Crop residues integration with nitrogen rates reduces yield-scaled nitrous oxide emissions and improves maize yield and soil quality

ABSTRACT

Maize production requires a large amount of nitrogen (N). However, a greater part of the N used gets lost to the environment as reactive forms including nitrous oxide (N₂O). N₂O emissions and associated soil-related factors were measured in a maize (Zea mays L.) field in the 5^th crop after initiation of the experiment in an annual maize-rice sequence. The treatments comprised two levels of crop residues (no residue, NR vs. 30 cm residue, CR) with four levels of N fertilizers (control; farmers’ practice, FP; national recommended dose, RD, and 125% of RD, 1.25 RD). Mean and cumulative N₂O emissions increased with N rate coupled with either residue level. The CR coupled with 1.25 RD had 10% higher N₂O emissions than the same rate as NR. In contrast, yield-scaled N₂O emissions were equal in 1.25 RD coupled with either residue level. However, higher N₂O emissions in CR than in NR can be offset by the corresponding improvement in soil elemental quality, e.g. soil organic carbon, total N, P, K and S. The N₂O emission factor, ranged from 0.99 to 1.34, and was higher in CR coupled with 1.25 RD than in any other combination suggesting that optimization of N rate is one of the best options to reduce N₂O emissions. Maize grain yield was higher in RD and 1.25 RD than in the farmers’ practice where the former two were similar to each other. Step-wise multiple regression showed that N application rate, soil organic carbon, total N and pH are the dominant factors controlling N₂O emissions. Our results suggest that maize production can benefit from residue retention with the current N rate (RD) for better yield, soil quality and N₂O mitigation.

Highlights

1. Optimum fertilizer rate coupled with crop residue reduces N2O emissions.2. N2O emission factors in maize are comparable with the IPCC default value.3. Yield-scaled N2O emissions were similar in fields with and without crop residues.4. Maize yield was higher in crop residue coupled with recommended N rate.5. Recommended N with crop residue incorporation increased soil elemental quality.

KEYWORDS:

• N₂O emissions
• crop residue
• N fertilizer
• emission factor
• Yield-scaled N₂O emission
• soil quality

1. Introduction

Sustainable agricultural management practices are required to balance food production, soil health and environmental impacts. Overpopulation and rising global food demand are pressuring the sustainability and effectiveness of food production (Conijn et al. 2018). Due to increased fertilizer and pesticide use, agricultural productivity has increased dramatically. However, this has led to soil and environmental degradation causing enhanced greenhouse gas (GHG) emissions (Davis et al. 2016). N₂O, a potent GHG emitted from agricultural land, has 298 times more potential for global warming than that of CO₂ (residence time 100 years) (Wang et al. 2015) and contributing to ozone layer depletion (Ravishankara et al. 2009; Wuebbles 2009). As agriculture alone accounts for around 81% of all N₂O emissions, there have been concerns over the past several decades (Krafenbauer and Wriessning 1995). Bouwman et al. (2002) reported 2.8 Tg of N₂O emissions from agricultural fields. However, the global estimates of N₂O emissions have, by far, the largest uncertainty requiring region, climate, soil and crop-specific data (Scheer et al. 2020; Ma et al. 2022).

Agriculture produces four billion metric tons of crop residues every year which perform a variety of environmental functions, including improving crop productivity and preserving soil fertility (Kumar and Goh 2000; Yang et al. 2022); controlling erosion, regulating nutrient cycling, reducing N loss, and boosting soil organic carbon (SOC) levels (Lal 2005). However, residue incorporation can increase N₂O emission by supplying a larger energy source for denitrifiers. Past researchers found conflicting effects of residue incorporation on N₂O emissions, e.g. enhanced (Huang et al. 2017), inhibitory (Ma et al. 2010; Sander et al. 2014) or no impact (Zhang et al. 2015). Since the early 1990s, residue impacts on soil N₂O emissions have drawn considerable attention; yet, it is still very difficult to forecast both the magnitude and the trajectory of soil N₂O emissions after residue amendment. When synthetic nitrogen (N) fertilizers, manure and crop residue are added to the soil, the amount of soil mineral N increases, which stimulates N₂O emissions (Davidson 2009; Akiyama et al. 2020). From a meta-analysis, Chen et al. (2013) indicated that crop residue C:N ratio, soil moisture, texture and pH are important determinants of whether residues have a positive or negative effect on N₂O emissions.

Maize is one of the major crops in the subtropical region with a rising trend of production for sustainable food security. Yet, the quantitative measurement of N₂O emissions from maize fields is scarce, thus limiting both the accuracy of national and global GHG emissions as well as the strategies for mitigations. For implementing the effective management that combines food security and environmental safety, especially in lowering GHG emissions, measured data on N₂O emissions are imperative. Regional N₂O emissions data are critical for directing sustainable strategies that address both environmental issues and agricultural output (Mazzetto et al. 2020). Additionally, the worldwide dilemma of ensuring food security while lowering GHG emissions has led to the frequent proposal of yield-scaled N₂O emissions as a measure (presented as g N₂O per ton grain yield) (Van Groenigen et al. 2010; Qin et al. 2012).

