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Article

Effect of Seedling Rates on Crop Yield and Methane Emissions from Rice Paddies

by
Qiping Chen
1,2,
Hao Li
2,
Hexian Huang
2 and
Wei Wang
1,*
1
Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
2
Ecology and Environment Monitoring Centre of Hunan, Changsha 410014, China
*
Author to whom correspondence should be addressed.
Atmosphere 2024, 15(11), 1342; https://doi.org/10.3390/atmos15111342
Submission received: 25 September 2024 / Revised: 2 November 2024 / Accepted: 6 November 2024 / Published: 8 November 2024
(This article belongs to the Special Issue Gas Emissions from Soil)
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Abstract

:
Agricultural strategies are urgently needed to mitigate greenhouse gas emissions without reducing crop yield. Seedling rate per hill will affect the quantity and quality of tillers, which may affect rice yield and CH4 emissions. Therefore, it is hypothesized that high yields with low yield-scaled CH4 emissions could be achieved with optimal seedling rate per hill. A field experiment was conducted with three densities (low seedling rate, LSR; moderate seedling rate, MSR; and high seedling rate, HSR) for two consecutive rice seasons. The CH4 fluxes were determined by the static chamber–GC method. The results showed no significant differences in rice yields, seasonal CH4 emissions, or yield-scaled CH4 emissions between the three treatments. For early rice, the HSR tended to achieve high yield without increasing yield-scaled CH4 emissions. As for late rice, the MSR showed similar rice yield, and tended to have lower yield-scaled CH4 emissions in comparison with the HSR. The results suggest that choosing an appropriate seedling rate per hill to increase grain yield while maintaining lower or comparable yield-scaled CH4 emissions can be a promising option to reduce CH4 emissions from rice paddies.

1. Introduction

Rice (Oryza sativa L.) is a staple food for more than half of the world population [1]. At the same time, rice cultivation is considered one of the major sources of methane (CH4), accounting for 11% of anthropogenic CH4 emissions [2]. The rice harvest area in China is around 30 million ha, contributing nearly half of the greenhouse gas emissions from cropland in China [3]. A major challenge of rice production involves the development of sustainable ways to produce more rice with fewer greenhouse gas emissions.
CH4 emissions are determined by the combined effects of production, oxidation, and transport. Rice plants have a significant impact on CH4 emissions by affecting the production, oxidation, and transport of CH4 to the atmosphere [4,5,6,7]. CH4 is produced by methanogens from the biological decomposition of organic materials in an anaerobic soil environment [8]. As plant density increases, more root exudates and sloughed tissues may increase CH4 production [9,10,11,12]. The main function of the aeration tissue of rice plants is to transmit atmospheric oxygen to the roots to maintain the growth of rice. The release of oxygen to the root environment can stimulate the oxidation of CH4 and reduce CH4 emissions [5,6,7,13]. About 60% to more than 90% of CH4 produced in the anaerobic zone of wetland is reoxidized in its aerobic zone [8]. At the same time, rice plants serve as a dominating transport pathway for CH4 emissions to the atmosphere, because more than 80% of CH4 escapes from soil to the atmosphere mainly through the vascular transport of plants [14,15,16]. In addition, the unobstructed transmission path to the atmosphere allows CH4 in the soil to be quickly discharged to the atmosphere, thereby reducing the probability of CH4 being oxidized. Higher rice plant density implies the higher transfer ability of CH4 through the aerenchyma. Singh et al. [17] have reported that seasonal CH4 emissions were significantly and positively correlated with the number of tillers, root porosity, and rice yield. According to previous studies, CH4 emissions are very intense during the tillering period [18,19]. The seedling rate per hill has a great impact on rice plant density, especially during the early growing stage, which may exert a big impact on CH4 emissions. Therefore, investigating the impact of seedling rates on CH4 emission could provide references to determine mitigation strategies, which is of great significance for realizing the green and sustainable development of rice production.
Besides area-scaled greenhouse gas emissions, it is recommended that yield-scaled greenhouse gas emissions (greenhouse gas emissions per unit yield) be used as a useful metric for evaluating mitigation strategies. Win–win strategies are urgently needed for rice cultivation to achieve high yield with low yield-scaled greenhouse gas emissions. Appropriate high seedling rate per hill has become popular, since it can increase the initial population, thus improving photosynthetic efficiency in the tillering stage. At the same time, high planting densities may enhance the capacity of rice paddies to provide substrates for CH4-producing microbes, increase CH4 consumption by oxygenating the rhizosphere, and transport CH4 from soils to the atmosphere, thus affecting CH4 emissions. Considering the potential effect of seedling rates on rice yield and CH4 emissions, we assume that the optimal seedling rate per hill can achieve high yield with less CH4 emissions, thereby reducing yield-scaled CH4 emissions. Therefore, we conducted a field experiment with three seedling rates. The objective of this study is to quantify crop yields and CH4 emissions under different seedling rates, so as to select a climate-friendly seedling rate to achieve high grain yield and low yield-scaled CH4 emissions.

