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Article

Effects of Solar Radiation on Dry Matter Distribution and Root Morphology of High Yielding Maize Cultivars

by
Xiaoxia Guo
1,2,
Yunshan Yang
1,
Huifang Liu
3,
Guangzhou Liu
2,
Wanmao Liu
3,
Yonghong Wang
4,
Rulang Zhao
4,
Bo Ming
2,
Ruizhi Xie
2,
Keru Wang
2,
Shaokun Li
1,* and
Peng Hou
2,*
1
The Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps, College of Agronomy, Shihezi University, Shihezi 832000, China
2
Key Laboratory of Crop Physiology and Ecology, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
3
College of Agronomy, Ningxia University, Yinchuan 750021, China
4
Institute of Crop Sciences, Ningxia Academy of Agricultural and Forestry Sciences, Yongning, Yinchuan 750105, China
*
Authors to whom correspondence should be addressed.
Agriculture 2022, 12(2), 299; https://doi.org/10.3390/agriculture12020299
Submission received: 21 January 2022 / Revised: 10 February 2022 / Accepted: 18 February 2022 / Published: 20 February 2022
(This article belongs to the Special Issue Physiological and Ecological Characteristics, and Sustainable Production of High Yield Maize)
Browse Figures
Versions Notes

Abstract

:
The root system connects the plant with the soil, which is a key factor in determining the utilization of soil resources and plant growth potential. Solar radiation can change maize shoot and root growth and affect grain formation. In this study, the effects of different solar radiation conditions on root morphology of three maize cultivars XY335, ZD958 and DH618 and their quantitative relationships were studied by conducting shading experiments. This study was conducted in maize high yield region of Qitai and Yinchuan, China, in 2018 and 2019. The planting densities were 7.5 × 104 (D1) and 12 × 104 (D2) plants ha−1. The shading levels were natural light (CK), shading 15% (S1), 30% (S2) and 50% (S3). The results showed that maize responded to the decreased solar radiation through the increase in ratio of shoot dry weight (SWR) to whole plant dry weight and the decrease in ratio of root dry weight (RWR) to whole plant dry weight. As the solar radiation decreased, the root length density (RLD), root surface area (RSA), average root diameter (ARD) and root length ratio (RLR) decreased, while the specific root length (SRL) increased. With 100 MJ m−2 decrease in solar radiation, the RWR, RLD, RSA and RLR each decreased by 1.47%, 0.5 mm cm−3,0.4 m m−2 and 0. 19 m g−1, respectively. Among the cultivars, the changes of DH618 were the fastest followed by XY335 and ZD958 but DH618 maintained the largest root system under any solar radiation condition. After the decrease of solar radiation, RWR, RLD and RLR were significantly positively correlated with the yield. This indicated that large root systems were conducive to the rapid response to decreased solar radiation and important for achieving stable and high yield. Maize cultivars with these type of root systems should be recommended to better adapt low solar radiation induced by regional variation or climate change.

1. Introduction

Solar radiation is an important ecological factor that affects crop growth and development and drives photosynthesis [1,2,3,4]. Enhancing photosynthesis also contributes to sustainable yield increases [5]. As is typical for C4 crops, maize has a stronger photosynthetic and material production capacity, yet ensuring suitable solar radiation conditions during the growth period of maize is of great importance for achieving a stable and high yield [6,7]. However, the solar radiation in China has decreased in recent years due to climate change and environmental pollution [8,9,10]. Especially in some maize growing areas, the maize growing season often encounters rainy weather, and the continuous dense cloud cover leads to less solar radiation [11,12]. Researchers have studied the effects of solar radiation on maize growth and development through shading experiments in order to alleviate the negative effects of solar radiation [13,14,15]. Overall, when solar radiation was decreased, the photosynthetic production capacity likewise decreased, and the accumulation of assimilates was insufficient [16,17]. At the same time, insufficient solar radiation leads to limited ear development, an unbalanced growth of female and male ears, a shortened grain filling period, and a final yield decline [18,19,20]. The plant growth is weak, and the risk of lodging also increases as solar radiation decreases [21,22].
The maize root system can effectively guarantee a connection between soil and plant, and this connection is important for obtaining soil resources. Roots help provide the necessary nutrients and water for plant vegetative and reproductive growth [23,24]. Good root system architecture contributes to nutrient and water absorption, and is one of the key determinants of plant growth potential [25,26]. The root system architecture includes root growth and spatial distribution, which has a high plasticity. Root growth refers to the comprehensive changes in the size and morphology of the root system. The biomass allocated to the root determines the size of the root and its ability to support the shoot [27]. Root morphology plays an important role in root development and function. The size and morphology of the root system determine the total volume of soil explored by the plant, and the total surface of exchange between roots and soil solution [28]. It is supposed that plants can optimize their root system architecture to adapt to unfavorable growth conditions [29,30]. Manipulating the root system architecture towards a distribution of roots in the soil that optimizes water and nutrient uptake, can both increase plant yield and optimize agricultural land use [31].
The root morphological parameters mainly include root length, average root diameter (ARD), and root surface area (RSA) [32]. Root morphology usually perceives external changes and can produce adaptive mechanisms through self-regulation [33]. When the external solar radiation changes, and the maize aboveground growth and development are limited, the photosynthate distributed to the root system is reduced, which affects root growth and morphological parameters [34]. The effect of solar radiation on maize root dry weight was shown to be greater than that on shoot dry weight. There is also a quantitative relationship between root dry weight and solar radiation [35]. However, whether the responses of maize shoot and root to solar radiation change are consistent remains unknown. It is also not clear whether there is a quantitative relationship between root morphology and solar radiation. As root morphology is more important to reflect the function of root than root dry weight [36,37], further research into the quantitative relationships between root morphology and solar radiation is essential for matching solar radiation to changes in the root system and increased grain yield.
The morphological differences among maize root system determines their absorption and utilization efficiency of water and nutrients and their adaptability to the environment [38]. It is an effective way to improve the utilization of soil resources to shape the appropriate root system, which is of great significance to further realize high yield [39]. With the improvement of cultivars, modern cultivars have a smaller root system than old cultivars, and the root biomass, root length and root surface area have decreased, showing the characteristics of “intra-row contraction and inter-row extension”, which has stronger adaptability to high fertilization level and high planting density [40,41]. In addition, the shoot of maize responded to the competition among plants through plant type adjustment. Research suggests that the upper leaves of the ear are more important at high density. When the yield potential increased from 15.0 Mg ha−1 to 22.5 Mg ha−1, the number of leaves on the upper ear increases by 0.8–1.1 [42]. The smaller stem–leaf angle is helpful for better light distribution at the bottom of the canopy, which can adapt to a larger population [43,44,45]. Therefore, modern cultivars have a high grain yield under a high planting density [46]. However, with the increase of planting density, light transmission decreases in the canopy, the aboveground growth is limited determining the less assimilates transported to the root system and results in poor root system [47,48]. However, there is limited research on the root morphology responses of different genotypes to changing solar radiations.
The plasticity of root morphology plays an important role in plant growth under the changing conditions of climate and solar radiation [49]. A few studies have focused on the effects of solar radiation on maize root system morphology by conducting shading experiments [50,51,52]. However, these studies were mainly conducted in regions of low solar radiation, which allow less flexibility in evaluating multiple solar radiation conditions [53,54]. Therefore, this study mainly analyzed the effects of solar radiation on maize shoot and root growth to make clear whether the effects were consistent and the quantitative relationship between morphology and solar radiation in the region with the highest solar radiation resources in China. The aim of this study is to provide a theoretical reference for high yield maize cultivar selection and breeding under different solar radiation conditions in different regions or induced by climate change.

