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Article

Improvement in Photosynthetic Rate and Grain Yield in Super-High-Yield Maize (Zea mays L.) by Optimizing Irrigation Interval under Mulch Drip Irrigation

by
Dongping Shen
†,
Guoqiang Zhang
†,
Ruizhi Xie
,
Bo Ming
,
Peng Hou
,
Jun Xue
,
Shaokun Li
and
Keru Wang
*
Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2020, 10(11), 1778; https://doi.org/10.3390/agronomy10111778
Submission received: 7 October 2020 / Revised: 31 October 2020 / Accepted: 12 November 2020 / Published: 13 November 2020
(This article belongs to the Section Water Use and Irrigation)
Browse Figures
Versions Notes

Abstract

:
High yield is one of the important goals of crop production, and close planting and optimum irrigation systems are important agronomic practices for increasing maize (Zea mays L.) grain yield. However, little is known about the effect of optimal irrigation interval on the photosynthetic rate (Pn) and dry matter accumulation (DM) of closely planted super-high-yield maize under drip irrigation under mulch. Therefore, the objective of this study was to determine the effects of irrigation interval on the leaf Pn, DM, and grain yield of closely planted super-high-yield maize under mulch drip irrigation in the Xinjiang Uygur Autonomous Region, Northwestern China. A field experiment was conducted using three irrigation intervals in 2016—namely, six days (D6), nine days (D9), and 12 days (D12)—and five irrigation intervals in 2017—namely, three days (D3), six days (D6), nine days (D9), 12 days (D12), and 15 days (D15). The Xianyu 335 high-yield maize hybrid was used in the test; the planting density was set to 12×104 plants ha−1, and an optimal irrigation quota of 540 mm was used. The results showed that during the irrigation period, (1) the soil moisture content (SMC), DM, leaf Pn, and grain yield of treatment D6 were higher than for other irrigation intervals, (2) the leaf Pn and stomatal conductance (GS) of the leaves of treatments D3, D9, D12, and D15 were significantly correlated with the SMC of the 0–40 cm soil layer, and (3) the leaf Pn of treatment D6 was significantly positively correlated with SMC in the 0–60 cm soil layer but not significantly correlated with GS. Irrigation treatment D6 was found to maintain high SMC, provide a water environment favorable to the growth of maize, and increase the leaf Pn and DM, and thereby obtain maize grain yield (20.6–21.0 t ha−1). Therefore, an optimal irrigation interval could be beneficial for adjusting soil moisture, leaf Pn, and DM in order to increase maize grain yield with drip irrigation under mulch.

1. Introduction

With a rapidly growing world population, food and water resources face great challenges. Water security is the basis of food security [1], and the shortage of water resources is the main problem limiting agricultural production in arid areas [2]. Therefore, the development of water-saving agriculture to improve the efficient use of water resources is an effective way to achieve the sustainable development of agriculture in arid areas.
Maize (Zea mays L.) is a staple crop around the world and plays an important role in ensuring food security [3]. Many studies have shown that increasing planting density is an effective way to increase maize yield [4,5,6,7]. Improving crop yield per unit land area is a key measure for increasing food security. Furthermore, irrigation is an important measure for increasing grain production. Drip irrigation and plastic film mulching are novel agricultural water conservation technologies that have been widely used in crop production [8]. Irrigation quota and interval are the most important parameters in crop irrigation management. Reasonable irrigation systems are conducive to the improvement in crop yield and the efficient use of water. Therefore, improving agricultural water productivity and grain yield through integrated measures is an important measure for ensuring water and food security.
Irrigation interval is an important factor in drip irrigation management as it affects soil moisture and its distribution [9,10]. Ran et al. [11] showed that under drip irrigation, the optimal irrigation interval (seven days) is conducive to the uniform distribution of soil water. Meanwhile, they found that a high irrigation interval (four days) resulted in high soil water content in the 0–40 cm soil layer and low soil water content in the 40–100 cm soil layer, resulting in a certain degree of water stress. Finally, the same authors showed that a low irrigation interval (10 days) was beneficial to water infiltration and lateral infiltration, leading to a high deep soil moisture content; however, since water replenishment was not timely, surface soil moisture content was low, and additionally this interval caused different levels of water stress. Under quota irrigation, excessively long or short irrigation intervals are normally not conducive to the distribution of soil moisture and the increase in soil water storage. Furthermore, excessively long irrigation intervals may cause water stress, and can also lead to substantial percolation below the root zone during irrigation since the large irrigation amount during each irrigation may exceed the soil water storage capacity. In contrast, excessively short irrigation intervals can lead to a lower irrigation amount during each irrigation, which may cause water stress. An optimum irrigation interval establishes a balance between soil moisture and oxygen conditions in the crop root zone, maintains uniform moisture distribution, and reduces plant water stress throughout the growing season [12].
Photosynthesis is the physiological basis for the formation of maize grains, with more than 90% of the dry matter in maize grains originating from photosynthesis in leaves [13]. Peng et al. [14] observed a positive correlation between leaf Pn and biomass and grain production in grain sorghum lines. Moreover, positive correlations have been recorded between crop Pn and dry matter production [15,16], while other studies have shown that the increase in Pn can increase crop yields [17]. Soil water stress is one of the most important factors restricting plant photosynthesis and growth [18]. In general, water stress reduces the photosynthetic capacity of plants, resulting in the decrease in photosynthetic rate and stomatal conductance, and thus affects the material production and yield formation of plants; the longer the stress lasts, the greater the decrease in the photosynthetic rate of plants [19,20]. Under mild water stress conditions, stomatal limitation is a main factor in the reduction in leaf photosynthetic rate, while under severe water stress, non-stomatal limitation is the main factor [18,21,22,23]. However, studies have shown that as maize Pn decreased during water stress, when plants were rewatered after the photosynthesis rate had dropped to 5–10% of its original value, maize Pn showed near full recovery in 2–4 days [24]. Additionally, Miyashita et al. [25] found that for water-stressed kidney bean, after rewatering, the rate of recovery of photosynthesis, transpiration, and stomatal conductance decreased gradually with increasing number of days without watering. Furthermore, studies have shown that, in cotton under water stress, leaf photosynthesis can quickly recover after rewatering and remains at a higher level for a longer period, thus increasing yield [26]. Generally, the irrigation interval affects the soil moisture status. If the irrigation interval is too long or too short, it will cause different degrees of water stress, which is not conducive to the photosynthesis and material production of the crop. Thus, determining the optimum irrigation interval is beneficial for the improvement in crop Pn, dry matter accumulation, and yield.
In a previous study, we obtained the optimum irrigation amount (540 mm) of super high-yield (17.4 t ha−1) maize with an irrigation interval of 9 days [27]. Therefore, in order to further explore and perfect ways to increase maize yield using water-saving irrigation technology, we hypothesized that optimizing the irrigation interval would further increase the leaf Pn and dry matter accumulation of super high-yield maize and thus increase grain yield. Thus, the objectives of the study were (i) to determine how irrigation interval affects dry matter accumulation and grain yield and (ii) to determine how irrigation interval affects maize Pn. The findings of this study not only clarify the maize high yield mechanism but should also be helpful for perfecting irrigation technology.