2. Materials and Methods

2.1. Experimental Site and Design

A field experiment was carried out at Taoyuan Agro-ecology Experimental Station of the Chinese Academy of Sciences (28°55′ N, 111°27′ E) in Taoyuan county, Hunan province. This site is characterized by a subtropical humid monsoon climate. The rainfall and air temperature, as recorded at a meteorological observatory of the Station, are shown in Figure 1. A rice–rice cropping rotation system is the typical farming method in this area. The soil originates from quaternary red clay and is classified as Stagnic Anthrosols. The major properties of the soil at 0–15 cm are as follows: pH (H2O) 4.8, organic C 19.0 g kg−1, total N 2.05 g kg−1, total P 0.66 g kg−1, and available P (Olsen) 23.1 mg kg−1.
The field experiment consisted of the following three treatments: (I) low seedling rate (LSR); (II) moderate seedling rate (MSR); and (III) high seedling rate (HSR) (Table 1). The treatments were conducted in triplicate with randomized block design. Each plot was 2 m × 3 m in size, with a rice–rice cropping rotation. Zhongjiazao-17, a conventional rice cultivar, was used for early rice, and Tianyouhuazhan, a hybrid rice cultivar, was used for late rice. For early rice, seedlings were transplanted on 26 April 2018, with 4 seedlings per hill (LSR), 6 seedlings per hill (MSR), and 8 seedlings per hill (HSR) at 20 cm × 20 cm spacing. For late rice, seedlings were transplanted on 14 July 2018, with 2 seedlings per hill (LSR), 3 seedlings per hill (MSR), and 4 seedlings per hill (HSR) at 20 cm × 20 cm spacing. There were 150 hills of rice plants for each plot. The fertilizers, urea, superphosphate, and muriate of potash, were applied at 182 kg N ha−1yr−1, 39 kg P ha−1yr−1, 198 kg K ha−1yr−1, respectively. All the plots were continuously submerged with a water layer of 2−10 cm. The harvest dates were 11 July 2018 for early rice, and 18 October 2018 for late rice.

2.2. Sampling and Measurement Methods

The CH4 fluxes were determined by the static chamber–GC method [19] at about 6-day intervals. For each chamber (60 cm width × 60 cm length × 100 cm height), an electric fan (12 V) was installed inside to mix the air, and an electronic thermometer was installed inside to record air temperature. Nine hills of rice plants were inside a chamber-base in each plot. Gas samples, taken from each chamber almost simultaneously, were collected between 09:20 and 10:40 local time. Approximately 30 mL of gas was injected into vacuum glass vials using a syringe at 0, 15, 30, 45, and 60 min. CH4 concentrations were analyzed using a gas chromatograph (GC, 7890A, Agilent Technologies Inc., Santa Clara, CA, USA). CH4 fluxes and seasonal CH4 emissions were calculated according to the formulas of Wu et al. [19]. The rice inside the chamber-base was harvested manually at maturity stage. Grain samples were oven-dried at 70 °C, and grain yields were calculated in kg ha−1 assuming that the moisture content was 14%.

2.3. Statistical Analysis

The data were analyzed statistically with analysis of variance (ANOVA) using Statistical Package for the Social Sciences 16.0 software. The mean values were compared with the Duncan’s post hoc test, and p < 0.05 was considered significant.

