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Article

Mitigation of the Ratio of Soil Dissolved Organic Carbon to Available Phosphorus Effectively Improves Crop Productivity under Mulching Measures on the Loess Plateau

College of Agronomy, Northwest A&F University, Yangling 712100, China
*
Author to whom correspondence should be addressed.
Submission received: 5 June 2023 / Revised: 3 July 2023 / Accepted: 3 July 2023 / Published: 7 July 2023
(This article belongs to the Special Issue Sustainable Management and Tillage Practice in Agriculture)

Abstract

:
Soil erosion and extensive management, as key factors limiting the sustainability of the agroecosystem in the Loess Plateau, severely hamper the high-quality development of regional agriculture. Soil fertility and element synergy can be enhanced by applying mulching measures properly. However, there is a lack of systematic research into how soil stoichiometric characteristics under mulching affect crop productivity. This study focused on the agroecosystem of the Loess Plateau. Based on the 11-year field positioning experiment, the management measures of straw mulching (SM), plastic mulching (PM) and ridge-film mulching (RM) were selected to investigate the effects of long-term mulching measures on the stoichiometric characteristics of topsoil and the impact of crop productivity under the ecological stoichiometry theory. The findings revealed a significant increase in soil carbon, nitrogen and phosphorus contents and microbial biomass under mulching. SM and RM significantly decreased the stoichiometric ratio of soil available nutrients, whereas PM and RM had effective alleviating effects on C:N and C:P imbalance. The yield components of long-term SM and RM greatly increased and responded favorably to the synergy of soil carbon and phosphorus. This study provides theoretical guidance and technical support for the assessment of the effective and sustainable use of agricultural resources on the Loess Plateau.

1. Introduction

The Loess Plateau, with its dry climate, sparse vegetation, and a unique landscape of gullies, is one of the most serious soil erosion areas in the world [1]. Of the variety of land use types present, farmland is the most vulnerable to water erosion due to human interference and lack of vegetation coverage, coupled with the loose quality of the soil [2,3]. The loss degree of soil carbon, nitrogen and phosphorus contents under erosion varies, resulting in abnormal changes in the covariation and coupling relationship between nutrient elements that are not conducive to the sustainable development of the agricultural ecosystem [4]. Therefore, it is critical to control soil nutrient loss and promote nutrient synergy in the area. Mulching measures reduce soil exposure and erosion intensity, effectively regulate the soil hydrothermal condition, and improve nutrient content and crop yield through the application of crop residues, plastic film, gravel, and other substances on the surface. An effective water and fertilizer conservation management model could further regulate the ecological stoichiometric characteristics of farmland, promoting the balanced supply of nutrients and improving the ecological environment and the agroecosystem service function in the Loess Plateau, effectively promoting sustainable agricultural production [5,6,7].
Ecological stoichiometry is regarded as the key theory for analyzing the dynamic balance of carbon, nitrogen, phosphorus elements, and energy flow in biological systems, and plays an important role in revealing the relationship between soil resource supply and microbial nutrient demand [8]. It has been found that the long-term application of conservation tillage based on mulching effectively reduces the stoichiometric ratio of soil resources, while microbial biomass stoichiometry does not change significantly, which is related to the self-regulation mechanism of microorganisms [7,9]. Straw mulching is a common measure aimed at improving soil fertility and promoting resource efficiency. Through the regulation of soil microbial ecosystems, the accumulation and decomposition of soil organic carbon tends towards balance, promoting the coordination of resources and contributing to the improvement of crop productivity [10,11]. Plastic mulching benefits agricultural production in arid regions by improving soil hydrothermal conditions, increasing soil carbon, nitrogen and phosphorus content, acquiring enzyme activity, regulating element covariation, and promoting the balance of soil resource supplies [12,13]. However, some studies have also found that plastic films result in a large amount of microplastic residues, whose accumulation and decomposition change the functional microbial diversity of the soil, thereby adversely affecting soil resource cycling and nutrient balance [14]. Ridge-film mulching improves soil structure by combining ridge and furrow, thus reducing nutrient loss and increasing the input of soil carbon source energy [15,16]. At the same time, the effective blocking of ridges on soil nitrogen leaching and the inhibition of sediment reduction on phosphorus loss causes the soil stoichiometric ratio to be lower than the national average for arable land, effectively maintaining the nutrient balance and alleviating the limitation of carbon and nitrogen in the surface layer [7]. Nevertheless, there are few studies comparing the impact of the stoichiometric characteristics of soil total nutrients, available nutrients, and microbial biomass on crop productivity under mulching measures. This is of fundamental importance in assessing the quality and sustainable production of farmland on the Loess Plateau.
This study was carried out on the agroecosystem of the Loess Plateau. On the basis of the field positioning experiment of conservation tillage since 2008, the effects of ecological stoichiometry on yield were revealed by measuring total nutrients, available nutrients, and microbial biomass in the topsoil under mulching measures. The objective was to provide a theoretical foundation for sustainable agricultural production on the Loess Plateau through the coupling of carbon, nitrogen and phosphorus elements.

