Introduction

Agriculture development is now facing a worldwide concern for sustainability mostly in three aspects: 1) food supply for an increasing population; 2) improving resources utilization efficiency and 3) mitigating detrimental items emission into the environment such as greenhouse gases (GHG). As one of the most important staple food, rice (Oryza sativa L.) feeds more than 50% of the world’s population (Zhou and Sun 2017). According to FAO (2019), China accounts for approximately 28% of the global rice production and 18% of the world’s planting area. Food supply, resources utilization and environmental issues in paddy ecosystems, especially in central and south China are getting more and more concerns.

Previous research has confirmed that rotation in paddy cropping systems, especially those with legumes could play an important role in promoting nutrient cycling, improving soil fertility and maintaining food production by reducing fertilizer investment (Nie et al. 2019). The release of environmental hazard compounds such as NO₃^- leaching and N₂O emission from farmland could also be reduced by rotation (Yu et al. 2014; Machado et al. 2021), or by replacing winter fallow with cover crops (Zhu et al. 2016). Fewer N losses were observed from crop residues than from chemical fertilizers when residues were incorporated into the soil in different rotation systems (Congreves et al. 2017; Taveira et al. 2020).

Studies on agricultural resources utilization have been focused on artificial nonrenewable resource inputs such as nitrogen fertilizer (Liu and Zhang 2011), irrigation water (Jia et al. 2020), etc. The local non-renewable climate resources including solar radiation and heat are usually evaluated for single season crop production (Du et al. 2019). The analysis of cropping effects on solar radiation and cumulative temperature use efficiency from an annual perspective are quite few but in urgent need. As reported by Zhang et al. (2013), food production potential of paddy ecosystems in central China has been increased greatly in the past decades because of an increasing air temperature. The most popular paddy cropping system in central China is single rice followed by winter fallow or rotated with a winter crop such as winter wheat (Triticum aestivum L.) and oil rape (Brassica campestris L.). Therefore, the effects of rotation on radiation and accumulative temperature use efficiency need to be clarified to make a better use of resource potential.

Agriculture is considered as a major anthropogenic source of CH₄ and N₂O, accounting for 50 and 60% of total CH₄ and N₂O emissions, respectively (Smith et al. 2007). About 30% of agricultural CH₄and 11% of N₂O emissions released to the atmosphere are generated from rice paddies over the world (Mer and Roger 2001). Compared with fallow, rotation with cereals such as wheat, or with a winter cover may have profound effects on CH₄ and N₂O emissions from paddy field by altering organic or inorganic fertilizers application (Tellez-Rio et al. 2017) and complex soil conditions (Kamp et al. 2001). The effects of rotation on CH₄ and N₂O emissions from paddy soils are yet to be measured to make a more sustainable rice production.

Rotation with winter crops has been recognized as effective to promote nutrient cycling and reduce N₂O emission from paddy fields (Yu et al. 2014; Zhu et al. 2016). However, the effects of winter crops rotation on radiation and heat use efficiencies, and global warming potential of paddy systems are not well reported. Therefore, this two-year field study was designed with the hypothesis that winter rotations can improve resource use efficiencies and mitigate GHG emissions compared with winter fallow in paddy systems of central China.

Materials and Methods

Site description

The field experiment (2017–2019) was conducted in a farmer’s field in Jiangling County (30°12'N, 112°31'E), Hubei province, central China. This region is in the middle reaches of Yangtze River, one of the most important rice planting areas in China. The climate is humid and mid-subtropical monsoon with an average temperature ranged from 16.0 to 16.4°C and an annual rainfall of 900–1100 mm. The soil is fluvo-aquic, and before the start of the experiment the soil fertility was: 26.44 g kg^-1total carbon, 2.44 g kg^-1total nitrogen, 170.9 mg kg^-1 alkaline hydrolyzed nitrogen, 0.38 g kg^-1total phosphorus, 12.7 mg kg^-1Olsen extractable phosphorus, 159.0 mg kg^-1available potassium, and pH (H₂0) 6.9.

Treatments and agronomic details

The study was started at October 28 in 2016, before that the cropping system in the experimental field was one season rice followed by winter fallow for more than 10 years. In this study three rice cropping systems were compared: rice-winter fallow (RF), rice-winter wheat (RW) and rice-rape (RR). The treatments were arranged in a completely randomized block design with three replications. Nine plots of 98 m²(14 m × 7 m) per individual plot were used. Plots were separated by 0.5 m wide ridges covered with plastic film to avoid water and nutrients runoffs.

