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Article

The Relationship of Soil Organic Carbon and Nutrient Contents to Maize Yield as Affected by Maize Straw Return Modes

by
Chuanyu Wang
1,
Yao Liang
2,
Jianzhao Liu
2,
Jingchao Yuan
2,
Jun Ren
2,
Yidan Geng
1,
Zeqiang Shao
3,
Jinjing Zhang
1,* and
Hongguang Cai
2,*
1
Key Laboratory of Soil Resource Sustainable Utilization for Commodity Grain Bases of Jilin Province, College of Resource and Environmental Science, Jilin Agricultural University, Changchun 130118, China
2
Key Laboratory of Black Soil Conservation and Utilization, Ministry of Agriculture and Rural Affairs, Jilin Academy of Agricultural Sciences, Changchun 130033, China
3
College of Resource and Environment Engineering, Jilin Institute of Chemical Technology, Jilin 132022, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2023, 13(22), 12448; https://doi.org/10.3390/app132212448
Submission received: 18 October 2023 / Revised: 14 November 2023 / Accepted: 14 November 2023 / Published: 17 November 2023
(This article belongs to the Section Earth Sciences)
Browse Figures
Versions Notes

Abstract

:
Returning crop residues to the field after harvesting is a proven effective strategy for improving soil fertility, carbon sequestration, and crop productivity. However, the relationships between crop residue return modes, SOC and nutrient contents, and crop yields are still unclear. In this study, a field trial was conducted to investigate the effects of different maize straw return modes, i.e., straw mulching (SMU), straw deep ploughing (SDP), and control without straw return (CK), on soil organic carbon (SOC) and nutrient contents in soil layers of 0–40 cm in a Mollisol. The relationships between straw return modes, SOC and nutrient contents, and maize yield were evaluated. Compared with CK, SMU and SDP significantly increased SOC, total nitrogen (N), available N, total phosphorus (P), and available P contents in all soil layers. Relative to SMU, SOC, total N, available N, total P, and available P contents were significantly lower in soil layers of 0–10 cm, but they were significantly higher in soil layers of 20–40 cm in SDP. Redundancy analysis indicated that total N, available N, and SOC were major factors controlling maize yield. Structural equation modeling further showed that straw return modes indirectly affected maize yield by directly and preferentially affecting total N and available N contents. The results indicated that SMU and SDP were beneficial for increasing SOC and nutrient contents at the surface and subsurface soils, respectively. Optimizing a nitrogen management strategy is important to achieve high maize yield with straw return.

