Optimal nitrogen regimes compensate for the impacts of seedlings subjected to waterlogging stress in summer maize

Wenming Wu; Shiji Wang; Hongjian Chen; Youhong Song; Lin Zhang; Chen Peng; Lili Jing; Jincai Li

doi:10.1371/journal.pone.0206210

Abstract

A field experiment was performed to explore the compensation effects of different nitrogen (N) regimes on the growth and photosynthetic capacity in different leaf layers of the summer maize hybrid of LuYu9105 under waterlogging at the seedling stage. The results showed that waterlogging significantly decreased the maximum green leaf area (gLA) by 10.0~15.3% and 9.3~22.5%, mainly due to the reduction in the below-ear layer leaves at the silking stage in 2014 and 2015, respectively. Waterlogging also significantly decreased the ear leaf photosynthetic rate (P_N), and F_v/F_m, F_v/F_o, Φ_PSII and qP at the below-ear layer leaves at the mid- and late-filling stages, which was accompanied by a reduction in the duration of grain-filling (T) by 2.6~5.9%, thus resulting in a loss of grain yield by 7.0~18.5%. Interestingly, a shift in N from basal application to topdressing at the big flare stage was shown to compensate the adverse effects of waterlogging by through increased gLA and leaf photosynthetic capacity at the ear layer and the above-ear layer, as well as a greater grain-filling rate, resulting in an increase in grain yield by 9.9~27.0% and 17.8~25.8% compared to other N treatments. Therefore, this study showed that optimal nitrogen regimes during maize growth are capable of compensating for the impacts caused by waterlogging at the seedling stage.

Citation: Wu W, Wang S, Chen H, Song Y, Zhang L, Peng C, et al. (2018) Optimal nitrogen regimes compensate for the impacts of seedlings subjected to waterlogging stress in summer maize. PLoS ONE 13(10): e0206210. https://doi.org/10.1371/journal.pone.0206210

Editor: Suzannah Rutherford, Fred Hutchinson Cancer Research Center, UNITED STATES

Received: February 26, 2018; Accepted: October 9, 2018; Published: October 23, 2018

Copyright: © 2018 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This work was supported by The National Key Research and Development Program of China (2017YFD0301307) (http://www.most.gov.cn/index.htm).

Competing interests: The authors have declared that no competing interests exist.

Introduction

Anhui Province is an important area for food supply in China, and maize is one of the major crops grown in the summer season. Summer maize is normally grown on mid-June after winter wheat has been harvested in a summer maize-winter wheat rotation area. Normally there is substantial rainfall from the mid-June that lasts nearly one month [1]. When the soil water content of the surface layer exceeds the field carrying capacity by at least 20%, this leads to free standing water on the soil surface [2, 3], and, consequently, maize seedling development is often subjected to waterlogging [1, 4].

Waterlogging has been shown to significantly affect maize growth and yield development [5–8], which depends on the genotype [9–11], the growth stage, and the duration of waterlogging [5, 7, 12]. Waterlogging inhibits the diffusion of gases through soil pores, and results in an enhancement of anaerobic respiration and accumulation of harmful substances in soil, which deteriorates rhizosphere environments [5, 13, 14], and restrains the growth and development of maize root, i.e., root length and number of root tips, causing a reduction of the absorption area [5, 15, 16]. Waterlogging also accelerates the leaf senescence process, via decreases in antioxidative enzyme activities and soluble protein content [7, 12, 17], resulting in the reduction of LAI, and disorders of leaf gas exchange and chlorophyll parameters [5, 18]. In addition, waterlogging restricts leaf photosystem II (PSII) photosynthetic activity and blocks photosynthetic electron transport [19], which reduces the quantum efficiency of PSII actual electron transfer and the photosynthetic rate (P_N) [5, 20]. Previous study show that the third leaf stage of maize is most susceptible to waterlogging [5]. The adverse effects of waterlogging in the early stage have much longer-term effects, and these adverse effects are still observed during the later growth period, resulting in a decrease in the aboveground matter accumulation, nutrient absorption and transition, grain filling rate, and grain yield [5, 19, 21–23]. However, previous studies have mainly focused on whole canopy response to waterlogging, and little is known about how different canopy layers responded. Leaves of maize plant can be classified into three groups: above-ear, ear and below-ear layers, which have different functions. How waterlogging impacts the different leaf layers still need further research.

Tackling waterlogging mainly depends on the following aspects: (1) to choose the water-resistant hybrids [9, 10, 24, 25]; (2) to investigate the compensate effects of biochemical preparation on the growth and production [17, 26]; (3) to explore new planting management to overcome the waterlogging disaster, such as ridge tillage or different drainage measurement [6, 27]. Previous researches also suggest to determine the waterlogging risk in fields with underlying impermeable layers that enhance lateral flow of water [28]. Nevertheless, how to change the fertilization method to alleviate the adverse effects of waterlogging on growth and grain yield of summer maize remains to be determined. N metabolism has been shown to contribute to cellular acclimation to low oxygen stress in plants [29]. In waterlogged soil, N losses from the soil [30], a lack of N and the decline of root absorption ability can cause a reduction in the leaf chlorophyll content and accelerate leaf senescence [31]. In contrast, an increase in N availability may improve photosynthetic capacity or stomatal control under water and N deficit conditions [32–35]. Furthermore, it has also been reported that N supply can increase the effective quantum yield of photochemical energy conservation in PSII [5, 36]. As a consequence, this is suggestive of compensating maize leaf functioning after waterlogging using N regimes. In the Anhui province, N fertilization is mainly 100% basal fertilizer. Due to the adverse effects of waterlogging, it can be seen that a shift of N from basal application to topdressing at the flare stage may compensate for waterlogging for the growth of summer maize. In this context, we conducted a 2-year field experiment to assess the adverse effects of waterlogging on the growth and development of different leaf layers, and the compensating effects of N regimes. Accordingly, the objectives of this study were i) to explore the adverse effects of waterlogging on the gLA, photosynthetic capacity and chlorophyll characteristics of different leaf layers; ii) to examine how different N regimes compensated for the adverse effects of waterlogging on maize growth and development.

Materials and methods

Plant materials and culture conditions

A field trial was conducted at the experimental station of the Anhui Academy of Agricultural Sciences, China (31°57′N, 117°11′E), in 2014 and 2015, using the summer maize hybrid “LuYu 9105”, which is one of the most widely grown hybrids in Anhui Province. The region has a temperate continental monsoon climate. The topsoil (0–20 cm) is yellow cinnamon soil, containing 21.6 g kg⁻¹ organic matter, 118.4 mg kg⁻¹ alkali-hydrolyzable N, 25.4 mg kg⁻¹ available P, and 269.6 mg kg⁻¹ available K.

Experimental design

In this experiment, a randomized complete block design was used to arrange two water supply treatments, i.e., waterlogging stress and no waterlogging (the control), with four replicates. Waterlogging was applied for 7 days from the fourth leaf stage. In the waterlogged treatment, 1 cm of water was maintained above the soil surface using a water valve to control water flow throughout the waterlogging period. Each plot was 3.6 m×6.7 m. There was a 3.0 m interval between two adjacent experimental plots and a ridge with a height of 0.4 m along the border of each plot. An independent water supply pipe was provided in each waterlogging plot to achieve waterlogging during the seedling stage; in contrast, the control treatment was rainfed and was not irrigated during this stage. The planting density was 75,000 plants ha^-1. Four N regimes (N1, N2, N3 and N4) were designed for the waterlogging and control treatments. The N fertilizer was urea, and the application rate was 240 kg ha^-1 for all treatments but with different proportions at the basal, jointing, and big flare stages (10:0:0 for N1, 7:3:0 for N2, 5:5:0 for N3, and 3:5:2 for N4). Fertilizers containing phosphorus (P₂O₅) and potassium (K₂O) were applied at respective rates of 105 kg ha^-1 and 135 kg ha^-1 per plot prior to sowing. After the waterlogging treatment was applied for 7 days, the water in the plot was drained, afterwards, the management of the waterlogging treatment was the same as in the control treatment. Weeds, diseases, and insect pests were rigorously controlled.