3. Results

3.1. CH4 Emissions

There were obvious differences in CH4 fluxes under different seedling rates during the tillering period, and thereafter the effect of seedling rates on CH4 emissions gradually vanished (Figure 2). The seasonal CH4 emissions in the late-rice season were 494.2, 516.3, and 575.1 kg ha−1 for the LSR, MSR, and HSR, respectively (Figure 3). Although there was no statistical difference in seasonal CH4 emissions between different seedling rates, seasonal CH4 emissions increased with increasing seedling rates.

3.2. Rice Yields and Yield-Scaled CH4 Emissions

The yields of early rice were 4499, 4874, and 5030 kg ha−1 for the LSR, MSR, and HSR, respectively (Figure 3c), and the yields of late rice were 5403, 5710, and 5687 kg ha−1 for the LSR, MSR, and HSR, respectively (Figure 3d). There was no significant difference in rice yields under different seedling rates. However, there was still a certain trend; the LSR had the lowest yield, whereas the MSR and HSR had similar yields. In the early-rice season, both yields and CH4 emissions increased with the increase in seedling rates; therefore, the yield-scaled CH4 emissions did not differ much, ranging from 48.8 to 50.5 g CH4 kg−1 grain (Figure 3e). In the late-rice season, the yields between the MSR and HSR were close to each other, but the CH4 emissions under the MSR was 10.2% lower than that under the HSR (p > 0.05). As a result, the MSR decreased the yield-scaled CH4 emissions by 10.4% (p > 0.05) (Figure 3f). Although there was no significant difference in yield-scaled CH4 emissions among different seedling rates, the results show that with an appropriate seedling rate, there is a potential to achieve high yields with lower yield-scaled CH4 emissions.

4. Discussion

4.1. Effect of Seedling Rates on CH4 Emissions

CH4 is a dominant greenhouse gas from rice fields. Nitrous oxide emissions were negligible (<1% of global warming potential; not shown here), and there was no statistically significant difference among treatments. The present study is an attempt to mitigate CH4 emissions by the optimal seedling rate per hill method. CH4 emissions showed seasonal variations, with pronounced CH4 emissions occurring during the tillering period of late rice (Figure 2). The observed seasonal variations in CH4 emissions from rice paddies are in agreement with previous reports [18,19]. On average, CH4 emissions from late rice were 2.74 times that of early rice. This might be ascribed to high temperature during the vegetative stage of late rice (Figure 1), which could stimulate the production of CH4. Thus, the mitigation of CH4 emissions from the late-rice season plays an important role in the reduction of CH4 emissions in double-cropping rice systems. Our experiment shows that there was no significant difference in seasonal CH4 emissions among treatments. However, the prominent difference was observed during the tillering period of late rice. One reason for this might be that the CH4 emissions were relatively low in early-rice season, making it difficult to observe the difference. By contrast, more CH4 emissions occurred in the late-rice season, especially during the tillering period. In the present study, early-rice variety may have less of a regulating effect on CH4, which might be another reason. Rice plants regulate CH4 emissions by facilitating its production, oxidation, and transport. There were differences in the transport of CH4, the release of oxygen, the allocation of photoassimilates, and root porosity among different rice varieties, which are key factors in CH4 emissions [14,17,20,21,22,23]. Plants with a high CH4 transport capacity do not necessarily emit more CH4, because they may also cause more CH4 oxidation in the rhizosphere, thereby enhancing CH4 oxidation and reducing CH4 emissions, without a significant impact on CH4 emissions [4,7,24]. Similarly, Yang et al. [25] found that the plant-mediated transport could be offset by reduced ebullitive CH4 emissions. Furthermore, after the tillering period in the late-rice season, the difference in CH4 fluxes among different seedling rates gradually vanished (Figure 2b). It might be that under the self-regulation of population density, the difference in tiller number between different seedling rates gradually becomes smaller.

