Impacts of Conservation Tillage on Soil Organic Carbon Mineralization in Eastern Inner Mongolia

Abstract

Soil organic carbon (SOC) mineralization plays the critical role of regulating carbon sequestration potential. This process is strongly influenced by agricultural practices, particularly tillage regimes and straw management. However, the complex interactions between tillage methods, straw types, and application rates in terms of SOC dynamics, especially in semi-arid agroecosystems like eastern Inner Mongolia, remain poorly understood. In this study, we assessed the combined effects of no tillage (NT) vs. rotary tillage (RT), three straw types (maize/MS, wheat/WS, and oilseed rape/OS), and three application rates (0.4%/low, 0.8%/medium, and 1.2%/high) on SOC concentration and mineralization using controlled laboratory incubation with soils from long-term plots. The key findings revealed that NT significantly increased the SOC concentration in the topsoil (0–20 cm) by an average of 14.5% compared to that in the RT. Notably, combining NT with medium-rate wheat straw (0.8%) resulted in the achievement of the highest SOC accumulation (28.70 g/kg). SOC mineralization increased with straw inputs, exhibiting significant straw type × rate interactions. Oilseed rape straw showed the highest specific mineralization rate (33.9%) at low input, while maize straw mineralized fastest under high input with RT. Therefore, our results demonstrate that combining NT with either 0.8% wheat straw or 1.2% maize straw represents an optimal application strategy, as the SOC concentration is enhanced by 12–18% for effective carbon sequestration in this water-limited semi-arid region. Therefore, optimizing SOC sequestration requires the integration of appropriate crop residue application rates and tillage methods tailored to different cropping systems.

1. Introduction

Soil organic carbon (SOC) serves as a crucial component of terrestrial carbon pools, playing a pivotal role in regulating global carbon cycling [1] and atmospheric CO₂ concentrations [2,3]. Multiple factors, including climate conditions, soil properties, cropping systems, and agricultural practices, collectively influence SOC mineralization and stabilization processes, thereby directly determining carbon sequestration potential. Nevertheless, the intricate interactions that occur among tillage regimes, cropping systems, and straw return rates remain insufficiently quantified for single-cropping systems in eastern Inner Mongolia, which significantly hinders our understanding of SOC cycling mechanisms and the development of effective climate adaptation strategies. Conservation tillage practices, such as no tillage (NT), minimize soil disturbance and protect SOC. In contrast, rotary tillage (RT; a reduced tillage practice) can disrupt soil structure and accelerate SOC mineralization by increasing microbial access and aeration [4]. Furthermore, straw incorporation serves as a primary source of external carbon input and significantly influences SOC dynamics [5,6]. Notably, the balance between SOC mineralization and stabilization under the addition of straw is highly sensitive to application rates [7,8]. However, key uncertainties persist regarding optimal straw management strategies for SOC sequestration.

Tillage practices affect SOC accumulation and mineralization as they alter the soil’s physical and chemical properties [9]. Previous studies have shown that conventional tillage methods, such as RT, expose SOC to air, accelerating its mineralization and leading to SOC depletion [10]. Conversely, conservation tillage practices, particularly NT, enhance surface SOC storage and stability by minimizing soil disturbance and retaining surface mulch [11,12]. The effects of tillage on SOC, however, are context-dependent. For example, in maize-upland rice systems, crop residue burning has been found to increase SOC levels [13], while variations in fertilization methods also significantly regulate this process [14]. Despite the fact that extensive research has been conducted on the effects of tillage, regional variations in soil properties, climate conditions, and cropping systems have yielded inconsistent conclusions, warranting further investigation. To address this gap, with this study, we specifically examine the complex interactions between tillage practices (NT or RT), straw types (maize, wheat, and oilseed rape), and application rates (low, medium, and high) in terms of SOC mineralization, aiming to provide more mechanistic insights beyond simple tillage comparisons.

Increasing straw return has been widely recognized as a key strategy that can be used to enhance SOC sequestration [15,16]. While higher annual straw inputs are commonly adopted to promote SOC accumulation [17], the quantitative effects of application rates on SOC dynamics—particularly the existence of an optimal rate that maximizes sequestration efficiency—remain insufficiently understood across different tillage systems. Furthermore, different straw types exhibit varying SOC sequestration efficiencies due to their distinct chemical compositions and decomposition characteristics; however, their comparative roles in SOC stabilization are still poorly understood. Another critical research gap lies in the predominant focus on single management practices, which does not account for the potential synergies among three key factors: tillage (affecting straw placement and soil environment), straw type (determining inherent decomposability and sequestration potential), and application rate (controlling carbon input quantity). We hypothesized that significant synergistic interactions exist among tillage practices, straw types, and application rates, leading to divergent effects on SOC concentration and mineralization kinetics across treatment combinations; specifically, an optimal combination strategy (defined by specific tillage–straw–application rate pairing) would maximize the efficiency of SOC sequestration.