Winter crops were transplanted or hand broadcast after rice harvest and straw incorporation by a rotary tiller in late October. For RR plots, rape seedlings (cv. Huayouza62, 30d) were transplanted at a density of 30 cm × 30 cm with a single seedling per hill. Wheat (cv. Zhengmai9023) seeds were hand broadcast at a rate of 225 kg ha^-1in RW plots. The rape and wheat received the same base fertilizer application: 96 kg N ha^-1, 60 kg P₂O₅ ha^-1 and 132 kg K₂O ha^-1(16:10:22% compound fertilizer). The rape was applied with twice top dressings as 36 kg N ha^-1(urea) and 7.5 kg B ha^-1(Na₂B₄O₇·10H₂O)each time while the wheat was top dressed with urea at a rate of 45 kg N ha^-1. RF plots were kept fallow during the whole winter season. In early June, after winter crops harvest and soil management, rice seedlings (cv. Longliangyouhuazhan, 30d) were transplanted at a spacing of 26 cm × 16 cm with 3 plants per hill. Rice plants received a fertilizer application in the form of 225 kg N ha^-1(urea), 75 kg P₂O₅ ha^-1(calcium superphosphate), and 180 kg K₂O ha^-1(potassium chloride). The fertilizer distribution was 40% N, 100% P₂O₅ and 50% K₂O for base fertilizers; 30% N for topdressing at tillering stage; 30% N and 50% K₂O for the second topdressing at grain filling stage. The rice field was flooded by a 3–5 cm depth of water except for the mid-season drainage.

At maturity, grain yield of each crop was measured by randomly selected two 4 m² areas for each plot. The above-ground biomass was separated into straw and grains and measured after oven drying at 75°C to constant weight.

CH₄ and N₂O flux measurements

CH₄and N₂O fluxes were measured from June 2017 to May 2019, by using a closed chamber/gas chromatography method (Sun et al. 2018). The closed chamber (45 cm × 45 cm × 100 cm) was put into the groove of a base which was fixed into the soil in each plot. Thereafter, water was filled into the groove to seal the chamber so no gas leaking will happen between the chamber and the covered field. A battery-driven fan was used to mix the air inside the chamber. For each flux measurement, three gas samples intervals were collected from 9:00 to 11:00 am by using a 25-mL syringe at 0, 8 and 16 min respectively, after the chamber was placed on the fixed base. The chamber was removed from its base after each gas sampling event. Gas samples were taken at 10–15 d intervals during the winter season and at 7–10 d intervals in the rice season.

CH₄and N₂O concentrations were determined by using a gas chromatograph (Agilent 7890B, CA, USA) equipped with a hydrogen flame ionization detector (FID) and an electron capture detector (ECD). The oven and FID were operated at 50 and 300°C, respectively. The temperatures for the column and ECD detector were maintained at 40 and 300°C, respectively.

Calculations for resource use efficiency and GHG emissions

The CH₄ and N₂O fluxes (F_i) were calculated based on the changes of concentration (ΔC) over the time duration (Δt) (Mosier et al. 2006). Cumulative CH₄ and N₂O emissions (CE_i) were calculated via the trapezoidal integration of the mean flux over sampling intervals (Mosier et al. 2006).

(1)

CE_i= (2)

Where ρ is the density of CH₄ or N₂O, V is the volume of the chamber above the enclosed soil with the area of A. T is the temperature inside the chamber (°C). D_i is the interval in days of the adjacent two sampling events and 24 are the hours in a day.

Based on a 100-year time frame, the GWP coefficient is 25 for CH₄ and 298 for N₂O to CO₂ equivalent (IPCC 2007). We calculated the combined GWP for 100 years using Eq. (3):

(3)

The yield scaled GWP was calculated according to Shang et al. (2011).

Yield-scaled GWP = GWP/Y (4)

Where, Y is the crop grain yield for the gas sampling season.

Data of radiation and temperature use efficiencies, including radiation production efficiency (RPE), radiation use efficiency (RUE), accumulative temperature production efficiency (ATPE) and accumulative temperature use efficiency (ATUE) of ≥10°C were calculated by Chang et al. (2016).