2. Materials and Methods

2.1. Experimental Design and Sampling

The experimental area is located in the Liudaogou watershed, Shenmu City, Shaanxi Province, China (110°21′–110°23′E, 38°46′–48°51′N), which was initially established in 2008. The region is a typical agricultural area of the Loess Plateau, with an average annual temperature of 8.4 °C and an annual rainfall of 437 mm (Figure 1). The soil type is Calcic Cambisols [17]. Three kinds of mulching measure were applied, including straw mulching (SM), plastic mulching (PM), and ridge-film mulching (RM), while no mulching (NM) was used as the control, with three replicates each. Soybeans of the cultivar Jindou 21 were planted in April at a sowing rate of 45 kg/ha and harvested in September. In accordance with local customs, the soybean soil was not fertilized. After removing large pieces of material like rocks, plant residues, and roots from the soil surface, the topsoil (0–30 cm) was collected using a five-point sampling method and uniformly mixed at the four-leaf stage (V4), full-pod stage (R4), and full-maturity stage (R8) of the soybeans in 2019. After passing through a 2mm sieve, one part of the composite sample was naturally air-dried for the determination of soil total nutrients, and the other part was kept fresh and stored at 4 °C for the detection of soil available nutrients and microbial biomass. Soybean plants that grow consistently within an area of 1 m2 were harvested in September, air dried, and threshed. The number of pods per plant, the number of seeds per plant, and the weight of 100 seeds were measured, and the number of plants per hectare and yield were calculated.

2.2. Analysis of Soil Properties

The pH of the soil water suspension (soil/water = 1:2.5) was measured using a pH meter (Model 206-C, Shanghai Sanxin Instrument Co., Shanghai, China). Soil moisture content (SMC) was determined using 105 °C drying method. Soil temperature (ST) was measured using a thermometer, and the temperature of the soil layer was read while collecting samples. Soil organic carbon (SOC) and total nitrogen (TN) were determined by K2Cr2O7 oxidation and Kjeldahl nitrogen analyzer (Kjeltec 8400, Foss, Copenhagen, Denmark), respectively. Total phosphorus (TP) was measured using the molybdenum blue method (Mapada Corporation, Shanghai, China). Dissolved organic carbon (DOC) was measured by leaching 10 g of fresh soil in a 0.5 mol/L 50 mL K2SO4 solution and using a TOC analyzer (TOC-L CPH, Shimadzu Co., Kyoto, Japan). Soil available nitrogen (AN) and available phosphorus (AP) were separately extracted using KCl and NaHCO3 solution, and determined using an AA3 continuous flow analyzer (SEAL AA3, Norderstedt, Germany). Soil microbial biomass was determined by fumigation [18]. Microbial biomass C (MBC), N (MBN), and P (MBP) were extracted using K2SO4 solution and NaHCO3 solution, respectively [18,19].

