant densities in 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying ethephon during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages. ** represents significantly different at the 0.01 level; * represents significantly different at the 0.05 level; ns represents no significant difference.
Figure 7. Antioxidant enzymes’ activities, MDA content, and soluble protein content as effects of plant growth regulator application at different leaf positions under two plant densities in 2020. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying ethephon during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages. ** represents significantly different at the 0.01 level; * represents significantly different at the 0.05 level; ns represents no significant difference.
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Figure 8. Mantel test correlation heatmap. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; ULA: upper leaf area; MLA: middle leaf area; LLA: lower leaf area; UA: upper leaf angle; MA: middle leaf angle; LA: lower leaf angle; ULI: upper light interception; MLI: middle light interception; LLI: lower light interception; Pn: photosynthetic rate; Chla: chlorophyll a content; Chlb: chlorophyll b content; SOD: superoxide dismutase activity; POD: peroxidase activity; CAT: catalase activity; MDA: malondialdehyde content; RGLAM: relative green leaf area at maturity; Vm: mean decreasing rate of RGLA; Ts: date of onset of leaf senescence; Vmax: maximum reduction rate of RGLA; Tmax: date of Vmax. ** represents significantly different at the 0.01 level; * represents significantly different at the 0.05 level.
Figure 8. Mantel test correlation heatmap. D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; ULA: upper leaf area; MLA: middle leaf area; LLA: lower leaf area; UA: upper leaf angle; MA: middle leaf angle; LA: lower leaf angle; ULI: upper light interception; MLI: middle light interception; LLI: lower light interception; Pn: photosynthetic rate; Chla: chlorophyll a content; Chlb: chlorophyll b content; SOD: superoxide dismutase activity; POD: peroxidase activity; CAT: catalase activity; MDA: malondialdehyde content; RGLAM: relative green leaf area at maturity; Vm: mean decreasing rate of RGLA; Ts: date of onset of leaf senescence; Vmax: maximum reduction rate of RGLA; Tmax: date of Vmax. ** represents significantly different at the 0.01 level; * represents significantly different at the 0.05 level.
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Table 1. Grain yield and yield components as effect of plant growth regulator application at different growth stages (leaf age) under two plant densities in 2019 and 2020.
Table 1. Grain yield and yield components as effect of plant growth regulator application at different growth stages (leaf age) under two plant densities in 2019 and 2020.
YearDensityRegulator ApplicationEar Number (Ears ha−1)Kernels per EarTKW (g)Grain Yield (t ha−1)
2019D1CK55,677.7 ± 2537.8 c587.6 ± 12.5 a328.2 ± 4.5 a12.5 ± 0.6 a
T1058,608.1 ± 1268.9 c581.0 ± 7.0 a310.8 ± 5.8 c12.3 ± 0.5 a
T1557,875.5 ± 2537.8 c592.1 ± 4.6 a319.6 ± 2.1 b12.7 ± 0.6 a
D2CK79,120.9 ± 2197.8 b476.2 ± 1.5 c289.9 ± 3.9 d12.7 ± 0.2 a
T1084,981.7 ± 1268.9 a462.4 ± 8.5 d276.7 ± 2.0 e12.6 ± 0.3 a
T1577,655.7 ± 1268.9 b494.5 ± 4.6 b294.2 ± 2.8 d13.1 ± 0.0 a
2020D1CK56,410.3 ± 2537.8 c560.4 ± 7.4 ab312.5 ± 1.6 ab11.5 ± 0.7 b
T1057,875.5 ± 2537.8 c550.7 ± 4.2 b303.3 ± 3.7 bc11.2 ± 0.5 b