1. Introduction

Returning crop residues to the field after harvesting is a proven effective strategy to improve soil fertility, carbon sequestration, and crop productivity [1]. The effects of crop residue return on soil quality and crop productivity depend on many factors, such as crop residue characteristics, initial soil properties, agronomic practices, and climate conditions. In the study by Islam et al. (2023), they reported that balanced mineral fertilization was more beneficial to soil organic carbon (SOC) accumulation in soil with initial SOC < 6 g/kg than in soil with initial SOC > 12 g/kg with straw returning [2]. Zhang et al. (2023) indicated that plow tillage was more favorable to SOC accumulation than no-tillage with straw returning [3]. Liu et al. (2023) found that no-tillage facilitated SOC accumulation with maize straw mulching, rotary tillage enhanced SOC accumulation with wheat straw incorporation, while plow tillage improved SOC accumulation with rice straw incorporation [4]. Wang et al. (2021) observed that SOC accumulation was more obvious with maize–wheat rotation than with continuous rice cropping and with paddy–wheat rotation than with wheat–maize rotation with the condition of straw returning [5]. The return modes of crop residues are one of the critical factors that impact soil fertility and crop productivity. Based on a meta-analysis from 420 publications in China, Huang et al. (2021) found that straw mulching was more beneficial to soil nutrient accumulations in areas with average annual rainfall of <400 mm and in the soils with neutral and alkaline pH values, loam texture, a straw returning amount of >9000 kg per hectare, and a nitrogen fertilizer application rate of <100 kg per hectare; by contrast, straw burying was more favorable to soil nutrient accumulations in areas with average annual rainfall of >800 mm and in soils with acidic pH values and clay texture [6]. Therefore, understanding the impacts of different return modes of crop residues on soil quality and crop productivity are necessary for the rational utilization of crop residues in agricultural ecosystems.
Mollisols, which are recognized as inherently fertile and productive soils around the world, are mainly distributed in the northeast region of China [7]. The Mollisol region of Northeast China is also one of the major maize (Zea mays L.) production areas in China and is known as the Golden Maize Belt of the world [8]. The total maize sown area in Northeast China has more than 6 × 106 ha, which accounts for about 30% of the nation’s total maize production [7]. However, the Mollisols in Northeast China have experienced serious degradation, including SOC and nutrient depletion, soil structure deterioration, and mollic epipedon thickness reduction, due to natural (e.g., erosion and climate change) and human disturbances (e.g., unreasonable tillage and fertilization regimes) during the last several decades [9,10,11,12]. With the improvement in the degree of agricultural mechanization, direct returning maize straw through mulching or deep ploughing to the field have been widely applied for combatting soil degradation in this region. Previous investigations have mainly concentrated on the impacts of either the mulching [13] or deep ploughing of maize straw [14] on SOC and nutrient contents in the Mollisols of Northeast China. For example, Cai et al. (2021) studied the impact of straw mulching on SOC content [13]. Liu et al. (2021) investigated the effects of straw mulching on soil total N, available N, and available P contents [15]. Cai et al. (2019) examined the impacts of straw deep plowing on SOC, total N, available N, and available P [14]. Tian et al. (2019) reported the influence of deep plowing with straw on SOC and TN contents [16]. However, there is little research that has compared the differences between the two straw return modes. Also, the relationship between the distribution patterns of SOC and nutrient contents with soil depths as affected by straw return modes is not well known. Furthermore, the relationships between straw return modes, soil depths, SOC and nutrient contents, and maize yield were still unclear.
The purpose of the present study was to explore the influences of different maize straw return modes on SOC and nutrients (including total nitrogen (N), available N, total phosphorus (P), and available P) contents at 0–40 cm soil depths in a Mollisol of Northeast China. The relationships between straw return modes, soil layer depths, SOC and nutrient contents, and maize yield were evaluated. Because different straw return modes have contrasting influences on the distribution of straw residues among soil layers, we thus hypothesized that the responses of SOC and nutrient contents to straw return modes depended on soil layer depths. Moreover, we also hypothesized that straw return modes indirectly affected maize yield by directly affecting SOC and nutrient contents.

2. Materials and Methods

2.1. Field Trial Site and Design

A field trial commenced in April 2015 in Gongzhuling (Jilin Province, China; 42°40′ N, 124°88′ E), with a temperate humid continental climate. The annual average air temperature in this area is approximately 5.6 °C, with a maximum air temperature of 23 °C in July and a minimum air temperature of −15 °C in January. The annual mean rainfall reaches 600 mm. Meteorological data, including maximum air temperature, minimum air temperature, and rainfall at this study site during maize growth period from May to October in the five experimental years (2015–2019), are graphed in Figure 1. The field was planted with a maize monoculture with 60,000 plants per hectare. The maize variety used was Fumin985, and approximately 90% of the root was distributed between 0−40 cm. The initial properties of the soil (Mollisol by USDA Soil Taxonomy) were determined using the recommended procedures [17], and the findings are given in Table 1.
The trial consisted of three treatments with three replications for each treatment using a randomized complete block design: (1) control without straw return (CK): straw was removed manually from the field after maize harvesting; (2) straw return by mulching (SMU): straw was chopped and mulched evenly on soil surface following maize harvesting; and (3) straw return by deep ploughing (SDP): straw was chopped, covered evenly on soil surface, and then ploughed to approximately 20–30 cm soil depth using a hydraulic overturning plow (Jindachuan Machinery Co., Ltd., Kaifeng, China). Each experimental plot was 702 m2. The mineral fertilizers for each treatment were applied annually at 225.0 kg N as urea and diammonium phosphate, 82.5 kg P2O5 as diammonium phosphate, and 82.5 kg K2O as potassium chloride per hectare, respectively. A part of mineral N fertilizer (90.0 kg N per hectare) and all mineral P and K fertilizers were used as base fertilizers, and the remaining mineral N fertilizer was used as topdressing at jointing stage of maize. Maize sowing (flat sowing with a no-tillage planter) and harvesting were in late April and early October, respectively. No additional irrigation was conducted out of the rainfall. Following mechanized harvesting of maize on 21 October 2019, grain yield per hectare (GY), hundred grain weight (HGW), ear number per hectare (EN), and grain number per ear (GNPE) were determined. The grain yield was expressed on 14% moisture basis.