Eco-efficiency analysis of N application in crops significantly contributes to higher yield and N₂O emissions as well (Dong et al. 2007; Davidson 2009). In recent years, people from developing countries are using more N fertilizer and incorporating residue (Bell et al. 2019). Yang et al. (2010) reported that N₂O emissions can be reduced by efficient use of N fertilizer and crop residue incorporation. However, there is a lack of research on N₂O emissions as influenced by the interactive effects of residue and fertilizer in floodplain soil of subtropical climate. In this study, we hypothesize that better N fertilizer rate coupled with crop residue incorporation could help maize production with the soil and N₂O benefits. The specific objectives of the research were as follows: (a) to measure N₂O emissions, yield-scaled N₂O emissions including the emission factor (EF) as influenced by the residue incorporation coupled with N fertilization rates; and (b) to investigate the short-term effects of N fertilizer rate and crop residue incorporation on yield and soil elemental quality.

2. Materials and methods

2.1 Experimental site description

The experiment was conducted in Muktagacha, a sub-district of Mymensingh in Bangladesh (Latitude: 24° 45’ 53.42” N; Longitude: 90° 15’ 25.13” E) and the site belongs to Agro-Ecological Zone 9 (AEZ-9), which was non-calcareous floodplain soils (Aeric Haplaquept in the U.S. Soil Taxonomy; FAO/UNDP 1988). The mean annual temperature at the experimental site was 26.1°C, with a subtropical monsoon climate including an average annual rainfall of 1640 mm for the past 10 years (2010–2019) (BBS 2020). The average monthly rainfall and temperature during the growing season were 25.2 mm and 27.6°C, respectively. Daily rainfall, including maximum and minimum temperatures data, is presented in Figure 1. The experimental soil was low in fertility consisting of 49% sand, 40% silt, and 11% clay, with soil bulk density 1.2 g cm⁻³, pH 5.3, organic C 8.12 g kg⁻¹, total N 0.73 g kg⁻¹, available P 5.9 mg kg⁻¹, exchangeable K 43 mg kg⁻¹, and available S 12.8 mg kg⁻¹.

Figure 1. Weather data for Mymensingh’s muktagacha (2021–22; December-June); column graph indicates the amount of rainfall (mm) in the primary axis, while the line graph demonstrated the maximum and minimum temperature (red; maximum, blue; minimum) with secondary axis.

2.2 Experimental design and crop management

The experiment has been conducted for two consecutive years during 2020–2022 with maize-rice double crop rotation in each of the 2 years, where irrigated maize was grown in winter to pre-monsoon season (December to May) and rainfed rice was grown in monsoon (July to November). Two sets of treatments used in a split-plot experiment were as follows: 1) residue incorporation of the previous crops (no residues were incorporated into soil as crops were cut at 2 cm above the soil surface leaving no residues in the field, conventionally practiced by the farmers, NR vs. 30 cm residue by height, meaning that crops were cut at a height of 30 cm above the soil surface, CR) assigned in the main plots, and 2) four fertilizer N rates were as follows: control, farmers’ practice (FP), recommended N fertilization dose (RD) and 125% of RD (1.25 RD) assigned in sub-plots, and replicated thrice. In the plots treated with crop residue application, maize and rice were cut at a height of 30 cm from the ground surface, and then the residues were incorporated into the soil by a rotary tiller during the final land preparation. All plots with either residues or without residues were tilled using a rotary tiller with the same number of passes. Based on a questionnaire survey (n = 50) in the experimental areas, the fertilizer FP rate was determined. The recommended fertilizer rate was adopted from the national fertilizer recommendations for the test crops (Ahmed et al. 2018) for the particular AEZ.

The N application rate for the CL-FP-RD-1.25 RD treatment was 0-152-225-281 kg ha⁻¹ from urea in both NR and CR. Phosphorus (P), potassium (K), sulphur (S), zinc (Zn) and boron (B) were applied at a rate of 60, 80, 30, 4 and 1 kg ha⁻¹, respectively, as triple super phosphate (TSP), muriate of potash (MoP), gypsum, zinc sulphate (heptahydrate) and boric acid. Except for N fertilizer, all the nutrients were applied at the time of final land preparation and effectively incorporated into the soils by tillage. The N fertilizer was applied at 15^th, 35^th and 55^th days after seed sowing in three equal splits. The tested maize variety was BARI Hybrid Maize-1, and the seed rate was 25 kg ha⁻¹. The distance between the seeds in each line was 30 cm, and the distance between two lines of seeds was 60 cm. Three days prior to the completion of the final land preparation, a non-selective herbicide called glyphosate (ACI Bangladesh Ltd.) was applied to the field at a rate of 1.85 kg ha⁻¹, and a post-emergence herbicide called pretilachlor (Superhit®) was applied at a rate of 450 g ha⁻¹. In addition, Brifer 5 G and Cidial 5 G were used as needed to manage insects.