2. Materials and Methods

2.1. Site Description and Weather Data

The field experiments were carried out in Qitai (Xinjiang Uygur Autonomous Re-gion, China, 43°50′ N, 89°46′ E) and Yinchuan (Ningxia Hui Autonomous Region, China, 38°13′ N, 106°14′ E) in 2018 and 2019. The specific location of the experiment site was shown in Figure 1. Each year it was sown in mid-April and harvested in mid-October. These are two locations among those with the highest solar radiation intensity in China. Qitai’s accumulated solar radiation during the maize growth period in 2018 and 2019 were 1702.8 and 1638.8 MJ m−2, and Yinchuan’s were 1682.7 and 1616.0 MJ m−2. The accumulated precipitation of Qitai during the maize growth period in 2018 and 2019 were 223.1 and 149.6 mm; and the average temperature were 16.8 and 18.2 °C, respectively. These data of Yinchuan were 181.9 and 132.8 mm; 20.9 and 21.0 °C, respectively (Figure 2).
The soil types of Qitai and Yinchuan are sandy soils. Soil total organic matter concentrations were 14.1 and 13.3 g kg−1, and alkaline-N were 87.6 and 64.5 mg kg−1, olsen-P were 53.8 and 19.9 mg kg−1, alkaline-K were 108.6 and 137.0 mg kg−1 in Qitai and Yinchuan, respectively [35].

2.2. Experiment Design

The experiment included 16 treatments (two cultivars, two densities and four shading levels) in both sites in 2018, 24 treatments (three cultivars, two densities and four shading levels) in Qitai, and 16 treatments in Yinchuan in 2019. The plot area was 110 m2, which includes 22 experimental rows of 10 m length and 0.55 m width, with a 1 m walkway between the plots. The shading period began when the plants were at the three-leaf stage and continued to the mature stage. Shading was achieved by building shade nets suitable for the required shading level at 1.5 m away from the maize canopy. The experiment adopted a split-plot design with three cultivars Xianyu 335 (XY335), Zhengdan 958 (ZD958), and Denghai 618 (DH618) as the main factor, two planting densities of 7.5 × 104 plants ha−1 (D1) and 12 × 104 plants ha−1 (D2) as subplot factors, and four shading levels of natural light as a control (CK), 15% shading (S1), 30% shading (S2), and 50% shading (S3) of natural light as the secondary subplot factor. All treatments were arranged completely randomly and replicated three times.

2.3. Field Management

In this study, irrigation was used in Qitai and Yinchuan, and the irrigation amount was about 540 mm to prevent water stress in the growing season. To ensure uniform emergence, all experimental plots were irrigated (15 mm) on the first day after sowing. Irrigation was applied every 9–10 days after 60 days of sowing [55]. The use of fertilizer followed that of Yang et al. [22] The specific fertilization scheme was shown in Table 1. Total fertilizer used in Yinchuan and Qitai, respectively, were 375 and 450 kg ha−1 N as urea, 188 and 225 kg ha−1 P2O5 (super phosphate), and 53 and 75 kg ha−1 K2O (potassium sulfate) to prevent nutrient stress. The diseases, pests and weeds of the test site were well controlled.

2.3.1. Total Intercepted Photosynthetically Active Radiation

From elongation to silking, the amount of photosynthetically active radiation reaching the top and bottom of the canopy was measured every 10 days with six replications by using a line quantum sensor (Sunscan, Delta-T Devices, Ltd.; Burwell, UK). The total intercepted photosynthetically active radiation (TIPAR) was calculated according to the method of Yang et al. [2]

2.3.2. Root Sampling

In 2018 and 2019, samples were taken at the silking stage. In each plot, the above ground parts of the three plants in the same row were cut manually, and then the roots were excavated layer by layer according to the soil profile method with the roots as the center (Figure 3A,B). The total depth of root excavation was 60 cm, which was divided into three layers: 0–20 cm, 21–40 cm and 41–60 cm [56]. For each layer, the excavation area of D1 and D2 was 0.24 × 0.55 m and 0.15 × 0.55 m respectively, and the total soil volume were 0.08 m3 and 0.05 m3 respectively. The soil of each layer was placed in a separate nylon bag, and then all roots were manually picked and cleaned with water until all the roots observed were white (Figure 3C). Take photos and record the cleaned main root system of 0–20 cm (Figure 4A,B). Then the roots cleaned of each soil layer were floated evenly and non-superposed in the water storage glass tank (length × width × height = 25 × 20 × 2 cm3), scan the clean roots with a scanner (Indo-nesia Epson V800) (Figure 4C), and store them in JPG format (Figure 4D,E). Finally, we used an analysis program (WinRhizo Pro Vision5.0, Canada) to analyze the scanned image to obtain root length, root surface area and root diameter. The scanned roots were dried at 85 °C to a constant weight to determine the root dry weight and the corresponding aboveground were dried together to determine the shoot dry weight. The specific introduction of root morphological parameters were shown in Table 2.

2.4. Statistical Analysis

Calculations were performed using Microsoft Excel 2010 software. The SPSS 21.0 software (IBM, Armonk, NY, USA) was used for variance analysis and correlation analysis to test for differences among treatments. RLD, RSA, ARD, SLR and RLR were firstly analyzed by one-way ANOVA followed by the Duncan’s test to compare the mean values among the treatments at p < 0.05. The formula calculated from the tested indicators are as follows [57]:
Shoot weight ratio (SWR) = (Shoot dry weight/whole plant dry weight) × 100%
Root weight ratio (RWR) = (Root dry weight/whole plant dry weight) × 100%
Root length density (RLD) = Root length/Soil volume (mm cm−3)
Specific root length (SRL) = Root length/Root dry weight (m g−1)
Root length ratio (RLR) = Root weight ratio × Specific root length (m g−1)

3. Results

3.1. Effects of Different Shading Levels on Maize Dry Matter Distribution

The distributions of plant dry matter to shoot and root were significantly affected by site, year, cultivar, planting density and shading levels, among which cultivars and shading levels had the greatest influence (Figure 5). For the aboveground, the SWR of XY335, ZD958 and DH618 control treatments were 91.2–93.3%, 92.6–93.8% and 83.3%, respectively. With the decrease of solar radiation, the SWR increased, and the increase degree was S3 > S2 > S1. The average SWR of shading treatment for XY335, ZD958 and DH618 were 94.1–95.3%, 95.4–96.0% and 92.9%, respectively. Compared with the control, the SWR of XY335, ZD958 and DH618 increased by 2.9%, 2.7% and 11.5% respectively with the decrease of solar radiation. For the underground, the RWR of XY335, ZD958 and DH618 control treatments were 6.7–8.9%, 6.2–7.4% and 16.7%, respectively. With the decrease of solar radiation, the RWR decreased, and the decrease degree was S3 > S2 > S1. The average RWR of shading treatment for XY335, ZD958 and DH618 were 4.7–5.9%, 4.0–4.6% and 7.1%, respectively. Compared with the control, the RWR of XY335, ZD958 and DH618 decreased by 33.1%, 37.2% and 57.3% respectively with the decrease of solar radiation (Figure 6). In summary, the increase in the SWR of XY335 and ZD958 and the decrease in the RWR after the decrease of solar radiation were both smaller than that of DH618. Under any solar radiation level, the shoot dry weights of XY335 and ZD958 were significantly higher than DH618, while the root dry weights were significantly lower than that of DH618. The shoot dry weight of XY335, ZD958 and DH618 decreased with radiation by 25.1, 23.1 and 17.4%, respectively; root dry weight decreased by 44.5, 43.9 and 53.7%, respectively (Figure 7).