RPE (g MJ^-1) = grain yield/solar radiation (5)

RUE (%) = primary productivity/solar radiation (6)

ATPE (kg hm^-2°C^-1d^-1) = grain yield/accumulative temperature (7)

ATUE (%) = accumulative temperature during crop season / annual accumulative temperature (8)

Statistical analysis

Data were analyzed by using the PROC ANOVA procedure in S.A.S. version 9.3 (S.A.S. Institute Inc., Cary, NC, USA). Means of rice yield, cumulative GHG emissions, GWP, yield-scaled GWP, crop yield and resources utilization efficiency were compared based on the least significant difference (LSD) test at the 0.05 probability level.

Results

Yield performance

Across the 2-year observation, no significant difference was detected for grain yield and above-ground biomass in the rice season between rice-fallow and rotation systems of rice-wheat or rice-rape (Fig. 1a, b). In spite of longer growing seasons for the winter crops, their grain yields were much smaller than those of rice (Fig. 1a). Wheat showed significant higher (P ≤ 0.05) grain yields than rape in paddy rotation systems in both years (Fig. 1a). When it came to the annual total grain yield, rice-wheat and rice-rape rotations had greater values than rice-fallow in both years. As shown in Fig. 1b, rice-wheat had the highest annual above-ground biomass because of a higher residue production from winter crops.

Solar radiation and heat efficiency

Indicators such as radiation production efficiency (RPE), radiation use efficiency (RUE), accumulative temperature production efficiency (ATPE) and accumulative temperature use efficiency (ATUE) of ≥10°C were successfully used for solar radiation and heat resources utilization comparisons among different farming systems. In this study, no significant difference was observed for RPE and ATPE during the rice season (Table 1). In the winter season, RPE and ATPE values were zero for rice-fallow because no crop was planted or harvested during winter seasons. For rice-wheat and rice-rape, wheat showed greater (P ≤ 0.05) RPE and ATPE values than rape (Table 1), mainly due to the higher grain yields and dry matter accumulation in rice-wheat plots (Fig. 1). The lower values for RPE and ATPE in the winter seasons could be attributed to the lower temperature in wheat and rape growing seasons. When compared with rice-fallow, the annual RPE and ATPE were significantly increased (P ≤ 0.05) by rice-wheat and by rice-rape in both years (Table 1). By calculation based on above ground dry matter accumulation, RUE values ranged from 0.80–1.68% (Table 1). The highest RUE values were observed in rice-wheat rotation plots, followed by rice-rape and rice-fallow. No significant diffidence was shown for RUE between rice-rape and rice-fallow in 2018–2019. Both the rotation treatments improved ATUE values significantly (P ≤ 0.05) than rice-fallow. Rice-wheat and rice-rape plots had similar ATUE values because of the same growing stages for the winter seasons.

The CH₄and N₂O fluxes and GWP

According to the two-year observation, CH₄ emission rates ranged respectively from 0.05 mg m^-2 h^-1 to 21.52 mg m^-2 h^-1 for the rice seasons and from 0 mg m^-2 h^-1 to 1.98 mg m^-2 h^-1 for the winter seasons (Fig. 2a). The three treatments showed a similar CH₄ emission trend during the rice seasons. Two major peaks were detected for CH₄ emission for all the treatments in rice seasons both in 2017 and in 2018. CH₄ emission rates rose steadily after rice transplanting at early June and got its first peak at late June when rice plants were at full tillering stage. Thereafter, CH₄ emission decreased sharply nearly to zero in the mid-season drainage. CH₄ emission started to increase again when the field was flooded with water and got the second peak at middle August when rice plants were at flowering stage. Little CH₄ emission was observed for the three treatments during the winter crop growing seasons (Fig. 2a). CH₄ fluxes were calculated for the rice season, the winter season and the annual level, respectively. As shown in Table 2, the two-year average values for CH₄ flux in the rice season was increased by 42.0% by rice-wheat but was decreased by 35.6% by rice-rape when compared with rice-fallow. For the annual level, CH₄ flux was promoted by 40.9% by rice-wheat and declined by 35.5% by rice-rape.