2. Materials and Methods

2.1. Experimental Region and Site

Field experiments were conducted during the maize growing season (April to October) in 2016 and 2017 at Qitai Farm (43°50′ N, 89°46′ E, altitude: 1020 m a.s.l.), located in the Xinjiang Uygur Autonomous Region, China. The climate in this region is characterized by minimal rainfall and abundant sunshine, and the diurnal temperature range is large. During the maize growing season, the total precipitation was 208.2 and 166.0 mm in 2016 and 2017, respectively, and the average sunshine hours were 7.8 and 8.3 h, respectively. Figure 1 shows the precipitation and average air temperature during the maize growing seasons in each of the two years.
The soil in the experimental field was sandy loam, and the top layer (0–60 cm) contained 23.1% clay, 35% silt, and 41.6% sand. The soil pH was 7.8, the bulk density was 1.29 g cm−3, and the field capacity was 23.15 g g−1. The organic matter, total N, available P, and available K contents in the upper 60 cm of soil were 14.9, 1.46, 49.7, and 99.7 mg kg−1, respectively. These physical and chemical properties were measured at the beginning of each field experiment.

2.2. Experiment Design and Field Management

Xianyu335 (XY335), a density-tolerant maize hybrid that is widely planted in China, was used in the current study. A single-factor randomized block design was used in the experiment. Three irrigation intervals were used in 2016, namely six days (D6), nine days (D9) (D9 is the irrigation interval used by local farmers), and 12 days (D12). Five irrigation intervals were used in 2017, namely three days (D3), six days (D6), nine days (D9), 12 days (D12), and 15 days (D15). Water supply was based on the local optimal irrigation quota (540 mm) and was applied via drip irrigation with a plastic-film mulching system [27]. The planting density was 12.0×104 plants ha−1 in both years. One day after sowing, 15 mm of water was applied to ensure uniform and rapid germination. To prevent late lodging and to harden seedlings, no irrigation was applied from sowing to 60 days after sowing [28]. The number of irrigation applications and the single irrigation amount of each irrigation interval in the irrigation cycle were 21 applications of 25 mm (D3), 12 applications of 43.75 mm (D6), nine applications of 58.33 mm (D9), seven applications of 75 mm (D12), and six applications of 87.5 mm (D15), respectively.
Maize was sown on 18 April in 2016 and on 21 April in 2017 and was harvested on 18 October in both 2016 and 2017. Plants were seeded in alternating wide and narrow rows (alternating row widths of 70 and 40 cm, respectively), and the spacing between plants within a row was 15 cm. The area of each plot was 66 m2 (10 × 6.6 m), and each irrigation treatment with three replications. Drip irrigation and plastic-film mulching were applied in both years. The drip irrigation system included single-wing drip tape (Tianye Inc., Shihezi, China) placed in the middle of each narrow row. The emitter spacing was 30 cm and the flow rate was 3.2 L h−1 at an operating pressure of 0.1 MPa. Each plot was connected to a precision water meter (LXS-25F, Ningbo Water Meter Co., Ltd., Ningbo, China) and a control valve. Water movement between plots was prevented by waterproof membranes buried at a depth of 100 cm below the soil surface between each plot and by 1-m-wide buffer zones between plots [28].
Before sowing, base fertilizers were applied at concentrations of 69 kg N ha−1 (urea, N 46%), 99 kg P ha−1 (ammonium phosphate, P2O5 44%), and 37.5 kg K ha−1 (potassium sulfate, K2O 50%). An additional 276 kg N ha−1 (urea, N 46%) was applied during the growing stage to ensure an adequate supply of nutrients. Chemical control (DA-6 Ethephon, China Agrotech, Shanxi, China) was applied at 600 mL ha−1 in the V8–V10 periods of maize. All weeds, diseases, and pests were controlled in the experimental plots [28].