3.2. Effects of Different Shading Levels on Maize Root Morphology

Different levels of solar radiation had obvious effects on the maize root system. As solar radiation decreased, the root system became smaller (Figure 8). Through Figure 9 we can further analyze the changes in root morphological parameters. The RLD of D2 density was significantly higher than D1 density, while the RSA and ARD were significantly lower than D1 density. The RLD and RSA of DH618 were significantly higher than those of XY335 and ZD958, and the ARD was significantly lower than that of ZD958 and XY335. With the decrease of solar radiation, RLD, RSA and ARD all decreased, the degree of decrease was S3 > S2 > S1. The RLD of DH618, XY335 and ZD958 under the control treatment were 4.6, 1.6 and 1.4 mm cm−3, respectively, which decreased with the decrease of solar radiation and the average decrease rate were 55.4%, 39.2% and 36.4%. The RSA of DH618, XY335 and ZD958 under the control treatment were 0.3, 0.2 and 0.2 m2, respectively, with the average decrease rate of 53.7%, 41.3% and 38.7% after solar radiation decrease. The ARD of DH618, XY335 and ZD958 under the control treatment were 0.3, 0.5 and 0.6 mm, respectively, with the average decrease rate of 21.1%, 19.2% and 13.8% after solar radiation decrease.

3.3. Effects of Different Shading Levels on the Acquisition Ability of Root

Root size and root morphology are important factors that determine the ability of roots to obtain underground resources. The RLR is closely related to the component reflecting the quantity of biomass allocated to the roots (RWR) and the pattern of investment of this biomass (SRL). From Figure 10(A1–A4), it was shown that the SRL increased after the solar radiation decrease, indicating that the root system became thinner under weak solar radiation. The SRL of DH618, XY335 and ZD958 under the control treatment were 14.7, 9.5 and 9.1 mg−1, respectively, and the average increase rate was 18.0%, 22.9% and 21.7% with the decrease of solar radiation. With the decrease of solar radiation, the RLR decreased significantly, and the degree of decrease was S3 > S2 > S1. Under natural light, the RLR of DH618, XY335, and ZD958 are 2.5, 0.7 and 0.6 m g−1, respectively. After shading, the RLR were 1.2, 0.6 and 0.5 m g−1 on average, with decrease rate of 50.2%, 21.1% and 20.4%, respectively (Figure 10(B1–B4)). The SRL of D2 density was significantly higher than D1 density, while the difference in RLR was not significant. The SRL and RLR of DH618 were significantly higher than those of XY335 and ZD958 (Figure 10).

3.4. Quantitative Relationships between TIPAR and Root Morphology

The analysis of TIPAR from the elongation stage to the silking stage and root morphology at silking showed that there were quantitative relationships between RWR, RLD, RSA, RLR, and TIPAR. With 100 MJ m−2 decrease of TIPAR, the RWR of DH618, XY335, and ZD958 decreased by 3.01, 0.76 and 0.63%, respectively. Similarly, the RLD decreased by 0.92, 0.31 and 0.27 mm cm−3, respectively, the RSA decreased by 0.59, 0.38 and 0.24 m2 m−2, respectively, and the RLR decreased by 0.41, 0.08 and 0.08 m g−1, respectively. Overall, as the TIPAR decreased by 1 MJ m−2, the RWR, RLD, RSA and RLR each decreased by 1.47%, 0.5 mm cm−3, 0.4 m m−2 and 0.19 m g−1, respectively (Figure 11).

3.5. Effects of Different Root Morphology on Maize Yield

The acquisition of soil resources by roots is conducive to the growth of aboveground, which in turn affects the yield. Under natural light, there were no significant positive correlations between RWR, RLD, RLR and yield, whereas under S1, S2 and S3 treatment there were significant positive correlations between RWR, RLD, RLR and yield except for RWR of S1. Under natural light and shading treatments, there were not significant positive correlations between RSA and yield. It showed that root size and root length under low solar radiation had a greater impact on yield than the normal environment (Figure 12).

4. Discussion

4.1. Effect of Solar Radiation on Maize Root and Shoot

Root systems are the main route for soil resources, not only by transportation but also by uptake, and their functions are closely related to root size and root morphology [58,59,60]. The root system obtains photoassimilates, which is helpful for the plant to overcome poor growing environments [61]. When the solar radiation condition is limited, photosynthetic products are preferentially distributed to the aboveground organs, and root growth is blocked [62,63]. In previous studies, it was found that the whole plant became smaller, and the aboveground and root biomass decreased after shading [16,64]. However, in this study, we found when the solar radiation decreased, the root weight ratio decreased while the shoot weight ratio increased (Figure 6). This indicated that the responses aboveground and underground to changes in solar radiation were not consistent. Changes in biomass allocation will affect the balance between root and shoot growth [65]. Several studies have shown that, for different maize cultivars, higher biomass allocations to shoots and less allocations to root biomass lead to a higher yield [66]. We also found similar results. Compared with XY335 and ZD958, DH618 responded more quickly to solar radiation, so it had a more coordinated relationship between shoot and root and it always maintained a higher root/shoot ratio. In addition to the rapid response of the root system, the larger root system helps to provide sufficient nutrients and water for the aboveground growth [67]. The larger root system mainly depends on the larger root dry weight. The root dry weight of DH618 was the largest under any solar radiation conditions, which might be conducive to its supply aboveground to ensure a high yield (Figure 7).
The change of root morphology is affected by root system size. It is generally considered that root length, root surface area and root fineness are the key morphological parameters affecting nutrient and water absorption [68,69]. Root length and root surface area are important factors that determine the degree of root system contacting with soil. Root length can be expressed by root length density, and root fineness reflects the size of the root diameter [54]. After the decrease in solar radiation, the decline of root dry weight will lead to the decline of root morphological parameters [34]. Root length density, root absorption area and active absorption area under low solar radiation were lower than those under high solar radiation [63]. Our results showed that the RLD, RSA and ARD decreased after the decrease of solar radiation (Figure 9). In our results, the decrease of RLD was 38.7–53.7%, which was lower than the experimental results of Gao et al. (53–66%) [54]. This may be due to cultivar differences. Under the same environmental conditions, the root system of different genotypes are significantly different [36]. Studies have shown that the total root length and root diameter of XY335 are less than those of ZD958 [70]. This is inconsistent with our results. In this study, under natural light conditions, the RLD and RSA showed the decreasing trend of DH618 > XY335 > ZD958 and the ARD showed the decreasing trend of XY335 > ZD958 > DH618. This may be due to the different environmental and soil conditions. The root system of DH618 was the most sensitive to solar radiation changes, followed by XY335 and ZD958. However, DH618 always maintained the largest root length density and root surface area to achieve more resources in the soil.
The ability to acquire underground resources can be reflected by RLD, which can be decomposed into RWR and SRL [71]. A large RWR means that more biomass is distributed to the root system, which is conducive to the root system to obtain a larger root length. Generally, large roots can improve the efficiency of root nitrogen absorption [72]. The distribution of root biomass in root length, which in SRL determines its efficiency in obtaining resources and a higher SRL is more efficient [73]. In this study, we found that the SRL increased after the solar radiation decreased (Figure 10), which was actually the root thinning. The RLR decreased with the decrease of solar radiation, which might be closely related to the decrease in RWR (Figure 6 and Figure 10). For the three cultivars, the SRL and RLR change of DH618 were the fastest in response to solar radiation. Compared with the other two cultivars, its RWR and SRL were larger, and the RLR was larger, which resulted in a stronger ability to acquire underground resources.
Although some studies reported the effects of solar radiation on maize root morphology by conducting shading experiments [50,51,52], the quantitative effects of solar radiation on root morphology were reported. In this study, the quantitative relationships between RWR, RLD, RSA, RLR and TIPAR during plant growth stages were established. The results showed that with every 100 MJ m−2 decline in TIPAR, the RWR, RLD, RSA and RLR each decreased by 1.47%, 0.5 mm cm−3, 0.4 m m−2 and 0.19 m g−1, respectively (Figure 11). The cultivars of ZD958, XY335 and DH618 showed different quantitative relationships. This can provide a theoretical reference for maize cultivar selection and breeding under different solar radiation conditions in different regions, or those induced by climate change.