The Inner Mongolian Plateau is a major grain-producing region [18], and it was an early adopter of conservation tillage in China [19]. Characterized by a typical semi-arid agroecosystem with low temperatures and precipitation, its agricultural importance is growing due to climate change. However, our understanding of carbon dynamics under conservation tillage (e.g., NT and RT) combined with straw return (varying types and rates) remains particularly limited in such semi-arid regions compared to more studied temperate/subtropical zones, such as the North China and Northeast Plains. This knowledge gap hinders the development of effective carbon management strategies for these vulnerable ecosystems.

Based on a long-term conservation tillage experiment performed in the semi-arid agroecosystem of eastern Inner Mongolia, with this study, we aimed to evaluate the combined effects of tillage methods, straw return, and application rates on SOC mineralization and stabilization. To complement the long-term field observations and capture rapid response dynamics, a 70-day laboratory incubation was performed. The specific objectives of this study were as follows:

(1)

Quantify tillage effects on surface soil (0–20 cm) SOC content and mineralization rates;

(2)

Characterize the impacts of straw type and application rates on SOC mineralization;

(3)

Assess the interactive effects of straw application rates, tillage practices, and straw types on SOC dynamics and mineralization.

2. Materials and Methods

2.1. Experimental Design

This study was performed as part of a long-term conservation tillage experiment initiated in 2017 and sampled in 2024 (a 7-year period) in Arongqi County (47°56′ N, 122°09′ E), Hulunbuir City, within China’s Inner Mongolia Autonomous Region. This region has a temperate continental monsoon climate, with historical averages (1957–2021) from the Arongqi Meteorological Bureau [20] showing the following: 624 mm annual precipitation, 2 °C mean annual temperature, and 2700 °C accumulated temperature (≥10 °C). The agricultural system follows a single-cropping pattern annually, with wheat, maize, and oilseed rape as the primary crops. Located in the southern Great Khingan Mountains, Arongqi County represents a significant agricultural production area in eastern Inner Mongolia [21], where these dominant crops generate substantial straw resources suitable for return practices [22,23].

To assess the straw input effects, a 70-day laboratory soil incubation experiment was performed. Based on the actual field practice conversions, three straw application rate gradients were established: 0.4% (low, L), 0.8% (medium, M), and 1.2% (high, H) [24,25,26]. The experimental design incorporated three factors: tillage methods: No tillage (NT) and rotary tillage (RT); crop straw types: Maize straw (MS), wheat straw (WS), and oilseed rape straw (OS); and straw addition rates: 0.4% (L), 0.8% (M), and 1.2% (H) by mass ratio on a dry mass basis (

Table 1. Details of the experimental treatments.

Tillage	Straw	Addition Rate	Addition Ratio
NT	MS	L	0.4% MS
		M	0.8% MS
		H	1.2% MS
	WS	L	0.4% WS
		M	0.8% WS
		H	1.2% WS
	OS	L	0.4% OS
		M	0.8% OS
		H	1.2% OS
RT	MS	L	0.4% MS
		M	0.8% MS
		H	1.2% MS
	WS	L	0.4% WS
		M	0.8% WS
		H	1.2% WS
	OS	L	0.4% OS
		M	0.8% OS
		H	1.2% OS

NT: no tillage; RT: rotary tillage; MS: maize straw; WS: wheat straw; OS: oilseed rape straw.

). This factorial arrangement resulted in eighteen treatment combinations, with three time replications. For each tillage method, we included a control treatment (CK) without straw return, using 30 g of dry soil as a blank reference. We also used empty incubation bottles containing only the NaOH solution (without soil or straw) to quantify and correct for background CO₂ absorption from the atmosphere during the bottle handling procedures (e.g., when opening bottles to remove samples or replace NaOH traps).

2.2. Soil Sampling

Soil samples were collected in October 2024 following crop harvest from the 0 to 20 cm soil layer. In the laboratory, visible plant residues and stones were manually removed. The samples were air-dried at room temperature, gently crushed, and passed through a 2 mm sieve to ensure homogeneity before being stored in sealed containers at room temperature until they were used for analysis. The soil in the study area is classified as Luvisol (FAO), dark brown earth (Chinese Soil Taxonomy), with a USDA texture classification of loam (sand/silt/clay = 40:35:25).

Prior to the experiment, soil samples from the 0 to 20 cm plow layer were analyzed to determine their basic physicochemical properties (

Table 2. Basic characteristics of the 0–20 cm soil layers before the experiment commenced.