2.3. Sampling and Measurements

Soil moisture content (SMC) was measured in 20-cm-thick soil layers (0–100 cm in depth) using the oven-drying method and a time-domain reflector (TDR, TRIME-T3, IMKO Inc., Switzerland, Germany). SMC was measured before sowing and at physiological maturity. In all treatments, five 100-cm-long trime tubes were deployed under the drip tape and between the drip tape and plants after sowing and in each year. Samples were collected before sowing, at physiological maturity, after rainfall, and one day before and after irrigation.
Additionally, five consecutive plants were collected from each plot during silking and physiological maturity, respectively, in order to determine plant aboveground dry matter. Plants were separated into stems, leaves, husks, and kernel fractions and were dried in an oven at 105 °C for 30 min and then at 80 °C to achieve a constant weight. The harvest index (HI) was calculated as the ratio between grain dry matter and total aboveground dry matter.
Furthermore, the photosynthetic rate (Pn) and stomatal conductance (GS) of the leaves were measured with a portable photosynthesis system (LI-6400, LI-COR Inc. Lincoln, NE, USA) in the silking to physiological maturity of maize plants; this was measured ten times and sixteen times in 2016 and 2017, respectively. Five ear leaves were randomly selected from each of five plants grown in each irrigation interval plot to measure leaf gas exchange, with three replicates per ear leaf, between 11:30 and 14:00 h local time on a clear day. During the measurements, the light intensity was set to 2000 μmol m−2 s−1, the air relative humidity was 75 ± 5%, the ambient CO2 concentration was 380 μmol mol−1, and the leaf temperature was the ambient temperature. The integral of Pn from 100–160 days (2016) and 95–160 days (2017) after sowing was calculated the area of the abscissa and the curve of Pn by using Origin 18.0 (OriginLab, MA, USA) software.
After maize physiological maturity, 13.2 m2 (central six rows (3.3 m) of each plot, 4 m long) were harvested from the three plots, and the grain mass was measured, respectively. The ears were determined for each plot. Twenty ears were collected from the middle four rows of each plot, and the kernel number per ear and 1000-kernel weight were measured. Grain yield was calculated at 14% moisture content, as determined using a PM-8188 portable moisture meter (Kett Electric Lab, Tokyo, Japan).

2.4. Statistical Analysis

Analysis of variance was used to test for differences in grain yield, dry matter, and HI as a function of irrigation interval. Means were compared using Fisher’s least significant difference tests with p < 0.05 (LSD0.05). Calculations were performed and charts were prepared using the Microsoft Excel 2019 (Microsoft Corporation, Redmond, WA, USA) and Sigmaplot 12.5 (Systat Software Inc., San Jose, CA, USA) softwares. Pn integral was calculated using Origin 18.0 (Origin Lab, MA, USA) software.

3. Results

3.1. Grain Yield and Yield Components

The grain yield of treatment D6 was the highest (20.6–21.0 t ha−1) in both years (Table 1). In 2016, the grain yield of D6 was 3.8% and 10.1% higher than that of D9 and D12, respectively; in 2017, the grain yield of D6 was 6.6%, 5.0%, 9.4%, and 22.1% higher than that of D3, D9, D12, and D15, respectively. Irrigation interval had no significant effect on the number of ears of maize. The 1000-kernel weight and the number of kernels per ear of treatment D6 were the highest in both years.

3.2. Dry Matter Accumulation and Harvest Index

The total dry matter accumulation at maturity, pre-flowering DM, post-flowering DM and HI of treatment D6 were significantly higher than those of other treatments in both years. In 2016, the DM and HI decreased with increasing irrigation interval. In 2017, the DM and HI increased first and then decreased with increasing irrigation interval (Table 2).

3.3. Photosynthetic Rate (Pn)

There were differences in Pn before and after irrigation at different irrigation intervals, and Pn decreased to varying degrees with increasing number of days after sowing (Figure 2). The Pn of treatment D6 changed little after irrigation compared to before irrigation. The Pn of treatments D3, D9, D12, and D15 increased significantly after irrigation, but it did not reach the original Pn level after rewatering. The Pn values of all of the treatments decreased with increasing number of days after sowing, and reached a minimum at maturity. At physiological maturity, the Pn of treatment D6 was 11.7%, 7.0%, 21.4%, and 48.4% higher than that of D3, D9, D12, and D15, respectively. The change trend of Pn at different irrigation intervals was similar between the two study years, however the Pn was generally higher in 2017 than in 2016.
Differences in Pn before and after irrigation at different irrigation intervals are shown in Table 3. In 2016, the decrease amplitude in Pn for the D6 treatment was 51.7% and 63.4% lower than that of the D9 and D12 treatments, respectively. In 2017, the decrease amplitude of Pn for treatment D6 was 54.71%, 46.53%, 60.31%, and 84.29% lower than that of treatments D3, D9, D12, and D15, respectively. The greater the change in Pn after irrigation compared to the value before irrigation, the greater the drought stress on the maize leaves, and the longer the interval between irrigations, the greater the effect on the leaf Pn. By calculating the integral of Pn from 100–160 days (2016) and 95–160 days (2017) after sowing, it was found that, in 2016, the Pn integral of treatment D6 was 10.0% and 17.6% higher than that of treatments D9 and D12, respectively, and 15.9%, 7.2%, 17.4%, and 28.7% higher than that of treatments D3, D9, D12, and D15, respectively. The fact that the Pn integral of D6 was higher than that of the other treatments indicates that the photosynthetic capacity of D6 was higher than that of other treatments. The Pn integral showed a significant correlation with pre-flowering and post-flowering DM and a significant correlation with grain yield (Figure 3). This shows that Pn affects the DM in maize and ultimately affects grain yield.

3.4. Soil Moisture Content (SMC)

The average SMC of each soil layer treated with different irrigation intervals during the irrigation period was different (Table 4). In previous research, we analyzed the dynamic changes in soil water storage under different irrigation intervals [28], and the results showed that the soil water storage of the 0–60 cm soil layer differed greatly between irrigation intervals. In this study, we further analyzed the SMC of 0–20, 20–40, and 40–60 cm layers, and found that treatment D3 caused a soil moisture deficit at depth; compared with treatment D3, the SMC of the 20–40 cm soil layer was relatively high in other treatments, and the average SMC of each layer in treatment D6 was higher than that of the other treatments. These results suggest that the longer the irrigation interval, the greater the water stress.