2.3 Soil sampling analysis

Replicated composite soils samples were collected from a depth of 15 cm for the examination of initial soil properties prior to the experimentation. Composite soil samples were also collected from the same depth adjacent to the N₂O gas sampling chambers to correlate the N₂O emissions with their soil-related properties. After air drying the soil was crushed and sieved using a 2 mm sieve. Soil texture was determined following the hydrometer method as described by Gee and Bauder (1979). Soil pH was measured with a soil:water ratio of 1:2.5 using a glass electrode pH metre (Hanna Bench Top pH Metre HI-2211). Soil organic carbon (wet oxidation technique) and total N were determined using the Walkley and Black (1934) and the micro-Kjeldahl technique (Jackson 1973) method, respectively. The Olsen extractant was used to measure the available P (Murphy and Riley 1962). A flame emission spectroscopic approach was used to assess the exchangeable K⁺. Available S content in soils was determined by a turbidimetric method (Hunt 1980).

2.4 N₂O gas sampling and flux calculation

The N₂O gas samples were collected in the maize field in the 5^th crop during December to May 2022 after two consecutive years of cropping with an annual sequence of maize-fallow-rice. N₂O gas samples were collected after each split application of urea using the static chamber technique (Hutchinson and Mosier 1981). Soda glass chambers, which measure 40 cm in width and 40 cm in height and placed in the middle of each plot to a depth of 10 cm, were fitted with stainless steel collars and covered in reflective paper. The static chamber includes a vent to allow pressure equilibration, a thermometer to measure the temperature inside the chamber, and a fan powered by a 12 V battery to assure well-mixed air during gas sampling. Each collar had a neoprene seal to ensure the chamber lid and base were airtight. This neoprene seal effectively created an airtight barrier, preventing any air leakage between the lid of the chamber and the frame. The gas samples were taken three times after chamber installation between 10:00 a.m. and 4:00 p.m. For each sampling session, three gas samples were collected at 30 min intervals: at 0, 30 and 60 min, using a 50-ml polypropylene syringe fitted with a 25-gauge Luer lock needle put into a three-way stopper and a Teflon tubing attached to the chamber. A 16 ml gas sample from the headspace was taken out and put into a 12 ml pre-evacuated vial in order to over-pressurize the vials (Labco Wycom Ltd.). Gas samples were collected on 0, 1, 3, 5, 7, 10, and 15 days after each split urea fertilization and thereafter at every week until the maturity of maize. During the gas sampling, composite soil samples were collected from spots adjacent to the gas chamber by using an auger and a core sampler at a depth of 0–15 cm, and they were kept in sealable plastic bags in a cooler box.

The gas samples were analysed on a Varian 3800 gas chromatograph (CP-3800, Varian, Inc., Switzerland) equipped with an electron capture detector and using Argon (Ar) as the carrier gas. The regular N₂O Flux was calculated by using

(1) $\frac{\mathit{N}2\mathit{OFlux}=\frac{\frac{\mathit{dGas}}{\mathit{dt}\ast }\left(\mathit{Vchamber}\ast \mathit{P}\ast 100\ast \mathit{MW}\right)}{\left(\mathit{R}\ast \mathit{T}\right)}\ast 10{ }^3\ast 1}{\mathit{A}}$(1)

Where “dGas” (ppb) represents the concentration changed over time, “dt” is the time difference, “10^3” is a unit conversion factor, “Vchamber” is the total chamber volume, “P” is atmospheric pressure in Pa (100 is to convert Pa to hPa), “MW” is molecular weight of N₂O-N, “R” is the ideal gas constant 8.314 J mol⁻¹ K⁻¹, “T” is average temperature inside the chamber in Kelvin and “A” is the basal area of the chamber.

The N₂O emissions on the days between scheduled sampling dates, when gas samples were not sampled in the field, were determined by integrating the area under the curve of each measurement point, following the methodology outlined in Vu et al. (2015). The area between two consecutive measurement intervals was calculated using the trapezoid formula (Eq 2) (Islam et al. 2020).

(2) $\mathit{At}\left(\mathit{xy}\right)=\frac{\left(\left(t{ }_y-t_x\right)\ast \left(E_t\mathit{x}-E_t\mathit{y}\right)\right)}{2}$(2)

The area A_t(xy) of the adjacent intervals of measurement days between t_x and t_y is calculated by considering the dates of the two measurements. The emissions of N₂O gas at these two measurement dates are denoted as E_tx and E_ty, respectively. The trapezoid formula is then applied to calculate the area between the two measurement intervals.

It is assumed that during the gas sampling emissions were linear between measurements when estimating cumulative emission. The cumulative N₂O emissions for the whole experimental period were calculated using the daily fluxes. By adding together all daily fluxes for the whole experimental period using linear interpolation between the sample points, the cumulative emissions of N₂O were computed (Zhang et al. 2013).

Besides that, the N₂O EFs were estimated based on

(3) $\mathit{EF}\left(\mathrm{\%}\right)=\left(N_2\mathit{O}\mathit{Emissions}\mathit{from}\mathit{N}\mathit{treated}\mathit{plot}-N_2\mathit{O}\mathit{Emissions}\mathit{from}\mathit{control}\mathit{plot}\right)/\frac{}{\left(\mathit{Rate}\mathit{of}\mathit{N}\mathit{application}\right)\ast 100}$(3)

Here, EF (%) = Emission factor percentage, N₂O Emissions from N treated plot = Cumulative N₂O Emissions from N fertilized plot in entire maize growing period, N₂O Emissions from control plot = Cumulative N₂O Emissions from unfertilized plot in entire maize growing period.