4.2. Effect of Root Morphology on Yield

In the absence of other factors, there is a simple linear relationship between yield and photosynthetically active radiation [74,75,76]. At the same time, too-high planting density results in a low solar radiation in the group, which will intensify the contradiction between individuals and groups, which is not conducive to the increase of the yield [77,78]. In addition to the aboveground regulation of grain formation, the root system also plays an important role [79,80]. The plant’s root system provides sufficient nutrients and moisture for development, which is conducive to a higher crop yield [67]. It has been found that, in most cases, crop yield is highly correlated and nearly linear with crop root mass [81]. In this study, we found that there was no significant correlation between RWR, RLD, RLR and yield under natural light, but there were significant positive correlations between RWR, RLD, RLR and yield after the decrease of solar radiation (Figure 12). This meant that root growth was more important for crop growth and yield after solar radiation decrease. This is similar to some studies in the Huang-Huai-Hai region of China where there are also significant positive correlations between root morphology and yield due to the lower solar radiation in that region [52,54].
Under the same environmental conditions, the root morphology of different genotypes are significantly different and preferable root morphology contributes to an increased yield of cultivars [36]. RWR is very important for root morphology. The larger the RWR, the larger the root system, which means that the root length in contact with the soil will be more and it is more conducive to extending into the deeper soil to efficiently acquire sufficient water and nutrient supply for grain formation [82]. In this study, the highest yield of DH618 might be due to its higher RWR, RLD and RLR than the other two cultivars under any solar radiation conditions, and its root system was finer, which was conducive to the acquisition of deep soil resources [83]. Cultivars with this kind of root morphology should be recommended to better adapt to a low solar radiation environment in different regions or those induced by climate change.

5. Conclusions

This study showed contrary effects of solar radiation on the dry matter distribution of maize shoot and root growth. As solar radiation decreased, SWR increased and RWR decreased. There were quantitative relationships between the root morphology parameters (RWR, RLD, RSA and RLD) of different cultivars and TIPAR. The root size, length and surface area were more responsive to solar radiation. Compared with the other two cultivars, DH618 had the largest root weight ratio, longer and finer roots under each treatment, and it changed rapidly with the decrease in solar radiation. This was conducive to the acquisition of soil resources. There was a positive correlation between RWR, RLD, RLR and yield under shading treatments, indicating that root size and root length had a greater effect on yield under low light conditions. Therefore, the selection of large root cultivars with the longer root length is beneficial to cope with low light stress.