3.5. Relationship between Soil Moisture Content and Photosynthetic Rate

The soil moisture content in different layers was found to affect Pn. The Pn was significantly linearly positively correlated with the SMC of the 0–20, 20–40, and 40–60 cm soil layers (Figure 4). From the slope of linear equations of Pn and SMC, the Pn was more strongly correlated with the SMC as the soil depth increases. The relationship between SMC and Pn in different soil layers under different irrigation intervals is shown in Figure 5. In treatments D3, D9, D12, and D15, the SMC of the 0–20 cm and 20–40 cm layers were significantly correlated with Pn, and the SMC of the 20–40 cm layer was more strongly correlated with Pn. In treatment D6, the SMC of the 0–20, 20–40, and 40–60 cm layers were significantly correlated with Pn, with the SMC of 40–60 cm being most strongly correlated with Pn. In treatments D3, D9, D12, and D15, there was no significant correlation between SMC and Pn in the 40–60 cm soil layer.

3.6. Relationship between Soil Moisture Content and Stomatal Conductance

Soil moisture content was found to affect the degree of stomatal closure and GS of leaves (Figure 6). In treatments D3, D9, D12, and D15, a significant linear relationship was shown between SMC and GS in the 0–20 and 20–40 cm soil layers, however, no correlation was observed between SMC and GS in the 40–60 cm soil layer. In treatment D6, there was no correlation between SMC and GS in any soil layer. Additionally, in treatment D6, when the SMC decreased, the SMC significantly affected the GS of leaves, however, when the SMC was high, the SMC did not significantly affect the GS. In treatment D6, the spatial and temporal distribution of SMC was relatively uniform and the GS was not affected by SMC.

4. Discussion

Irrigation interval is an important factor for drip-irrigation management since it affects soil moisture distribution, water uptake by roots, and soil moisture content [29,30]. As irrigation interval decreases, the upper-layer soil moisture increases within a certain range and the upper soil layer storage increases [30,31]. Selecting an appropriate irrigation interval can increase soil moisture content. In the present study, it was found that irrigation interval D6 maintained a favorable soil moisture environment in the upper 60 cm soil layer. These results were also reported in Zhang et al. [28]. Based on the results of Zhang et al. [28], the present study found that the effect of irrigation interval on SMC was different in different soil layers (Table 4). In the 0–60 cm soil layer, the average SMC of different soil layers was highest in treatment D6. The main reason for this is that treatment D6 led to the highest soil water storage and lowest evapotranspiration and soil water evaporation of all the treatments [28].
The results of the present study suggest that different irrigation levels lead to different soil moisture content and water stress, and the soil moisture regime affects crop photosynthesis. The results of the present study show that the soil moisture content of the 0–60 cm soil layer has a very significant positive correlation with Pn, and that the greater the soil depth, the greater the impact of soil moisture content on Pn (Figure 4). Different irrigation intervals were found to lead to different SMCs and different effects of SMC on Pn. In treatments D3, D9, D12, and D15, the SMC in the 0–60 cm soil layer was lower than in treatment D6 (Table 4) and the Pn was lower than in treatment D6 (Figure 2). Since treatment D6 maintained a higher SMC than the other treatments, while other irrigation interval treatments were subjected to different degrees of water stress [28], water stress caused stomata to close and Pn to decline [32]. Generally, according to the effect of SMC on crop Pn, the Pn of leaves is indirectly affected by stomatal and non-stomatal constraints. Liu et al. [33] showed that stomatal limitation is the main reason for the decline in crop Pn under water stress. Wu et al. [34] showed that the slight water deficit is due to the decrease in GS, which limits Pn, with increasing water deficit, the main factor affecting Pn changes from stomatal limitation to non-stomatal limitation. Similar results were obtained in the present study, where it was observed that, as the average SMC decreased during the irrigation period, the Pn also decreased [35]. The possible reason for the decrease in Pn is that water stress inhibits GS. In the present study, it was found that for treatment D3, the SMC of the 0–60 cm soil layer was lower and the Pn was higher than for treatments D12 and D15 (Table 3). The possible reason for this is that the irrigation interval of treatment D3 is short, which may have caused a slight water deficit and it has a compensation effect after rewatering and enhances Pn. This result is consistent with previous studies [36,37,38,39]. However, in treatments D3, D9, D12, and D15, the soil moisture content of the 40–60 cm soil layer has no significant relationship with GS and Pn (Figure 5 and Figure 6). A possible reason for this is that the SMC of this soil layer is low, and the water stress can inhibit the stomata opening to some extent, which leads to a change in GS from stomatal limitation to non-stomatal limitation during irrigation. Meanwhile, for treatment D6, the SMC in the 0–60 cm soil layer was not significantly related to GS, but was significantly related to Pn, indicating that the spatial and temporal distribution of SMC in this treatment was relatively uniform; in turn, this suggests that this treatment provided a good water environment for maize, and that the plant was not stressed and SMC did not affect GS, resulting in a high Pn. Additionally, the results show that the Pn of each treatment was higher in 2017 than in 2016. A possible reason for this is that there were more rainy days in 60–120 days after sowing in 2016, which may have reduced the Pn of maize.
Irrigation interval is an important factor affecting crop growth in an irrigation system. Under the condition of quota irrigation, the optimal irrigation interval is conducive to crop dry matter accumulation and yield improvement [40,41]. Leaf Pn is an important indicator of plant photosynthesis, which directly determines the level of plant productivity [42]. Irrigation interval affects crop photosynthesis and dry matter production by affecting soil moisture. Reddy et al. [43] showed that excessively long or short irrigation intervals are not conducive to crop growth and yield improvement. This can be attributed to the fact that soil water stress decreases the Pn and GS, which finally results in the decrease in crop biomass and yield [19,44]. Under long-term water stress, Pn decreases, resulting in a reduction in the capacity for the production of photosynthetic material, a sharp decline in the ability to build carbon reservoirs, and a significant decline in grain yield [13]. In this study, the irrigation interval was found to affect soil moisture. Nevertheless, it was also found that soil water affected the Pn and material accumulation of maize, and the relationship between the dry matter accumulation of grain yield and irrigation interval was quadratic. Treatment D6 achieved the highest 1000-kernel weight and the number of kernels per ear and grain yield (20.6–21.0 t ha−1) and highest pre-flowering and post-flowering DM accumulation in both study years (Table 1 and Table 2). These results indicate that the irrigation interval treatment affects the yield of maize by affecting the DM, 1000-kernel weight and grain number per ear. Thus, a suitable irrigation interval thus conducive to growth and development of maize, and thereby increase maize yield. The grain yield of D6 obtained in the present study was 20.7% higher than that obtained by Zhang et al. [27] (17.4 t ha−1) for the same area and conditions. The main reasons that D6 achieved the highest grain yield of all treatments is that it maintained a favorable soil moisture environment in the upper 60 cm soil layer and improved photosynthetic production and dry matter accumulation. In the present study, the observed trend of dry matter accumulation is consistent with the trend of Pn. These results are similar to those of previous studies [14,15,16]. If the irrigation interval is too short, the irrigation water remains on the soil surface and cannot be absorbed and utilized by the root system, which will cause crop water stress, and thus affect the Pn and dry matter accumulation and eventually lead to a decline in grain yield. Meanwhile, if the irrigation interval is too long, the crops will also be subject to water stress, which will reduce the Pn and dry matter accumulation, leading to a decrease in grain yield. Therefore, an appropriate irrigation interval is helpful to improve the Pn and dry matter accumulation of maize and thereby increase grain yield.