Green leaf area (gLA)

Leaves were grouped into three leaf layers, i.e., ear layer leaves (three-ear leaves), above-ear layer leaves (the leaves above the three-ear leaves), and below-ear layer leaves (the leaves below the three-ear leaves). At the silking stage, four plants were randomly selected in each plot to determine leaf area. gLA per plant = ∑A×B×0.75.

A is the leaf length, B is the maximum leaf widt.

Leaf N concentration

Fresh samples were heated in an oven for 30 min at 105°C to deactivate enzymes and were then dried at 70°Cto a constant weight. The dried samples were ground to determine the N concentration. Plant samples were digested using the H₂SO₄–H₂O₂ method, and the total N concentration was measured using a continuous flow auto-analyzer (AAIII; SEAL Analytical, Germany).

Leaf gas exchange characteristics

At the mid- and late-filling stages, the net photosynthetic rate (P_N), stomatal conductance (g_s), transpiration rate (T_r), and intercellular CO₂ concentration (c_i) of the ear leaves were measured using a portable gas exchange system (LI-6400, LI-COR, Lincoln, USA). Three plants from each plot were measured on clear days between 9:30–11:00 A.M. Measurement conditions remained consistent: LED light source, PAR of 1400 μmol m⁻², flow rate of 500 cm³ min^–1, constant CO₂ concentration of 360 μmol mol⁻¹, air temperature of 30°C, and relative humidity of 65%.

Chlorophyll fluorescence was determined on above-ear leaves, ear leaves and below-ear leaves by non-destructively measuring photo-physiological parameters using pulse amplitude modulation fluorometry (PAM-2500, Walz, Germany) at the silking stage, mid-filling stage and late-filling stage. Initial fluorescence (F₀) and maximal fluorescence (F_m) were measured after 30 min of dark adaptation. The intensity of the saturation pulses used to determine the maximal fluorescence emission in the presence (F_m’) and absence (F_m) of quenching was 4000 μmol (photon) m^–2 s^–1 for 0.8 s, whereas “actinic light” was 600 μmol (photon) m^–2 s^–1. Steady-state fluorescence (F_s), basic fluorescence after light induction (F₀’), maximal PSII photochemical efficiency (F_v/F_m), effective quantum yield of PSII (Ф_PSII), and photochemical (qP) fluorescence quenching coefficients were also recorded.

Grain filling characteristics

The silking date was recorded when the silks emerged in 50% of the plants in a plot. Three ears of every plot from randomly selected plants were harvested at 10, 20, 30, 40, 50 and 60 days after anthesis and 100 grains were cut from the middle of each sampled ear [37]. The dry weight of 100 grains for each ear was measured after drying to a constant weight in a forced air oven at 80°C.

The dynamics of grain weight during grain filling followed Richards' growth equation [38]: where Y is the grain weight, K is the ultimate grain weight, t is the day after pollination, and A and B are coefficients determined by regression.

The data of the early grain filling period was , the middle grain filling period was , the late grain filling period was , the duration of the early grain filling period was T₁ = t₁, the duration of the middle grain filling period was T₂ = t₂−t₁, the duration the late grain filling period was T₃ = t₃−t₂, the grain-filling duration was T = t₃, the mean grain-filling rate was , the maximum grain-filling rate was , the grain weight during the early grain filling period was , the grain weight during the middle grain filling period was , the grain weight during the late grain filling period was , the grain-filling rate during the the early grain filling period was , the grain filling rate during the middle grain filling period was , the grain filling rate during the late grain filling period was .

Grain yield

At the maturity stage, 30 cobs were harvested from three rows at the center of each plot to determine the yield and ear characteristics, including ear length, row number, and kernel number per row. All kernels were air-dried, and grain yield was calculated at 14% moisture, which is the standard for maize storage or sale in China (GB/T29890-2013). Grain yield (kg ha⁻¹) = harvested ears (ears ha⁻¹) × kernel number per ear × 1000-grain weight (g 1000 grains⁻¹)/10⁶ × (1– sample moisture content %) / (1–14%).

Statistical analysis

The effects of waterlogging stress, N treatments, and their interactions were analyzed using two-way analysis of variance (ANOVA; p = 0.05). Differences between the means of the waterlogging and N treatments were compared using LSD multiple-range tests at 0.05 probability levels. Statistical analyses were performed using SPSS 13.0 (SPSS, Chicago, IL, USA), and all figures were drawn using SigmaPlot 10.0.

Results

gLA

Waterlogging significantly decreased gLA by 14.5, 14.3, 13.2 and 9.9% in 2014, and 22.6, 20.7, 14.9 and 9.7% in 2015 in different N treatments, respectively, compared to the corresponding control (Fig 1). Waterlogging decreased gLA by 14.1~24.9% and 0.3~12.9% in the below-ear layer, by 1.9~2.6% and 6.3~18.7% in the ear layer, by 13.4~32.2% and 11.0~43.8% in the above-ear layer, compared to the corresponding controls in 2014 and 2015, respectively (Fig 2). N shifted from basal application to topdressing at the big flare stage effectively improved gLA under waterlogging. The gLA of the N4 treatment was significantly higher than that of the other N treatments in the ear layer by 6.8~24.8% and in the above-ear layer by 26.2~72.7% under waterlogging, 7.0~37.4% in the above-ear layer of the control in 2014 and 2015, respectively.

Download:

Fig 1. Green leaf area at the silking stage across differing nitrogen regimes.

The error bars represent the standard errors of the mean. Different letters above the bars indicate significant differences (p < 0.05) among different N regimes. N1: 100% N applied as basal fertilizer, N2: 70% N applied as basal fertilizer and 30% N applied at the jointing stage, N3: 50% N applied as basal fertilizer and 50% N applied at the jointing stage, N4: 30% N applied as basal fertilizer, 50% N applied at the jointing stage and 20% N applied at the big flare stage.

https://doi.org/10.1371/journal.pone.0206210.g001

Download:

Fig 2. Green leaf area of different leaf layers at the silking stage.

The error bars represent the standard errors of the mean. Different letters above the bars indicate significant differences (p < 0.05) among different N regimes. N1: 100% N applied as basal fertilizer, N2: 70% N applied as basal fertilizer and 30% N applied at the jointing stage, N3: 50% N applied as basal fertilizer and 50% N applied at the jointing stage, N4: 30% N applied as basal fertilizer, 50% N applied at the jointing stage and 20% N applied at the big flare stage.

https://doi.org/10.1371/journal.pone.0206210.g002

Leaf nitrogen concentrations

Waterlogging resulted in a significant reduction in N concentration in the different leaf layer leaves (Table 1). Specifically, waterlogging reduced the N concentration by 5.1 and 22.1% in the below-ear layer, 2.9 and 12.1% in the ear layer, and 6.7 and 15.3% in the above-ear layer leaves at the silking stage and by 14.4, 9.5, and 6.2% and 14.0 3.2, and 12.8% of the below-ear layer, the ear layer and the above-ear layer leaves at the maturity stage in 2014 and 2015, respectively. Waterlogging decreased N concentrations in below-ear layer leaves by the greatest amount. However, in three of the regimes (N2, N3 and N4), where N shifted from a basal application to topdressing, the effect of waterlogging on the N concentration was effectively alleviated. Among these regimes, the N4 treatment at the respective silking and maturity stages had the greatest effect, and the values were increased by 23.5, 21.8, and 9.0% and 8.5, 36.7, and 25.4% at the silking stage, and by 41.6, 47.1, and13.6% and 48.4, 7.9, and 33.4% at the maturity stage in the below-ear layer, the ear layer and the above-ear layer, compared to the N1 treatment under waterlogging in 2014 and 2015, respectively.