T1557,142.9 ± 3806.7 c563.7 ± 9.9 a316.5 ± 1.4 a11.9 ± 0.9 b
D2CK75,457.9 ± 1268.9 b476.8 ± 4.5 d292.1 ± 9.4 d12.2 ± 0.2 b
T1086,446.9 ± 2537.8 a437.6 ± 2.0 e268.3 ± 8.4 e11.8 ± 0.1 b
T1576,190.5 ± 1268.9 b496.0 ± 4.0 c300.8 ± 1.5 cd13.2 ± 0.3 a
CV0.170.100.060.06
ANOVAYearns*****
Density********
PGR********
Y*Dns****ns
Y*Pns**ns
D*P******ns
Y*D*Pnsnsnsns
D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; TKW: thousand-kernel weight; CK: indicates the treatment without spraying plant growth regulator during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages; CV: coefficient of variation. Values followed by different small letters within a column are significantly different at 5% probability level. ** represents significantly different at the 0.01 level; * represents significantly different at 0.05 level; ns represents no significant difference.
Table 2. Ear characteristics as effect of plant growth regulator application at different growth stages (leaf age) under two plant densities in 2019 and 2020.
Table 2. Ear characteristics as effect of plant growth regulator application at different growth stages (leaf age) under two plant densities in 2019 and 2020.
YearDensityRegulator ApplicationEar Length (cm)Number of Total FloretsTotal Abortive Rate (%)
2019D1CK17.8 ± 0.1 ab808.5 ± 24.4 a27.3 ± 0.7 c
T1017.7 ± 0.1 b812.5 ± 26.3 a28.4 ± 2.9 c
T1518.2 ± 0.3 a805.8 ± 25.8 a26.5 ± 2.5 c
D2CK15.3 ± 0.3 d746.7 ± 25.4 b36.2 ± 2.4 a
T1014.6 ± 0.3 e738.0 ± 10.1 b37.3 ± 2.0 a
T1516.5 ± 0.4 c730.7 ± 13.7 b32.3 ± 0.6 b
2020D1CK19.2 ± 0.9 a819.0 ± 3.5 a31.6 ± 1.1 d
T1018.3 ± 1.6 a804.7 ± 11.2 a31.6 ± 1.5 d
T1519.1 ± 0.5 a821.3 ± 9.3 a31.4 ± 1.9 d
D2CK16.8 ± 0.4 bc775.3 ± 15.3 b38.5 ± 1.3 b
T1015.7 ± 0.4 c764.7 ± 23.9 b42.7 ± 1.8 a
T1517.8 ± 0.2 ab758.3 ± 13.0 b34.6 ± 0.6 c
CV0.090.050.15
ANOVAYear*****
Density******
PGRns****
Y*Dnsnsns
Y*Pnsnsns
D*Pns***
Y*D*Pnsnsns
D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying plant growth regulator during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages; CV: coefficient of variation. Values followed by different small letters within a column are significantly different at 5% probability level. ** represents significantly different at the 0.01 level; * represents significantly different at 0.05 level; ns represents no significant difference.
Table 3. Leaf area and leaf angle effect of plant growth regulator application at different growth stages (leaf age) under two plant densities in 2019 and 2020.
Table 3. Leaf area and leaf angle effect of plant growth regulator application at different growth stages (leaf age) under two plant densities in 2019 and 2020.
YearDensityRegulator ApplicationLeaf Area (cm2)Leaf Angle (°)
Upper LeavesMiddle LeavesLower LeavesUpper LeavesMiddle LeavesLower Leaves
2019D1CK662.7 ± 24.5 a1029.4 ± 2.0 a646.8 ± 7.3 a25.0 ± 3.5 ab27.5 ± 3.2 ab32.0 ± 5.0 a
T10598.4 ± 35.6 b962.2 ± 27.6 bc574.5 ± 19.4 b27.3 ± 2.1 a28.1 ± 5.9 ab32.5 ± 3.2 a
T15589.9 ± 3.7 b993.0 ± 18.2 ab580.8 ± 25.6 b27.6 ± 2.8 a28.8 ± 2.3 a33.4 ± 3.3 a
D2CK587.2 ± 19.5 b925.1 ± 17.7 c527.9 ± 6.4 c21.5 ± 0.7 bc26.7 ± 1.4 ab28.5 ± 1.2 a
T10515.9 ± 18.4 c913.0 ± 55.5 c584.9 ± 12.1 b21.8 ± 0.9 bc22.3 ± 1.3 b26.4 ± 5.5 a
T15448.0 ± 25.4 d955.6 ± 18.2 bc564.5 ± 32.6 b19.4 ± 0.3 c26.8 ± 1.2 ab26.2 ± 2.1 a
2020D1CK599.3 ± 21.1 a826.9 ± 9.7 a608.5 ± 6.2 a28.2 ± 1.7 a31.7 ± 0.3 abc31.5 ± 1.7 b