Author Contributions

Conceptualization, P.H. and S.L.; methodology, X.G. and P.H.; software, X.G.; validation, P.H. and S.L.; formal analysis, X.G., B.M., R.X., K.W., P.H. and S.L.; investigation, X.G., Y.Y., H.L., G.L., W.L., Y.W. and R.Z.; resources, P.H. and S.L.; data curation, X.G.; writing—original draft preparation, X.G.; writing—review and editing, X.G. and P.H.; visualization, X.G. and P.H.; supervision, S.L. and P.H.; project administration, S.L.; funding acquisition, P.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Natural Science Foundation of China (32172118, 31871558), the National Key Research and Development Program of China (2016YFD0300110, 2016YFD0300101), Basic Scientific Research Fund of Chinese Academy of Agricultural Sciences (S2021ZD05), and the Agricultural Science and Technology Innovation Program (CAAS-ZDRW202004).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Richards, R.A. Selectable traits to increase crop photosynthesis and yield of grain crops. J. Exp. Bot. 2000, 51, 447–458. [Google Scholar] [CrossRef] [PubMed]
  2. Yang, Y.-S.; Guo, X.-X.; Liu, H.-F.; Liu, G.-Z.; Liu, W.-M.; Ming, B.; Xie, R.-Z.; Wang, K.-R.; Hou, P.; Li, S.-K. The effect of solar radiation change on the maize yield gap from the perspectives of dry matter accumulation and distribution. J. Integr. Agric. 2021, 20, 482–493. [Google Scholar] [CrossRef]
  3. Yang, Y.S.; Guo, X.X.; Liu, G.Z.; Liu, W.M.; Xue, J.; Ming, B.; Xie, R.Z.; Wang, K.R.; Hou, P.; Li, S.K. Solar radiation effects on dry matter accumulations and transfer in maize. Front. Plant Sci. 2021, 12, 727134. [Google Scholar] [CrossRef] [PubMed]
  4. Hou, P.; Liu, Y.E.; Liu, W.M.; Yang, H.S.; Xie, R.Z.; Wang, K.R.; Ming, B.; Liu, G.Z.; Xue, J.; Wang, Y.H.; et al. Quantifying maize grain yield losses caused by climate change based on extensive field data across China. Resour. Conserv. Recy. 2021, 174, 105811. [Google Scholar] [CrossRef]
  5. Wu, A.; Hammer, G.L.; Doherty, A.; Von Caemmerer, S.; Farquhar, G. Quantifying impacts of enhancing photosynthesis on crop yield. Nat. Plants 2019, 5, 380–388. [Google Scholar] [CrossRef] [PubMed]
  6. El-Sharkawy, M.A. Prospects of photosynthetic research for increasing agricultural productivity, with emphasis on the tropical C4 Amaranthus and the cassava C3-C4 crops. Photosynthetica 2016, 54, 161–184. [Google Scholar] [CrossRef]
  7. Jansson, C.; Vogel, J.; Hazen, S.; Brutnell, T.; Mockler, T. Climate-smart crops with enhanced photosynthesis. J. Exp. Bot. 2018, 69, 3801–3809. [Google Scholar] [CrossRef]
  8. Hu, Q.; Ma, X.; He, H.; Pan, F.; He, Q.; Huang, B.; Pan, X. Warming and Dimming: Interactive Impacts on Potential Summer Maize Yield in North China Plain. Sustainability 2019, 11, 2588. [Google Scholar] [CrossRef] [Green Version]
  9. Meng, Q.; Liu, B.; Yang, H.; Chen, X. Solar dimming decreased maize yield potential on the North China Plain. Food Energy Secur. 2020, 9, e235. [Google Scholar] [CrossRef]
  10. Zhao, J.; Kong, X.; He, K.; Xu, H.; Mu, J. Assessment of the radiation effect of aerosols on maize production in China. Sci. Total Environ. 2020, 720, 137567. [Google Scholar] [CrossRef]
  11. Abakumova, G.M.; Gorbarenko, E.V.; Nezval, E.I.; Shilovtseva, O.A. Fifty years of actinometrical measurements in Moscow. Int. J. Remote Sens. 2008, 29, 2629–2665. [Google Scholar] [CrossRef]
  12. Gao, J.; Zhao, B.; Dong, S.; Liu, P.; Ren, B.; Zhang, J. Response of Summer Maize Photosynthate Accumulation and Distribution to Shading Stress Assessed by Using 13CO2 Stable Isotope Tracer in the Field. Front. Plant Sci. 2017, 8, 1821. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Zhang, J.W.; Dong, S.T.; Wang, K.J.; Hu, C.H.; Liu, P. Effects of shading in field on key enzymes involved in starch synthesis of summer maize. Acta Agronica Sinica 2008, 34, 1470–1474. [Google Scholar] [CrossRef]
  14. Liu, W.D.; Matthijs, T. Physiological mechanisms underlying heterosis for shade tolerance in maize. Crop Sci. 2009, 49, 1817–1826. [Google Scholar] [CrossRef]
  15. Ren, B.; Cui, H.; Camberato, J.J.; Dong, S.; Liu, P.; Zhao, B.; Zhang, J. Effects of shading on the photosynthetic characteristics and mesophyll cell ultrastructure of summer maize. Die Nat. 2016, 103, 67–79. [Google Scholar] [CrossRef] [PubMed]
  16. Cui, H.-Y.; Jin, L.-B.; Li, B.; Dong, S.-T.; Liu, P.; Zhao, B.; Zhang, J.-W. Effects of shading on dry matter accumulation and nutrient absorption of summer maize. Ying Yong Sheng Tai Xue Bao J. Appl. Ecol. 2013, 24, 3099–3105. [Google Scholar]
  17. Qian, C.-J.; Zhang, W.; Zhong, X.-M.; Li, F.-H.; Shi, Z.-S. Comparative studies on the photosynthetic characteristics of two maize (Zea mays L.) near-isogenic lines differing in their susceptibility to low light intensity. Emir. J. Food Agric. 2017, 1, 300–311. [Google Scholar] [CrossRef] [Green Version]
  18. Zhong, X.M.; Shi, Z.S.; Li, F.H.; Huang, H.J. Photosynthesis and chlorophyll fluorescence of infertile and fertile stalks of paired near-isogenic lines in maize (Zea mays L.) under shade conditions. Photosynthetica 2014, 52, 597–603. [Google Scholar] [CrossRef]
  19. Yang, H.; Shi, Y.; Xu, R.; Lu, D.; Lu, W. Effects of shading after pollination on kernel filling and physicochemical quality traits of waxy maize. Crop J. 2016, 4, 235–245. [Google Scholar] [CrossRef] [Green Version]
  20. Gao, J.; Shi, J.; Dong, S.; Liu, P.; Zhao, B.; Zhang, J. Grain development and endogenous hormones in summer maize (Zea mays L.) submitted to different light conditions. Int. J. Biometeorol. 2018, 62, 2131–2138. [Google Scholar] [CrossRef]
  21. Xue, J.; Gou, L.; Zhao, Y.; Yao, M.; Yao, H.; Tian, J.; Zhang, W. Effects of light intensity within the canopy on maize lodging. Field Crops Res. 2016, 188, 133–141. [Google Scholar] [CrossRef]
  22. Yang, Y.S.; Guo, X.X.; Hou, P.; Xue, J.; Liu, G.Z.; Liu, W.M.; Wang, Y.H.; Zhao, R.L.; Ming, B.; Xie, R.Z.; et al. Quantitative effects of solar radiation on maize lodging resistance mechanical properties. Field Crops Res. 2020, 255, 107906. [Google Scholar] [CrossRef]
  23. Eapen, D.; Barroso, M.L.; Ponce, G.; Campos, M.E.; Cassab, G.I. Hydrotropism: Root growth responses to water. Trends Plant Sci. 2005, 10, 44–50. [Google Scholar] [CrossRef]
  24. Hardtke, C.S.; Villalobos, D.P. The Brachypodium distachyon Root System: A Tractable Model to Investigate Grass Roots. In Genetics and Genomics of Brachypodium; Plant Genetics and Genomics: Crops and Models; Vogel, J.P., Ed.; Springer: Cham, Switzerland, 2015; Volume 18, pp. 245–258. [Google Scholar]
  25. Singh, V.; Oosterom, E.J.V.; Jordan, D.R.; Messina, C.D.; Cooper, M.; Hammer, G.L. Morphological and architectural development of root systems in sorghum and maize. Plant Soil 2010, 333, 287–299. [Google Scholar] [CrossRef]
  26. Takehisa, H.; Sato, Y.; Igarashi, M.; Abiko, T.; Antonio, B.A.; Kamatsuki, K.; Minami, H.; Namiki, N.; Inukai, Y.; Nakazono, M.; et al. Genome-wide transcriptome dissection of the rice root system: Implications for developmental and physiological functions. Plant J. 2011, 69, 126–140. [Google Scholar] [CrossRef]
  27. Berry, P.; Baker, C.; Hatley, D.; Dong, R.; Wang, X.; Blackburn, G.; Miao, Y.; Sterling, M.; Whyatt, J. Development and application of a model for calculating the risk of stem and root lodging in maize. Field Crops Res. 2020, 262, 108037. [Google Scholar] [CrossRef]
  28. Nacry, P.; Bouguyon, E.; Gojon, A. Nitrogen acquisition by roots: Physiological and developmental mechanisms ensuring plant adaptation to a fluctuating resource. Plant Soil 2013, 370, 1–29. [Google Scholar] [CrossRef] [Green Version]
  29. Lynch, J.P.; Chimungu, J.G.; Brown, K.M. Root anatomical phenes associated with water acquisition from drying soil: Targets for crop improvement. J. Exp. Bot. 2014, 265, 6155–6166. [Google Scholar] [CrossRef] [Green Version]
  30. Rogers, E.D.; Benfey, P.N. Regulation of plant root system architecture: Implications for crop advancement. Curr. Opin. Biotechnol. 2015, 32, 93–98. [Google Scholar] [CrossRef]