Download:

Table 1. Leaf N concentrations in different leaf layers at the silking and maturity stages.

https://doi.org/10.1371/journal.pone.0206210.t001

Leaf photosynthetic capacity

Waterlogging led to a noticeable decrease in P_N, g_s and T_r at the mid-filling stage (16.1, 25.0, and 5.1%) and at the late-filling stage (28.9, 12.1, and 10.9%, respectively) compared to the corresponding control. An increase in c_i was observed in maize subjected to waterlogging, with 19.3% greater values at the mid-filling stage and 61.3% greater values at the late-filling stage. Compared to the mid-filling stage, P_N, g_s and T_r decreased by 38.9, 31.1 and 21.8% in the late-filling stage under waterlogging, whereas in the control, P_N, g_s and T_r decreased by approximately 27.9, 41.2 and 16.8%, respectively (Table 2).

Download:

Table 2. Effects of waterlogging imposed at the seedling stage on photosynthetic capacity at the grain-filling stage (2015).

https://doi.org/10.1371/journal.pone.0206210.t002

At the mid-filling stage, there was no significant difference among different N regimes for P_N, g_s and T_r. At the late-filling stage, these characteristics showed higher values in N4 than in N1 and N2, with increases of 63.3 and 55.3% (P_N), 43.2 and 7.0% (g_s), and 34.5 and 12.3% (T_r) compared to N1 and N2 under waterlogging, and 80.6 and 8.0% (P_N), 47.7 and 19.6% (g_s), and 25.0 and 2.9% (T_r) compared to the control, respectively (Table 3).

Download:

Table 3. Effects of different N regimes on the photosynthetic capacity of summer maize subjected to waterlogging stress at the seedling stage (2015).

https://doi.org/10.1371/journal.pone.0206210.t003

PSII photochemical characteristics

Waterlogging resulted in a significant reduction of the maximal efficiency of PSII photochemistry (F_v/F_m) (Figs 3 and 4), the potential efficiency of PSII photochemistry (F_v/F_o) (Figs 5 and 6), the actual quantum yield of PSII (Φ_PSII) (Fig 7) and the photochemical quenching of chlorophyll fluorescence (qP) (Table 4) at the silking and grain-filling stages, compared to the control. At the silking stage, the maximum values of F_v/F_m, F_v/F_o, Φ_PSII and qP were measured in the above-ear layer leaves, followed by the ear layer and the below-ear layer leaves. At the grain filling stage, F_v/F_m and F_v/F_o were ranked as ear leaf layer > above-ear layer > below-ear layer. During the grain-filling process, the F_v/F_m and F_v/F_o of below-ear leaves decreased the most. However, a shift in N fertilizer from a basal application to topdressing at the big flare stage alleviated waterlogging damage to F_v/F_m and F_v/F_o. F_v/F_m and F_v/F_o in the N4 treatment was notably higher than in the other N treatments, with increases of 1.9~2.8% and 7.6~11.7% in the below-ear layer, 2.8~3.9% and 1.1~16.7% in the ear layer, and 1.3~5.9% and 7.1~26.8% in the above-ear layer in 2014. The values increased by 1.1~3.0% and 9.5~12.1%, 0.8~1.3% and 3.5~5.3%, and 0.9~1.2% and 5.0~8.6% for the N4 treatment, compared to the corresponding leaf layers of the N1 treatment under waterlogging in 2015.

Download:

Fig 3. Maximal efficiency of PSII (F_v/F_m) in different leaf layers under different N treatments (2014).

The error bars represent the standard errors of the mean. Different letters above the bars indicate significant differences (p < 0.05) among the different N treatments. A,D: above-ear leaves; B,E: ear leaves; C,F: below-ear leaves. N1: 100% N applied as basal fertilizer, N2: 70% N applied as basal fertilizer and 30% N applied at the jointing stage, N3: 50% N applied as basal fertilizer and 50% N applied at the jointing stage, N4: 30% N applied as basal fertilizer, 50% N applied at the jointing stage and 20% N applied at the big flare stage.

https://doi.org/10.1371/journal.pone.0206210.g003

Download:

Fig 4. Maximal efficiency of PSII (F_v/F_m) in different leaf layers under different N treatments (2015).

The error bars represent the standard errors of the mean. Different letters above the bars indicate significant differences (p < 0.05) among the different N treatments. A,D: above-ear leaves; B,E: ear leaves; C,F: below-ear leaves. N1: 100% N applied as basal fertilizer, N2: 70% N applied as basal fertilizer and 30% N applied at the jointing stage, N3: 50% N applied as basal fertilizer and 50% N applied at the jointing stage, N4: 30% N applied as basal fertilizer, 50% N applied at the jointing stage and 20% N applied at the big flare stage.

https://doi.org/10.1371/journal.pone.0206210.g004

Download:

Fig 5. Potential efficiency of PSII (F_v/F₀) in different leaf layers under different N treatments (2014).

The error bars represent the standard errors of the mean. Different letters above the bars indicate significant differences (p < 0.05) among the different N treatments. A,D: above-ear leaves; B,E: ear leaves; C,F: below-ear leaves. N1: 100% N applied as basal fertilizer, N2: 70% N applied as basal fertilizer and 30% N applied at the jointing stage, N3: 50% N applied as basal fertilizer and 50% N applied at the jointing stage, N4: 30% N applied as basal fertilizer, 50% N applied at the jointing stage and 20% N applied at the big flare stage.

https://doi.org/10.1371/journal.pone.0206210.g005

Download:

Fig 6. Potential efficiency of PSII (F_v/F₀) in different leaf layers under different N treatments (2015).

The error bars represent the standard errors of the mean. Different letters above the bars indicate significant differences (p < 0.05) among the different N treatments. A,D: above-ear leaves; B,E: ear leaves; C,F: below-ear leaves. N1: 100% N applied as basal fertilizer, N2: 70% N applied as basal fertilizer and 30% N applied at the jointing stage, N3: 50% N applied as basal fertilizer and 50% N applied at the jointing stage, N4: 30% N applied as basal fertilizer, 50% N applied at the jointing stage and 20% N applied at the big flare stage.

https://doi.org/10.1371/journal.pone.0206210.g006

Download:

Fig 7. Actual quantum yield of PSII (𝚽_PSII) in leaf layers under different N treatments (2015).

The error bars represent the standard errors of the mean. Different letters above the bars indicate significant differences (p < 0.05) among the different N treatments. A,D: above-ear leaves; B,E: ear leaves; C,F: below-ear leaves. N1: 100% N applied as basal fertilizer, N2: 70% N applied as basal fertilizer and 30% N applied at the jointing stage, N3: 50% N applied as basal fertilizer and 50% N applied at the jointing stage, N4: 30% N applied as basal fertilizer, 50% N applied at the jointing stage and 20% N applied at the big flare stage.

https://doi.org/10.1371/journal.pone.0206210.g007

Download:

Table 4. Effects of different N treatments on the photochemical quenching of variable chlorophyll fluorescence (qP) (2015).

https://doi.org/10.1371/journal.pone.0206210.t004

A shift in N fertilizer from a basal application to topdressing at the big flare stage had no effect on Φ_PSII and qP at the silking stage. However, at the mid- and late-filling stages, the highest Φ_PSII and qP were measured in the N4 treatment. Waterlogging decreased Φ_PSII in N1, N2 and N3 by 1.5~6.6% in the below-ear layer, 5.4~14.2% in the ear layer, and by 1.1~13.3% in the above-ear layer leaves, compared to the N4 treatment. The values of qP were reduced by 0.3~24.2% in the below-ear layer and 1.4~15.2% in the ear layer leaves of the N1 treatment, compared to the N4 under waterlogging. Additionally, the values of qP were decreased by 2.3~7.1% in the below-ear layer, 1.5~3.0% in the ear layer and 1.3~11.6% in the above-ear layer leaves of the N1 treatment, compared to the N4 of the control.

Relationship between N concentration and chlorophyll fluorescence parameters

The N concentrations in the different leaf layers were significantly and positively linearly correlated with F_v/F_m (y = 0.0447x + 0.6659; R² = 0.7196**, p < 0.01) and F_v/F_o (y = 0.5281x + 1.8809; R² = 0.4467**, p < 0.01). However, there was no significant correlation between the N concentration of the different leaf layers and Φ_PSII or qP.