2.2. Soil Sampling and Analysis

The soil was sampled after maize harvesting on 21 October 2019. Soil cores were taken randomly from each plot from the 0–10, 10–20, 20–30, and 30–40 cm depths and then mixed into a composite sample for each depth. The samples were sieved to 2 mm after being air-dried.
The SOC, total N, available N, total P, and available P contents were measured according to the standard procedures recommended [17]. In brief, SOC content was tested using a sulfuric acid and potassium dichromate oxidation at 170–180 °C followed by titrating excess dichromate using ferrous sulfate. Total N content was determined by the Kjeldahl method with a KDY-9820 automatic Kjeldahl distillation–titration apparatus (Tongrunyuan Electromechanical Technology Co., Ltd., Beijing, China). Available N content was measured using the alkali diffusion method, in which NH4+ collected in boric acid solution under alkaline conditions was titrated using standard 0.01 mol/L sulfuric acid. Total P was extracted using concentrated sulfuric acid and perchloric acid digestion, and available P was extracted with 0.5 mol/L sodium bicarbonate at pH 8.5. P concentrations in the extracts were then determined colorimetrically using a 721 visible spectrophotometer (Youke Instrument Co., Ltd., Shanghai, China) by applying molybdenum blue method.

2.3. Statistical Analysis

The main and interactive effects of straw return modes and soil depths on SOC, total N, available N, total P, and available P were assessed by two-way ANOVA. The differences of SOC, total N, available N, total P, available P, and maize yield among straw return modes as well as among soil depths were analyzed by one-way ANOVA as the data contained a normal distribution (Shapiro–Wilks) and variances were homogenous (Levene, both p > 0.05), and the data were log-transformed if necessary. Multiple comparisons were performed using least significant difference (LSD) test at significance level of p < 0.05. Pearson correlation coefficients were used to examine the relationships between SOC, total N, total P, available N, available P, and maize yield at significance levels of p < 0.05 and p < 0.01. Statistical tests were carried out with SPSS software (version 22.0; SPSS Inc., Chicago, IL, USA).
The similarities and distinctions of SOC, total N, total P, available N, and available P contents among straw return modes were determined using Principal component analysis (PCA) with Canoco software (version 5.0; Microcomputer Power, Ithaca, NY, USA). The major soil properties affecting maize yield were determined by redundancy analysis (RDA), and the Monte Carlo Permutation test (499 permutations) at significance level of p < 0.05 was used to assess the significance of explanatory environmental variables.
To test the causal relationships among straw return modes, soil layer depths, SOC and nutrient contents, and maize yield, a structural equation model (SEM) was constructed using AMOS software (version 24.0; SPSS Inc., Chicago, IL, USA). The most optimum model was acquired by gradually removing the insignificant paths. The probability (P), insignificant chi-square test (χ2/df), goodness-of-fit index (GFI), and root mean square error of approximation (RMSEA) were used to evaluate the fitness of final model.