5. Conclusions

Soil moisture, leaf Pn, GS, dry matter accumulation, and grain yield were investigated as a function of irrigation interval for drip irrigation under mulch at an experimental site in the Xinjiang, Northwestern China. Under the irrigation quota of 540 mm, the optimum irrigation interval was found to be six days. At this interval, the upper 60 cm soil layer maintained a high soil moisture content, producing a soil moisture environment favorable to maize growth, and additionally increased leaf Pn and increased dry matter accumulation, thereby increasing maize grain yield. Grain yield reached from 20.6 to 21.0 t ha−1. These results show that an optimum irrigation interval helps optimize soil moisture content and increases leaf Pn and dry matter accumulation, and thereby increases crop grain yield. Similar management practices may be applied in similar soil types and climates.

Author Contributions

K.W., R.X. and S.L. conceived and designed the experiment; D.S. and G.Z. performed the experiments; D.S., G.Z., B.M., P.H. and J.X. analyzed the data; D.S. and G.Z. wrote the paper; K.W. and S.L. revised the final draft manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key Research and Development Program of China (Grant No. 2016YFD0300605), the China Agriculture Research System (CARS-02-25), and the Agricultural Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences.

Acknowledgments

The authors thank the reviewers for their valuable comments and suggestions.

Conflicts of Interest

The authors declare that there are no conflict of interest.