Grain filling characteristics

Waterlogging significantly decreased the final grain weight (K) by 9.8~19.0% in 2014 and 5.5~13.9% in 2015, respectively, compared to the corresponding control (Fig 8). The grain-filling process was analyzed using Richard’s equation. According to the equation, waterlogging had adverse influences on the duration of grain filling (T) by 2.6~5.9% (Table 5). However, a shift in N from a basal application to topdressing at the big flare stage effectively alleviated the reduction of K by 5.3 and 22.3% under waterlogging and increased it by 18.0 and 12.6% for the control, compared to N1 in 2014 and 2015, respectively. Additionally, a shift in N from a basal application to topdressing at the big flare stage improved T, V_a and V_m, by 0.6~7.9%, 4.4~13.0% and 2.1~20.6%, respectively, compared to other N treatments. The results indicated that a shift in N from a basal application to topdressing could alleviate the adverse effects of waterlogging on the grain filling characteristics.

Download:

Fig 8. Grain-filling in different N treatments during post-anthesis stage.

N1: 100% N applied as basal fertilizer, N2: 70% N applied as basal fertilizer and 30% N applied at the jointing stage, N3: 50% N applied as basal fertilizer and 50% N applied at the jointing stage, N4: 30% N applied as basal fertilizer, 50% N applied at the jointing stage and 20% N applied at the big flare stag.

https://doi.org/10.1371/journal.pone.0206210.g008

Download:

Table 5. Effects of different nitrogen treatments on grain filling characteristics parameters under waterlogging in the seedling stage.

https://doi.org/10.1371/journal.pone.0206210.t005

Grain yield

Waterlogging significantly decreased the grain yield of summer maize by 7.0% in 2014 and 18.5% in 2015, compared to the control. However, a shift in N from a basal application to topdressing effectively alleviated the reduction of grain yield caused by waterlogging, and there was no interaction effect between waterlogging and N regimes. The grain yield of the N4 treatment increased by 27.0, 23.4, and 9.9% in 2014 and 25.8, 21.8, and 17.8% in 2015, compared to the N1, N2 and N3 treatments under waterlogging. The values were increased by 17.0, 12.8, and 9.6% in 2014 and 28.8, 27.9, and 21.6% in 2015, respectively, compared to the N1, N2 and N3 treatments of the control, respectively (Table 6).

Download:

Table 6. Effects of different nitrogen regimes on the grain yield of summer maize subjected to waterlogging at the seedling stage.

https://doi.org/10.1371/journal.pone.0206210.t006

Discussion

Adverse effects of waterlogging on gLA and leaf photosynthetic capacity

Waterlogging affects crop growth and development [5, 7, 22], and decreases maize gLA [6]. In this study, waterlogging significantly decreased the gLA of maize, which was in agreement with previous studies [6, 20]. The reduction of gLA under waterlogging may related to the decline in ZR, IAA and GA contents, and the increase in leaf ABA contents, resulting in an acceleration of leaf senescence [12, 13]. Interestingly, waterlogging significantly decreased gLA in the below-ear and above-ear layer leaves. The reduction of gLA in the below-ear layer may due to the decline in the absorption ability of root, which inhibits N absorption and transport [23], resulting in a deficiency of N in below-ear layer leaves and an acceleration of leaf senescence.

The gLAI is an important indicator of the canopy architecture at different growth stages, and a longer gLA duration and photosynthetic capacity during the post-silking period is one of several traits associated with an improvement in maize yield [39]. Our study showed that waterlogging caused a significant reduction in P_N and g_s accompanied by a significant increase in c_i in the ear leaves, indicating that non-stomatal closure was the main reason for the decrease in P_N, which differed from previous report [20]. Moreover, waterlogging had negative effect on F_v/F_m, F_v/F_o, Φ_PSII and qP, especially for the below-ear layer leaf values. Photosynthates of the below-ear layer leaves mainly supply root growth. Under waterlogging conditions, diffusion of gases through soil pores is inhibited, resulting in enhanced of anaerobic respiration and accumulation of harmful substances in soil, and deterioration of rhizosphere environments [14, 21,40]. Root development is constrained, which leads to abnormal growth of shoot parts [7, 20], especially the below-ear layer leaves. Furthermore, the decline of gLA may cause an increase in light transmittance and excessive light leakage losses, consequently decreasing irradiation energy utilization efficiency and P_N [4, 41]. Optimum canopy function is a key factor in achieving a higher yield [42, 43]. The grain number and 1000-grain weight are established in the grain filling stage [44]. It was clear that waterlogging reduced the photosynthetic capacity, by decreasing the leaf N concentration, gLA and P_N, indicating a reduction in “source” characteristics. In addition, waterlogging decreased the grain-filling duration (T). The “source” characteristics were constrained, resulting in a reduction of “sink” (i.e., grain yield decreases) characteristics for waterlogged summer maize.

The compensating effect of the N regime on the development of maize

Nitrogen (N) is essential in the synthesis of the photosynthetic apparatus, which is closely related to the gLA and P_N [36, 41, 45, 46]. However, the compensating effects of N on gLA, N concentration and photosynthetic capacity in different leaf layers of summer maize subjected to waterlogging at the seedling stage remain unclear. Our results indicated that a shift in N from a basal application to topdressing at the big flare stage increased N concentration and gLA in the leaves, especially in the ear layer and above-ear layer leaves, which alleviated the decline in gLA induced by waterlogging, thus increasing the gLA of the ear and above-ear layers and compensating for the gLA decrease in the below-ear layer leaves. The compensating effect of N was significant and ultimately resulted in an increase in gLA compared to 100% basal fertilizer application. N element can increase cytokinin synthesis in the roots and subsequent transport to the leaves [47], and enhance the new leaf area expansion, eventually increasing gLA, dry matter accumulation and transport.

N also enhances root and shoot development through increased maize root exudation and total abundance of soil bacteria [48]. Low leaf N concentrations have a negative effect on the P_N [36, 49]. N deficiency can decrease the activity of Rubisco and PEPC enzymes, and the degradation of Rubisco and PEPC can decrease the photosynthetic capacity during the leaf senescence process [36]. Additionally, supplying N increases the chlorophyll content and P_N of plants [36, 41]. Our results showed that with the improvement in the gLA and N concentration, the photosynthetic capacity was improved at the ear layer leaves in the later filling stage, and the chlorophyll fluorescence parameters PSII was improved at the ear layer and above-ear layer leaves, indicating that the supplied N could increase the effective quantum yield of photochemical energy conservation in PSII, which is in agreement with previous studies [4, 36, 50]. Photosynthates of above-ear layer leaves supply tassel and grains, while those of the ear layer mainly supply grain filling. A shift in N from basal application to topdressing at the big flare stage was conducive to alleviating the decrease in the grain yield, by maintaining a higher gLA, P_N, F_v/F_m, and N concentration in the ear layer and above-ear layer leaves, and a higher grain filling rate during the grain-filling period, ultimately alleviating waterlogging damages. Simultaneously, our results indicated that waterlogging inhibited the gLA and photosynthetic capacity, which was improved, but not reversed, by the N regimes. This phenomenon may due to the deterioration of morphological characteristics and the decline of the absorption area of root under waterlogging [4], which leads to abnormal development of the canopy. Improvement of the compensating effects to reach an optimum status still requires future research via the improvement of root and the interaction of root and shoot by N regimes. Consequently, changing the normal fertilization method (100% basal fertilizer) to a combination of basal and topdressing application is recommended to improve maize growth in areas subjected to waterlogging during the seedling stage.

Conclusion

Waterlogging at the seedling stage had significantly adverse effects on gLA, N concentration, and photosynthetic capacity, especially in the below-ear layer leaves. A shift in N from basal application to topdressing at the big flare stage could compensate for the adverse effects of waterlogging, by increasing the gLA, N concentration, and photosynthetic capacity in the ear and above-ear layer leaves. This greater leaf photosynthesis increased grain yield primarily via improved grain-filling rate. Overall, this study indicated that shifting the N application to the big flare stage was able to compensate for the adverse effects, but could not reverse the adverse effects caused by waterlogging at the seedling stage.

Supporting information

S1 File. This excel file includes green leaf area in different leaf layers at the silking stage.