Soil Properties	NT	RT
SOC (g/kg)	27.2	26.1
Total nitrogen (g/kg)	2.57	2.51
Available phosphorus (mg/kg)	3.75	7.83
Available potassium (mg/kg)	464.2	461.7
pH	6.03	6.16

NT: no tillage; RT: rotary tillage.

). The soil water content and maximum field water-holding capacity were measured using the gravimetric method. The total nitrogen content was determined using the Kjeldahl method, and the SOC concentration was analyzed via dichromate oxidation (K₂Cr₂O₇-H₂SO₄ system).

Air-dried maize, wheat, and oilseed rape straw, sourced from the same field, were roughly ground and sieved through a 2 mm mesh sieve.

2.3. Laboratory Incubation

All soil samples were adjusted to 70% of their maximum field water-holding capacity. For different treatments, straw was added to 30 g dry soil samples under both NT and RT conditions. In the NT treatments, straw was evenly spread on the soil surface (an approximately 0.5 cm thick layer), and it was not mixed. For the RT treatments, straw and soil were thoroughly homogenized using a sterile glass rod. The prepared soil samples were then sealed in airtight incubation bottles. All of the bottles were placed in an incubator maintained at 25 °C with 15% relative humidity for a one-week pre-incubation period. This pre-incubation period allowed for the soil microbial communities to acclimatize to the experimental conditions, ensuring that we collected more precise and consistent results in the subsequent measurements.

Following the pre-incubation period, the samples were incubated at 25 °C for 70 days. Each bottle contained a 10 mL beaker with 10 mL of 1 M NaOH solution to trap CO₂ that was released during the incubation. On days 3, 5, 10, 15, 20, 30, 50, and 70 of the experiment, the NaOH-containing beakers were removed from the bottles so that they could undergo analysis. The CO₂ released from the soil (indicating mineralization) was quantified using hydrochloric acid back-titration. The results were expressed as CO₂-C emissions per kg of organic carbon (SOCam mg CO₂-C/kg soil).

2.4. Measurement of SOC Content and Mineralization

2.4.1. SOC Content

The SOC content was determined using the Walkley–Black method following the standard protocol (Walkley & Black, 1934). Air-dried soil samples sieved to <0.15 mm (0.2 g) were digested with K₂Cr₂O₇-H₂SO₄ at 210 °C for 5 min and then titrated with FeSO₄. The SOC concentration (g/kg) was calculated after the blank correction.

2.4.2. SOC Mineralization

The NaOH absorption back-titration method was used to determine SOC mineralization. For the 30 g soil sample under cultivation, a beaker containing 20 mL of 1 mol/L NaOH solution was placed on a rack. On the nth day of mineralization incubation, the NaOH absorption solution was taken out, and 1 mL of 1 mol/L BaCl₂ solution was added to the absorption solution to precipitate CO₃²⁻ as BaCO₃. After it was left to stand, 2–3 drops of phenolphthalein indicator were added, and the solution was titrated with 0.2 mol/L HCl until the red color disappeared. The amount of CO₂ released was calculated based on the difference in HCl consumption between the blank group and the sample group, and the cumulative organic carbon mineralization amount (mg C/g) was obtained.

2.5. Data Calculation

Soil organic carbon (SOC) mineralization was achieved through NaOH-trapped CO₂ back-titration with HCl. Cumulative mineralization (CN) was calculated by adding up the daily mineralization values (CN) over time. Specific mineralization (SOCpm) was found via normalizing the absolute mineralization (SOCam) to the soil SOC concentration.

Mineralization dynamics were modeled using a first-order kinetic equation:

$${\mathrm{C}}_{\mathrm{N}} = {\mathrm{C}}_{\mathrm{p}} \times \left(1 - {\mathrm{e}}^{\left(-\mathrm{K}0 \times \mathrm{t}\right)}\right)$$

(1)

where C_N is the cumulative mineralization amount of organic carbon after time t (mg C/kg soil); C_p is the carbon amount with the potential to be mineralized; and K0 is a fixed-rate constant for decomposition. The two unknown quantities (C_p and K0) were estimated using SPSS 27.0 (SPSS Inc., Chicago, IL, USA). The complete calculation procedures are provided in the Supplementary Materials (cites references [27,28]).

2.6. Statistical Analysis

Experimental data were processed and analyzed using Microsoft Office 2024 software and SPSS 27.0 software. Three-way analysis of variance (ANOVA) was performed using SPSS 27.0 to elucidate the impacts of each treatment (tillage methods, crop straw types, and straw addition rates) on the cumulative amount of SOC mineralization. When the significance level was set at p < 0.05, Tukey’s method was used to conduct multiple comparisons of the means among different treatments, aiming to identify whether significant differences existed among the treatment groups. We also conducted first-order kinetic model fitting to obtain the mineralization rate using SPSS 27.0. Moreover, GraphPad Prism 9.5 software was used to visualize the experimental data and generate relevant charts, thereby intuitively presenting the experimental results for the analysis and discussion.