Table 1: The 2-year (2017–2019) radiation and temperature production efficiency and use efficiency of different cropping patterns

Year	Treatment	RPE (g MJ^-1）			RUE (%)	ATPE (kg hm^-2°C^-1d^-1）			ATUE (%)
Year	Treatment	Rice season	Winter season	Annual	RUE (%)	Rice season	Winter season	Annual	ATUE (%)
2017–2018
	RF	0.51 ± 0.02 a	0 c	0.26 ± 0.01 b	0.91 c	5.17 ± 0.3 a	0 c	3.70 ± 0.18 b	71.63 b
	RR	0.52 ± 0.01 a	0.16 ± 0.00 b	0.35 ± 0.00 a	1.23 b	5.24 ± 0.1 a	4.68 ± 0.61 b	5.15 ± 0.05 a	93.88 a
	RW	0.52 ± 0.01 a	0.26 ± 0.03 a	0.40 ± 0.01 a	1.68 a	5.25 ± 0.1 a	7.71 ± 0.77 a	5.74 ± 0.16 a	95.23 a
2018–2019
	RF	0.45 ± 0.02 a	0 c	0.24 ± 0.02 b	0.80 b	4.4 ± 0.2 a	0 c	3.18 ± 0.17 b	72.87 b
	RR	0.47 ± 0.02 a	0.15 ± 0.00 b	0.29 ± 0.01 a	1.01 b	4.62 ± 0.2 a	4.32 ± 0.05 b	4.55 ± 0.18 a	92.71 a
	RW	0.47 ± 0.02 a	0.25 ± 0.03 a	0.37 ± 0.01 a	1.48 a	4.65 ± 0.2 a	7.57 ± 0.66 a	5.32 ± 0.16 a	92.01a

Mean ± standard deviation. Different lower-case letters indicate the significantly differences (P < 0.05) based on LSD multiple range tests. RF represents rice-fallow, RR represents rice-rape, RW represents rice-wheat. RPE represents radiation production efficiency, RUE represents radiation use efficiency, ATPE represents accumulative temperature production efficiency of ≥10°C, ATUE represents accumulative temperature use efficiency of ≥10°C

12.21

Fig. 1: Correlation between the average crop grain yield (a) and above ground biomass (b). RF represents rice-fallow, RR represents rice-rape, RW represents rice-wheat. The Correlation shows positive correlation between grain yield and above ground biomass

N₂O emission rates ranged respectively from 0 to 420.7 μg m^-2 h^-1for the rice seasons and from 0 to 169.5 μg m^-2 h^-1for the winter seasons (Fig. 2b). In general, N₂O rates were greater in the rice seasons than in the winter seasons in the two-year observation. Dramatically different N₂O emission patterns were measured among treatments and years. In the rice seasons and the beginning of the winter season in 2017, most of the N₂O rates were higher than 100 μg m^-2 h^-1for rice-wheat plots. For the year 2018, the rice season’s N₂O rates showed an impulse trend regardless of the treatments. N₂O emission peaks were obviously higher in 2018 than those in 2017 (Fig. 2b). When compared with rice-fallow, N₂O seasonal flux in the rice season was increased by 54.2 and 8.3% in rice-wheat and rice-rape plots, respectively. For the annual level, N₂O emission was promoted by 66.7 and 26.3% in rice-wheat and rice-rape plots, respectively (Table 2).

Global warming potential (GWP) was calculated based on the data for CH₄and N₂O annual emissions to make an integrated estimation of the global warming effects of the greenhouse gases emitted from the field. In this study, GWP values of CH₄and N₂O were highest in rice-wheat treatment and lowest in rice-rape treatment during both years (Table 2). The increased GWP could be a result of a greater annual CH₄ emission as CH₄ emission contributed the most part of GWP. We also estimated yield-scaled GWP which was calculated as GWP divided by grain yield. As shown in Table 2, yield-scaled GWP of rice-rape was the lowest while no significant difference was found between rice-wheat and rice-fallow.

Discussion

Although rotation with rape or with wheat showed no effect on radiation and heat use efficiencies during the rice season; however, rotation prompted the radiation and heat use efficiencies from the perspective of annual production. Moreover, the CH₄and N₂O emissions from paddy soils differed with rotation with different winter crops (Table 2).

There were diverse reports on the effects of rotation on the main cereal crop yields when the same rotation pattern was applied continuously over years. Crops followed by legume rotations usually showed promoted nitrogen accumulation and higher grain yields (Yu et al. 2014; Zhu et al. 2016). Sometimes, yield reduction of the main crop resulted from rotation could be attributed to the competition for nitrogen after the incorporation of the second crop residue, such as rape and ryegrass because of a high carbon/nitrogen ratio (Armstrong et al. 1996; Nie et al. 2019), in spite that the rotation treatments were coupled with crop residue return, which means an additional nitrogen supply during the main rice crop season (Zhu et al. 2016). In this study, rotation with wheat or with rape had no significant effect on the grain yield and above ground biomass of rice for both years, possibly due to the high level of rice grain yields (ranged from 12.1 to 13.6 t ha^-1, Fig. 1a). However, rotation prompted crops production from the perspective of annual production.