The effects of different nitrogen regimes on the green leaf area of different leaf layers at the silking stage are based on this dataset.

https://doi.org/10.1371/journal.pone.0206210.s001

(XLSX)

S2 File. This excel file includes nitrogen concentration of different leaf layers at the silking and maturity stages.

The effects of different nitrogen regimes on nitrogen concentration of different leaf layers are based on this dataset.

https://doi.org/10.1371/journal.pone.0206210.s002

(XLSX)

S3 File. This excel file includes photosynthetic rate at the silking stage.

The effects of different nitrogen regimes on the photosynthetic capacity at the silking stage are based on this dataset.

https://doi.org/10.1371/journal.pone.0206210.s003

(XLSX)

S4 File. This excel file includes chlorophyll fluorescence parameters of different leaf layers at different growth stages.

The effects of different nitrogen regimes on the chlorophyll fluorescence parameters of different leaf layers at different growth stages are based on this dataset.

https://doi.org/10.1371/journal.pone.0206210.s004

(XLSX)

S5 File. This excel file includes grain weight during grain filling stage.

The effects of different nitrogen regimes on grain weight during grain filling stage are based on this dataset.

https://doi.org/10.1371/journal.pone.0206210.s005

(XLSX)

S6 File. This excel file includes grain yield.

The effects of different nitrogen regimes on the grain yield of summer maize subjected to waterlogging at the seedling stage.

https://doi.org/10.1371/journal.pone.0206210.s006

(XLSX)