3. Results

3.1. SOC Concentration

Through performing an analysis of variance (ANOVA), we demonstrated the significant main effects of tillage (T), straw type (S), straw addition rate (R) (

Table 3. SOC concentration under different treatments after laboratory incubation.

Treatment		L	M	H
NT	MS	25.12 ± 0.8b	25.93 ± 0.9b	27.37 ± 0.5a
	WS	27.17 ± 0.7a	27.41 ± 0.4a	27.50 ± 0.2a
	OS	25.29 ± 0.3b	25.46 ± 0.5b	27.46 ± 0.3a
	CK	25.14 ± 0.5c
RT	MS	24.75 ± 0.1a	25.65 ± 0.7a	27.15 ± 0.4a
	WS	25.10 ± 0.1a	25.67 ± 0.2a	26.80 ± 0.2a
	OS	22.65 ± 0.2b	23.52 ± 0.1b	24.20 ± 0.1b
	CK	22.89 ± 0.1c

NT: no tillage; RT: rotary tillage; MS: maize straw; WS: wheat straw; OS: oilseed rape straw; CK: control (no straw); L: low rate (0.4%); M: medium rate (0.8%); H: high rate (1.2%). Values are mean ± standard deviation (n = 3). Values followed by different letters within the same column are significantly different at p < 0.05.

), and their interactions on the SOC content after undergoing laboratory incubation (p < 0.01) (

Table 4. ANOVA of the SOC concentration under treatments.

Treatment	p
T	<0.01
S	<0.01
R	<0.01
T × S	N.S.
T × R	<0.01
R × S	<0.01
T × R × S	<0.01

T: tillage method; S: straw type; R: straw addition rate; N.S.: not significant.

). Across all of the treatments, the SOC concentrations showed a progressive increase, with higher straw addition rates spanning from low to high levels. Under NT conditions, the application of wheat straw at low to medium rates yielded the highest SOC concentrations, exceeding maize straw by 5.70–8.16% and oilseed rape straw by 7.43–7.66%. However, at high addition rates, no significant differences in the SOC concentration were detected among the three straw types under NT. In contrast, in the rotary tillage (RT) treatments, oilseed rape straw had the lowest SOC concentrations, which were 9.06–12.19% lower than that of maize straw and 9.14–10.81% lower than that of wheat straw.

NT consistently maintained higher SOC concentrations than RT across all of the straw treatments. The mean SOC content under NT (26.8 ± 1.2 g/kg) was significantly greater than that under RT (23.4 ± 1.5 g/kg). Without the addition of straw, NT enhanced the SOC concentration by 9.83% relative to RT. When straw was incorporated, this NT advantage ranged from 0.81% to 13.47%, with the smallest differences observed for maize straw (0.81–1.50%) and more substantial differences for wheat (2.61–8.24%) and oilseed rape straw (8.25–13.47%).

3.2. SOC Mineralizability

3.2.1. Absolute SOC Mineralization

The tillage methods, straw application rates, and their interactions significantly influenced the absolute SOCam, whereas the differences among straw types were not statistically significant. As shown in

Table 5. SOCam under different treatments after laboratory incubation.

Treatment		L	M	H
NT	MS	256.22 ± 28.46b	434.31 ± 60.26b	702.67 ± 55.70a
	WS	303.90 ± 12.54a	487.17 ± 12.08b	682.17 ± 28.28b
	OS	279.40 ± 21.47a	524.94 ± 6.62a	654.71 ± 8.34b
	CK	160.92 ± 29.07
RT	MS	281.06 ± 29.69b	563.39 ± 13.58a	767.88 ± 45.72a
	WS	325.34 ± 27.39a	546.82 ± 10.63a	649.13 ± 35.58b
	OS	324.84 ± 3.30a	509.25 ± 9.64a	617.57 ± 21.20b
	CK	167.34 ± 23.68

NT: no tillage; RT: rotary tillage; MS: maize straw addition; WS: wheat straw addition; OS: oilseed rape straw addition; CK: no straw addition; L: low straw addition rate; M: medium straw addition rate; H: high straw addition rate. Values are mean ± standard deviation (n = 3). Values followed by different letters within the same column are significantly different at p < 0.05 (Tukey’s test).