3. Results and Discussion

3.1. Maize Grain Yield and Yield Components

After five years of field experiments, the GY was 3.01% (p > 0.05) and 6.40% (p > 0.05) higher, the HGW was 2.37% (p > 0.05) and 5.77% (p < 0.05) higher, and the GNPE was 11.8% (p < 0.05) and 11.8% (p < 0.05) higher in the SDP than in the CK and SMU treatments, respectively. In contrast, the EN in the SDP treatment was 11.4% (p < 0.05) and 9.68% (p < 0.05) lower than that in the CK and SMU treatments, respectively (Figure 2). The higher GY in the SDP was possibly due to the fact that the maize straw was less decomposed, causing its nutrients to be less available for crop growth, while the maize straw was placed deeper and, thus, released more nutrients for crop growth by increasing the contact area of the maize straw with soil enzymes and microorganisms under SDP [6].

3.2. SOC and Nutrient Contents

Both straw return modes and soil layer depths had significant effects on SOC and nutrient contents. And the interaction effect between straw return modes and soil depths was also significant for the contents of SOC and nutrients (Table 2).
With the increase of soil depth, SOC and nutrient contents gradually and significantly decreased in the CK and SMU treatments. In contrast, SOC and total N contents in the 20–30 cm depth were significantly larger, and available N content in the 10–20 cm depth was significantly larger than those in the other depths in the SDP treatment. However, total P and available P contents gradually and significantly decreased with the increase of soil depths in the SDP treatment (Figure 3). It has been previously reported that tillage systems have a profound influence on crop root growth. The favorable hydrothermal conditions in mulching-based no-tillage systems could increase root vitality and expansion and, thus, enhance the utilization of soil moisture and available nutrients for crop growth. Moreover, mulching-based no-tillage could significantly increase root length, surface area, and tip number in the 0–40 cm soil layer [18]. In a study by Gao et al. (2014), they reported a positive correlation between root proliferation with soil nutrient absorption capacity and crop yield in mulching-based no-tillage systems [19]. Relative to conventional and minimum tillage, deep tillage was more beneficial for root growth [20]. The downward growth of roots may need to absorb more P nutrients, which would result in the decrease of P nutrients in deeper soil depths.
In comparison with the CK treatment, SOC and nutrient contents in the 0–40 cm soil depths were significantly greater in both the SMU and SDP treatments. The exception was for the SMU treatment, where total N content was significantly lower and total P content did not significantly differ in the 30–40 cm soil layer as compared to the CK treatment (Figure 3). Similar results were also reported in some previous studies [21,22,23,24,25]. In contrast, some other studies found that straw mulching did not significantly influence SOC [26,27,28,29] and total N [30] contents in the 20–40 cm soil depth. These conflicting outcomes may be attributed to the influences of many factors, including climate conditions, soil properties, and straw returning years. For example, Zheng et al. (2021) showed that straw mulching had no significant influence on SOC content in the 20–40 cm soil depth in an Argiudoll of Northeast China after a three-year field experiment [28]. However, Ndzelu et al. (2020) observed that straw mulching markedly increased SOC content in the 20–40 cm soil depth in a Haplic Cambisol of South Africa after a five-year field experiment [24]. Thus, further studies were needed to ascertain the main factors that affected SOC content under the condition of SMU.
The contents of SOC and total N in the 0–20 cm soil depth were 1.30–11.9% and 2.16–3.54% larger in the SMU than in the SDP treatment, while SOC and total N contents in the 20–40 cm soil depth were 11.4––9.2% and 8.12–10.5% lower in the former than in the latter treatment, respectively. However, no significant difference was found for SOC content between the SMU and the SDP treatments in the 10–20 cm soil depth. Furthermore, available N, total P, and available P contents were significantly greater in the SMU than in the SDP treatment in the 0–10 cm soil depth, while they were significantly greater in the SDP than in the SMU treatments in the other soil depths (Figure 3). The results proved our hypothesis that the responses of SOC and nutrient contents to straw return modes depended on soil layer depths. In the SMU treatment, straw was mulched on the soil surface, and the decomposition of straw accordingly led to more SOC and nutrients concentrated on the surface soil. However, straw was ploughed to the 20–30 cm soil depth in the SDP treatment, which resulted in higher SOC and nutrient contents in the subsurface soil. Furthermore, deep ploughing can break plow pan layers, which subsequently facilitates the growth of crop roots in the subsurface soil and raises the inputs of carbon and nutrients from maize roots [31]. It was previously reported that straw mulching reduced soil erosion [32] but caused shallow and stringent plough layer thickness [21]; on the contrary, straw deep ploughing enlarged plough layer thickness [33] while could increase the risk of soil erosion [34]. Based on our present and previous studies, straw mulching and deep ploughing have their own advantages and disadvantages. Thus, we recommend the combination of rotation tillage (i.e., alternation of no-tillage and deep ploughing) and straw return in future agricultural practices.