References

1. Liu S, Wang H, Yan DH, Qin TL, Wang ZL, Wang FX. Crop growth characteristics and waterlogging risk analysis of Huaibei Plain in Anhui Province, China. Journal of Irrigation and Drainage Engineering. 2017; 143: 04017042
- View Article
- Google Scholar
2. Agarwal S, Grover A. Molecular biology, biotechnology and genomics of flooding-associated low O2 stress response in plants. Critical Review in Plant Sciences. 2006; 25: 1–21.
- View Article
- Google Scholar
3. Nilsen E, Orcutt DM. The physiology of plants under stress abiotic factors. Wiley New York. 1996; 689.
4. Wu WM, Li JC, Chen HJ, Wang SJ, Wei FZ, Wang CY, et al. Effects of nitrogen fertilization on chlorophyll fluorescence change in maize (Zea mays L.) under waterlogging at seedling stage. Journal of Food Agriculture and Environment. 2013; 11: 545–552.
- View Article
- Google Scholar
5. Ren BZ, Zhang JW, Dong ST, Liu P, Zhao B. Root and shoot responses of summer maize to waterlogging at different stages. Agronomy Journal. 2016; 108: 1060–1069.
- View Article
- Google Scholar
6. Ren BZ, Dong ST, Liu P, Zhao B, Zhang JW. Ridge tillage improves plant growth and grain yield of waterlogged summer maize. Agricultural Water Management. 2016; 177: 392–399.
- View Article
- Google Scholar
7. Ren BZ, Zhang JW, Li X, Fan X, Dong ST, Liu P, et al. Effects of waterlogging on the yield and growth of summer maize under field conditions. Canadian Journal of Plant Science. 2014; 94: 23–31.
- View Article
- Google Scholar
8. Florio EL, Mercau JL, Jobbágy EG, Nosetto MD. Interactive effects of water-table depth, rainfall variation, and sowing date on maize production in the Western Pampas. Agricultural Water Management. 2014; 146: 75–83
- View Article
- Google Scholar
9. Lone AA, Khan MH, Dar ZA, Wani SH. Breeding strategies for improving growth and yield under waterlogging conditions in maize: a review. Maydica. 2016; 61.
- View Article
- Google Scholar
10. Thirunavukkarasu N, Hossain F, Mohan S, Shiriga K, Mittal S, Sharma R, et al. Genome-wide expression of transcriptomes and their co-expression pattern in subtropical maize (Zea mays L.) under waterlogging stress. Plos One. 2013; 8: e70433. pmid:23936429
- View Article
- PubMed/NCBI
- Google Scholar
11. Osman KA, Tang B, Wang YP, Chen JH, Yu F, Li L, et al. Dynamic QTL analysis and candidate gene mapping for waterlogging tolerance at maize seedling stage. Plos One. 2013; 8: e79305. pmid:24244474
- View Article
- PubMed/NCBI
- Google Scholar
12. Ren BZ, Zhang JW, Dong ST, Liu P, Zhao B. Reponses of carbon metabolism and antioxidant system of summer maize to waterlogging at different stages. Journal of Agronomy and Crop Science. 2018: 1–10.
- View Article
- Google Scholar
13. Araki H, Hamada A, Hossain MA, Takahashi T. Waterlogging at jointing and/or after anthesis in wheat induces early leaf senescence and impairs grain filling. Field Crops Research. 2012; 137: 27–36.
- View Article
- Google Scholar
14. Przywara G, Stcdaniewski W. The influence of waterlogging at different temperatures on penetration depth and porosity of roots and on stomatal diffusive resistance of pea and maize seedlings. Acta Physiological Plantarum. 1999; 21: 405–411.
- View Article
- Google Scholar
15. Grzesiak MT, Ostrowska A, Hura K, Rut G, Janowiak F, Rzepka A, et al. Interspecific differences in root architecture among maize and triticale genotypes grown under drought, waterlogging and soil compaction. Acta Physiological Plantarum. 2014; 36: 3249–3261.
- View Article
- Google Scholar
16. Du HW, Shen XM, Huang YQ, Huang M, Zhang ZX. Overexpression of Vitreoscilla hemoglobin increases waterlogging tolerance in Arabidopsis and maize. BMC Plant Biology. 2016, 16: 35. pmid:26833353
- View Article
- PubMed/NCBI
- Google Scholar
17. Ren BZ, Zhu YL, Zhang JW, Dong ST, Liu P, Zhao B. Effects of spraying exogenous hormone 6-benzyladenine (6-BA) after waterlogging on grain yield and growth of summer maize. Field Crops Research. 2016; 188: 96–104.
- View Article
- Google Scholar
18. O’Neill PM, Shanahan JF, Schepers JS. Use of chlorophyll fluorescence assessments to differentiate corn hybrid response to variable water conditions. Crop Science. 2006; 46: 681–687.
- View Article
- Google Scholar
19. Yordanova RY, Popova LP. Flooding-induced changes in photosynthesis and oxidative status in maize plants. Acta Physiological Plantarum. 2007; 29: 535–541.
- View Article
- Google Scholar
20. Liang ZJ, Tao HB, Wang P. Recovery effects of morphology and photosynthetic characteristics of maize (Z) seedling after waterlogging. Acta Ecologica Sinica. 2009; 29: 3977–3986.
- View Article
- Google Scholar
21. Ashraf M, Rehman H. Mineral nutrient status of corn in relation to nitrate and long-term waterlogging. Journal of Plant Nutrition. 1999; 22: 1253–1268.
- View Article
- Google Scholar
22. Irfan M, Hayat S, Hayat Q, Afroz S, Ahmad A. Physiological and biochemical in plants under waterlogging. Protoplasma. 2010; 241: 3–17. pmid:20066446
- View Article
- PubMed/NCBI
- Google Scholar
23. Ren BZ, Dong ST, Zhao B, Liu P, Zhang JW. Responses of nitrogen metabolism uptake and translocation of maize to waterlogging at different growth stages. Frontiers in Plant Science. 2017; 8: 1216. pmid:28744299
- View Article
- PubMed/NCBI
- Google Scholar
24. Souza TCD, Castro EMD, Magalhaes PC, Alves ET, Pereira FJ. Early characterization of maize plants in selection cycles under soil flooding. Plant Breeding. 2012; 131: 493–501.
- View Article
- Google Scholar
25. Zaidi PH, Rafique S, Singh NN. Response of maize (Zea mays L) genotypes to excess soil moisture stress: morpho-physiological effects and basis of tolerance. European Journal of Agronomy. 2003; 19: 383–399.
- View Article
- Google Scholar
26. Ren BZ, Zhang JW, Dong ST, Liu P, Zhao B, Li H. Nitrapyrin Improves Grain Yield and Nitrogen Use Efficiency of Summer Maize Waterlogged in the Field. Agronomy Journal. 2017; 109: 185–192.
- View Article
- Google Scholar
27. Chandio AS, Lee TS, Mirjat MS. Simulation of horizontal and vertical drainage systems to combat waterlogging problems along the rohri canal in Khairpur District, Pakistan. Journal of Irrigation & Drainage Engineering. 2013; 139: 710–717.
- View Article
- Google Scholar
28. Nyakudya IW, Stroosnijder L, Nyagumbo I. Infiltration and planting pits for improved water management and maize yield in semi-arid Zimbabwe. Agricultural Water Management. 2014; 141: 30–46.
- View Article
- Google Scholar
29. Bailey-Serres J, Fukao T, Gibbs DJ, Holdsworth MJ, Lee SC, Licausi F, et al. Making sense of low oxygen sensing. Trends in Plant Science. 2012; 17: 129–138. pmid:22280796
- View Article
- PubMed/NCBI
- Google Scholar
30. Meyer WS, Barrs HD, Mosier AR, Schaefer NL. Response of maize to three short-term periods of waterlogging at high and low nitrogen levels on undisturbed and repacked soil. Irrigation Science. 1987, 8: 257–272.
- View Article
- Google Scholar
31. Massignam AM, Chapman SC, Hammer GL, Fukai S. Effects of nitrogen supply on canopy development of maize and sunflower. Crop &Pasture Science. 2012; 62: 1045–1055.
- View Article
- Google Scholar
32. Liu WJ, Yuan S, Zhang NH, Lei T, Duan HG, Liang HG, et al. Effects of water stress on photosystem II in two wheat cultivars. Biologia Plantarum. 2006; 50: 597–602.
- View Article
- Google Scholar
33. Polesskaya OG, Kashirina EI, Alekhina ND. Changes in the activity of antioxidant enzymes in wheat leaves and roots as a function of nitrogen source and supply. Russian Journal of Plant Physiology. 2004; 51: 615–620.
- View Article
- Google Scholar
34. Ning P, Fritschi FB, Li CJ. Temporal dynamics of post-silking nitrogen fluxes and their effects on grain yield in maize under low to high nitrogen inputs. Field Crops Research. 2017; 204: 249–259.
- View Article
- Google Scholar
35. Chen YL, Wu DL, Mu XH, Xiao CX, Chen FJ, Yuan LX, et al. Vertical Distribution of Photosynthetic Nitrogen Use Efficiency and Its Response to Nitrogen in Field-Grown Maize. Crop Science. 2016; 56: 397–407.
- View Article
- Google Scholar
36. Wei SS, Wang XY, Shi DY, Li YH, Zhang JW, Liu P, et al. The mechanisms of low nitrogen induced weakened photosynthesis in summer maize (Zea mays L.) under field conditions. Plant Physiology and Biochemistry. 2016; 105: 118–128. pmid:27101123
- View Article
- PubMed/NCBI
- Google Scholar
37. Gambin BL, Borras L, Otegui ME. Source-sink relations and kernel weight differences in maize temperate hybrids. Field Crops Research. 2006; 95: 316–326.
- View Article
- Google Scholar
38. Shen XS, Zhu YJ, Guo TC, Li GQ, Qu HJ. Effects of sulphur application on characteristics of grain filling and grain yield of winter wheat cultivar Yumai 50. Acta Bot. Boreal -Occident Sin. 2007; 27: 1265–1269.
- View Article
- Google Scholar
39. Duvick DN. The contribution of breeding to yield advances in maize (Zea mays L.). Advances in Agronomy. 2005; 86: 83–145.
- View Article
- Google Scholar
40. Zou XL, Jiang YY, Liu L, Zhang ZX, Zheng YL. Identification of transcriptome induced in roots of maize seedling at the late stage of waterlogging. BMC Plant Biology. 2010, 10: 189. pmid:20738849
- View Article
- PubMed/NCBI
- Google Scholar
41. Ren BZ, Zhang JW, Dong ST, Liu P, Zhao B. Effects of waterlogging on leaf mesophyll cell ultrastructure and photosynthetic characteristics of summer maize. Plos One. 2016; 11: e0161424. pmid:27583803
- View Article
- PubMed/NCBI
- Google Scholar
42. Peng YF, Zeng XT, Houx JH III, Boardman DL, Li CJ, Fritschi FB. Pre- and post-silking carbohydrate concentrations in maize ear-leaves and developing ears in response to nitrogen availability. Crop Science. 2016; 56: 1–10.
- View Article
- Google Scholar
43. Sun XF, Ding ZS, Wang XB, Hou HP, Zhou BY, Yue Y, et al. Subsoiling practices change root distribution and increase post-anthesis dry matter accumulation and yield in summer maize. PLos One. 2017; 12: e0174952. pmid:28384233
- View Article
- PubMed/NCBI
- Google Scholar
44. Jones RJ, Schreiber BMN, Roessler JA. Kernel sink capacity in maize: Genotypic and maternal regulation. Crop Science. 1996; 36: 301–306.
- View Article
- Google Scholar
45. Zong YZ, Shangguan ZP. Nitrogen deficiency limited the improvement of photosynthesis in maize by elevated CO₂ under drought. Journal of Integrative Agriculture. 2014; 1: 73–81.
- View Article
- Google Scholar
46. Wei SS, Wang XY, Zhang JW, Liu P, Zhao B, Li G, et al. The role of nitrogen in leaf senescence of summer maize and analysis of underlying mechanisms using comparative proteomics. Plant Science. 2015; 233: 72–81. pmid:25711815
- View Article
- PubMed/NCBI
- Google Scholar
47. Song WJ, Li J, Sun HW, Huang SJ, Gong XP, Ma QY, et al. Increased photosynthetic capacity in response to nitrate is correlated with enhanced cytokinin levels in rice cultivar with high responsiveness to nitrogen nutrients. Plant Soil. 2013; 373: 981–993.
- View Article
- Google Scholar
48. Zhu SS, Vivanco JM, Manter DK. Nitrogen fertilizer rate affects root exudation, the rhizosphere microbiome and nitrogen-use-efficiency of maize. Applied Soil Ecology. 2016; 107: 324–333.
- View Article
- Google Scholar
49. Mu XH, Chen QW, Chen FJ, Yuan LX, Mi GH. Dynamic remobilization of leaf nitrogen components in relation to photosynthetic rate during grain filling maize. Plant Physiology and Biochemistry. 2018; 129: 27–34. pmid:29787936
- View Article
- PubMed/NCBI
- Google Scholar
50. Shangguan ZP, Shao MA, Dyckmans J. Effects of nitrogen nutrition and water deficit on net photosynthetic rate and chlorophyll fluorescence in winter wheat. Plant Physiology and Biochemistry. 2000; 156: 46–51.
- View Article
- Google Scholar

[ref1] 1. Liu S, Wang H, Yan DH, Qin TL, Wang ZL, Wang FX. Crop growth characteristics and waterlogging risk analysis of Huaibei Plain in Anhui Province, China. Journal of Irrigation and Drainage Engineering. 2017; 143: 04017042
View Article
Google Scholar

[2] View Article

[3] Google Scholar

[ref2] 2. Agarwal S, Grover A. Molecular biology, biotechnology and genomics of flooding-associated low O2 stress response in plants. Critical Review in Plant Sciences. 2006; 25: 1–21.
View Article
Google Scholar

[5] View Article

[6] Google Scholar

[ref3] 3. Nilsen E, Orcutt DM. The physiology of plants under stress abiotic factors. Wiley New York. 1996; 689.