Additionally, the yield-scaled N₂O emission (YSNE) was calculated as per Equation 4(4) $\mathit{YSNE}=\frac{\left(\mathit{Cumulative}N{ }_2\mathit{O}\mathit{emission}\left(\mathit{gNk}{g}^{-1}\right)\right)}{\left(\mathit{Grain}\mathit{yield}\left(\mathit{tonha}{ }^{-1}\right)\right)}$(4) (Huang et al. 2017) to calculate the N₂O emissions per ton of yield production, which is a crucial metric for regulating food production and lowering the environmental impact at a time.

(4) $\mathit{YSNE}=\frac{\left(\mathit{Cumulative}N{ }_2\mathit{O}\mathit{emission}\left(\mathit{gNk}{g}^{-1}\right)\right)}{\left(\mathit{Grain}\mathit{yield}\left(\mathit{tonha}{ }^{-1}\right)\right)}$(4)

2.6 Yield calculation

The 4 m² of maize plot that was harvested covered the centre of each plot. In the no residue plot, plants were cut manually at 2 cm above the ground surface and removed from the field while in the residue treated plot, they were cut at 30 cm height. Following drying, the yield was estimated by using the below equation.

(5) $\mathit{Grain}\mathit{yield}\left(\mathit{ton}\mathit{ha}-1\right)=\frac{\left(\mathit{Grain}\mathit{yield}\left(\mathit{gm}\right)\ast 10000\right)}{\left(4m{ }^2\ast 1000\ast 1000\right)}$(5)

2.7 Statistical analysis

A two-way analysis of variance (ANOVA) was performed using residue as the main-plot and N rate as a sub-plot in a split plot design to determine the significant variations for the individual and the interaction effects among residue and N application rates. The data distribution for normality was assessed before conducting an ANOVA. Post-hoc testing was carried out (p < 0.05) in order to discern the variability of the treatment effects of N fertilization rates with crop residue incorporation using the Tukey–Kramer multiple comparison test. All analyses were performed using Statistix-10® statistical software, and Microsoft Excel was used to construct the graphical visualization. On SPSS, stepwise multiple regressions were carried out to clarify the connections between N₂O fluxes and soil properties (IBM SPSS Statistics, version 20).

3. Results

3.1 Time course of N₂O emissions

The N₂O emission peaks increased immediately after urea application (Figure 2), irrespective of the treatment, showing the highest peaks on day 1 in all three splits. Among the three split applications of urea, the highest peaks were observed after the third split application in comparison with the other two splits. Moreover, the highest N₂O peaks in CR were much greater than that in NR (Figure 2(a)). In both NR and CR, the N₂O emission peaks returned to background levels on day 10–12 after the urea application. The emission peaks increased with the fertilizer application rate being the highest in 1.25 RD and the lowest in FP, except for the control (Figure 2(b)). N₂O peaks were as high as 213 g N ha⁻¹ d⁻¹ in CR with 1.25 RD treatment combination.

Figure 2. Time course ± SE of N₂O emissions in response to (a) different levels of residue and (b) N fertilizer rate in maize field; crop residue retention = CR and No residue = NR; FP = farmers’ practice, RD = recommended dose, 1.25 RD = 125% of recommended dose; arrows indicate the day of split urea application.

3.2 Mean and cumulative N₂O emissions

The mean and cumulative N₂O emissions from the maize field were significantly influenced by the interaction effect of crop residue and N fertilization rates (Table 1) (p < 0.001). The highest N₂O emissions were found in CR coupled with 1.25 RD (CR-1.25 RD; 59.5 g N ha⁻¹ d⁻¹), followed by NR-1.25 RD (54.3 g N ha⁻¹d⁻¹). The RD coupled with either residue level had similar N₂O emissions to each other. In contrast, the lowest mean emissions were in control-NR treatment (2.2 g N ha⁻¹d⁻¹), which was even lower than control-CR (2.9 g N ha⁻¹d⁻¹). The cumulative N₂O was 10% higher in CR coupled with 1.25 Rd than in the same N rate without CR. N₂O emission factor (EF) was significantly higher in CR couped with 1.25 RD (1.34%) than any other treatment combination being the lowest in NR coupled with control (0.99%).

Table 1. Interaction effect of crop residue and different N fertilization rates on mean, cumulative N₂O emissions and the emission factor (EF%) in maize field (n = 3; mean ± SE).