4.2. Effect of Seedling Rates on Yield

The number of panicles is a main factor contributing of rice yield, and is closely related to the number of tillers. In the present study, a high seedling rate tended to increase rice yield (p > 0.05). Other researchers showed that rice yield increased with increasing density [26,27,28,29]. The reasons may be as follows: first, seedling rates have a small impact on rice yield (<10%); second, the environmental variability of field trials is large. So the number of repetitions should be increased, or multi-year trials should be conducted.
Some researchers recommend the sparse planting of rice to explore the potential of individual plant to increase the total yield by cultivating large ears. Particularly, the System of Rice Intensification (SRI), transplanting a single young seedling per hill, has been promoted to improve rice yields [30,31]. However, it has been reported that the yield variability under SRI management is generally greater than that of conventional practices, which means that there is a certain risk of yield reduction, such as insufficient tillers due to pests, flooding or bad weather, which makes SRI less attractive [32]. In addition, SRI requires seedlings with strong tillering ability and a relatively long growth cycle after transplanting [33]. The key to high yield is whether it can produce enough photosynthetic material to ensure firm grouting. A double-cropping rice system that is harvested twice a year is constrained by time-limited temperature resources, particularly toward the end of the late-rice season [31]. Dense planting can ensure the number of tillers, and lead to the earlier maturing of rice, which can shorten the field period, thereby reducing crop stress by low temperatures toward the end of the late-rice season. In addition, dense planting is usually promoted to compensate for fertilizer reduction and ensure crop yield [26,27,28,29]. Therefore, relatively dense planting is suitable for a double-cropping rice system.

4.3. Optimal Seedling Rates for Both Yield and CH4 Emissions

Sustainable rice cultivation is crucial for food production and the mitigation of climate change. As the world’s population grows, food production faces new challenges. The aim of this study was to find an optimal seedling rate per hill that would optimize rice yield while limiting greenhouse gas emissions. Our study shows that with the increase in seedling rates in the early-rice season, the yield tended to increase, while yield-scaled CH4 emissions were similar (Figure 3). By contrast, in the late-rice season, the yield of the MSR tended to be higher than that of the LSR, and CH4 emissions tended to be lower than that of the HSR (Figure 3). Lower productivity means more cropland is required, so measures to achieve high yield with low or similar yield-scaled CH4 emissions can be chosen as mitigation strategies. The results showed that in the double-cropping rice system, the HSR is appropriate for early rice, while the MSR is appropriate for late rice. Although the HSR increased material and labor costs; the benefits of additional rice yield can offset these costs. Optimal seedling rates are a sustainable option to achieve economic and ecological perspectives.
This study only demonstrated the impact of rice seeding rates per hill on yield and CH4 emissions. Besides seedling rates, the rice plants with different physiological and morphological characteristics will affect yield and CH4 emissions [21,23,34]. Furthermore, fertilization and irrigation can change the physiological and morphological characteristics of rice plants [23,26,27]. Future studies could focus on the performance of different rice varieties under various seedling rates, as well as fertilization and irrigation models, which may improve root traits and optimize the photosynthate allocation to grains synergistically.

5. Conclusions

This study revealed a potential for mitigating CH4 emissions from rice paddies through the optimal seedling rate. For early rice, a high seedling rate tended to achieve high yield without increasing yield-scaled CH4 emissions. As for late rice, the MSR showed similar rice yield, and tended to lower yield-scaled CH4 emissions in comparison with the HSR. This finding illustrates that achieving higher rice productivity with appropriate seedling rates may not necessarily come at the expense of increased yield-scaled CH4 emissions. Therefore, selecting an appropriate seedling rate per hill to achieve high grain yield while maintaining low or comparable yield-scaled CH4 emissions may be a promising option to reduce CH4 emissions from rice paddies.

Author Contributions

Conceptualization, W.W.; Methodology, W.W.; Software, W.W.; Validation, W.W.; Formal analysis, W.W.; Investigation, W.W. and Q.C.; Data curation, W.W.; Writing—original draft, Q.C., H.H., W.W. and H.L.; Writing—review and editing, W.W. and H.L.; Visualization, W.W.; Supervision, W.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Natural Science Foundation of Changsha (Grant No. kq2208244), the Innovation Ecological Construction Program of Hunan (Grant No. 2023WK2003), and the Science and Technology Innovation Platform Project of Hunan (Grant No. 2022PT1010).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