References

  1. Kang, S.Z. Special issue: Improving agricultural water productivity to ensure food security under changing environments. Agric. Water Manag. 2017, 179, 1–4. [Google Scholar] [CrossRef]
  2. Wang, J.X.; Li, Y.R.; Huan, J.K.; Yan, T.T.; Sun, T.H. Growing water scarcity, food security and government responses in China. Glob. Food Secur. 2017, 14, 9–17. [Google Scholar] [CrossRef]
  3. Li, S.K.; Zhao, J.R.; Dong, S.T.; Zhao, M.; Li., C.H.; Cui, Y.H.; Liu, Y.H.; Gao, J.L.; Xue, J.Q.; Wang, L.C.; et al. Advances and prospects of maize cultivation in China. Acta. Agron. Sin. 2017, 50, 1941–1959. [Google Scholar]
  4. Tollenaar, M.; Lee, E.A. Yield potential, yield stability and stress tolerance in maize. Field Crops Res. 2002, 75, 161–169. [Google Scholar] [CrossRef]
  5. Grassini, P.; Thorburn, J.; Burr, C.; Cassman, K.G. High-yield irrigated maize in the Western U.S. Corn Belt: I. On-farm yield, yield potential, and impact of agronomic practices. Field Crops Res. 2011, 120, 142–150. [Google Scholar] [CrossRef] [Green Version]
  6. Li, J.; Xie, R.Z.; Wang, K.R.; Ming, B.; Guo, Y.Q.; Zhang, G.Q.; Li, S.K. Variations in maize dry matter, harvest index, and grain yield with plant density. Agron. J. 2015, 107, 829–834. [Google Scholar] [CrossRef]
  7. Li, J.; Xie, R.Z.; Wang, K.R.; Hou, P.; Ming, B.; Zhang, G.Q.; Liu, G.Z.; Wu, M.; Yang, Z.S.; Li, S.K. Response of canopy structure, light interception and grain yield to plant density in maize. J. Agric. Sci. 2018, 156, 785–794. [Google Scholar] [CrossRef]
  8. Qin, S.J.; Li, S.E.; Kang, S.Z.; Du, T.S.; Tong, L.; Ding, R.S. Can the drip irrigation under film mulch reduce crop evapotranspiration and save water under the sufficient irrigation condition? Agric. Water Manag. 2016, 177, 128–137. [Google Scholar] [CrossRef]
  9. Sensoy, S.; Ertek, A.; Gedik, I.; Kucukyumuk, C. Irrigation frequency and amount affect yield and quality of field-grown melon (Cucumis melo L.). Agric. Water Manag. 2007, 88, 269–274. [Google Scholar] [CrossRef]
  10. Liu, M.X.; Yang, J.S.; Li, X.M.; Yu, M.; Wang, J. Effects of irrigation amount and frequency on soil water distribution and water use efficiency in a cotton field under mulched drip irrigation. Chin. J. Eco-Agric. 2011, 22, 3203–3210. [Google Scholar]
  11. Ran, H.; Jiang, G.Y.; Xu, H.J.; Li, M.G.; Hao, M.C. Effects of irrigation frequency and nitrogen rate on dry matter accumulation and yield of spring wheat under drip irrigation. J. Triticeae Crops. 2015, 35, 379–386. [Google Scholar]
  12. Wan, S.Q.; Kang, Y.H. Effect of drip irrigation frequency on radish (Raphanus sativus L.) growth and water use. Irrig. Sci. 2006, 24, 161–174. [Google Scholar] [CrossRef]
  13. Dai, J.Y.; Shen, X.Y.; Xu, S.C.; Wang, L.Z.; Zhu, Y.L. Effect of water stress on photosynthetic performance and yield of Maize. Acta. Agron. Sin. 1995, 3, 108–115. [Google Scholar]
  14. Peng, S.B.; Krieg, D.R.; Girma, F.S. Leaf photosynthetic rate is correlated with biomass and grain production in grain sorghum lines. Photosynth. Res. 1991, 28, 1–8. [Google Scholar] [CrossRef] [PubMed]
  15. Crosbie, T.M.; Pearce, R.B.; Mock, J.J. Relationship among CO2-exchange rate and plant traits in Iowa Stiff Stalk Synthetic maize population. Crop Sci. 1978, 18, 87–90. [Google Scholar] [CrossRef]
  16. Dwyer, L.M.; Tollenaar, M.; Stewart, D.W. Changes in plant density dependence of leaf photosynthesis of maize (Zea mays L.) hybrids, 1959 to 1988. Can. J. Plant Sci. 1991, 71, 1–11. [Google Scholar] [CrossRef] [Green Version]
  17. Long, S.P.; Zhu, X.G.; Naidu, S.L.; Ort, D.R. Can improvement in photosynthesis increase crop yields? Plant. Cell Environ. 2006, 29, 315–330. [Google Scholar] [CrossRef]
  18. Chaves, M.M.; Pereira, J.S.; Maroco, J.; Rodrigues, M.L.; Ricardo, C.P.P.; Osorio, M.L.; Carvalho, I.; Faria, T.; Pinheiro, C. How plants cope with water stress in the field. Photosynthesis and growth. Ann. Bot. 2002, 89, 907–916. [Google Scholar] [CrossRef] [Green Version]
  19. Liu, Z.G.; Chen, J.P.; Duan, A.W.; Meng, Z.J.; Zhang, J.Y.; Liu, Z.D. Effects of different soil water treatments on Photosynthetic and other physiological characteristics of summer maize leaves. Agric. Res. Arid. Areas 2006, 1, 91–95. [Google Scholar]
  20. Hirasawa, T.; Hsiao, T.C. Some characteristics of reduced leaf photosynthesis at midday in maize growing in the field. Field Crops Res. 1999, 62, 53–62. [Google Scholar] [CrossRef]
  21. Farquhar, G.D.; Sharkey, T.D. Stomatal conductance and photosynthesis. Annu. Rev. Plant Physiol. 1982, 33, 317–345. [Google Scholar] [CrossRef]
  22. Flexas, J.; Bota, J.; Loreto, F. Diffusive and metabolic limitations to photosynthesis under drought and salinity in C3 plants. Plant Biol. 2004, 6, 269–279. [Google Scholar] [CrossRef] [PubMed]
  23. Zhou, S.X.; Duursma, R.A.; Medlyn, B.E.; Kelly, J.W.G.; Prentice, I.C. How should we model plant responses to drought? An analysis of stomatal and non-stomatal responses to water stress. Agric. For. Meteorol. 2013, 182–183, 204–214. [Google Scholar] [CrossRef]
  24. Lal, A.; Edwards, G.E. Analysis of Inhibition of Photosynthesis under Water Stress in the C4 Species Amaranthus cruentus and Zea mays: Electron transport, CO2 fixation and carboxylation capacity. Aust. Plant Physiol. 1996, 23, 403–412. [Google Scholar] [CrossRef]
  25. Miyashita, K.; Tanakamaru, S.; Maitani, T.; Kimura, K. Recovery responses of photosynthesis, transpiration, and stomatal conductance in kidney bean following drought stress. Environ. Exp. Bot. 2005, 53, 205–214. [Google Scholar] [CrossRef]