Residue	N-rate	Mean N2O fluxes (g N ha^−1 d^−1)	Cumulative N2O fluxes (g N ha^−1)	EF (%)
NR	Control	2.2 ± 0.1 g	145.4 ± 6.8 g
	FP	24.8 ± 0.7 e	1637.5 ± 47.7 e	0.99 ± 0.03 d
	RD	39.7 ± 0.9 c	2622.9 ± 56.9 c	1.11 ± 0.03 c
	1.25 RD	54.3 ± 0.6 b	3583.3 ± 38 b	1.23 ± 0.01 b
CR	Control	2.9 ± 0.1 f	193.6 ± 9 f
	FP	27.2 ± 1.7 d	1794.8 ± 109.5 d	1.06 ± 0.07 cd
	RD	39.9 ± 0.4 c	2634.2 ± 29 c	1.09 ± 0.01 c
	1.25 RD	59.5 ± 0.4 a	3930 ± 24.8 a	1.34 ± 0.01 a
Statistics (p < 0.05)
Residue (R)		**	**	*
Fertilizer (F)		***	***	***
R × F		**	**	*

Crop residue incorporation = CR and No residue = NR; FP = Farmer’s practice, RD = Recommended dose, 1.25 RD = 125% of Recommended dose; mean ± standard error with different letters varies significantly where *means p < 0.05, **means p < 0.01, ***means p < 0.001.

3.3 Soil elemental quality and their relationships with N₂O emissions

The interaction effects of crop residue and N fertilization substantially altered soil total N, P, K, and S including SOC and total N (TN) (Table 2). The greatest TN in soil was measured in CR-1.25 RD (0.16%) treatment, which was statistically comparable to the CR-RD (0.15%), CR-FP (0.13%) and NR-1.25 RD (0.13%) treatment combinations. The lowest TN was found in control-NR (0.08%), which were statistically similar to control-CR (0.10%), NR-FP (0.11%), and NR-RD (0.11%) treatment combinations (Table 2). Likewise, the highest SOC was found in CR-1.25 RD (0.70%), which was statistically equivalent to CR-RD (0.70%) and CR-FP (0.65%), and was followed by treatment combinations NR-1.25 RD (0.59%) and NR-RD (0.57%). On the other hand, the lowest SOC was found in the control-NR treated plot. The TN and SOC contents increased with the increment of N fertilization rates integrated with crop residue (p < 0.05). After conducting a stepwise multiple linear regression analysis, we revealed a model that demonstrated the strongest agreement between soil SOC, TN, pH and N application rate with cumulative N₂O emissions. The model follows the Eqn. 6 (Table 3).

(6) $\mathrm{In}{\mathrm{N}}_2\mathrm{O}={0.01}^{\ast }\mathrm{N}\mathrm{rate}(\mathrm{kg}\mathrm{h}{\mathrm{a}}^{-1})+{2.8}^{\ast }\mathrm{SOC}(\mathrm{\%})+{1.7}^{\ast }\mathrm{TN}(\mathrm{\%})\text{break}-{2.5}^{\ast }\mathrm{pH}+18.5;({\mathrm{R}}^2=\mathit{0.97}\mathit{;}\mathit{p}<\mathit{0.001}\mathit{;}\mathit{n}\mathit{=}\mathit{24}\mathit{)}$(6)

Table 2. Interaction effect of crop residue and different N fertilization rates on soil SOC, TN, P, K, S content and pH (n = 3; mean ± SE).

Residue	N-rates	SOC (%)	TN (%)	K (meq./100 g soil)	Available S (ppm)	Available P (ppm)	Soil pH
NR	Control	0.47 ± 0.01 d	0.08 ± 0 d	0.11 ± 0.02 d	9.05 ± 0.02 d	4.2 ± 0.32 e	6.05 ± 0 c
	FP	0.53 ± 0.01 cd	0.11 ± 0.01 bcd	0.19 ± 0.02 abc	17.97 ± 0.97 c	9.52 ± 0.01 c	6.17 ± 0.03 bc
	RD	0.57 ± 0.01 bc	0.11 ± 0.01 bcd	0.16 ± 0.03 cd	21.7 ± 1.27 bc	19.56 ± 1.15 a	6.32 ± 0.04 bc
	1.25 RD	0.59 ± 0.02 bc	0.13 ± 0.01 abc	0.18 ± 0.02 bcd	31.29 ± 0.42 a	14.97 ± 0.43 b	6.45 ± 0.02 ab
CR	Control	0.55 ± 0.03 cd	0.10 ± 0.01 cd	0.17 ± 0.01 cd	19.83 ± 3.06 bc	4.52 ± 2.59 d	6.13 ± 0.04 c
	FP	0.65 ± 0.01 ab	0.13 ± 0.01 abc	0.14 ± 0.01 cd	23.92 ± 2.02 b	13.32 ± 2.31 b	6.20 ± 0.03 bc
	RD	0.70 ± 0.01 a	0.15 ± 0.01 ab	0.27 ± 0.01 a	23.23 ± 1.73 b	16.88 ± 2.37 ab	6.45 ± 0.01 ab
	1.25 RD	0.70 ± 0.01 a	0.16 ± 0.01 a	0.25 ± 0.03 ab	31.72 ± 2.02 a	16.65 ± 2.13 abc	6.70 ± 0.04 a
Statistics (p < 0.05)
Residue		**	*	**	*	*	*
N fertilizer		***	***	*	*	*	*
Residue * Fertilizer		**	**	*	*	**	**

Crop residue incorporation = CR and No residue = NR; FP = Farmers’ practice, RD = Recommended dose, 1.25 RD = 125% of Recommended dose; mean ± standard error with different letters varies significantly where *means p < 0.05, **means p < 0.01, ***means p < 0.001.