[ref4] 4. Wu WM, Li JC, Chen HJ, Wang SJ, Wei FZ, Wang CY, et al. Effects of nitrogen fertilization on chlorophyll fluorescence change in maize (Zea mays L.) under waterlogging at seedling stage. Journal of Food Agriculture and Environment. 2013; 11: 545–552.
View Article
Google Scholar

[9] View Article

[10] Google Scholar

[ref5] 5. Ren BZ, Zhang JW, Dong ST, Liu P, Zhao B. Root and shoot responses of summer maize to waterlogging at different stages. Agronomy Journal. 2016; 108: 1060–1069.
View Article
Google Scholar

[12] View Article

[13] Google Scholar

[ref6] 6. Ren BZ, Dong ST, Liu P, Zhao B, Zhang JW. Ridge tillage improves plant growth and grain yield of waterlogged summer maize. Agricultural Water Management. 2016; 177: 392–399.
View Article
Google Scholar

[15] View Article

[16] Google Scholar

[ref7] 7. Ren BZ, Zhang JW, Li X, Fan X, Dong ST, Liu P, et al. Effects of waterlogging on the yield and growth of summer maize under field conditions. Canadian Journal of Plant Science. 2014; 94: 23–31.
View Article
Google Scholar

[18] View Article

[19] Google Scholar

[ref8] 8. Florio EL, Mercau JL, Jobbágy EG, Nosetto MD. Interactive effects of water-table depth, rainfall variation, and sowing date on maize production in the Western Pampas. Agricultural Water Management. 2014; 146: 75–83
View Article
Google Scholar

[21] View Article

[22] Google Scholar

[ref9] 9. Lone AA, Khan MH, Dar ZA, Wani SH. Breeding strategies for improving growth and yield under waterlogging conditions in maize: a review. Maydica. 2016; 61.
View Article
Google Scholar

[24] View Article

[25] Google Scholar

[ref10] 10. Thirunavukkarasu N, Hossain F, Mohan S, Shiriga K, Mittal S, Sharma R, et al. Genome-wide expression of transcriptomes and their co-expression pattern in subtropical maize (Zea mays L.) under waterlogging stress. Plos One. 2013; 8: e70433. pmid:23936429
View Article
PubMed/NCBI
Google Scholar

[27] View Article

[28] PubMed/NCBI

[29] Google Scholar

[ref11] 11. Osman KA, Tang B, Wang YP, Chen JH, Yu F, Li L, et al. Dynamic QTL analysis and candidate gene mapping for waterlogging tolerance at maize seedling stage. Plos One. 2013; 8: e79305. pmid:24244474
View Article
PubMed/NCBI
Google Scholar

[31] View Article

[32] PubMed/NCBI

[33] Google Scholar

[ref12] 12. Ren BZ, Zhang JW, Dong ST, Liu P, Zhao B. Reponses of carbon metabolism and antioxidant system of summer maize to waterlogging at different stages. Journal of Agronomy and Crop Science. 2018: 1–10.
View Article
Google Scholar

[35] View Article

[36] Google Scholar

[ref13] 13. Araki H, Hamada A, Hossain MA, Takahashi T. Waterlogging at jointing and/or after anthesis in wheat induces early leaf senescence and impairs grain filling. Field Crops Research. 2012; 137: 27–36.
View Article
Google Scholar

[38] View Article

[39] Google Scholar

[ref14] 14. Przywara G, Stcdaniewski W. The influence of waterlogging at different temperatures on penetration depth and porosity of roots and on stomatal diffusive resistance of pea and maize seedlings. Acta Physiological Plantarum. 1999; 21: 405–411.
View Article
Google Scholar

[41] View Article

[42] Google Scholar

[ref15] 15. Grzesiak MT, Ostrowska A, Hura K, Rut G, Janowiak F, Rzepka A, et al. Interspecific differences in root architecture among maize and triticale genotypes grown under drought, waterlogging and soil compaction. Acta Physiological Plantarum. 2014; 36: 3249–3261.
View Article
Google Scholar

[44] View Article

[45] Google Scholar

[ref16] 16. Du HW, Shen XM, Huang YQ, Huang M, Zhang ZX. Overexpression of Vitreoscilla hemoglobin increases waterlogging tolerance in Arabidopsis and maize. BMC Plant Biology. 2016, 16: 35. pmid:26833353
View Article
PubMed/NCBI
Google Scholar

[47] View Article

[48] PubMed/NCBI

[49] Google Scholar

[ref17] 17. Ren BZ, Zhu YL, Zhang JW, Dong ST, Liu P, Zhao B. Effects of spraying exogenous hormone 6-benzyladenine (6-BA) after waterlogging on grain yield and growth of summer maize. Field Crops Research. 2016; 188: 96–104.
View Article
Google Scholar

[51] View Article

[52] Google Scholar

[ref18] 18. O’Neill PM, Shanahan JF, Schepers JS. Use of chlorophyll fluorescence assessments to differentiate corn hybrid response to variable water conditions. Crop Science. 2006; 46: 681–687.
View Article
Google Scholar

[54] View Article

[55] Google Scholar

[ref19] 19. Yordanova RY, Popova LP. Flooding-induced changes in photosynthesis and oxidative status in maize plants. Acta Physiological Plantarum. 2007; 29: 535–541.
View Article
Google Scholar

[57] View Article

[58] Google Scholar

[ref20] 20. Liang ZJ, Tao HB, Wang P. Recovery effects of morphology and photosynthetic characteristics of maize (Z) seedling after waterlogging. Acta Ecologica Sinica. 2009; 29: 3977–3986.
View Article
Google Scholar

[60] View Article

[61] Google Scholar

[ref21] 21. Ashraf M, Rehman H. Mineral nutrient status of corn in relation to nitrate and long-term waterlogging. Journal of Plant Nutrition. 1999; 22: 1253–1268.
View Article
Google Scholar

[63] View Article

[64] Google Scholar

[ref22] 22. Irfan M, Hayat S, Hayat Q, Afroz S, Ahmad A. Physiological and biochemical in plants under waterlogging. Protoplasma. 2010; 241: 3–17. pmid:20066446
View Article
PubMed/NCBI
Google Scholar

[66] View Article

[67] PubMed/NCBI

[68] Google Scholar

[ref23] 23. Ren BZ, Dong ST, Zhao B, Liu P, Zhang JW. Responses of nitrogen metabolism uptake and translocation of maize to waterlogging at different growth stages. Frontiers in Plant Science. 2017; 8: 1216. pmid:28744299
View Article
PubMed/NCBI
Google Scholar

[70] View Article

[71] PubMed/NCBI

[72] Google Scholar

[ref24] 24. Souza TCD, Castro EMD, Magalhaes PC, Alves ET, Pereira FJ. Early characterization of maize plants in selection cycles under soil flooding. Plant Breeding. 2012; 131: 493–501.
View Article
Google Scholar

[74] View Article

[75] Google Scholar

[ref25] 25. Zaidi PH, Rafique S, Singh NN. Response of maize (Zea mays L) genotypes to excess soil moisture stress: morpho-physiological effects and basis of tolerance. European Journal of Agronomy. 2003; 19: 383–399.
View Article
Google Scholar

[77] View Article

[78] Google Scholar

[ref26] 26. Ren BZ, Zhang JW, Dong ST, Liu P, Zhao B, Li H. Nitrapyrin Improves Grain Yield and Nitrogen Use Efficiency of Summer Maize Waterlogged in the Field. Agronomy Journal. 2017; 109: 185–192.
View Article
Google Scholar

[80] View Article

[81] Google Scholar

[ref27] 27. Chandio AS, Lee TS, Mirjat MS. Simulation of horizontal and vertical drainage systems to combat waterlogging problems along the rohri canal in Khairpur District, Pakistan. Journal of Irrigation & Drainage Engineering. 2013; 139: 710–717.
View Article
Google Scholar

[83] View Article

[84] Google Scholar

[ref28] 28. Nyakudya IW, Stroosnijder L, Nyagumbo I. Infiltration and planting pits for improved water management and maize yield in semi-arid Zimbabwe. Agricultural Water Management. 2014; 141: 30–46.
View Article
Google Scholar

[86] View Article

[87] Google Scholar

[ref29] 29. Bailey-Serres J, Fukao T, Gibbs DJ, Holdsworth MJ, Lee SC, Licausi F, et al. Making sense of low oxygen sensing. Trends in Plant Science. 2012; 17: 129–138. pmid:22280796
View Article
PubMed/NCBI
Google Scholar