3.3. Relationships between Maize Straw Return Modes, Soil Depths, SOC and Nutrient Contents, and Maize Yield

The Pearson correlation results showed that SOC and nutrient contents were positively correlated with each other, and there were also positive correlations between SOC and nutrient contents with GNPE. However, a negative correlation was detected between SOC and nutrient contents with EN (Figure 4).
According to the PCA analysis, the first two axes contributed 98.1% and 1.95% of the SOC and nutrient contents, respectively. The SOC and nutrient contents were clearly distinguished among the three straw return treatments (especially between the CK and SMU treatments versus the SDP treatment) in the ranking diagram (Figure 5a), suggesting that the SDP mode had a more remarkable influence on SOC and nutrient contents. The results of the RDA analysis indicated that SOC and nutrient contents explained 87.5% of the variation in maize yield. RDA1 and RDA2 interpreted 86.8% and 0.66% of maize yield, respectively. The total N, available N, and SOC were significant factors in shaping maize yield, which explained 49.8%, 31.8%, and 5.70% of the total observed variance in maize yield, respectively (Figure 5b).
The findings of SEM demonstrated that straw return modes had a direct and positive effect, but soil depths had a negative effect on SOC and nutrient contents. The total N and available N exhibited direct and positive effects on HGW and GNPE; available P exhibited a direct and positive effect on EN, and SOC, total P, and available P exhibited direct and negative effects on GNPE. Moreover, HGW, GNPE, and EN had a direct and positive effect on GY. The larger positive standardized path coefficients were observed between HGW with total N (13.3) and available N (6.58) (Figure 6). Our results suggested that straw return modes indirectly affected maize yield by directly and preferentially affecting total N and available N contents, which was consistent with our hypothesis. Therefore, an optimizing N management strategy is important to achieve high maize yield with straw return.
In conclusion, the results from the five-year field experiment showed that straw return modes had contradicting influences on the distributions of SOC and nutrients within soil depths. Both SMU and SDP significantly increased SOC, total N, available N, total P, and available P contents in all soil layers compared with CK. SMU was more beneficial for increasing SOC and nutrient contents within the surface soil, while SDP was more beneficial within the subsurface soil. Total N, available N, and SOC were major factors controlling maize yield. The straw return modes indirectly affected maize yield by directly and preferentially affecting total N and available N contents. An optimizing N management strategy is important to achieve high maize yield with straw return. We recommend the combination of rotation tillage and straw return for enhancing carbon sequestration, improving nutrient availability, and long-term sustainable maize production in rain-fed areas of Northeast China in future agricultural practices. However, a long-term study is essential to confirm the findings from the present study.