Table 3. Estimated coefficients of physico-chemical properties selected as significant explanatory variables using a stepwise procedure for the model of N₂O emissions (n = 24).

Cumulative N2O fluxes (g N ha^−1)	Equation element	Estimate	s. e.	p-Value	Partial R^2
Ln N2O	Intercept	18.5	2.96	***
	N rate (kg/ha)	0.01	0.00	***	0.93
	% OC	2.8	0.99	*	0.27
	% TN	1.7	3.71	*	0.45
	pH	−2.5	0.52	**	0.65

Following stepwise multiple linear regressions of ln N₂O, the calculated coefficients of soil physico-chemical characteristics were selected as important explanatory variables for the models that had the best fit to predict the observed fluxes, where 93% of the variation could be explained by N application (kg ha⁻¹) alone and 65% of the variations could be explained by the soil pH (Table 3).

Integration of crop residue with N rate increased the exchangeable K contents, being higher in CR-RD (0.27 meq 100 gm⁻¹) and CR-1.25 RD (0.25 meq 100 gm⁻¹) than all other treatment combinations. The largest S content was observed in the CR-1.25 RD and NR-1.25 RD treatments (31.7 ppm and 31.3 ppm, respectively), whereas the lowest S level was identified in the NR control treatment (Table 2). Like the exchangeable K, the available P and S contents were also higher in RD and 1.25 RD coupled with the CR than all other treatment combinations. Being the lowest, absolute N control coupled with the CR had higher soil elemental contents than the NR. Likewise, the interaction effect of crop residue and N fertilization rates significantly influenced soil pH (p < 0.001), with 1.25 RD and RD coupled with CR had higher soil pH than all other treatment combinations except the 1.25 Rd with NR (Table 2).

3.4 Maize yield and yield-scaled N₂O emissions (YSNE)

The interaction effect of crop residue and N application rates significantly influenced maize yield (p < 0.001) (Figure 3). The highest yield was observed in the CR-RD treatment combination, which was statistically equal to the CR-1.25 RD treatment, followed by NR-1.25 RD, NR-RD, CR-FP, NR-FP. By contrast, the minimum yield production was contributed by the control treatment regardless of the residue level (Figure 3).

Figure 3. Interaction effect of crop residue and different N fertilization rates on maize yield; crop residue retention = CR and No residue = NR; FP = farmers’ practice, RD = recommended dose, 1.25 RD = 125% of recommended dose; bars with different letters vary significantly from each other at p < 0.05.

The interaction effect of crop residue and N rates significantly influenced the yield-scaled N₂O emissions (p < 0.001) (Figure 4). The 1.25 RD treatment in combination with CR generated the maximum YSNE (325.6 g N₂O-N ton grain⁻¹) to produce per ton yield, which was statistically similar to NR-1.25 RD (298.7 g N₂O ton grain⁻¹) treatment combinations, followed by NR-RD, CR-RD and NR-FP treatments. The lowest YSNE was achieved by NR-CL (61 g N₂O-N ton grain⁻¹) treatment combinations. Additionally, as compared to the farmers’ practice (NR-FP) and the current RD integrated with CR and NR, the yield-scaled emissions were similar to each other.

Figure 4. Interaction effect of crop residue and different N fertilization rates on yield-scaled N₂O emissions in maize field; crop residue retention = CR and No residue = NR; FP = farmers’ practice, RD = recommended dose, 1.25 RD = 125% of recommended dose; bars with different letters vary significantly from each other at p < 0.05.

4. Discussion

Contrary to our hypothesis, incorporating crop residue leads to higher N₂O emissions, but consistent with the hypothesis, the interaction effect of crop residue and high N fertilizer on yield-scaled N₂O emissions was similar to the high N rate coupled with no residue. In the following discussion, we examine the dynamics of N₂O fluxes in relation to residue retention and N applications.

4.1 Treatment effects on N₂O emissions

The largest N₂O emissions were observed 1–2 days after urea application in all splits for all treatments. Among the split applications, the largest N₂O peaks were observed after the third split application of urea where crop residue coupled with the increasing N rate increased the emission peaks. Aligned to our results Mazzetto et al. (2020) and Zhang et al. (2011) reported that from maize field the N₂O emissions increased within the first 10 days of chemical fertilizer application and wheat straw incorporation in soils. Third splits of urea resulted in elevated N₂O emissions, which can be ascribed to the enhanced plant vegetative growth and root exudation, which increased the availability of labile carbon and promoted the microorganism activity linked to N₂O emissions (Islam et al. 2020). The duration of N₂O peaks (from beginning to until it goes down to the background level) induced by fertilization was 10–12 days in our research which was in agreement with Islam et al. (2020) where the authors found that N₂O peaks up to 10 days after urea application in maize. The results signify that field measurement of N₂O emissions should be more frequent after fertilizer applications so that emission peaks are not missed and more frequent emission measurements would better define the duration of emission peaks.