2.3. Statistical Analysis

Soil stoichiometric imbalance is expressed as the relationship between the stoichiometric ratio of available resources (A) or total resources (T) and the stoichiometric ratio of microbial biomass (B). The calculation formula is as follows:
A C : N   I m b a l a n c e   ( o r   C : P ,   N : P ) = A C : N / B C : N   ( o r   C : P ,   N : P )
T C : N   I m b a l a n c e   ( o r   C : P ,   N : P ) = T C : N / B C : N   ( o r   C : P ,   N : P )
To evaluate whether the stoichiometry of soil microbial biomass changes with resource stoichiometry, stoichiometric homeostasis (H) was calculated using the following formula [20]:
H = log e x / log e y log e c
where x is the stoichiometric ratio of soil resources, y is the stoichiometric ratio of microbial biomass, and c is a constant. Stoichiometric values were strictly homeostatic if the slope of the linear regression (1/H) was not significant (p > 0.05). When 1/H was significant (p < 0.05), they were arbitrarily classified as homeostatic (0 < 1/H < 0.25), weakly homeostatic (0.25 < 1/H < 0.5), weakly plastic (0.5 < 1/H < 0.75), or plastic (1/H > 0.75). If 1/H was negative, the absolute value was used.
ANOVA in IBM SPSS 22.0 was used to test the response of soil nutrients, stoichiometric ratio, and stoichiometric imbalance to the mulching measures. Linear regression analysis was performed using R 3.6.0 software in order to evaluate the relationship between stoichiometric ratios. R 3.6.0 was applied to indicate the correlation between stoichiometric characteristics and yield components. Variance partitioning analysis (VPA) was performed using R 3.6.0 to explore the explanation ratio of environmental factors to soil stoichiometric imbalance. Redundancy analysis (RDA) of soil stoichiometric imbalance variation on yield was performed using Canoco 5.0.

3. Results

3.1. Soil Physicochemical Properties and Stoichiometric Ratios

On the Loess Plateau, soil physicochemical properties responded in diverse ways to the mulching measures. The responses of TN, DOC, AN, and AP contents changed dynamically with the stage of soybean growth, and the variation in soil total nutrient and available nutrient was primarily affected by SM and RM (Table 1). The unequal accumulation of soil carbon, nitrogen, and phosphorus levels under the long-term influence of mulching measures caused an alteration in the stoichiometric ratio. The findings demonstrated that mulching reduced the stoichiometric ratio of soil resources, particularly in the cases of DOC:AN, DOC:AP, and AN:AP under SM and RM (p < 0.05, Figure 2d–f). Under the interaction between mulching and growth stage, SOC:TN increased considerably (Figure 2a). Significant responses to PM and RM were observed in SOC:TP and TN:TP. The interaction between mulching and growth stage was clearly present in the dynamic variations of DOC:AN and DOC:AP (p < 0.01, Figure 2).
In all of the important crop growth stages, long-term RM markedly increased the contents of MBC, MBN, and MBP (p < 0.001, Figure 3a–c). MBC:MBN, MBC:MBP, and MBN:MBP all showed significant responses to the interaction between mulching and growth stage, with a larger range of variation than the stoichiometric ratio of resources (p < 0.01, Figure 3d–f). According to the correlation between the stoichiometric ratios of soil resources and microbial biomass under mulching, SOC:TN had a significant negative linear impact only on the variance of MBC:MBN (p < 0.05, Figure 4).

3.2. Soil Stoichiometric Imbalance

Soil stoichiometric imbalance refers to the ratio of soil resource stoichiometry to microbial biomass stoichiometry, which is used to illustrate the dynamic balance of nutrient supply and demand. The results indicated that under PM and RM, the difference in the stoichiometric ratios of soil resources and microbial biomass resulted in an efficient relief of the stoichiometric imbalance, which was mostly represented in C:N and C:P (p < 0.05, Figure 5). Furthermore, whereas C:P and N:P imbalance displayed a tendency to first decrease and then increase, soil C:N imbalance rose significantly with soybean growth (Figure 5). Between total and accessible nutrients, the response of stoichiometric imbalance to mulching measures varied. Combined with the VPA of environmental influence on stoichiometric imbalance, soil hydrothermal properties, nutrient content and microbial biomass explained 91% and 90% of the variation in stoichiometric imbalance with respect to available and total nutrients, respectively. The most crucial regulating component among them was the available nutrients (Figure 6a). In contrast to total nutrients, it was clear that the stoichiometric imbalance based on the available nutrients responded more strongly to mulching measures, hydrothermal characteristics, nutrient content, and microbial biomass (p < 0.05, Figure 6b). Further evidence from microbial homeostasis showed that, in addition to plasticity based on SOC:TN, microbial communities had strict C:N, C:P, and N:P homeostasis (Table 2).

