Sustainable Rice Farming: The Benefits of Substituting Fertilizer-N with Milk Vetch for Improved Soil Structure and Quality

doi:10.21203/rs.3.rs-4867389/v1

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Research Article

Sustainable Rice Farming: The Benefits of Substituting Fertilizer-N with Milk Vetch for Improved Soil Structure and Quality

https://doi.org/10.21203/rs.3.rs-4867389/v1

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Purpose

Chinese milk vetch (MV) is widely used in rice yield enhancement because of the huge nitrogen (N) substitution potential. However, the proper substitution rate of MV for N fertilizer and its effect on carbon sequestration and nutrient retention in soil aggregates remains unknown.

Method

A 10-year field experiment was conducted to investigate the effects of different MV substitution rates on soil aggregate stability, nutrient retention, and soil quality in a double rice cropping system. The treatments included no fertilizer (CK), 100% NPK fertilizer (N₁₀₀), recommended N supply by different proportions of MV (N₈₀G₂₀, N₆₀G₄₀, N₄₀G₆₀, N₂₀G₈₀)

Result

Compared with the N₁₀₀ treatment, the N₈₀G₂₀ and the N₆₀G₄₀ treatment increased the mean weight diameter (MWD) by 4.2% and 5.3%, and the geometric mean diameter (GMD) by 7.7% and 12.1%, respectively. The N₆₀G₄₀ treatment significantly increased the labile organic carbon content and carbon pool management index by 24.7% and 45.0%, respectively. N₈₀G₂₀ and N₆₀G₄₀ treatments directly increased total nitrogen (TN) and total phosphorus (TP) in macro-aggregates (> 0.25mm), and improved the contribution of total nutrients in > 2mm aggregate. Compared with the N₁₀₀ treatment, the N₆₀G₄₀ treatment improved TN, TP and TK by 6.0%, 9.3% and 5.6%. Incorporating MV improved the soil quality index (SQI), with N₆₀G₄₀ treatment improved the most by 34.1%. And the grain yield increased significantly with the increasing SQI. Substituting 20–60% of N by MV can sustain grain yield. However, a higher substitution rate significantly reduced grain yield, particularly in the early rice.

Conclusions

Consequently, Incorporating MV to substitute 20–40% N fertilizer can enhance soil structure by improving the proportion of macro-aggregates, thereby improving nutrient retention and soil quality. This study provides a sustainable and eco-friendly approach in the double rice cropping systems.

Green manure

Soil aggregate

Soil organic carbon

Soil quality

Using leguminous plants such as Chinese milk vetch (Astragalus sinicus L, MV) and hairy vetch (Lolium perenne L) is an economical and environmentally friendly strategy. Especially in double rice cropping systems, planting MV during the winter fallow period can prevent soil degradation and effectively improved the ecological environment (Cao et al., 2009). After ploughing the MV into the paddy field, it can provide nitrogen (N), phosphorus (P), and potassium (K) for subsequent crops. This increased soil enzyme activity, enhanced nutrient turnover by microbes, ultimately improved soil fertility and rice yields (Zhou et al., 2019; Gao et al., 2020; Zhou et al., 2020).

Chemical fertilizers (CFs) application is an effective measure to increase crop yields directly by providing a large amount of nutrients to crops. However, excessive use of CFs can lead to soil acidification (Zhang., 2010), disrupt soil physical structure (Luan et al., 2019), and exacerbate the risk of agricultural non-point source pollution (Wu and Ge, 2019). Controlling N fertilizer within 40%-70% of the amount commonly used by farmers is sufficient to maintain yield while reducing N losses significantly in the environment (Ju et al., 2009). Widely considered to be a good way to substitute N fertilizer by MV, the MV improved soil nutrients directly, moreover, it can promote the nutrient retention by enhancing soil aggregate stability.

As the main carrier of nutrients, the quantity of soil aggregates is closely related to organic carbon content (Liu et al., 2023). Continued use of organic materials can enhance the binding between soil particles, promoted microaggregate formation, and thereby enhanced soil aggregate stability (Chen et al., 2001; Li et al., 2016; Topps et al., 2021). As a green and clean organic fertilizer source, mulching MV also had significant advantages in enhancing soil physical structure and increasing nutrient contents in soil aggregates (Kamran et al., 2021). The incorporation of MV significantly enhanced the quantity of 2-0.25mm and 0.25-0.053mm microaggregates (Yu et al., 2020), and also increased the particulate organic carbon content within aggregates, which is beneficial for microaggregate formation, the newly formed aggregates can provide good physical protection for organic carbon. Additionally, as a typical nitrogen-rich crop, its decomposition can produce a large amount of N-containing organic compounds (Gao et al., 2018), increasing the soil N pool and thereby enhancing soil N supply capacity. However, understanding how the incorporation of MV improved nutrient retention requires further investigation, particularly under different proportion of MV.