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Atmosphere 15 01342 g001
Figure 1. Dynamics of precipitation and air temperature.
Figure 1. Dynamics of precipitation and air temperature.
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Figure 2. The dynamics of CH4 fluxes under different seedling rates. The bar with each point indicates the range of the standard error. LSR, 4 seeds per hill for early rice and 2 seeds per hill for late rice; MSR, 6 seeds per hill for early rice and 3 seeds per hill for late rice; HSR, 8 seeds per hill for early rice and 4 seeds per hill for late rice. (a) The dynamics of CH4 fluxes under different seedling rates during early -rice seasons; (b) The dynamics of CH4 fluxes under different seedling rates during late -rice seasons.
Figure 2. The dynamics of CH4 fluxes under different seedling rates. The bar with each point indicates the range of the standard error. LSR, 4 seeds per hill for early rice and 2 seeds per hill for late rice; MSR, 6 seeds per hill for early rice and 3 seeds per hill for late rice; HSR, 8 seeds per hill for early rice and 4 seeds per hill for late rice. (a) The dynamics of CH4 fluxes under different seedling rates during early -rice seasons; (b) The dynamics of CH4 fluxes under different seedling rates during late -rice seasons.
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Figure 3. Seasonal CH4 emissions, rice yields, and yield-scaled CH4 emissions under different seedling rates. The bar over each column represents the range of the standard error. The same lowercase letters above the bars indicate no statistically significant difference (p > 0.05). LSR, 4 seeds per hill for early rice and 2 seeds per hill for late rice; MSR, 6 seeds per hill for early rice and 3 seeds per hill for late rice; HSR, 8 seeds per hill for early rice and 4 seeds per hill for late rice. (a) Seasonal CH4 emissions under different seedling rates for early -rice; (b) Seasonal CH4 emissions under different seedling rates for late -rice; (c) Rice yield under different seedling rates for early -rice; (d) Rice yield under different seedling rates for late -rice; (e) Yield-scaled CH4 emissions under different seedling rates for early -rice; (f) Yield-scaled CH4 emissions under different seedling rates for late -rice.
Figure 3. Seasonal CH4 emissions, rice yields, and yield-scaled CH4 emissions under different seedling rates. The bar over each column represents the range of the standard error. The same lowercase letters above the bars indicate no statistically significant difference (p > 0.05). LSR, 4 seeds per hill for early rice and 2 seeds per hill for late rice; MSR, 6 seeds per hill for early rice and 3 seeds per hill for late rice; HSR, 8 seeds per hill for early rice and 4 seeds per hill for late rice. (a) Seasonal CH4 emissions under different seedling rates for early -rice; (b) Seasonal CH4 emissions under different seedling rates for late -rice; (c) Rice yield under different seedling rates for early -rice; (d) Rice yield under different seedling rates for late -rice; (e) Yield-scaled CH4 emissions under different seedling rates for early -rice; (f) Yield-scaled CH4 emissions under different seedling rates for late -rice.
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Table 1. The experimental treatments.
Table 1. The experimental treatments.
Low Seedling RateModerate Seedling RateHigh Seedling Rate
Early rice4 seedlings per hill6 seedlings per hill8 seedlings per hill
Late rice2 seedlings per hill3 seedlings per hill4 seedlings per hill
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Chen, Q.; Li, H.; Huang, H.; Wang, W. Effect of Seedling Rates on Crop Yield and Methane Emissions from Rice Paddies. Atmosphere 2024, 15, 1342. https://doi.org/10.3390/atmos15111342

AMA Style

Chen Q, Li H, Huang H, Wang W. Effect of Seedling Rates on Crop Yield and Methane Emissions from Rice Paddies. Atmosphere. 2024; 15(11):1342. https://doi.org/10.3390/atmos15111342

Chicago/Turabian Style

Chen, Qiping, Hao Li, Hexian Huang, and Wei Wang. 2024. "Effect of Seedling Rates on Crop Yield and Methane Emissions from Rice Paddies" Atmosphere 15, no. 11: 1342. https://doi.org/10.3390/atmos15111342

APA Style

Chen, Q., Li, H., Huang, H., & Wang, W. (2024). Effect of Seedling Rates on Crop Yield and Methane Emissions from Rice Paddies. Atmosphere, 15(11), 1342. https://doi.org/10.3390/atmos15111342

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