  31. de Dorlodot, S.; Forster, B.; Pages, L.; Price, A.; Tuberosa, R.; Draye, X. Root system architecture: Opportunities and constraints for genetic improvement of crops. Trends Plant Sci. 2007, 12, 474–481. [Google Scholar] [CrossRef]
  32. Gowda, V.R.; Henry, A.; Yamauchi, A.; Shashidhar, H.; Serraj, R. Root biology and genetic improvement for drought avoidance in rice. Field Crops Res. 2011, 122, 1–13. [Google Scholar] [CrossRef]
  33. Maurel, C.; Simonneau, T.; Sutka, M. The significance of roots as hydraulic rheostats. J. Exp. Bot. 2010, 61, 3191–3198. [Google Scholar] [CrossRef] [Green Version]
  34. Franco, J.A.; Bañón, S.; Vicente, M.M.J.; Miralles, J.; Martínez-Sánchez, J.J. Review Article: Root development in horticultural plants grown under abiotic stress conditions—A review. J. Hortic. Sci. Biotech. 2011, 86, 543–556. [Google Scholar] [CrossRef]
  35. Guo, X.; Yang, Y.; Liu, H.; Liu, G.; Liu, W.; Wang, Y.; Zhao, R.; Ming, B.; Xie, R.; Wang, K.; et al. Effects of solar radiation on root and shoot growth of maize and the quantitative relationship between them. Crop Sci. 2020, 61, 1414–1425. [Google Scholar] [CrossRef]
  36. Hund, A.; Richner, W.; Soldati, A.; Fracheboud, Y.; Stamp, P. Root morphology and photosynthetic performance of maize inbred lines at low temperature. Eur. J. Agron. 2007, 27, 52–61. [Google Scholar] [CrossRef]
  37. Zou, H.Y.; Zhang, F.C.; Wu, L.F.; Xiang, Y.Z.; Fan, J.L.; Li, Z.J.; Li, S.E. Normalized root length density distribution model for spring maize under different water and fertilizer combination. Trans. Chin. Soc. Agric. Eng. 2018, 34, 133–142. [Google Scholar]
  38. Tuberosa, R.; Salvi, S.; Sanguineti, M.C.; Maccaferri, M.; Giuliani, S.; Landi, P. Searching for quantitative trait loci controlling root traits in maize: A critical appraisal. Plant Soil 2003, 255, 35–54. [Google Scholar] [CrossRef]
  39. Mu, X.H.; Chen, F.J.; Wu, Q.P.; Chen, Q.W.; Wang, J.F.; Yuan, L.X.; Mi, G.H. Genetic improvement of root growth in-creases maize yield via enhanced post-silking nitrogen uptake. Eur. J. Agron. 2015, 63, 55–61. [Google Scholar] [CrossRef]
  40. Zhang, F.L.; Niu, X.K.; Zhang, Y.M.; Xie, R.Z.; Liu, X.; Li, S.K.; Gao, S.J. Studies on the root characteristics of maize varieties of different eras. J. Integr. Agric. 2013, 12, 426–435. [Google Scholar] [CrossRef]
  41. Shao, H.; Xia, T.T.; Wu, D.L.; Chen, F.J.; Mi, G.H. Root growth and root system architecture of field-grown maize in response to high planting density. Plant Soil 2018, 430, 395–411. [Google Scholar] [CrossRef]
  42. Liu, G.; Hou, P.; Xie, R.; Ming, B.; Wang, K.; Xu, W.; Liu, W.; Yang, Y.; Li, S. Canopy characteristics of high-yield maize with yield potential of 22.5 Mg ha−1. Field Crops Res. 2017, 213, 221–230. [Google Scholar] [CrossRef]
  43. Liu, G.; Yang, H.; Xie, R.; Yang, Y.; Liu, W.; Guo, X.; Xue, J.; Ming, B.; Wang, K.; Hou, P.; et al. Genetic gains in maize yield and related traits for high-yielding cultivars released during 1980s to 2010s in China. Field Crops Res. 2021, 270, 108223. [Google Scholar] [CrossRef]
  44. Vazin, F.; Hassanzadeh, M.; Madani, A.; Nassiri-Mahallati, M.; Nasri, M. Modeling light interception and distribution in mixed canopy of common cocklebur (Xanthium stramarium) in competition with corn. Planta Daninha 2010, 28, 455–462. [Google Scholar] [CrossRef] [Green Version]
  45. Li, C.; Li, Y.; Shi, Y.; Song, Y.; Zhang, D.; Buckler, E.; Zhang, Z.; Wang, T.; Li, Y. Genetic Control of the Leaf Angle and Leaf Orientation Value as Revealed by Ultra-High Density Maps in Three Connected Maize Populations. PLoS ONE 2015, 10, e0121624. [Google Scholar] [CrossRef]
  46. Hou, P.; Liu, Y.; Liu, W.; Liu, G.; Xie, R.; Wang, K.; Ming, B.; Wang, Y.; Zhao, R.; Zhang, W.; et al. How to increase maize production without extra nitrogen input. Resour. Conserv. Recycl. 2020, 160, 104913. [Google Scholar] [CrossRef]
  47. Purcell, L.C.; Ball, R.A.; Reaper, J.D.; Vories, E.D. Radiation use efficiency and biomass production in soybean at different plant population densities. Crop Sci. 2002, 42, 172–177. [Google Scholar] [CrossRef]
  48. Mao, L.L.; Zhang, L.Z.; Zhao, X.H.; Liu, S.D.; van der Werf, W.; Zhang, S.P.; Spiertz, H.; Li, Z.H. Crop growth, light utilization and yield of relay intercropped cotton as affected by plant density and a plant growth regulator. Field Crops Res. 2014, 155, 67–76. [Google Scholar] [CrossRef]
  49. Zhou, M.; Wang, J.; Bai, W.; Zhang, Y.; Zhang, W.H. The response of root traits to precipitation change of herbaceous species in temperate steppes. Funct. Ecol. 2019, 33, 2030–2041. [Google Scholar] [CrossRef]
  50. Gao, Q.; Li, M.; Pu, L.; Yan, J.Y.; Li, Q.; Xiao, J.L.; Jin, P. Effects of weak light and waterlogging stress at jointing stage on photosynthesis, root growth and yield of spring maize. J. Jiangsu Agric. Sci. 2018, 34, 1276–1286. [Google Scholar]
  51. Wang, Q.; Zhao, X.Y.; Liu, D.Y.; Yan, Z.H.; Li, H.P.; Dong, P.F.; Li, C.H. Root morphological, physiological traits and yield of maize under waterlogging and low light stress. Sci. Agric. Sin. 2020, 53, 3479–3495. [Google Scholar]
  52. Shi, D.Y.; Li, Y.H.; Xia, D.J.; Zhang, J.W.; Liu, P.; Zhao, B.; Dong, S.T. Effects of planting density on root characteristics and nitrogen uptake in summer maize. Sci. Agric. Sin. 2017, 50, 2006–2017. [Google Scholar]
  53. Lambers, H.; Posthumus, F. The Effect of Light Intensity and Relative Humidity on Growth Rate and Root Respiration of Plantago lanceolata and Zea mays. J. Exp. Bot. 1980, 31, 1621–1630. [Google Scholar] [CrossRef]
  54. Gao, J.; Shi, J.; Dong, S.; Liu, P.; Zhao, B.; Zhang, J. Grain yield and root characteristics of summer maize (Zea mays L.) under shade stress conditions. J. Agron. Crop Sci. 2017, 203, 562–573. [Google Scholar] [CrossRef]
  55. Zhang, G.; Shen, D.; Xie, R.; Ming, B.; Hou, P.; Xue, J.; Li, R.; Chen, J.; Wang, K.; Li, S. Optimizing planting density to improve nitrogen use of super high-yield maize. Agron. J. 2020, 112, 4147–4158. [Google Scholar] [CrossRef]
  56. Hou, P.; Chen, X.P.; Cui, Z.L.; Li, S.Q.; Wang, W.; Ye, Y.L.; Chen, Y.X.; Zhang, F.S. Potential maize yield realization and related driving factors in four typical soils. Chin. J. Eco-Agric. 2012, 20, 874–881. [Google Scholar] [CrossRef]
  57. Vescio, R.; Abenavoli, M.R.; Sorgonà, A. Single and Combined Abiotic Stress in Maize Root Morphology. Plants 2020, 10, 5. [Google Scholar] [CrossRef] [PubMed]
  58. Sattelmacher, B.; Gerendas, J.; Thoms, K.; Brück, H.; Bagdady, N. Interaction between root growth and mineral nutrition. Environ. Exp. Bot. 1993, 33, 63–73. [Google Scholar] [CrossRef]
  59. Jackson, R.B.; Sperry, J.S.; Dawson, T.E. Root water uptake and transport: Using physiological processes in global predictions. Trends Plant Sci. 2000, 5, 482–488. [Google Scholar] [CrossRef]
  60. Fan, J.; McConkey, B.; Wang, H.; Janzen, H. Root distribution by depth for temperate agricultural crops. Field Crops Res. 2016, 189, 68–74. [Google Scholar] [CrossRef] [Green Version]
  61. Bañoc, D.M.; Yamauchi, A.; Kamoshita, A.; Wade, L.J.; Pardales, J.R.; Banco, D.M. Dry Matter Production and Root System Development of Rice Cultivars under Fluctuating Soil Moisture. Plant Prod. Sci. 2000, 3, 197–207. [Google Scholar] [CrossRef]
  62. Ogawa, A.; Kawashima, C.; Yamauchi, A. Sugar Accumulation along the Seminal Root Axis, as Affected by Osmotic Stress in Maize: A Possible Physiological Basis for Plastic Lateral Root Development. Plant Prod. Sci. 2005, 8, 173–180. [Google Scholar] [CrossRef] [Green Version]
  63. Zhou, T.; Wang, L.; Sun, X.; Wang, X.C.; Chen, Y.L.; Rengel, Z.; Liu, W.G.; Yang, W.Y. Light intensity influence maize ad-aptation to low P stress by altering root morphology. Plant Soil 2020, 447, 183–197. [Google Scholar] [CrossRef]
  64. Amos, B.; Walters, D.T. Maize root biomass and net rhizodeposited carbon: An analysis of the literature. Soil Sci. Soc. Am. J. 2006, 70, 1489–1503. [Google Scholar] [CrossRef]