Here, we used a ten-year continuous field experiment to explore the effects of substituting N fertilizer by MV on grain yield, the distribution and stability of soil aggregates, soil carbon pool composition, and nutrient content in soil aggregates. The main objectives of this study were to: 1) investigate the effect of MV with 20%-80% N fertilizer applied on soil aggregate stability and relate these to SOC fractions contents 2) explore nutrient distribution in different aggregates and its contribution on nutrient retention 3) identify a better practice for combined application of MV and N fertilizer that benefits both soil quality and crop yield. Addressing these questions will provide references for the efficient utilization of MV in rice-rice-green manure rotation systems.

Experimental description

The field experiment began in 2008 at the Hunan Academy of Agricultural Sciences in Yuanqiao Village (29°13′ N, 112°28′ E), Sanxianhu Town, Nanxian County, Hunan Province, China. The area experiences a subtropical humid climate with an annual mean precipitation of 1238 mm and temperature of 16.6 ℃. The soil in this region is classified as purple clay soil (Huang et al., 2021), with its basic physicochemical characteristics are provided in Table S1.

This long-term field study involved the cultivation of early and late rice (Oryza sativa L.), with MV used as a green manure during the winter fallow. The experiment included six treatments with varying proportions of N fertilizer and MV, arranged in a randomized complete block design with three repetitions per treatment. Each treatment plot measured 20 square meters (5 m × 4 m) and was separated by ridges to prevent nutrient and water exchange.

Half (50%) of urea and potassium chloride fertilizer (recommended as local standard) was applied one day before rice transplantation, with the remaining 50% top-dressed during the tillering stage. Superphosphate was applied entirely one day before transplantation (Table 1). Early rice (Xiangzaoxian 45) was planted at the end of April and harvested in mid-July, while late rice (Huanghuazhan) was planted at the end of July and harvested at the end of October. MV was directly seeded in the experimental plots before the harvest of late rice (except for the CK and N₁₀₀ treatments). 10 days before the transplanting of early rice, MV was harvested and incorporated into the soil at the depth of 5–8 cm. The specific amount of MV in each treatment was determined based on equal N nutrient input (Table S2). Other filed management followed the best local practices.

Soil sampling and measurements

We used a stainless-steel auger to collect the soil sample at a depth of 0–20 cm. Three soil cores were taken from each plot to form a composite soil sample. Soil samples were air-dried and sieved through a 10 mm sieve to remove stones and plant debris. Subsequently, broke the sample along natural fractures and sieved through a 2 mm sieve for aggregate size fractions analysis. Water-aggregates stability was measured according to Elliott (1986) and Xiong et al. (2021), divided into six size fractions: >2mm, 1-2mm, 0.5-1mm, 0.25-0.5mm, 0.053-0.25mm, < 0.053mm.

Soil pH and SOC was measured using our previous methods (Xiao et al., 2023). Total and available N, P and K were determined following Estefan et al. (2013). Labile organic carbon (LOC), High labile organic carbon (HLOC) and medium labile organic carbon (MLOC) was determined by 333, 33, 167 mol·L^− 1 KMnO₄, respectively (Blair et al., 1995).

Statistical analysis

Aggregate stability calculations. Soil aggregate stability was evaluated using the indices of mean weight diameter (MWD) and geometric mean diameter (GMD). A higher value indicates stronger aggregate stability. The calculation formulas are as follows (Kemper W D and Rosenau R C 1986; Yan et al., 2008):

MWD=$\:{\sum\:}_{i=1}^{n}{W}_{i}\stackrel{-}{{X}_{i}}$ (1)

GMD = exp ($\:{\sum\:}_{i=1}^{n}{W}_{i}ln\stackrel{-}{{X}_{i}}$) (2)

In the equation, $\:\stackrel{-}{{\text{X}}_{\text{i}}}\:$represents the average diameter of a certain level of soil aggregates (In this study, the average diameters of different levels of soil aggregates are 5 mm, 1.5 mm, 0.75 mm, 0.375mm, 0.15mm and 0.027mm respectively), and $\:{\text{W}}_{\text{i}}$ is the dry mass percentage of the ith level of aggregates to the total dry mass.