3.3. Effect of Soil Stoichiometric Characteristics on Yield Components

Long-term mulching exerted clear effects in terms of increasing yield components (p < 0.05, Table 3). These included increases of 4.08–16.33%, 9.25–34.91%, 3.20–57.73% and 11.66–19.12% in the number of plants/hm2, number of pods/plant, number of seeds/plant, and 100-seed weight, respectively. The yield increased by 18.18–62.43%, and the effect of SM and RM was particularly evident. An analysis of the effects of soil stoichiometric ratio and stoichiometric imbalance on yield showed that variation in both DOC:AN and DOC:AP were significantly negatively correlated with yield components (p < 0.05, Figure 7a), and the inhibition of DOC:AP was more evident. When combined with RDA, stoichiometric imbalance was found to account for 79.89% of the variation in yield, where there was a significant effect of C:P imbalance based on the available nutrients, and the explanation rate reached 35.5% (p < 0.05, Figure 7b). Therefore, it can be concluded that soil carbon and phosphorus content and their synergy play an important role in improving crop productivity.

4. Discussion

Agricultural soil physicochemical characteristics and microbial biomass under long-term mulching on the Loess Plateau regulated the effect on yield generated by soil stoichiometry. The supply of soil resources fluctuated steadily over the years under continuous field management [21]. Taken together with the results following six years of nutrient data based on this field-positioning experiment, long-term mulching was found to lead to the slow accumulation of SOC, TN and TP in the topsoil, forming some potential for nutrient sequestration [22]. Crop straws are rich in carbon, such as cellulose and lignin, which can provide a source of organic matter for soil and promote microbial activities. However, some studies have found that mulching measures significantly accelerate the mineralization rate of soil organic matter in farmland, resulting in a significant reduction of soluble carbon due to soil microbial respiration emissions, breaking the inherent carbon stability [23]. For example, the decomposition process of straw by microorganisms mainly consists of carbon mineralization. At the same time, the active regulation of the hydrothermal conditions of the topsoil by the return of straw promotes the release of nitrogen, resulting in a significant decrease in C:N due to the differences in soil carbon and nitrogen content [24]. In addition, the improvement of soil hydrothermal conditions under plastic mulching and ridge-film mulching mitigates soil erosion by increasing the number of water-stable aggregates, which in turn promotes nutrient accumulation [25]. Some studies have also shown that continuous ridge-film mulching in semi-arid areas significantly increases soil available nitrogen content and crop biomass, but the rainwater harvesting effect of ridges and furrows also increases the soil leaching risk of inorganic nitrogen, weakening crop nutrient utilization, and thus affecting the synergistic effect of soil carbon and nitrogen [26].
In contrast to total nutrients, the response of soil available nutrients to long-term mulching measures was dynamic during the growth stage of the crop. During the vegetative growth period, plants have an urgent need for both above- and belowground nutrient supply. The intense competition between plants and microorganisms for soil available nutrients weakens the increase in DOC and AN content resulting from mulching [27,28]. As an indicator of microbial activity and soil fertility, microbial biomass plays a major role in the circulation and supply of resources [29]. In this study, straw produced a large number of carbon sources for microbial use during long-term input and decomposition, thereby promoting the growth of the microbial population. Reductions in soil water loss under plastic mulching and ridge-film mulching create a microenvironment conducive to microbial activities, and continuous field management reduces additional anthropogenic disturbance to provide a relatively stable habitat space [26,30].
In addition, the differential accumulation of soil carbon, nitrogen and phosphorus contents also led to a change in stoichiometric properties. In this study, soil resource supply based on available nutrient stoichiometry and total nutrient stoichiometry was analyzed. The results showed that the application of long-term mulching measures in the Loess Plateau effectively reduced the stoichiometric characteristics of the soil available nutrients, thus promoting crop productivity. Meanwhile, the stoichiometric characteristics of microbial biomass were dynamic, primarily under the synergistic effect of mulching and growth stage. A meta-analysis on the effects of mulching measures on soil stoichiometry found that soil total carbon and nitrogen contents increased synergistically under mulching for more than 10 years, but C:N ratio did not change [31]. In agroecosystems, the effect of mulching on soil stoichiometric ratio depends on multiple factors, such as mulch type and environmental management. In general, straw mulching has a significant effect on improving soil quality and promoting synergistic changes in nutrient elements, especially in areas with poor fertility [32,33]. However, available nutrients, as the key substances for plant absorption and utilization, in the competition between plants and soil microorganisms, promote an increase in microbial demand for nutrients, leading to a discrepancy between the stoichiometric ratios of resources and microbial biomass [34]. Despite the strong nitrogen-fixation ability of legumes, soil diazotrophic microorganisms are unable to compensate for long-term nitrogen loss. In addition, the increasing amount of plant residue and litter during the mature stage provides energy sources for microbial activities, leading to an increase in C:P imbalance [35]. Soil phosphorus significantly has been shown to significantly improve pod formation and yield components, and effectively promote nutrient transfer to seeds during the reproductive stage [36,37]. It is also the primary reason that cooperation of phosphorus and carbon can significantly enhance soybean productivity.