N₂O emissions data in this study were comparable with past research, e.g. Kim et al. (2021) measured 6–7 kg N₂O-N ha⁻¹ y⁻¹ in an upland soil in South Korea, but lower than Ottaiano et al. (2020). N₂O emissions were linearly correlated with fertilizer N rates implying that mitigation of N₂O emissions is required to optimize the N rate, which balances yields, soil quality and N₂O emissions. Fertilizer N increases substrate nitrate (NO₃⁻) content which undergoes denitrification when conditions are favourable. Similar to N₂O, ammonia emissions in rice fields in the same agroecological zone linearly increased with fertilizer N application which was likely due to the greater availability of substrate ammonium with higher N rate (Ferdous et al. 2023). Mazzetto et al. (2020) found that daily N₂O emissions were significantly elevated when N fertilizer was applied to the soil. Many other previous reports also acknowledged increased N₂O from enhanced N fertilization, which is in line with our finding (Baggs et al. 2000; Russow et al. 2008). N₂O emissions in maize fields can be due to both nitrification and denitrification. In irrigated maize, water addition increases water-filled pore space to up to saturation, which is most likely to favour denitrification. As a convention, the irrigation water supply in maize was up to only saturation and no standing water was allowed, after the short spell of saturation soils started aeration which may have stimulated nitrification. Moreover, the N₂O peaks existed to up to 10–12 days which is likely to have resulted from both denitrification and nitrification.

Nutrient cycling and GHG emissions in the soil environment are affected by crop residue decomposition. Crop residues function as an energy source (C as an electron donor) for microbes and favour N₂O production. If the available N inputs from crop residues and synthetic fertilizers were equal, crop residues would have a higher impact on soil N₂O emissions (Chen et al. 2013). Crop residues would add N that could lower the fertilizer requirement and thus indirectly reduce N₂O emissions (Yang et al. 2022) when a revised fertilizer recommendation with a lower rate than the current fertilizer use is followed by the farmers. Crop residue reduces fertilizer N input. The availability of NH₄⁺ and NO₃⁻ can be influenced by the release of organic matter and N from crop residues. This in turn affects how quickly NH₄⁺ is converted to NO₃⁻ and how quickly NO₃⁻ is converted to gaseous forms during nitrification and denitrification (Chen et al. 2013), respectively. Jahangir et al. (2022) observed a positive correlation between crop residue retention and N₂O emissions in rice and wheat, consistent with our findings. Crop residue encourages the microbial community to produce N₂O by creating favourable conditions for microbial activity, providing favourable soil moisture contents, conditioning optimum temperatures, and increasing N availability (Horváth et al. 2010; Hu et al. 2013; Cantarella et al. 2018). Another contributing factor to the increased N₂O emissions with crop residue incorporation is associated with O₂ shortage in soil caused by stimulated microbial respiration due to enhanced microbial activity (Jahangir et al. 2022). Furthermore, applying N fertilizer increases the microbial community’s access to mineral N, resulting in higher N₂O emissions. Baggs et al. (2000) found greater N₂O emissions measured in the field after incorporation of crop residues with a low C:N ratio (Baggs et al. 2000). Due to the greater accessibility of mineral N, residue integration significantly increased N₂O emissions, particularly when integrated with N fertilizations. In contrast, Li et al. (2016) reported that leguminous crop residues will stimulate more N₂O emissions than ryegrass, while the emissions depend significantly on residue quality and soil moisture. However, such effects may depend on the decomposition stage of residues which at its initial stage can cause immobilization but with the progress of mineralization and with added N fertilizer it can cause N₂O emissions. Results about the residue effects on N₂O emissions that are in conflict are likely the consequence of variations in residue properties, soil texture and soil pH (Chen et al. 2013). The N₂O EF is close to the IPCC default EFs (1.11 in RD with NR and 1.09 in RD with CR), which increased to 1.23 in 1.25RD coupled with NR and 1.34 in the same fertilizer rate coupled with CR, suggesting that excessive fertilizer N increases N₂O emissions without increasing crop yield.

4.2 Treatment effects on soil quality

The interaction effect of crop residue and N fertilization significantly altered soil SOC, TN, S, K, P and soil pH. Soil TN and SOC increased with the increment of N fertilization (Table 2), as well as with residue integration suggesting a positive relation between higher SOC and N supply with high organic matter mineralization, which was also supported by Mahal et al. (2019). In agreement with our results, Mulvaney et al. (2009) reported that N fertilizer enhances SOM mineralization by increasing the SOC content, because mineralization of added residues increases microbial necro mass depending on the nature of biomass and microbial efficiency. The C₄ plants, like maize, are more efficient at photosynthesis and require more N for their more energy-demanding C₄ photosynthetic pathway (Burgess and Wang 2023) in its vegetative growth stage. Hence, it is probable that maize used lower N fertilization rate more effectively than greater rates, suggesting higher N application in maize cultivation might accumulate TN content in the soil, which will further encounter more N₂O emissions.