Contribution rate. The contribution rate of organic carbon (total nitrogen) in a certain level of aggregates to the total organic carbon (total nitrogen) in the soil is calculated as follows:

= organic carbon (total nitrogen) content in the level of aggregates / (g·kg^− 1) × content of the level of aggregates / (g·kg^− 1) / 1,000 / organic carbon (total nitrogen) content in the soil / (g·kg^− 1)) × 100].

Soil carbon pool. The calculation formula for the CPMI is as follows (Troyer et al 2011; Lin et al 2023):

CPMI = CPI×AI×100 (3)

Carbon Pool Index (CPI) is the SOC of the sample (g/kg) divided by SOC of the reference soil (g/kg); AI (Carbon Pool Activity Index) is the sample carbon pool activity (A) divided by reference soil carbon pool activity; The difference between SOC and LOC is non-labile organic carbon (NLOC). The reference soil in this study is set as the soil before the start of the experiment in 2008.

Soil quality index (SQI). The calculation of SQI can be summarized as follows: (1) identifying primary soil properties for analysis; (2) calculating the weight of each indicator to obtain a score; (3) integrating all indicator scores to obtain an overall SQI value. Based on previous study, six parameters were selected for evaluating soil quality, including pH, SOM, TN and the AN, AP and AK (Zhang et al., 2023). Consistent to previous study, using principal component analysis (PCA) to assign the weight (Sun et al., 2003). The weights assigned to each indicator are detailed in Table 1.

As recommended by Li et al. (2013), a type S function was used as the standard scoring function to calculate soil indicator scores,

$$\:f\left(x\right)=\:\left\{\begin{array}{c}0.1\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:x<L\\\:\frac{0.9\left(x-L\right)}{U-L}+0.1\:\:\:\:\:\:\:L\le\:x\le\:U\\\:0.1\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:x>U\end{array}\right.\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(4\right)$$

In the equation, x represents the monitoring value of the indicator; f(x) denotes the score of the indicator ranging from 0.1 to 1.0; L and U are the lower and the upper threshold values of the indicator, respectively.

The soil pH has an ideal range and its function is as follows (Shang et al., 2014):

$$\:f\left(x\right)=\left\{\begin{array}{c}\:\:\:\:0.1\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:x<x1,x>x4\\\:\frac{0.9\left(x-x1\right)}{x2-x1}+0.1\:\:\:\:\:\:\:\:\:\:x1\le\:x\le\:x2\\\:1.0\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:x2\le\:x<x3\\\:\frac{0.9\left(x-x3\right)}{x4-x3}+0.1\:\:\:\:\:\:\:\:\:x3\le\:x<x4\end{array}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(5\right)\right.$$

where x1 = 4.5; x2 = 5.5; x3 = 6.5; x4 = 8.5.

As Doran and Parkin (1994) described, the SQI was calculated as follow:

$$\:\:\text{S}\text{Q}\text{I}=\sum\:_{i=1}^{n}（Wi\times\:Qi）\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(6\right)$$

where n is the total number of indicators in the MDS, Wi is the assigned weight of each indicator and Qi is the indicated score.

Table 1

Results of PCA and the community and weighted value of each soil quality indicator.
Soil parameters	PC1	PC2	Community	Total Weight
pH	0.46	0.83	0.901	0.193
SOM	0.87	0.15	0.770	0.165
TN	0.65	-0.64	0.825	0.177
AN	0.78	-0.06	0.618	0.133
AP	0.95	-0.07	0.898	0.193
AK	0.80	0.02	0.646	0.139
Proportion Explained	0.5873	0.1890

Statistical analysis. Using one-way analysis of variance and multiple comparison test to analyze significant differences among all fertilizer treatments based on SPSS 20.0. All Figures were drawn using Origin 9.8 software. R software (version 4.4.1) with the “random Forest” package was used to analyze the relative influence (%) of the soil chemical properties on SQI and grain yield (Xiao et al., 2024).

Grain yield

In the early rice season, rice yield initially increased and then decreased with increasing substitution of N fertilizer. The yield of the N₆₀G₄₀ treatment is the highest, showing a 2.6% increase compared to the N₁₀₀ treatment. However, when the substitution rate reached 80%, there was a significant decrease in crop yield. In the late rice season, yield gradually decreased with increasing N fertilizer substitution, although none of the reductions reached a significant level compared to the N₁₀₀ treatment.