T10607.2 ± 1.3 a791.7 ± 25.8 bc553.4 ± 6.2 b29.0 ± 0.9 a35.1 ± 3.6 a31.8 ± 1.1 b
T15570.4 ± 27.5 b837.8 ± 8.1 a526.7 ± 2.4 c27.4 ± 0.2 a33.7 ± 2.6 ab35.3 ± 1.7 a
D2CK518.5 ± 10.3 c780.0 ± 23.3 b460.3 ± 13.7 d26.8 ± 0.9 ab30.8 ± 0.4 bc31.0 ± 2.6 b
T10473.4 ± 5.0 d720.7 ± 1.8 c467.8 ± 4.7 d25.1 ± 1.8 b28.9 ± 1.3 c30.4 ± 1.9 b
T15435.8 ± 11.3 e790.4 ± 19.3 b418.0 ± 3.5 e22.1 ± 0.9 c32.3 ± 0.8 abc32.0 ± 1.6 b
CV0.130.110.120.130.140.12
ANOVAYear***********
Density************
PGR******nsnsns
Y*Dnsns**nsnsns
Y*P**ns**nsnsns
D*P**ns**nsnsns
Y*D*Pnsns*nsnsns
D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying plant growth regulator during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages; CV: coefficient of variation. Values followed by different small letters within a column are significantly different at 5% probability level. ** represents significantly different at the 0.01 level; * represents significantly different at 0.05 level; ns represents no significant difference.
Table 4. Leaf senescence characteristics of the effect of plant growth regulator application at different growth stages (leaf age) under two plant densities (D1: 60,000 plant ha−1 and D2: 90,000 plant ha−1) in 2019 and 2020.
Table 4. Leaf senescence characteristics of the effect of plant growth regulator application at different growth stages (leaf age) under two plant densities (D1: 60,000 plant ha−1 and D2: 90,000 plant ha−1) in 2019 and 2020.
YearDensityRegulator ApplicationEquation ParameterCorrelation CoefficientSenescence Process Indices
bcR2RGLAM (%)Vm (%)Ts (Days)Vmax (%)Tmax (Days)
2019D1CK4.510.100.99554.950.9016.372.3947.20
T103.770.070.99661.460.7711.591.7853.06
T155.240.100.97657.580.8522.032.6050.34
D2CK3.970.090.99042.651.1511.622.2045.08
T103.360.080.99336.651.375.172.0041.98
T153.980.070.99656.930.6514.401.8055.24
2020D1CK4.480.090.99353.770.9216.582.3248.27
T104.180.080.98952.900.9415.022.0650.76
T154.040.080.99654.580.9114.351.9152.99
D2CK5.000.120.99836.741.2717.742.9043.12
T103.410.080.99339.661.215.702.0541.61
T154.420.090.99648.491.0316.562.2349.64
D1: 60,000 plant ha−1; D2: 90,000 plant ha−1; CK: indicates the treatment without spraying ethephon during the entire growth period; T(n): indicates the treatment of spraying ethephon at n-leaf stages; RGLAM: relative green leaf area at maturity; Vm: mean decreasing rate of RGLA; TS: date of onset of leaf senescence; Vmax: maximum reduction rate of RGLA; Tmax: date of Vmax.
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Xu, T.; Wang, D.; Si, Y.; Kong, Y.; Shao, X.; Geng, Y.; Lv, Y.; Wang, Y. Plant Growth Regulators Enhance Maize (Zea mays L.) Yield under High Density by Optimizing Canopy Structure and Delaying Leaf Senescence. Agronomy 2024, 14, 1262. https://doi.org/10.3390/agronomy14061262

AMA Style

Xu T, Wang D, Si Y, Kong Y, Shao X, Geng Y, Lv Y, Wang Y. Plant Growth Regulators Enhance Maize (Zea mays L.) Yield under High Density by Optimizing Canopy Structure and Delaying Leaf Senescence. Agronomy. 2024; 14(6):1262. https://doi.org/10.3390/agronomy14061262

Chicago/Turabian Style

Xu, Tong, Dan Wang, Yu Si, Yuanyuan Kong, Xiwen Shao, Yanqiu Geng, Yanjie Lv, and Yongjun Wang. 2024. "Plant Growth Regulators Enhance Maize (Zea mays L.) Yield under High Density by Optimizing Canopy Structure and Delaying Leaf Senescence" Agronomy 14, no. 6: 1262. https://doi.org/10.3390/agronomy14061262

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