Author Contributions

This experiment was conceived and designed by J.Z., H.C. and J.R. The data from the experiments were collected by C.W., Y.L., J.L. and J.Y. and analyzed by C.W., Y.G. and Z.S. The reagents, chemicals, materials, and analysis tools were contributed by H.C. and J.Z. This paper was written by C.W. and modified by all authors. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China, Project No. 2021YFD150020104, and by the Science and Technology Development Planning Project of Jilin Province of China, Project No. 20230302006NC.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to laboratory regulations.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Air temperature and rainfall at the study site during maize growth period in 2015−2019.
Figure 1. Air temperature and rainfall at the study site during maize growth period in 2015−2019.
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Figure 2. Maize grain yield (a), hundred grain weight (b), ear number (c), and grain number per ear (d) under different maize straw return modes. Vertical bars represent the standard deviation of means (n = 3). The bars having different lowercase and uppercase letters denote significant differences among straw return treatments (p < 0.05). CK—no maize straw returning; SMU—maize straw mulching; SDP—maize straw deep ploughing.
Figure 2. Maize grain yield (a), hundred grain weight (b), ear number (c), and grain number per ear (d) under different maize straw return modes. Vertical bars represent the standard deviation of means (n = 3). The bars having different lowercase and uppercase letters denote significant differences among straw return treatments (p < 0.05). CK—no maize straw returning; SMU—maize straw mulching; SDP—maize straw deep ploughing.
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Figure 3. Soil organic carbon (a), total nitrogen (b), total phosphorus (c), available nitrogen (d), and available phosphorus (e) under different maize straw return modes. Vertical bars represent the standard deviation of means (n = 3). The bars different lowercase and uppercase letters denote significant differences among straw return treatments and among soil depths, respectively (p < 0.05). CK—no maize straw returning; SMU—maize straw mulching; SDP—maize straw deep ploughing.
Figure 3. Soil organic carbon (a), total nitrogen (b), total phosphorus (c), available nitrogen (d), and available phosphorus (e) under different maize straw return modes. Vertical bars represent the standard deviation of means (n = 3). The bars different lowercase and uppercase letters denote significant differences among straw return treatments and among soil depths, respectively (p < 0.05). CK—no maize straw returning; SMU—maize straw mulching; SDP—maize straw deep ploughing.
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Figure 4. Pearson’s correlation coefficients between soil organic carbon and nutrient contents and maize yield under different maize straw return modes. Significance levels are denoted with * p < 0.05 and ** p < 0.01. SOC—soil organic carbon; TN—total nitrogen; TP—total phosphorus; AN—available nitrogen; AP—available phosphorus; HGW—hundred grain weight; EN—ear number; GNPE—grain number per ear; GY—grain yield.
Figure 4. Pearson’s correlation coefficients between soil organic carbon and nutrient contents and maize yield under different maize straw return modes. Significance levels are denoted with * p < 0.05 and ** p < 0.01. SOC—soil organic carbon; TN—total nitrogen; TP—total phosphorus; AN—available nitrogen; AP—available phosphorus; HGW—hundred grain weight; EN—ear number; GNPE—grain number per ear; GY—grain yield.
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Figure 5. Principle component analysis (PCA) plot of soil organic carbon and nutrient contents (a) and redundancy analysis (RDA) plot of relationships between soil organic carbon and nutrient contents with maize yield (b) under different maize straw return modes. CK—no maize straw returning; SMU—maize straw mulching; SDP—maize straw deep ploughing; SOC—soil organic carbon; TN—total nitrogen; TP—total phosphorus; AN—available nitrogen; AP—available phosphorus; HGW—hundred grain weight; EN—ear number; GNPE—grain number per ear; GY—grain yield.