5. Conclusions

On the basis of ecological stoichiometry theory, this study demonstrated the soil stoichiometric characteristics and their impact on crop yield under the long-term cumulative effect of mulching measures in the Loess Plateau. We came to the conclusion that that the SOC, TN, TP, and microbial biomass in topsoil were significantly enhanced under SM and RM, and that the differential accumulation of soil DOC, AN, and AP had an impact on C:N. The stoichiometric characteristics of microbial biomass were not impacted by resource stoichiometry, except for SOC:TN, because of its homeostatic properties. The difference in stoichiometric ratios between soil resources and microbial biomass showed that long-term PM and RM on C:N and C:P imbalance were effectively mitigated. Among these, the decrease in DOC:AP and the alleviation of C:P imbalance showed an obvious increasing effect on crop yield. In conclusion, this study confirmed that long-term application of RM on the Loess Plateau can effectively increase soil resource availability, alleviate soil stoichiometric imbalance, and enhance agriculture productivity and sustainability.

Author Contributions

Conceptualization, methodology, writing—original draft preparation, X.W.; investigation, visualization, writing—original draft preparation, J.-Q.H.; visualization, formal analysis, J.-J.S., G.-X.G., W.X.; writing—review and editing, J.-Z.B., Y.-Z.F.; funding acquisition, X.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Doctoral Research Start-up Fund of Northwest A&F University (Z1090121109), and the Shaanxi Science and Technology Development Plan Project [2023-JC-QN-0197].