  65. Hébert, Y.; Guingo, E.; Loudet, O. The Response of Root/Shoot Partitioning and Root Morphology to Light Reduction in Maize Genotypes. Crop Sci. 2001, 41, 363–371. [Google Scholar] [CrossRef]
  66. Li, Y.; Wang, X.; Zhu, Y.; Li, D.; Gao, Y. Effects of stage drought and re-watering on photosynthesis, root shoot ratio and water use efficiency of summer maize (Zea mays L.). Appl. Ecol. Environ. Res. 2020, 18, 7643–7653. [Google Scholar] [CrossRef]
  67. Liu, Z.; Zhu, K.; Dong, S.; Liu, P.; Zhao, B.; Zhang, J. Effects of integrated agronomic practices management on root growth and development of summer maize. Eur. J. Agron. 2017, 84, 140–151. [Google Scholar] [CrossRef]
  68. Wu, Q.; Pagès, L.; Wu, J. Relationships between root diameter, root length and root branching along lateral roots in adult, field-grown maize. Ann. Bot. 2016, 117, 379–390. [Google Scholar] [CrossRef] [Green Version]
  69. Zobel, R.W.; Kinraide, T.B.; Baligar, V.C. Fine root diameters can change in response to changes in nutrient concentrations. Plant Soil 2007, 297, 243–254. [Google Scholar] [CrossRef]
  70. Chen, Y.L.; Wu, Q.P.; Chen, X.C.; Chen, F.J.; Zhang, Y.J.; Li, Q.; Yuan, L.X.; Mi, G.H. Root growth and its response to increasing planting density in different maize hybrids. Plant Nutr. Fertil. Sci. 2012, 18, 52–59. [Google Scholar]
  71. Ryser, P.; Lambers, H. Root and leaf attributes accounting for the performance of fast- and slow-growing grasses at different nutrient supply. Plant Soil 1995, 170, 251–265. [Google Scholar] [CrossRef]
  72. Chen, X.; Zhang, J.; Chen, Y.; Li, Q.; Chen, F.; Yuan, L.; Mi, G. Changes in root size and distribution in relation to nitrogen accumulation during maize breeding in China. Plant Soil 2013, 374, 121–130. [Google Scholar] [CrossRef]
  73. Eissenstat, D.M. Costs and benefits of constructing roots of small diameter. J. Plant Nutr. 1992, 15, 763–782. [Google Scholar] [CrossRef]
  74. Braconnier, S. Maize-coconut intercropping: Effects of shade and root competition on maize growth and yield. Agronomie 1998, 18, 373–382. [Google Scholar] [CrossRef]
  75. Zhao, J.; Yang, X.; Lin, X.; Sassenrath, G.F.; Dai, S.; Lv, S.; Chen, X.; Chen, F.; Mi, G. Radiation Interception and Use Efficiency Contributes to Higher Yields of Newer Maize Hybrids in Northeast China. Agron. J. 2015, 107, 1473–1480. [Google Scholar] [CrossRef]
  76. Liu, G.-Z.; Liu, W.-M.; Hou, P.; Ming, B.; Yang, Y.-S.; Guo, X.-X.; Xie, R.-Z.; Wang, K.-R.; Li, S.-K. Reducing maize yield gap by matching plant density and solar radiation. J. Integr. Agric. 2021, 20, 363–370. [Google Scholar] [CrossRef]
  77. Van Ittersum, M.K.; Cassman, K.G. Yield gap analysis—Rationale, methods and applications—Introduction to the Special Issue. Field Crops Res. 2013, 143, 1–3. [Google Scholar] [CrossRef] [Green Version]
  78. Yang, Y.S.; Xu, W.J.; Hou, P.; Liu, G.Z.; Liu, W.M.; Wang, Y.H.; Zhao, R.L.; Ming, B.; Xie, R.Z.; Wang, K.R.; et al. Improving maize grain yield by matching maize growth and solar radiation. Sci. Rep.-UK 2019, 9, 1–11. [Google Scholar] [CrossRef] [Green Version]
  79. Hammer, G.L.; Dong, Z.; McLean, G.; Doherty, A.; Messina, C.; Schussler, J.; Zinselmeier, C.; Paszkiewicz, S.; Cooper, M. Can Changes in Canopy and/or Root System Architecture Explain Historical Maize Yield Trends in the US Corn Belt? Crop Sci. 2009, 49, 299–312. [Google Scholar] [CrossRef]
  80. Xia, H.-Y.; Zhao, J.; Sun, J.-H.; Bao, X.-G.; Christie, P.; Zhang, F.-S.; Li, L. Dynamics of root length and distribution and shoot biomass of maize as affected by intercropping with different companion crops and phosphorus application rates. Field Crops Res. 2013, 150, 52–62. [Google Scholar] [CrossRef]
  81. Li, S.-X.; Wang, Z.-H.; Malhi, S.; Li, S.-Q.; Gao, Y.-J.; Tian, X.-H. Chapter 7 Nutrient and Water Management Effects on Crop Production, and Nutrient and Water Use Efficiency in Dryland Areas of China. Adv. Agron. 2009, 102, 223–265. [Google Scholar] [CrossRef]
  82. Zarebanadkouki, M.; Kroener, E.; Kaestner, A.; Carminati, A.M. Visualization of root water uptake: Quantification of deuterated water transport in roots using neutron radiography and numerical modeling. Plant Physiol. 2014, 166, 487–499. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Ju, C.; Buresh, R.J.; Wang, Z.; Zhang, H.; Liu, L.; Yang, J.; Zhang, J. Root and shoot traits for rice varieties with higher grain yield and higher nitrogen use efficiency at lower nitrogen rates application. Field Crops Res. 2015, 175, 47–55. [Google Scholar] [CrossRef]
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Figure 1. The positions of two experimental sites.
Figure 1. The positions of two experimental sites.
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Figure 2. Weather data of the site from 2018 to 2019. (A) 2018 Qitai, (B) 2019 Qitai, (C) 2018 Yinchuan, (D) 2019 Yinchuan.
Figure 2. Weather data of the site from 2018 to 2019. (A) 2018 Qitai, (B) 2019 Qitai, (C) 2018 Yinchuan, (D) 2019 Yinchuan.
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Figure 3. Maize roots were collected in the field. This method will be adopted in both Qitai and Yinchuan in 2018 and 2019. (A) Plant selection and shoot cutting; (B) Excavating fixed soil layer by layer; (C) Root system cleaning.
Figure 3. Maize roots were collected in the field. This method will be adopted in both Qitai and Yinchuan in 2018 and 2019. (A) Plant selection and shoot cutting; (B) Excavating fixed soil layer by layer; (C) Root system cleaning.
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Figure 4. The whole picture of maize root system and root system scan pictures. (A,B) was the shooting method of the main maize root system. The maize roots of different treatments were fixed on the black background cloth, and the camera was fixed on the tripod 50 cm away from the roots system for shooting; (C) is the instrument for root scanning; (D,E) was a partial image of a clean root scanned and it selected from thou-sands of images. All the treatments roots were scanned in this way.
Figure 4. The whole picture of maize root system and root system scan pictures. (A,B) was the shooting method of the main maize root system. The maize roots of different treatments were fixed on the black background cloth, and the camera was fixed on the tripod 50 cm away from the roots system for shooting; (C) is the instrument for root scanning; (D,E) was a partial image of a clean root scanned and it selected from thou-sands of images. All the treatments roots were scanned in this way.
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Figure 5. ANOVA results for shoot weight ratio (SWR, %), root weight ratio (RWR, %), root length density (RLD, mm cm−3), root surface area (RSA, m2), average root diameter (ARD, mm), specific root length (SRL, m g−1) and root length ratio (RLR, m g−1). S: site; Y: year; C: cultivar; D: planting densities; SL: shading level. *, ** significant differences at p < 0.05 and p < 0.01, respectively. ns represents no significant differences.
Figure 5. ANOVA results for shoot weight ratio (SWR, %), root weight ratio (RWR, %), root length density (RLD, mm cm−3), root surface area (RSA, m2), average root diameter (ARD, mm), specific root length (SRL, m g−1) and root length ratio (RLR, m g−1). S: site; Y: year; C: cultivar; D: planting densities; SL: shading level. *, ** significant differences at p < 0.05 and p < 0.01, respectively. ns represents no significant differences.
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Figure 6. Distribution ratio of aboveground and underground biomass under different shading levels and planting densities. (A) 2018 Yinchuan; (B) 2019 Yinchuan; (C) 2018 Qitai; (D) 2019 Qitai.
Figure 6. Distribution ratio of aboveground and underground biomass under different shading levels and planting densities. (A) 2018 Yinchuan; (B) 2019 Yinchuan; (C) 2018 Qitai; (D) 2019 Qitai.