, SOCam increased significantly with the increase in the straw application rates. At low application levels, maize straw exhibited the lowest SOCam, which was 9.05–15.58% lower than that of oilseed rape straw and 15.75–18.61% lower than that of wheat straw. Under NT with a medium straw application, oilseed rape straw had the highest SOCam, which was 7.75% higher than that of wheat straw and 20.87% higher than that of maize straw. At high straw application levels, however, maize straw resulted in significantly higher SOCam than that of wheat and oilseed rape straw. Specifically, under RT with a high maize straw application, SOCam reached the highest value among all of the treatment combinations, representing a 173% increase compared to the low maize straw application of the same straw type. Although no significant interaction between the tillage methods and straw types was found when comparing the same straw type, the interactions between the tillage method and application rate, between the straw type and application rate, and the three-way interaction among tillage, straw type, and application rate all had significant effects on SOCam. In summary, NT consistently maintained significantly higher SOC concentrations than RT, with the magnitude of this difference being modulated by both the straw type and application rate. The advantage of NT was most pronounced in the absence of straw and with the addition of wheat or oilseed rape straw (

Table 6. ANOVA of SOCam under different treatments.

Treatment	p
T	<0.01
S	N.S.
R	<0.01
T × S	N.S.
T × R	<0.01
R × S	<0.01
T × R × S	<0.01

T: tillage method; S: straw type; R: straw addition rate; N.S.: not significant.

).

Cumulative SOC mineralization increased over time in all of the treatments, with consistent dynamics characterized by rapid initial growth followed by gradual deceleration. Cumulative mineralization (CN) increased with an increase in the straw application rates from the beginning of the incubation, with steeper upward slopes at higher addition rates (Figure 1 and Figure 2). During the rapid increase phase, the slopes for high addition rates were significantly steeper (p < 0.05) than those for low/medium rates and the control (CK) group. The mineralization trends under rotary tillage (RT) closely mirrored those under no tillage (NT), with consistent patterns in terms of curve shapes, relative positions, and statistical significance across all of the treatment groups.

The three straw types exhibited remarkably similar mineralization patterns when applied at equivalent rates, demonstrating nearly identical mineralization quantities and curve slopes (Figure 3 and Figure 4). However, under high straw addition conditions, maize straw showed greater mineralization than both wheat and oilseed rape straw. Notably, straw incorporation significantly enhanced both the total amount of soil mineralization and the mineralization curve slope compared to the treatments that did not have straw added to them (p < 0.05).

3.2.2. Specific SOC Mineralization Rate (SOCpm)

Both tillage practices and straw addition rates significantly affected the specific SOC mineralization rate (SOCpm) (p < 0.01), whereas straw types showed no significant effect. As presented in

Table 7. SOCpm under different treatments after laboratory incubation.

Treatment		L	M	H
NT	MS	10.21 ± 1.2	11.72 ± 0.5	11.87 ± 0.3
	WS	16.01 ± 2.5	16.98 ± 0.2	19.09 ± 0.4
	OS	27.81 ± 2.5	26.80 ± 1.3	22.50 ± 1.0
	CK	6.41 ± 1.2
RT	MS	11.36 ± 1.2	12.70 ± 1.3	24.12 ± 0.1
	WS	22.44 ± 0.6	21.30 ± 0.5	16.50 ± 4.0
	OS	33.90 ± 1.7	27.60 ± 1.6	25.52 ± 1.0
	CK	7.31 ± 1.0

NT: no tillage; RT: rotary tillage; MS: maize straw addition; WS: wheat straw addition; OS: oilseed rape straw addition; CK: no straw addition; L: low straw addition rate; M: medium straw addition rate; H: high straw addition rate. Values are mean ± standard deviation (n = 3).

, the SOCpm values under no tillage (NT) were consistently lower than those under rotary tillage (RT), with the NT treatments showing a 15.70–28.66% reduction compared to RT under equivalent conditions. For the maize straw treatments, SOCpm exhibited a positive correlation with the increase in the straw addition rates. At high application rates, the SOCpm values were elevated by 1.28–11.18% compared to the medium rates and by 16.26–24.30% relative to the low rates. Conversely, oilseed rape straw demonstrated an inverse relationship, with low addition rates resulting in 3.77–22.82% and 23.6–32.84% higher SOCpm than the medium and high rates, respectively. This pattern likely stems from oilseed rape straw’s inherent chemical properties—such as its lower lignin content and higher water-soluble carbon (e.g., sugars and organic acids)—which enable rapid microbial colonization and decomposition when supplied at low rates. At high inputs, however, excessive labile carbon may induce nutrient limitation (e.g., N scarcity) or microbial metabolic repression, slowing down mineralization. Wheat straw showed divergent patterns depending on the tillage method used; SOCpm increased along with the addition rate under NT but decreased under RT. Among the three straw types, oilseed rape straw consistently yielded the highest SOCpm values, followed by wheat straw and then maize straw. Through conducting a statistical analysis, we revealed that while the interactions between tillage methods and straw types, and between tillage methods and addition rates, had no significant effects on SOCpm, significant interactions were observed for the three-way interaction among these farming practices (

Table 8. ANOVA of specific SOC mineralization under treatments.