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Location and climatological features of the experimental area.
Figure 1. Location and climatological features of the experimental area.
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Figure 2. Stoichiometric characteristics of soil total nutrients (ac) and available nutrients (df) at different stages under long-term mulching. Error bars indicate standard deviation (n = 3). Different lowercase letters indicate statistically significant differences among mulching treatments (p < 0.05). NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching; V4: four-leaf stage; R4: full-pod stage; R8: full-maturity stage.
Figure 2. Stoichiometric characteristics of soil total nutrients (ac) and available nutrients (df) at different stages under long-term mulching. Error bars indicate standard deviation (n = 3). Different lowercase letters indicate statistically significant differences among mulching treatments (p < 0.05). NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching; V4: four-leaf stage; R4: full-pod stage; R8: full-maturity stage.
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Figure 3. Soil microbial biomass (ac) and microbial stoichiometry (df) at different stages under long-term mulching. Error bars indicate standard deviation (n = 3). Different lowercase letters indicate statistically significant differences among mulching treatments (p < 0.05). NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching; V4: four-leaf stage; R4: full-pod stage; R8: full-maturity stage.
Figure 3. Soil microbial biomass (ac) and microbial stoichiometry (df) at different stages under long-term mulching. Error bars indicate standard deviation (n = 3). Different lowercase letters indicate statistically significant differences among mulching treatments (p < 0.05). NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching; V4: four-leaf stage; R4: full-pod stage; R8: full-maturity stage.
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Figure 4. Relationship between soil total (ac) and available (df) C, N, P stoichiometry and microbial biomass stoichiometry. The solid and dashed lines represent significant and insignificant linear correlations, respectively. NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching; V4: four-leaf stage; R4: full-pod stage; R8: full-maturity stage.
Figure 4. Relationship between soil total (ac) and available (df) C, N, P stoichiometry and microbial biomass stoichiometry. The solid and dashed lines represent significant and insignificant linear correlations, respectively. NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching; V4: four-leaf stage; R4: full-pod stage; R8: full-maturity stage.
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Figure 5. Soil stoichiometric imbalances at different stages under long-term mulching. Stoichiometric imbalances based on the soil total nutrients (ac) and available nutrients (df). Error bars indicate standard deviation (n = 3). Different lowercase letters indicate statistically significant differences among mulching treatments (p < 0.05). NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching; V4: four-leaf stage; R4: full-pod stage; R8: full-maturity stage.
Figure 5. Soil stoichiometric imbalances at different stages under long-term mulching. Stoichiometric imbalances based on the soil total nutrients (ac) and available nutrients (df). Error bars indicate standard deviation (n = 3). Different lowercase letters indicate statistically significant differences among mulching treatments (p < 0.05). NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching; V4: four-leaf stage; R4: full-pod stage; R8: full-maturity stage.
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Figure 6. Effects of soil physicochemical properties and microbial biomass on stoichiometric imbalance under the effect of mulching. Variational decomposition analysis (VPA) determined the explanation rate of soil variables for stoichiometric imbalances (a). The total effective value of the driving variable on stoichiometric imbalances calculated by total and available nutrients (b). The number shows the explanatory ratio. Asterisks indicate significant total effects (* p < 0.05).
Figure 6. Effects of soil physicochemical properties and microbial biomass on stoichiometric imbalance under the effect of mulching. Variational decomposition analysis (VPA) determined the explanation rate of soil variables for stoichiometric imbalances (a). The total effective value of the driving variable on stoichiometric imbalances calculated by total and available nutrients (b). The number shows the explanatory ratio. Asterisks indicate significant total effects (* p < 0.05).