[89] View Article

[90] PubMed/NCBI

[91] Google Scholar

[ref30] 30. Meyer WS, Barrs HD, Mosier AR, Schaefer NL. Response of maize to three short-term periods of waterlogging at high and low nitrogen levels on undisturbed and repacked soil. Irrigation Science. 1987, 8: 257–272.
View Article
Google Scholar

[93] View Article

[94] Google Scholar

[ref31] 31. Massignam AM, Chapman SC, Hammer GL, Fukai S. Effects of nitrogen supply on canopy development of maize and sunflower. Crop &Pasture Science. 2012; 62: 1045–1055.
View Article
Google Scholar

[96] View Article

[97] Google Scholar

[ref32] 32. Liu WJ, Yuan S, Zhang NH, Lei T, Duan HG, Liang HG, et al. Effects of water stress on photosystem II in two wheat cultivars. Biologia Plantarum. 2006; 50: 597–602.
View Article
Google Scholar

[99] View Article

[100] Google Scholar

[ref33] 33. Polesskaya OG, Kashirina EI, Alekhina ND. Changes in the activity of antioxidant enzymes in wheat leaves and roots as a function of nitrogen source and supply. Russian Journal of Plant Physiology. 2004; 51: 615–620.
View Article
Google Scholar

[102] View Article

[103] Google Scholar

[ref34] 34. Ning P, Fritschi FB, Li CJ. Temporal dynamics of post-silking nitrogen fluxes and their effects on grain yield in maize under low to high nitrogen inputs. Field Crops Research. 2017; 204: 249–259.
View Article
Google Scholar

[105] View Article

[106] Google Scholar

[ref35] 35. Chen YL, Wu DL, Mu XH, Xiao CX, Chen FJ, Yuan LX, et al. Vertical Distribution of Photosynthetic Nitrogen Use Efficiency and Its Response to Nitrogen in Field-Grown Maize. Crop Science. 2016; 56: 397–407.
View Article
Google Scholar

[108] View Article

[109] Google Scholar

[ref36] 36. Wei SS, Wang XY, Shi DY, Li YH, Zhang JW, Liu P, et al. The mechanisms of low nitrogen induced weakened photosynthesis in summer maize (Zea mays L.) under field conditions. Plant Physiology and Biochemistry. 2016; 105: 118–128. pmid:27101123
View Article
PubMed/NCBI
Google Scholar

[111] View Article

[112] PubMed/NCBI

[113] Google Scholar

[ref37] 37. Gambin BL, Borras L, Otegui ME. Source-sink relations and kernel weight differences in maize temperate hybrids. Field Crops Research. 2006; 95: 316–326.
View Article
Google Scholar

[115] View Article

[116] Google Scholar

[ref38] 38. Shen XS, Zhu YJ, Guo TC, Li GQ, Qu HJ. Effects of sulphur application on characteristics of grain filling and grain yield of winter wheat cultivar Yumai 50. Acta Bot. Boreal -Occident Sin. 2007; 27: 1265–1269.
View Article
Google Scholar

[118] View Article

[119] Google Scholar

[ref39] 39. Duvick DN. The contribution of breeding to yield advances in maize (Zea mays L.). Advances in Agronomy. 2005; 86: 83–145.
View Article
Google Scholar

[121] View Article

[122] Google Scholar

[ref40] 40. Zou XL, Jiang YY, Liu L, Zhang ZX, Zheng YL. Identification of transcriptome induced in roots of maize seedling at the late stage of waterlogging. BMC Plant Biology. 2010, 10: 189. pmid:20738849
View Article
PubMed/NCBI
Google Scholar

[124] View Article

[125] PubMed/NCBI

[126] Google Scholar

[ref41] 41. Ren BZ, Zhang JW, Dong ST, Liu P, Zhao B. Effects of waterlogging on leaf mesophyll cell ultrastructure and photosynthetic characteristics of summer maize. Plos One. 2016; 11: e0161424. pmid:27583803
View Article
PubMed/NCBI
Google Scholar

[128] View Article

[129] PubMed/NCBI

[130] Google Scholar

[ref42] 42. Peng YF, Zeng XT, Houx JH III, Boardman DL, Li CJ, Fritschi FB. Pre- and post-silking carbohydrate concentrations in maize ear-leaves and developing ears in response to nitrogen availability. Crop Science. 2016; 56: 1–10.
View Article
Google Scholar

[132] View Article

[133] Google Scholar

[ref43] 43. Sun XF, Ding ZS, Wang XB, Hou HP, Zhou BY, Yue Y, et al. Subsoiling practices change root distribution and increase post-anthesis dry matter accumulation and yield in summer maize. PLos One. 2017; 12: e0174952. pmid:28384233
View Article
PubMed/NCBI
Google Scholar

[135] View Article

[136] PubMed/NCBI

[137] Google Scholar

[ref44] 44. Jones RJ, Schreiber BMN, Roessler JA. Kernel sink capacity in maize: Genotypic and maternal regulation. Crop Science. 1996; 36: 301–306.
View Article
Google Scholar

[139] View Article

[140] Google Scholar

[ref45] 45. Zong YZ, Shangguan ZP. Nitrogen deficiency limited the improvement of photosynthesis in maize by elevated CO₂ under drought. Journal of Integrative Agriculture. 2014; 1: 73–81.
View Article
Google Scholar

[142] View Article

[143] Google Scholar

[ref46] 46. Wei SS, Wang XY, Zhang JW, Liu P, Zhao B, Li G, et al. The role of nitrogen in leaf senescence of summer maize and analysis of underlying mechanisms using comparative proteomics. Plant Science. 2015; 233: 72–81. pmid:25711815
View Article
PubMed/NCBI
Google Scholar

[145] View Article

[146] PubMed/NCBI

[147] Google Scholar

[ref47] 47. Song WJ, Li J, Sun HW, Huang SJ, Gong XP, Ma QY, et al. Increased photosynthetic capacity in response to nitrate is correlated with enhanced cytokinin levels in rice cultivar with high responsiveness to nitrogen nutrients. Plant Soil. 2013; 373: 981–993.
View Article
Google Scholar

[149] View Article

[150] Google Scholar

[ref48] 48. Zhu SS, Vivanco JM, Manter DK. Nitrogen fertilizer rate affects root exudation, the rhizosphere microbiome and nitrogen-use-efficiency of maize. Applied Soil Ecology. 2016; 107: 324–333.
View Article
Google Scholar

[152] View Article

[153] Google Scholar

[ref49] 49. Mu XH, Chen QW, Chen FJ, Yuan LX, Mi GH. Dynamic remobilization of leaf nitrogen components in relation to photosynthetic rate during grain filling maize. Plant Physiology and Biochemistry. 2018; 129: 27–34. pmid:29787936
View Article
PubMed/NCBI
Google Scholar

[155] View Article

[156] PubMed/NCBI

[157] Google Scholar

[ref50] 50. Shangguan ZP, Shao MA, Dyckmans J. Effects of nitrogen nutrition and water deficit on net photosynthetic rate and chlorophyll fluorescence in winter wheat. Plant Physiology and Biochemistry. 2000; 156: 46–51.
View Article
Google Scholar

[159] View Article

[160] Google Scholar

Figures

Abstract

Introduction

Materials and methods

Plant materials and culture conditions

Experimental design

Green leaf area (gLA)

Leaf N concentration

Leaf gas exchange characteristics

Grain filling characteristics

Grain yield

Statistical analysis

Results

gLA

Leaf nitrogen concentrations

Leaf photosynthetic capacity

PSII photochemical characteristics

Relationship between N concentration and chlorophyll fluorescence parameters

Grain filling characteristics

Grain yield

Discussion

Adverse effects of waterlogging on gLA and leaf photosynthetic capacity

The compensating effect of the N regime on the development of maize

Conclusion

Supporting information

S1 File. This excel file includes green leaf area in different leaf layers at the silking stage.

S2 File. This excel file includes nitrogen concentration of different leaf layers at the silking and maturity stages.

S3 File. This excel file includes photosynthetic rate at the silking stage.

S4 File. This excel file includes chlorophyll fluorescence parameters of different leaf layers at different growth stages.

S5 File. This excel file includes grain weight during grain filling stage.

S6 File. This excel file includes grain yield.

References