Treatment	ANOVA
T	<0.01
S	N.S.
R	<0.01
T × S	N.S.
T × R	N.S.
R × S	<0.01
T × R × S	<0.01

T: tillage method; S: straw type; R: straw addition rate; N.S.: not significant.

).

3.3. SOC Mineralization Rate Constant (K0)

The R² values of most of the treatments exceeded 0.99, indicating a high level of model fit and reliable curve fitting results. The tillage, straw type, and straw addition rate all significantly influenced the SOC mineralization rate constant. Under NT, the SOC mineralization rate constant (K0) was lowest at the high straw addition rates (though still higher than no straw addition), while the low straw addition rates had the highest K0. Under RT, the SOC mineralization rate constant (K0) increased with the higher straw addition rates, peaking at the high addition rate. Among the three straw types, maize had the highest SOC mineralization rate constant, followed by oilseed rape and then wheat (

Table 9. The parameter values of the first-order kinetic single-compartment carbon mineralization model, which were derived by fitting cumulative carbon mineralization data under NT.

Treatment	Parameter
	Cp	K0	R2
MS
L	25.97	0.072	0.992
M	42.35	0.069	0.997
H	71.63	0.058	0.997
WS
L	30.72	0.064	0.99
M	49.67	0.061	0.999
H	69.01	0.058	0.998
OS
L	28.23	0.070	0.987
M	53.99	0.057	0.997
H	65.44	0.065	0.998
CK	16.40	0.039	0.974

MS: maize straw addition; WS: wheat straw addition; OS: oilseed rape straw addition; L: low straw addition rate (0.4%); M: medium straw addition rate (0.8%); H: high straw addition rate (1.2%); CK: blank control (no straw addition).

and

Table 10. The parameter values of the model, which were derived by fitting cumulative carbon mineralization data under RT.

Treatment	Parameter
	Cp	K0	R2
MS
L	291.355	0.05	0.997
M	570.546	0.052	0.996
H	760.477	0.06	0.996
WS
L	333.492	0.048	0.997
M	559.958	0.045	0.997
H	660.216	0.051	0.997
OS
L	343.525	0.043	0.996
M	535.886	0.043	0.998
H	629.634	0.050	0.998
CK	215.079	0.020	0.987

MS: maize straw addition; WS: wheat straw addition; OS: oilseed rape straw addition; L: low straw addition rate (0.4%); M: medium straw addition rate (0.8%); H: high straw addition rate (1.2%); CK: blank control (no straw addition).

).

4. Discussion

4.1. Effects of Tillage on SOC Accumulation and Mineralization

The results indicate that NT was more effective than RT in terms of preserving and concentrating SOC. This is probably because NT does not disturb the soil as much and enhances the accumulation of surface mulch [29]. Our results showed that NT significantly promoted the SOC concentration regardless of the straw return or rate (Table 3). Without straw return, the SOC concentration in the NT treatment was 9.83% higher than that in the RT treatment, while with straw return, NT increased the SOC concentration by 0.81–13.47% compared to RT. The greater SOC retention under NT can be attributed to reduced soil disturbance, which minimizes the exposure of protected organic carbon to microbial decomposition. Furthermore, the undisturbed soil environment under no tillage (NT) promotes the development of a more extensive and denser shallow root network within the topsoil layer (0–20 cm) [30]. These roots continuously release exudates and rhizodeposits (including cell debris and mucilage), which serve as critical sources of labile organic carbon in soil, significantly regulating microbial activity and community composition [31]. The distinct microenvironment of soil drives the formation of specialized microbial communities, which contribute to enhancing the physicochemical stabilization of soil organic carbon [32]. Similar studies have shown that undisturbed soils—such as those in no till—exhibit significantly higher seasonal stability in terms of bacterial richness and diversity compared to tilled cornfields [33], which may enhance SOC stability by reducing the abundance and activity of copiotrophic microbes that rapidly decompose labile carbon, thereby slowing down SOC turnover. NT also reduced soil mineralization, while RT significantly increased SOCam across all of the straw types, with NT showing 3.84% lower SOCam than RT without straw return. SOCpm under NT was 15.70–28.66% lower than that under RT, including a 12.31% reduction without straw return, likely due to suppressed microbial metabolic activity under reduced soil aeration and disturbance [34].