The real time measurement of soil pH at 3 days after fertilizer N application showed an increased value of soil pH. Due to abiotic association and interactions between hydrogen ions and organic anions (Tang and Yu 1999; Rukshana et al. 2011), the pH of the soil increased with the increased residue level (Table 2), which is in line with previous study (Butterly et al. 2013). Biological decarboxylation of organic anions (Yan et al. 1996) and the ammonification of organic N compounds (Helyar and Porter 1989) could be other justifications for increasing soil pH after fertilizer N in the CR plots. Crop residue treated plots remain more reduced due to consumption of oxygen by residue decomposition and thus increase soil pH (Uddin et al., 2021). Potassium content significantly increased with residue retention as crop residues contain significant amounts of K (Andrews et al. 2021) and are rendered accessible for plant uptake through decomposition. Soil available P and S content was recorded to be increasing with increasing N fertilization rate integrated with crop residue (Table 2). The availability of P may be considerably influenced by crop residue mineralization. The rise in soil pH in integrated N fertilizer and CR treated plots can cause the greater availability of P in comparison with the plots without residues. Likewise, the presence of organic residue can enhance the available S content in soils through the mineralization of organic S compounds.

4.3 Maize yield and yield-scaled N₂O emissions

Yield-scaled N₂O emissions were significantly altered by the interaction effect of N fertilizer and residue incorporation, which was in agreement with Huang et al. (2017). Qin et al. (2012) estimated yield-scaled N₂O emissions of 140–498 g N₂O-N per ton of maize, which was comparatively higher than our emission data (61–326 g N₂O-N ton grain⁻¹) and can be likely due to the differences in soil, climatic conditions and in management practices of maize. Conversely, Adviento-Borbe et al. (2007) found lower yield-scaled N₂O emissions (99–281 g N₂O), which is also comparable to our results. The range of yield-scaled N₂O emissions was larger in our study because of the variations in the management practices with a range of N applications coupled with or without residue incorporation. Yield-scaled N₂O emissions could be reduced if maize yield is increased (Huang et al. 2017). However, achieving higher yield in low fertility soil requires higher N application which correspondingly increases N₂O emissions, suggesting the identification of an optimum N rate which balances yield and N₂O emissions. Higher N fertilizer rate coupled with CR than the current RD did not increase maize yield rather it increased N₂O and yield-scaled N₂O emissions. On the other hand, RD coupled with CR increased maize yield over the current FP without increasing the yield-scaled N₂O emissions suggesting that the currently recommended dose of 225 kg N ha⁻¹ coupled with CR in such a low fertility soil could help mitigate N₂O emissions while increasing the yields (Table 1, Figures 3 and 4). According to Huang et al. (2017), straw incorporation raised N₂O emissions by 18–31%, yield by 3–7%, and YSNE by 12–30% compared to without straw treatment. In this short-term experiment, we recorded the weak effect of residue on the grain production and higher N₂O emissions, which was consistent with Huang et al. (2017). Increased N₂O production in CR coupled with residues is the likely effect of the added C which stimulated soil micro-organisms by providing a C source, thereby increasing N₂O emissions (Ambus et al. 2001; Huang et al. 2004, 2013). Contrasting to this, yield-scaled emissions were similar in N rate integrated with CR incorporated plots to the no residue (NR) plots with the same N rate for more efficient use of the added N in the nutrient poor soils. Plant response to the added residue and fertilizer is a function of the soil's native fertility. Malhi et al. (2011) observed a significant effect on maize yield when crop residue was incorporated in combination with the N fertilization in high fertility black Chernozem soil. The FP coupled with either residue level had a lower yield than all other treatment combinations. Despite being non-significant, there was an increasing trend in maize yield in FP-CR over FP-NR; the results are an indication of increased N supply from the added residue, which may have been significant from the continuation of residue application for a longer period. In a five-year trial, Jat et al. (2019), reported that plots that received residue increased maize yield by 10–17% compared to plots with residue removed. This result may be due to the improvement in plant nutrient contents (Kaschuk et al. 2010), improved moisture conditions (Parihar et al. 2017; Jat et al. 2019), and the physicochemical and biological properties of soils in CR (Jahangir et al. 2022) due to relatively long-term residue integration.

5. Conclusions

N₂O emissions from intensively managed maize fields in subtropical climatic conditions are a significant source of atmospheric N₂O. A higher N fertilization rate increases gaseous N loss via volatilization and denitrification but does not necessarily increase maize yield, which suggests that an optimum N rate can balance both crop yield and gaseous loss of N towards achieving the sustainable development goals. An increase in soil organic carbon and total N contents in residue incorporated soils is most likely due to faster residue mineralization in this subtropical humid climate. The experiment implies that the national recommended N fertilizer rate (e.g. RD; 32% more than the FP) coupled with crop residue incorporation improves soil elemental quality without increasing yield-scaled N₂O emissions. Achieving food security in the changing climate while mitigating N₂O emissions and improving soil quality requires optimizing N fertilizer rate.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors agree to make data and materials supporting the results or analyses presented in their paper available upon reasonable request.

Additional information

Funding

This research was financially supported by BAS-USDA (Bangladesh Academy of Sciences-USDA) Endowment Program-Phase 4 in association with the IAEA coordinated research program (CRP) # CRP D1.50.20.