  26. Luo, H.H.; Zhang, Y.L.; Zhang, W.F. Effects of water stress and rewatering on photosynthesis, root activity, and yield of cotton with drip irrigation under mulch. Photosynthetica 2015, 54, 65–73. [Google Scholar] [CrossRef]
  27. Zhang, G.Q.; Liu, C.W.; Xiao, C.H.; Xie, R.Z.; Ming, B.; Hou, P.; Liu, G.Z.; Xu, W.J.; Shen, D.P.; Wang, K.R.; et al. Optimizing water use efficiency and economic return of super high yield spring maize under drip irrigation and plastic mulching in arid areas of China. Field Crops Res. 2017, 211, 137–146. [Google Scholar] [CrossRef]
  28. Zhang, G.Q.; Shen, D.P.; Ming, B.; Xie, R.Z.; Jin, X.L.; Liu, C.W.; Hou, P.; Xue, J.; Chen, J.L.; Zhang, W.X.; et al. Using irrigation intervals to optimize water-use efficiency and maize yield in Xinjiang, northwest China. Crop J. 2019, 7, 322–334. [Google Scholar] [CrossRef]
  29. El-Hendawy, S.E.; Hokam, E.M.; Schmidhalter, U. Drip irrigation frequency: The effects and their interaction with nitrogen fertilization on sandy soil water distribution, maize yield and water use efficiency under Egyptian conditions. J. Agron. Crop Sci. 2008, 194, 180–192. [Google Scholar] [CrossRef]
  30. Wang, F.X.; Kang, Y.H.; Liu, S.P. Effects of drip irrigation frequency on soil wetting pattern and potato growth in North China Plain. Agric. Water Manag. 2006, 79, 248–264. [Google Scholar] [CrossRef]
  31. Cao, H.X.; Kang, S.Z.; He, H. Effects of evaporation and irrigation frequency on soil water distribution. Trans. CSAE 2003, 19, 1–4. [Google Scholar]
  32. Bonyor, J.S. Plant productivity and environment. Science 1982, 218, 443–448. [Google Scholar]
  33. Liu, M.; Qi, H.; Sun, S.X.; Bai, X.L.; Jiang, W.C.; Yang, G.H.; Zhang, Z.; Liang, P.Y.; Meng, X.H.; Cong, X. Effects of water stress on photosynthetic characteristics of maize. J. Maize Sci. 2008, 16, 86–90. [Google Scholar]
  34. Wu, H.X.; Guo, L.L.; Hao, L.H. Effects of water and CO2 concentration on stomatal characteristics, gas exchange parameters and biomass of Winter Wheat. Acta. Agron. Sin. 2018, 44, 1570–1576. [Google Scholar]
  35. Flexas, J.; Galmes, J.; Medrano, H.; Ribas-Carbo, M. Keeping a positive carbon balance under adverse conditions: Responses of photosynthesis and respiration to water stress. Physiol. Plantarum. 2006, 127, 343–352. [Google Scholar] [CrossRef]
  36. Kang, S.Z.; Shi, W.J.; Zhang, J.H. An improved water-use efficiency for maize grown under regulated deficit irrigation. Field Crops Res. 2000, 67, 207–214. [Google Scholar] [CrossRef]
  37. Romero, P.I.; Dodd, C.; Martinez-Cutillas, A. Contrasting physiological effects of partial root zone drying in field-grown grapevine (Vitis vinifera L. cv. Monastrell) according to total soil water availability. J. Exp. Bot. 2012, 63, 4071–4083. [Google Scholar] [CrossRef] [Green Version]
  38. Chai, Q.; Gan, Y.; Zhao, C.; Xu, H.L.; Waskom, R.M.; Niu, Y.; Siddique, K.H.M. Regulated deficit irrigation for crop production under drought stress. A review. Agron. Sustain. Dev. 2015, 36, 1–21. [Google Scholar] [CrossRef] [Green Version]
  39. Ali, S.; Xu, Y.Y.; Jia, Q.M.; Ahmad, I.; Wei, T.; Ren, X.L.; Zhang, P.; Din, R.X.; Cai, T.; Jia, Z.K. Cultivation techniques combined with deficit irrigation improves winter wheat photosynthetic characteristics, dry matter translocation and water use efficiency under simulated rainfall conditions. Agric. Water Manag. 2018, 201, 207–218. [Google Scholar] [CrossRef]
  40. Ertek, A.; Şensoy, S.; Küçükyumuk, C.; Gedik, İ. Irrigation frequency and amount affect yield components of summer squash (Cucurbita pepo L.). Agric. Water Manag. 2004, 67, 63–76. [Google Scholar] [CrossRef]
  41. Qin, J.H.; Chen, Y.J.; Zhou, C.Y.; Pang, B.P.; Meng, M.L. Effects of frequency of drip irrigation frequency under mulch on potato growth, yield and water use efficiency. Chin. J. Eco-Agric. 2013, 21, 824–830. [Google Scholar] [CrossRef]
  42. Wang, L.; Dong, S.T.; Liu, P.; Zhang, J.W.; Zhao, B. Effects of water nitrogen interaction on Photosynthetic Physiological Characteristics and yield of Winter Wheat. J. Soil Water Conserv. 2018, 32, 301–308. [Google Scholar]
  43. Reddy, S.R.; Chalam, P.S.; Sankara, G.; Reddi, H.; Raju, A.P. Effect of irrigation frequency and nitrogen on groundnut yield and nutrient uptake. Plant Soil 1982, 65, 257–263. [Google Scholar] [CrossRef]
  44. Sobrado, M.A.; Turner, N.C. Photosynthesis, dry matter accumulation and distribution in the wild sunflower Helianthus petiolaris and the cultivated sunflower Helianthus annuus as influenced by water deficits. Oecologia 1986, 69, 181–187. [Google Scholar] [CrossRef]
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Figure 1. Precipitation and average air temperature in the maize growing season during 2016 and 2017.
Figure 1. Precipitation and average air temperature in the maize growing season during 2016 and 2017.
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Figure 2. Changes of leaf photosynthetic rate of maize under different irrigation intervals. The abbreviations “DX” represent irrigation intervals of X days (e.g., “D6” represents an irrigation interval of six days).
Figure 2. Changes of leaf photosynthetic rate of maize under different irrigation intervals. The abbreviations “DX” represent irrigation intervals of X days (e.g., “D6” represents an irrigation interval of six days).
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Figure 3. The relationship between photosynthetic rate integral and dry matter accumulation (DM) (a) and grain yield (b). * significant at 0.05 level; ** significant at 0.01 level.