The interactive effects that took place between tillage and the straw return rate significantly influenced the SOC concentration and SOCam [25]. A previous study has shown that NT with straw return enhances SOC accumulation [35], aligning with our finding that high straw return rates coupled with NT further increased the SOC concentration [24]. The underlying mechanisms through which NT combined with straw return enhances SOC may include the following: reduced disturbance promotes the formation of macroaggregates, physically protecting SOC from microbial decomposition; straw inputs elevate the soil C/N ratio, promoting microbially mediated humification that facilitates stable SOC accumulation.

4.2. Effects of Straw Type on SOC Accumulation and Mineralization

Differences in chemical composition—particularly C:N ratios, lignin content, water-soluble compounds, crude protein, cellulose, and lignin content—result in distinct decomposition patterns among crop straw types [36], leading to varying rates of microbial decomposition and humification. In upland soils, straw decomposition rates typically follow oilseed rape > maize > wheat [37], a trend strongly linked to oilseed rape’s lower C:N ratio (15–20:1) and low lignin content (<15%), which accelerate microbial colonization and carbon turnover. Our results showed that under NT conditions, the incorporation of wheat straw yielded significantly higher SOC concentrations than those of both maize and oilseed rape straw. Conversely, under RT, oilseed rape straw resulted in lower SOC concentrations than those of maize and wheat straw, though no significant difference was observed between maize and wheat. These findings contrast with previous studies suggesting that maize straw contributes more to SOC accumulation than wheat straw [38], a discrepancy that may stem from differences in C:N stoichiometry. Our maize straw had a moderate C:N ratio (20–25:1) and lignin content (12–15%), leading to intermediate decomposition rates that depend on tillage, with high inputs under RT (via thorough mixing) accelerating microbial access and mineralization. At high application rates, maize straw demonstrated significantly greater absolute SOC mineralization (SOCam) compared to wheat and oilseed rape straw. Notably, medium application rates of oilseed rape straw under NT conditions produced the highest SOCam values, consistent with its rapid decomposition characteristics. The superior SOC accumulation observed with wheat straw under NT could be attributed to its relatively high lignin content (typically 18–22%). The recalcitrant nature of lignin contributes to the formation and persistence of particulate organic matter (POM). More importantly, the slower decomposition rate facilitates greater microbial processing and transformation of carbon into more stable forms compared to faster-decomposing straw types like oilseed rape, which may lead to greater initial mineralization losses [39].

4.3. Effects of the Straw Addition Rate on SOC Accumulation and Mineralization

The straw addition rate significantly influenced the SOC concentration, confirming Meng et al.’s findings [40]. Our study demonstrated a positive correlation between the straw application rates and SOC concentration under both NT and RT systems, with concurrent increases in both the absolute (SOCam) and potential (SOCpm) mineralization rates. Significant interactive effects between straw types and application rates were observed for SOC parameters (SOC, SOCam, and SOCpm), likely attributable to the distinct decomposition characteristics of different straw types [37]. First-order kinetic modeling revealed non-linear variations in the mineralization rate constants (K0) in response to straw addition rates (Table 8 and Table 9), suggesting complex mineralization dynamics dependent on application levels. This simple model treats all decomposing material in a simple pool, which is a simplified view of reality. While two-pool models can distinguish the mineralization of labile and recalcitrant carbon pools, our 70-day incubation focuses on the rapid straw decomposition phase. The single-compartment model provides a simple and clear method to compare the overall mineralization rates during this early stage, aligning with our research objectives.

4.4. Recommendations for Straw Return in Conservation Tillage in Inner Mongolia

Based on the interactive effects of tillage and straw return on SOC dynamics, we propose using targeted recommendations for semi-arid farming regions in Inner Mongolia, detailed in the following subsections.

4.4.1. Prioritize NT to Enhance Soil Carbon Retention

As detailed in Figure 5, NT significantly enhanced the SOC concentrations in the 0–20 cm soil layer, demonstrating 0.81% to 13.47% higher values compared to rotary tillage (RT), while simultaneously reducing potential SOC mineralization (SOCpm) by 15.70–28.66%. These results highlight NT’s superior capacity to achieve soil carbon sequestration. Our findings suggest that NT should be prioritized in agricultural management systems, particularly under conditions of low or absent straw return, where its carbon retention benefits—achieved through minimized soil disturbance—are most pronounced for maximizing carbon storage.