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Figure 7. Maize shoot dry weight and root dry weight of different cultivars under different shading levels by averaging two densities. (A): Shoot dry weight; (B): Root dry weight. The bars represented the error standard (n = 24). Analysis of variance was used to compare the differences of CK, S1, S2 and S3 among different cultivars. No shared lowercase letters indicate significant differences between treatments at p < 0.05.
Figure 7. Maize shoot dry weight and root dry weight of different cultivars under different shading levels by averaging two densities. (A): Shoot dry weight; (B): Root dry weight. The bars represented the error standard (n = 24). Analysis of variance was used to compare the differences of CK, S1, S2 and S3 among different cultivars. No shared lowercase letters indicate significant differences between treatments at p < 0.05.
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Figure 8. Maize root of DH618 under different shading level (CK: natural light control; S1: 15% shading; S2: 30% shading; S3: 50% shading) at D2 (12 × 104 plants ha−1) planting densities at the silking stage.
Figure 8. Maize root of DH618 under different shading level (CK: natural light control; S1: 15% shading; S2: 30% shading; S3: 50% shading) at D2 (12 × 104 plants ha−1) planting densities at the silking stage.
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Figure 9. Maize root length density (RLD, mm cm−3), root surface area (RSA, m2) and average root diameter (ARD, mm) under different shading levels and planting densities. The bars represented the error standard (n = 3). Analysis of variance was used to compare the differences of CK, S1, S2 and S3 among different cultivars under D1 or D2 density. No shared lowercase letters indicate significant differences between shading levels at p < 0.05. No shared capital letters indicate significant differences between planting densities at p < 0.05. No shared capital letters and * indicate significant differences between planting cultivars at p < 0.05. (A1,B1,C1): 2018 Yinchuan; (A2,B2,C2): 2019 Yinchuan; (A3,B3,C3): 2018 Qitai; (A4,B4,C4): 2019 Qitai.
Figure 9. Maize root length density (RLD, mm cm−3), root surface area (RSA, m2) and average root diameter (ARD, mm) under different shading levels and planting densities. The bars represented the error standard (n = 3). Analysis of variance was used to compare the differences of CK, S1, S2 and S3 among different cultivars under D1 or D2 density. No shared lowercase letters indicate significant differences between shading levels at p < 0.05. No shared capital letters indicate significant differences between planting densities at p < 0.05. No shared capital letters and * indicate significant differences between planting cultivars at p < 0.05. (A1,B1,C1): 2018 Yinchuan; (A2,B2,C2): 2019 Yinchuan; (A3,B3,C3): 2018 Qitai; (A4,B4,C4): 2019 Qitai.
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Figure 10. Acquisition ability of maize roots to underground resources. The bars represented the error standard (n = 3). Analysis of variance was used to compare the differences of CK, S1, S2 and S3 among different cultivars under D1 or D2 density. No shared lowercase letters indicate significant differences between treatments at p < 0.05. No shared capital letters indicate significant differences between planting densities at p < 0.05. No shared capital letters and * indicate significant differences between planting cultivars at p < 0.05. (A1,B1): 2018 Yinchuan; (A2,B2): 2019 Yinchuan; (A3,B3): 2018 Qitai; (A4,B4): 2019 Qitai.
Figure 10. Acquisition ability of maize roots to underground resources. The bars represented the error standard (n = 3). Analysis of variance was used to compare the differences of CK, S1, S2 and S3 among different cultivars under D1 or D2 density. No shared lowercase letters indicate significant differences between treatments at p < 0.05. No shared capital letters indicate significant differences between planting densities at p < 0.05. No shared capital letters and * indicate significant differences between planting cultivars at p < 0.05. (A1,B1): 2018 Yinchuan; (A2,B2): 2019 Yinchuan; (A3,B3): 2018 Qitai; (A4,B4): 2019 Qitai.
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Figure 11. Quantitative relationships between TIPAR and root weight ratio (RWR, %) (A), root length density (RLD, mm cm−3) (B), root surface area (RSA, m2 m−2) (C), average root diameter (ARD, mm m−2) (D), specific root length (SRL, m g−1) (E) and root length ratio (RLR, m g−1) (F). The bars represented the error standard (n = 24). ** significant differences at p < 0.05 and p < 0.01, respectively.
Figure 11. Quantitative relationships between TIPAR and root weight ratio (RWR, %) (A), root length density (RLD, mm cm−3) (B), root surface area (RSA, m2 m−2) (C), average root diameter (ARD, mm m−2) (D), specific root length (SRL, m g−1) (E) and root length ratio (RLR, m g−1) (F). The bars represented the error standard (n = 24). ** significant differences at p < 0.05 and p < 0.01, respectively.
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Figure 12. The correlation between root weight ratio (RWR, %), root length density (RLD, mm cm−3), root surface area (RSA, m2 m−2), root length ratio (RLR, m g−1) and yield of maize. *, ** significant differences at p < 0.05 and p < 0.01, respectively. ns represents no significant differences. Blue: RWR. Red: RLR. Purple: RSA. Orange: RLD.
Figure 12. The correlation between root weight ratio (RWR, %), root length density (RLD, mm cm−3), root surface area (RSA, m2 m−2), root length ratio (RLR, m g−1) and yield of maize. *, ** significant differences at p < 0.05 and p < 0.01, respectively. ns represents no significant differences. Blue: RWR. Red: RLR. Purple: RSA. Orange: RLD.
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Table
Table 1. Fertilizer application in maize growing season in Qitai and Yinchuan in 2018 and 2019.
Table 1. Fertilizer application in maize growing season in Qitai and Yinchuan in 2018 and 2019.
Base FertilizersTopdressing
NP2O5K2ON
Kg ha−1Kg ha−1Kg ha−1Kg ha−1
Qitai15022575300
Yinchuan7518853300
Table
Table 2. Root traits and their functional characteristics.
Table 2. Root traits and their functional characteristics.
Root TraitFunctional Characteristics
Total root length/surface area (RSA)/root weight ratio (RWR)The total system size: the size of contact with soil (major determinant of water and nutrient uptake as an entire root system)
Root length density (RLD)Rate of water and nutrient uptake
Root diameterPotential for penetration ability, branching, hydraulic conductivity
Specific root length (SRL)Degree of branching, density of root materials, porosity due to aerenchyma development
Source: reference [32].
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Guo, X.; Yang, Y.; Liu, H.; Liu, G.; Liu, W.; Wang, Y.; Zhao, R.; Ming, B.; Xie, R.; Wang, K.; et al. Effects of Solar Radiation on Dry Matter Distribution and Root Morphology of High Yielding Maize Cultivars. Agriculture 2022, 12, 299. https://doi.org/10.3390/agriculture12020299

AMA Style

Guo X, Yang Y, Liu H, Liu G, Liu W, Wang Y, Zhao R, Ming B, Xie R, Wang K, et al. Effects of Solar Radiation on Dry Matter Distribution and Root Morphology of High Yielding Maize Cultivars. Agriculture. 2022; 12(2):299. https://doi.org/10.3390/agriculture12020299

Chicago/Turabian Style

Guo, Xiaoxia, Yunshan Yang, Huifang Liu, Guangzhou Liu, Wanmao Liu, Yonghong Wang, Rulang Zhao, Bo Ming, Ruizhi Xie, Keru Wang, and et al. 2022. "Effects of Solar Radiation on Dry Matter Distribution and Root Morphology of High Yielding Maize Cultivars" Agriculture 12, no. 2: 299. https://doi.org/10.3390/agriculture12020299

APA Style

Guo, X., Yang, Y., Liu, H., Liu, G., Liu, W., Wang, Y., Zhao, R., Ming, B., Xie, R., Wang, K., Li, S., & Hou, P. (2022). Effects of Solar Radiation on Dry Matter Distribution and Root Morphology of High Yielding Maize Cultivars. Agriculture, 12(2), 299. https://doi.org/10.3390/agriculture12020299

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