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Figure 7. Relationship between soil stoichiometric ratio and yield. Correlation between soil stoichiometry and yield components (a). The interpretation rate of the redundancy analysis (RDA) of the impact of stoichiometric imbalances on yield (b). Asterisks indicate significant correlations (* p < 0.05, ** p < 0.01). T: Total nutrients; A: Available nutrients.
Figure 7. Relationship between soil stoichiometric ratio and yield. Correlation between soil stoichiometry and yield components (a). The interpretation rate of the redundancy analysis (RDA) of the impact of stoichiometric imbalances on yield (b). Asterisks indicate significant correlations (* p < 0.05, ** p < 0.01). T: Total nutrients; A: Available nutrients.
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Table 1. Soil physicochemical properties at different stages under long-term mulching.
Table 1. Soil physicochemical properties at different stages under long-term mulching.
StageIndexNMSMPMRMp
V4pH8.26 (0.02)8.16 (0.08)8.20 (0.06)8.15 (0.04)0.087
SMC (%)5.84 (0.44)6.64 (0.37)7.43 (0.20)7.94 (0.67)0.002
ST (°C)21.40 (0.35)21.67 (0.42)22.08 (0.88)21.93 (1.10)0.706
SOC (g/kg)4.12 (0.36)4.52 (0.51)3.50 (0.48)3.80 (0.06)0.062
TN (g/kg)0.35 (0.03)0.42 (0.02)0.38 (0.02)0.43 (0.02)0.016
TP (g/kg)0.43 (0.03)0.50 (0.06)0.52 (0.03)0.54 (0.03)0.036
DOC (mg/kg)51.51 (1.97)52.21 (9.64)45.03 (3.69)41.21 (3.83)0.117
AN (mg/kg)6.35 (0.72)6.74 (0.48)5.89 (0.21)7.39 (1.10)0.140
AP (mg/kg)1.21 (0.18)2.72 (0.40)1.15 (0.21)1.98 (0.11)<0.001
R4pH7.67 (0.10)7.78 (0.01)7.83 (0.03)7.81 (0.04)0.029
SMC (%)8.5 1(0.49)8.22 (0.18)8.56 (0.16)7.58 (0.21)0.013
ST (°C)25.16 (0.23)24.71 (0.25)25.33 (0.57)26.53 (0.48)0.003
SOC (g/kg)3.35 (0.42)4.19 (0.36)3.61 (0.44)3.55 (0.48)0.173
TN (g/kg)0.30 (0.01)0.34 (0.04)0.31 (0.03)0.31 (0.01)0.295
TP (g/kg)0.46 (0.04)0.53 (0.05)0.53 (0.03)0.52 (0.06)0.290
DOC (mg/kg)38.44 (4.73)38.06 (5.71)32.62 (2.05)51.25 (7.34)0.015
AN (mg/kg)3.84 (0.15)4.22 (0.10)3.80 (0.18)4.53 (1.13)0.422
AP (mg/kg)2.16 (0.77)3.92 (0.86)2.98 (0.18)4.35 (1.08)0.039
R8pH7.92 (0.04)7.96 (0.02)8.01 (0.06)7.97 (0.03)0.106
SMC (%)11.64 (0.15)11.74 (0.34)12.14 (0.44)12.44 (0.84)0.271
ST (°C)15.73 (0.23)15.85 (0.23)15.11 (0.69)17.02 (0.85)0.020
SOC (g/kg)3.56 (0.12)4.40 (0.35)3.76 (0.19)3.83 (0.07)0.006
TN (g/kg)0.35 (0.04)0.37 (0.04)0.30 (0.01)0.34 (0.02)0.088
TP (g/kg)0.44 (0.01)0.47 (0.02)0.50 (0.04)0.51 (0.05)0.150
DOC (mg/kg)50.03 (2.57)47.72 (4.02)31.12 (4.98)35.10 (2.93)0.001
AN (mg/kg)3.77 (0.44)5.27 (1.22)4.14 (0.10)6.06 (1.36)0.060
AP (mg/kg)1.01 (0.34)1.89 (0.53)1.20 (0.44)1.75 (0.49)0.127
Values indicate the mean value followed by the standard deviation in parentheses (n = 3). NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching; V4: four-leaf stage; R4: full-pod stage; R8: full-maturity stage.
Table 2. Microbial homeostasis (H) in topsoil.
Table 2. Microbial homeostasis (H) in topsoil.
Indexln(Resource)ln(Microbe)|1/H|pHomeostasis
Total nutrientC:NC:N0.8690.023Plastic
C:PC:P0.6320.212Strictly homeostatic
N:PN:P0.4200.377Strictly homeostatic
Available nutrientC:NC:N0.3590.049Weakly homeostatic
C:PC:P0.0380.782Strictly homeostatic
N:PN:P0.1060.382Strictly homeostatic
Table 3. Crop yield components under mulching.
Table 3. Crop yield components under mulching.
MulchPlants/hm2Pods/PlantSeeds/Plant100-Seed Weight (g)Yield (kg/hm2)
NM245,000 (15,000)21.83 (0.64)59.69 (0.33)9.78 (0.11)814.58 (92.18)
SM270,000 (20,000)28.31 (1.89)80.48 (7.72)11.65 (0.16)1254.95 (0.24)
PM285,000 (5000)23.85 (0.54)61.60 (2.90)10.92 (0.12)962.71 (46.06)
RM255,000 (5000)29.45 (0.95)94.15 (2.78)11.30 (0.25)1323.09 (27.48)
p0.025<0.001<0.001<0.001<0.001
The values represent the mean value followed by the standard deviation in parentheses (n = 3). NM: no mulching; SM: straw mulching; PM: plastic mulching; RM: ridge-film mulching.
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Hao, J.-Q.; Song, J.-J.; Gao, G.-X.; Xu, W.; Bai, J.-Z.; Feng, Y.-Z.; Wang, X. Mitigation of the Ratio of Soil Dissolved Organic Carbon to Available Phosphorus Effectively Improves Crop Productivity under Mulching Measures on the Loess Plateau. Agronomy 2023, 13, 1810. https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy13071810

AMA Style

Hao J-Q, Song J-J, Gao G-X, Xu W, Bai J-Z, Feng Y-Z, Wang X. Mitigation of the Ratio of Soil Dissolved Organic Carbon to Available Phosphorus Effectively Improves Crop Productivity under Mulching Measures on the Loess Plateau. Agronomy. 2023; 13(7):1810. https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy13071810

Chicago/Turabian Style

Hao, Jia-Qi, Jia-Jie Song, Guo-Xi Gao, Wen Xu, Jin-Ze Bai, Yong-Zhong Feng, and Xing Wang. 2023. "Mitigation of the Ratio of Soil Dissolved Organic Carbon to Available Phosphorus Effectively Improves Crop Productivity under Mulching Measures on the Loess Plateau" Agronomy 13, no. 7: 1810. https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy13071810

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