4.4.2. Optimize Straw Type Selection Based on Soil and Crop System Characteristics

Under NT, the medium wheat straw return (0.8%) showed the highest SOC concentration (28.70 g/kg), likely due to its high C/N ratio and humification efficiency. The relatively high lignin content in wheat straw (~18–22% [29]) appears to synergize well with NT. Reduced disturbance under NT allows for the slower decomposition of this recalcitrant component, facilitating its incorporation into more stable soil organic matter pools over time. In contrast, the rapid decomposition of oilseed rape straw under NT (high initial SOCam, Table 5) may lead to greater initial carbon being lost as CO₂ before stable fractions can form. Under RT, oilseed rape straw resulted in lower SOC concentration than gramineous straws, possibly due to rapid decomposition and carbon loss. Wheat straw return is recommended for wheat-growing areas in eastern Inner Mongolia, while maize straw return is suitable for maize-dominated regions. For oilseed rape-growing areas, deep plowing should be combined in order to slow down decomposition and avoid short-term carbon losses.

The straw application rate positively correlated with SOC mineralization, but an excessive input may imbalance the labile carbon ratios. The medium wheat straw return (0.8%) under NT showed optimal comprehensive benefits, balancing the increase in the SOC concentration and avoiding mineralization surges from high inputs. Based on regional soil fertility and crop yields, we recommend controlling the straw application rates at 0.8–1.2% (mass fraction) to achieve a dynamic balance between carbon retention and mineralization.

4.5. Limitations and Future Directions

This study was conducted under controlled laboratory conditions where temperature and humidity were constant—conditions that do not fully replicate the variability in environmental conditions in the field that influence straw decomposition and SOC mineralization. The constant optimal moisture (70% WHC) and temperature (25 °C) in our incubation likely accelerated the decomposition processes compared to the fluctuating and often suboptimal conditions (e.g., spring droughts and freezing winters) encountered in the field—notably seasonal temperature swings (e.g., −20 to 30 °C), erratic precipitation patterns (spring droughts followed by summer monsoons), and freeze–thaw cycles in winter—which disrupt straw structure and alter microbial activity. While our results reveal fundamental interactions and the potential mineralization capacity, they represent a ‘best-case’ scenario for microbial activity, which may not be reflected in in-field dynamics, where seasonal stressors (e.g., drought-induced microbial dormancy) can slow down decomposition. Straw decomposition is also influenced by microbes and their metabolites [41,42]; further investigation into how different straw types affect soil microbial communities is required. The optimal effect of wheat straw observed here may relate to the regional annual average temperature, suggesting that straw type selection may need to be adjusted in higher-accumulated-temperature regions. Additionally, root exudates and other dynamic carbon inputs were not considered, warranting future research into their synergistic effects with straw return. In addition, long-term field experiments simulating natural soil mineralization processes across seasons and years, incorporating measurements of crop yield, soil physical properties (aggregate stability), and microbial community dynamics, are essential to fully understand and validate the impact of straw return strategies (type, rate, and tillage) on soil carbon sequestration and agricultural sustainability in semi-arid agroecosystems like Inner Mongolia. The controlled incubation data obtained here, particularly those focused on mineralization rates under different straw–tillage combinations, can serve as valuable input parameters for refining process-based models (e.g., DSSAT and DayCent) that simulate SOC dynamics under real-world field conditions.

5. Conclusions

With this study, we investigated the combined effects of tillage methods, straw types, and application rates on the dynamics and mineralization of soil organic carbon (SOC) using controlled laboratory experiments. In the 0–20 cm soil layer, no tillage (NT) significantly increased the SOC concentration—by 0.81% to 13.47% compared to rotary tillage (RT)—with the greatest difference observed in the treatments without straw return.

Under NT, the SOC concentration after wheat straw return was significantly higher than that after maize and oilseed rape straw return, while under RT, the SOC concentration after oilseed rape straw return was significantly lower than that after maize and wheat straw return. At low straw application rates (0.4%), oilseed rape straw exhibited the highest specific SOC mineralization rate (33.9%) compared to maize and wheat. Absolute SOC mineralization increased significantly with the straw addition rates, with mineralization at high straw application rates (1.2%) increasing by 40.2–61.8% (NT) and 26.8–41.2% (RT) compared to that at medium and low rates.

In the semi-arid agroecosystems of eastern Inner Mongolia, combining no tillage (NT) with 0.8% wheat straw or 1.2% maize straw increased the SOC concentration by 12–18%, representing the optimal carbon sequestration strategy under low annual precipitation and cool conditions. This strategy can be adapted according to local cropping systems: wheat-producing areas should prioritize 0.8% wheat straw return; maize-growing areas should adopt 1.2% maize straw return; and we recommend that oilseed rape areas combine straw return with rotary tillage to achieve moderately rapid decomposition and minimize carbon loss. Adopting these tailored strategies not only results in carbon storage being enhanced, but can also reduce costs (e.g., fewer tillage passes) and support stable crop yields over time by improving soil health. Through our findings, we have delivered targeted solutions for the management of SOC in semi-arid agricultural regions, addressing the precipitation deficits that are characteristic of such ecosystems.