Rotation might change climate resources utilization such as light and heat in two ways. First, when compared with fallow, rotation with winter crops could utilize the light and heat resources which would otherwise be wasted in the winter season (Chen et al. 2021). Second, the management of the winter crops might affect the growth of the following main summer crop (Huang et al. 2006). In this study, rotation systems are more productive than rice-fallow, mostly due to the winter crops utilization on light and temperature resources. The annual yield and biomass advantages of rice-wheat and rice-rape were mainly resulted from the significantly increased radiation and temperature use efficiency (Table 1). Because of no difference was found for rice grain yields, the yield based light and heat utilization indices such as radiation production efficiency and accumulative temperature production efficiency in the rice seasons were not significantly affected by rotation in this study. When it comes to the winter season, wheat had a greater potential than rape in improving light and temperature resources.

CH₄and N₂O emissions are closely related to farming system changes including crop species, fertilizer application, water management and straw returning in paddy fields (Yao et al. 2017; Sumaira et al. 2019; Zhao et al. 2020). The CH₄ emission peaks observed in this study were similar with those measured in other studies based on cropping system management (Zhang et al. 2015; Xu et al. 2016), when the paddy soil was flooded and the rice plants were at a rapid growing stage. Winter rotation coupled with winter crops straw incorporation didn't change the CH₄ emission trend during the rice season. However, the seasonal CH₄ emission flux was dramatically different among different winter rotations when compared with fallow. The increased CH₄ emission for rice-wheat ranged 26.5–64.0% for the rice season and 29.1–55.6% for the whole year, respectively. The promoted CH₄ emission could be attributed to the enhanced above ground biomass yield of wheat and a larger quantity of straw returning into the soil after wheat harvest (Ma et al. 2009). Organic material incorporation, especially those with a high C/N ratio, provided available carbon substrate for CH₄ production methanogens.

Similar with CH₄ emission, N₂O emission flux was smaller in the winter seasons than in the rice seasons, possibly due to the lower temperature. N₂O production and emission from paddy soils are mainly happened during the processes of nitrification and denitrification (Wang et al. 2016). Crop rotations associated with different organic carbon and nitrogen management could change the substrate availability and the activity of functional microorganisms. Rice-wheat increased N₂O emission in the rice seasons while no significant difference for rice-rape and rice-fallow. The reason could be explained by the difference in the quality and quantity of straw returning into the soil followed by different winter crops.

Global warming potential could be a useful indicator to investigate integrative effects of different greenhouse gases from agricultural systems. The relationship of food production and greenhouse gases emission could be further measured by introducing the yield-scaled GWP. In spite that the global warming potential of N₂O is approximately 12 times larger than that of CH₄, the average CH₄emissions was nearly 35 times that of N₂O, resulting in the major contribution for GWP from CH₄ emission (Table 2). Because of a significant increase of CH₄ emission, the GWP values were highest in rice-wheat, followed by rice-fallow and rice-rape. The yield-scaled GWP was decreased by rice-rape because of its lower CH₄ emission.

Conclusion

Annual grain yield, radiation and heat resources utilization and their production efficiency were improved by rotation with winter crops. The CH₄ emission from paddy soils as well as yield-scaled GWP was increased by rice-wheat and decreased by rice-rape system. These results suggested rice-rape could be more sustainable cropping pattern to increase solar radiation and heat resources utilization and mitigate greenhouse gases emission.

Acknowledgements

This work was supported by the National Key Program of Research & Development of China (2017YFD0301400), National Natural Science Foundation of China (No. 31870424), Hubei Key Program of Research and Development (No. 2020BBA044, 2020BBB089).

Author Contributions

Gong Songling: Initial draft and data analysis; Li Chengwei: Data collection; Liu Zhangyong: Data analysis method; Zhu Bo: Framework and overall idea of the paper.

Conflicts of Interest

The authors declare there is no conflict of interest regarding the publication of this paper.

Data Availability

The data will be available upon reasonable request to the corresponding author.

Ethics Approval

Not applicable.

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Received 22 January 2021; Accepted 25 February 2021; Published 10 May 2021

Abstract