Figure 3. The relationship between photosynthetic rate integral and dry matter accumulation (DM) (a) and grain yield (b). * significant at 0.05 level; ** significant at 0.01 level.
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Figure 4. The relationship between soil moisture and leaf photosynthetic rate (Pn) in different soil layers. ** significant at 0.01 level.
Figure 4. The relationship between soil moisture and leaf photosynthetic rate (Pn) in different soil layers. ** significant at 0.01 level.
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Figure 5. Relationship between soil moisture content and leaf photosynthetic rate in different soil layers at different irrigation intervals. * significant at 0.05 level; ** significant at 0.01 level; ns—not significant at p0.05.
Figure 5. Relationship between soil moisture content and leaf photosynthetic rate in different soil layers at different irrigation intervals. * significant at 0.05 level; ** significant at 0.01 level; ns—not significant at p0.05.
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Figure 6. The relationship between soil moisture and stomatal conductance (GS) in different soil layers at different irrigation intervals. ** significant at 0.01 level; ns—not significant at p0.05.
Figure 6. The relationship between soil moisture and stomatal conductance (GS) in different soil layers at different irrigation intervals. ** significant at 0.01 level; ns—not significant at p0.05.
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Table
Table 1. Grain yield, ear number, kernel number, and kernel weight of maize at different irrigation intervals.
Table 1. Grain yield, ear number, kernel number, and kernel weight of maize at different irrigation intervals.
YearIrrigation IntervalEar Number (Ears m−2)Kernel no. per Ear1000-Kernel Weight (g)Grain Yield (t ha−1)
2016D611.9 ± 0.02 a524.6 ± 24.48 a385.0 ± 1.49 a20.6 ± 0.13 a
D911.9 ± 0.06 a495.4 ± 15.66 b358.1 ± 4.33 b19.8 ± 0.09 b
D1211.9 ± 0.06 a447.6 ± 25.49 c348.6 ± 4.90 c18.7 ± 0.15 c
2017D311.8 ± 0.08 a509.2 ± 39.62 b405.1 ± 2.42 b19.7 ± 0.18 b
D611.8 ± 0.09 a540.6 ± 33.39 a422.7 ± 1.62 a21.0 ± 0.08 a
D911.8 ± 0.08 a510.6 ± 29.03 b404.7 ± 0.79 b20.0 ± 0.25 b
D1211.8 ± 0.12 a467.7 ± 28.41 c379.1 ± 4.51 c19.2 ± 0.18 c
D1511.8 ± 0.09 a427.4 ± 38.30 d371.6 ± 1.72 d17.2 ± 0.20 d
Values were means ± STD. Means within a column followed by different letters differ significantly at p < 0.05.
Table
Table 2. Dry matter accumulation (DM) and harvest index at different irrigation intervals.
Table 2. Dry matter accumulation (DM) and harvest index at different irrigation intervals.
YearIrrigation IntervalPre-Flowering DM (kg m−2)Post-Flowering DM (kg m−2)Total DM at Maturity (kg m−2)HI
2016D61.72 ± 0.01 a2.74 ± 0.01 a4.46 ± 0.01 a0.53 ± 0.01 a
D91.61 ± 0.01 b2.46 ± 0.01 b4.07 ± 0.01 b0.52 ± 0.00 b
D121.50 ± 0.01 c2.08 ± 0.00 c3.58 ± 0.00 c0.51 ± 0.01 c
2017D31.77 ± 0.01 c2.29 ± 0.04 b4.07 ± 0.04 b0.52 ± 0.00 b
D61.86 ± 0.01 a2.51 ± 0.02 a4.37 ± 0.02 a0.53 ± 0.00 a
D91.80 ± 0.01 b2.27 ± 0.03 b4.08 ± 0.03 b0.52 ± 0.00 b
D121.67 ± 0.01 d1.98 ± 0.01 c3.65 ± 0.01 c0.51 ± 0.00 c
D151.57 ± 0.02 e1.72 ± 0.03 d3.29 ± 0.01 d0.50 ± 0.01 c
Values were means ± STD. Means within a column followed by different letters differ significantly at p < 0.05. DM, dry matter accumulation; HI, harvest index.
Table
Table 3. Changes of photosynthetic rate amplitude and integral before and after irrigation for different irrigation intervals.
Table 3. Changes of photosynthetic rate amplitude and integral before and after irrigation for different irrigation intervals.
YearIrrigation IntervalPn Amplitude (%)Pn Integral (μmol m−2s−1)
2016D610.01794.3
D920.71631.8
D1227.31526.4
2017D317.01671.7
D67.71937.9
D914.41807.7
D1219.41650.9
D1549.01505.8
Table
Table 4. Changes in the average soil moisture content of various soil layers during the irrigation period under different irrigation intervals.
Table 4. Changes in the average soil moisture content of various soil layers during the irrigation period under different irrigation intervals.
YearIrrigation IntervalAverage Soil Moisture Content (%)
0–20 cm20–40 cm40–60 cm0–60 cm
2016D623.5 ± 2.525.5 ± 1.724.9 ± 1.824.7 ± 1.88
D922.3 ± 3.223.8 ± 2.022.9 ± 2.423.0 ± 2.45
D1222.1 ± 3.523.5 ± 2.523.0 ± 2.622.9 ± 2.82
2017D318.6 ± 3.918.5 ± 3.618.8 ± 3.418.6 ± 3.2
D620.0 ± 3.524.3 ± 2.122.9 ± 1.822.4 ± 2.2
D919.8 ± 3.723.3 ± 2.420.8 ± 2.321.3 ± 2.4
D1218.8 ± 3.823.0 ± 2.321.5 ± 2.521.1 ± 2.7
D1518.2 ± 4.421.7 ± 3.519.4 ± 3.219.8 ± 3.4
Values were means ± STD.
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Shen, D.; Zhang, G.; Xie, R.; Ming, B.; Hou, P.; Xue, J.; Li, S.; Wang, K. Improvement in Photosynthetic Rate and Grain Yield in Super-High-Yield Maize (Zea mays L.) by Optimizing Irrigation Interval under Mulch Drip Irrigation. Agronomy 2020, 10, 1778. https://doi.org/10.3390/agronomy10111778

AMA Style

Shen D, Zhang G, Xie R, Ming B, Hou P, Xue J, Li S, Wang K. Improvement in Photosynthetic Rate and Grain Yield in Super-High-Yield Maize (Zea mays L.) by Optimizing Irrigation Interval under Mulch Drip Irrigation. Agronomy. 2020; 10(11):1778. https://doi.org/10.3390/agronomy10111778

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Shen, Dongping, Guoqiang Zhang, Ruizhi Xie, Bo Ming, Peng Hou, Jun Xue, Shaokun Li, and Keru Wang. 2020. "Improvement in Photosynthetic Rate and Grain Yield in Super-High-Yield Maize (Zea mays L.) by Optimizing Irrigation Interval under Mulch Drip Irrigation" Agronomy 10, no. 11: 1778. https://doi.org/10.3390/agronomy10111778

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