Table 2

Rice grain yield in different fertilization treatments
Treatment	Yield
Treatment	Early rice	Late rice	Annual
CK	2490 ± 161^a) c^b)	4593 ± 233 b	7083 ± 359 c
N₁₀₀	5027 ± 201 a	7693 ± 291 a	12720 ± 497 a
N₈₀G₂₀	5047 ± 183 a	7413 ± 462 a	12460 ± 639 ab
N₆₀G₄₀	5157 ± 175 a	7077 ± 176 a	12233 ± 130 ab
N₄₀G₆₀	4723 ± 57 ab	6934 ± 369 a	11660 ± 346 ab
N₂₀G₈₀	4407 ± 219 b	6797 ± 181 a	11203 ± 394 b

Different lowercase letters represent the correlation was significant (P < 0.05).

Means ± standard errors (n = 3)

Distribution of soil aggregates and their stability indices

Under all treatments substituting partial N fertilizer with MV, the proportions of > 2mm and 1-2mm water-stable aggregates were the highest (68%-72%) and the lowest (4.2%-4.4%), respectively. The incorporation of MV increased the content of > 2mm water-stable aggregates across all treatments. The N₆₀G₄₀ treatment exhibited the highest content (72.41%), but as the amount of MV increased, there was a decreasing trend in the content of > 2mm water-stable aggregates. Analysis of the proportion of water-stable aggregates smaller than < 0.25mm showed similar trends for aggregates between 0.053-0.25mm and those smaller than 0.053mm across different treatments. In both cases, the N₁₀₀ treatment had the highest proportion, while the N₆₀G₄₀ treatment had the lowest. Compared with the N₁₀₀ treatment, the N₆₀G₄₀ treatment reduced the contents of 0.053-0.25mm and < 0.053mm water-stable aggregates by 15.44% and 18.67%, respectively. The subsequent reductions were observed in the N₄₀G₆₀ (13.04% and 10.00%) and N₈₀G₂₀ (9.60% and 9.24%) treatments. The changes in MWD and GMD were consistent across all treatments (Fig. 1c, Fig. 1d). Long-term fertilization reduced soil aggregate stability. Compared with the CK, the MWD and GMD of the N₁₀₀ treatment decreased by 2.19% and 3.27%, respectively. Different substitution rates of MV improved soil aggregate stability. Compared with the N₁₀₀ treatment, N₈₀G₂₀ increased MWD and GMD by 4.19% and 7.73%, respectively, while N₆₀G₄₀ increased MWD and GMD by 5.31% and 12.08%, respectively.

Figure 1 Effects of fertilizer-N substituted by MV on different proportions of soil aggregate (a, b), MWD(c) and GMD(d).

SOC density fractions

Incorporating MV positively impacted the content of soil active organic carbon (Fig. 2a). The N₆₀G₄₀ treatment showed the most significant improvement, followed by N₄₀G₆₀. The order of LOC content across various treatments was N₆₀G₄₀ > N₄₀G₆₀ > N₈₀G₂₀ > N₂₀G₈₀ > N₁₀₀ > CK. Compared with the N₁₀₀ treatment, N₄₀G₆₀ mainly increased the content of HLOC by 24.34%, while N₆₀G₄₀ primarily increased the content of MLOC by 16.40%. As shown in Fig. 2b, all treatments significantly increased soil AI, CPI, and CPMI, with increased ranging from 7.77–30.10%, 5.55–15.74%, and 18.91–44.96%, respectively. As the proportion of N fertilizer substitution increased, CPI and CPMI initially increased and then decreased. The N₆₀G₄₀ treatment showed the most significant improvement, with CPI and CPMI increasing by 15.74% and 44.96%, respectively, compared with the N₁₀₀ treatment,

Figure 2 Effects of fertilizer-N substituted by MV on organic carbon content of whole soil.

Soil aggregate nutrients and its distribution

Substituting CF with MV increased the content of soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), and total potassium (TK) in the 1-2mm aggregate, with total nutrient content increasing alongside higher MV substitution rates (Fig. 3a). The SOM content initially increased and then decreased with decreasing aggregate particle size, peaking in the 1-2mm aggregate, followed by the > 2mm aggregate. Apart from the 1-2mm aggregate, the N₈₀G₂₀ treatment exhibited the highest SOM content in other particle size aggregates, ranging from 17.75–27.09 g kg^− 1. The TN and TP contents of soil aggregate gradually decreased with decreasing particle size and were mainly concentrated in macro-aggregates (> 0.25mm). The highest TN content was observed in the > 2mm aggregate under the N₈₀G₂₀ treatment, at 3.19 g kg^− 1. Compared with the N₈₀G₂₀ treatment, the N₄₀G₆₀ treatment significantly reduced the TN content in the 0.053-0.25mm and < 0.053mm aggregates. The N₈₀G₂₀ treatment also significantly increased TP content in the 1-2mm aggregate compared with the N₁₀₀ treatment. Regarding TK content, the N₆₀G₄₀ treatment increased the content in the > 2mm and 1-2mm aggregates compared with the N₁₀₀ treatment, although the increase was not statistically significant.