Figure 5. Principle component analysis (PCA) plot of soil organic carbon and nutrient contents (a) and redundancy analysis (RDA) plot of relationships between soil organic carbon and nutrient contents with maize yield (b) under different maize straw return modes. CK—no maize straw returning; SMU—maize straw mulching; SDP—maize straw deep ploughing; SOC—soil organic carbon; TN—total nitrogen; TP—total phosphorus; AN—available nitrogen; AP—available phosphorus; HGW—hundred grain weight; EN—ear number; GNPE—grain number per ear; GY—grain yield.
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Figure 6. Structural equation model relating soil organic carbon and nutrient contents to maize grain yield as affected by maize straw return modes and soil layer depths. R2 indicates the proportion of variance explained by each variable. Numbers on arrows are standardized path coefficients; arrow thickness represents the magnitude of the standardized path coefficient. Red arrows indicate positive effects, blue arrows indicate negative effects, and dashed arrows indicate non-significant paths that were removed in the final model. Significance levels are denoted with * p < 0.05, ** p < 0.01, and *** p < 0.001. χ2/df—non-significant chi—square test; P—probability; GFI—goodness-of-fit index; RMSEA—root mean square error of approximation; SRM—straw return mode; SOC—soil organic carbon; TN—total nitrogen; TP—total phosphorus; AN—available nitrogen; AP—available phosphorus; HGW—hundred grain weight; EN—ear number; GNPE—grain number per ear; GY—grain yield.
Figure 6. Structural equation model relating soil organic carbon and nutrient contents to maize grain yield as affected by maize straw return modes and soil layer depths. R2 indicates the proportion of variance explained by each variable. Numbers on arrows are standardized path coefficients; arrow thickness represents the magnitude of the standardized path coefficient. Red arrows indicate positive effects, blue arrows indicate negative effects, and dashed arrows indicate non-significant paths that were removed in the final model. Significance levels are denoted with * p < 0.05, ** p < 0.01, and *** p < 0.001. χ2/df—non-significant chi—square test; P—probability; GFI—goodness-of-fit index; RMSEA—root mean square error of approximation; SRM—straw return mode; SOC—soil organic carbon; TN—total nitrogen; TP—total phosphorus; AN—available nitrogen; AP—available phosphorus; HGW—hundred grain weight; EN—ear number; GNPE—grain number per ear; GY—grain yield.
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Table 1. Selected properties of the soil used at the beginning of the experiment in 2015.
Table 1. Selected properties of the soil used at the beginning of the experiment in 2015.
Soil Depth
(cm)		pHSOC
(g/kg)		Total N
(g/kg)		Total P
(g/kg)		Total K
(g/kg)		Available N
(mg/kg)		Available P
(mg/kg)		Available K
(mg/kg)
0–205.399.560.810.2411.3193.120.4144.1
20–405.739.410.760.2010.9147.517.9153.8
pH was determined in a soil/water suspension of 1:2.5. SOC—soil organic carbon; N—nitrogen; P—phosphorus; K—potassium.
Table 2. Results of two-way ANOVA for the effects of maize straw return modes and soil layer depths on SOC and nutrient contents.
Table 2. Results of two-way ANOVA for the effects of maize straw return modes and soil layer depths on SOC and nutrient contents.
Source of Variationd.f.SOCTotal NTotal PAvailable NAvailable P
FpFpFpFpFp
Return modes (A)21675.1<0.01396.3<0.0163.2<0.011664.5<0.011020.1<0.01
Soil depths (B)33613.8<0.011260.0<0.01853.8<0.013437.1<0.0111,206.1<0.01
A × B6232.0<0.0183.2<0.0121.1<0.01201.0<0.01395.0<0.01
Error24
d.f.—degrees of freedom; F—variance ratio; p—significance level; SOC—soil organic carbon; N—nitrogen; P—phosphorus; K—potassium.
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MDPI and ACS Style

Wang, C.; Liang, Y.; Liu, J.; Yuan, J.; Ren, J.; Geng, Y.; Shao, Z.; Zhang, J.; Cai, H. The Relationship of Soil Organic Carbon and Nutrient Contents to Maize Yield as Affected by Maize Straw Return Modes. Appl. Sci. 2023, 13, 12448. https://doi.org/10.3390/app132212448

AMA Style

Wang C, Liang Y, Liu J, Yuan J, Ren J, Geng Y, Shao Z, Zhang J, Cai H. The Relationship of Soil Organic Carbon and Nutrient Contents to Maize Yield as Affected by Maize Straw Return Modes. Applied Sciences. 2023; 13(22):12448. https://doi.org/10.3390/app132212448

Chicago/Turabian Style

Wang, Chuanyu, Yao Liang, Jianzhao Liu, Jingchao Yuan, Jun Ren, Yidan Geng, Zeqiang Shao, Jinjing Zhang, and Hongguang Cai. 2023. "The Relationship of Soil Organic Carbon and Nutrient Contents to Maize Yield as Affected by Maize Straw Return Modes" Applied Sciences 13, no. 22: 12448. https://doi.org/10.3390/app132212448

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