The alkali-hydrolysable N (AN) and available P (AP) in soil aggregates gradually decreased with decreasing aggregate particle size (Fig. 3b). Compared with the N₁₀₀ treatment, the N₈₀G₂₀ treatment increased AN content in the 1-2mm and 0.25-0.5mm aggregates by 7.83% and 3.27%, respectively. Similarly, the N₆₀G₄₀ treatment followed this trend. Under different proportions of MV, the trend in AP content across various aggregate size was consistent with AN. The N₈₀G₂₀ treatment significantly increased AP content in the 1-2mm and 0.5-1mm aggregates by 29.23% and 27.79%, respectively, compared to the N₁₀₀ treatment. Incorporating MV reduced the available potassium (AK) in various particle aggregates, except for the 1-2mm size, with the reduction increasing alongside higher MV substitution rates. Compared with the N₁₀₀ treatment, the N₂₀G₈₀ treatment reduced the AK content in the 0.5-1mm aggregate significantly.

Under different substitution rates of N fertilizer, >2mm aggregates contributed more to SOM and TN contents, with their contribution rates initially increasing and then decreasing as the MV proportion increased (Fig. 4). Compared with the N₁₀₀ treatment, all treatments substituting N fertilizer with MV increased the contribution rates of > 2mm aggregate to SOM and TN. The N₄₀G₆₀ and N₆₀G₄₀ treatments showed the greatest increase, with SOM contribution rates increasing by 3.41% and 4.07%, and TN contribution rates increasing by 6.00% and 8.17%, respectively. Meanwhile, these treatments reduced the contribution rates of < 0.25mm aggregate, with SOM contribution rates decreasing by 15.77% and 15.65%, and TN contribution rates decreasing by 5.17% and 7.55%, respectively. Substituting N fertilizer with MV also increased the contribution rates of > 2mm aggregate to soil TP and TK, with the N₆₀G₄₀ treatment showing the highest increases of 9.31% and 5.63%, respectively, compared with the N₁₀₀ treatment. Conversely, it reduced the contribution rates of < 0.25mm aggregate to soil TP and TK, with reductions of 34.66% and 17.96%, respectively, compared with the N₁₀₀ treatment.

Figure 3 Effects of N fertilizer substituted by MV on aggregate-associated SOM, TN, TP and TK; AN, AP and AK contents

Figure 4 Effects of N fertilizer substituted by MV on SOM, TN, TP and TK contribution rates in soil aggregates

SQI and rice grain yield

Soil chemical properties. Incorporating MV significantly increased the soil AN, AP and AK contents (Table 3), compared with CK, the AN in N₄₀G₆₀ treatment and the AP content in N₆₀G₄₀ treatment improved by 21.08% and 72.33%, respectively. Substitution N fertilizer with MV significantly increased SOM and TN contents, with the N₆₀G₄₀ treatment showing the greatest improvement among all treatments. Compared to the N₁₀₀ treatment, SOM and TN contents improved by 10.16% and 9.52%, respectively.

Table 3

Chemical properties of the whole soil.
Treatments		pH	SOM	TN	TP	TK	AN	AP
CK	7.58 ± 0.08 b	38.4 ± 1.31 c	2.67 ± 0.01 b	0.99 ± 0.03 c	22.2 ± 0.55 ab	204 ± 3.0 d	11.9 ± 3.45 b	55.1 ± 1.22 b
N₁₀₀	7.67 ± 0.03 ab	43.3 ± 2.50 b	2.73 ± 0.19 b	1.16 ± 0.06 ab	21.4 ± 0.47 bc	224 ± 6.8 c	38.0 ± 7.36 a	74.6 ± 4.94 a
N₈₀G₂₀	7.65 ± 0.02 ab	43.7 ± 1.52 b	2.58 ± 0.14 b	1.09 ± 0.06 b	21.3 ± 0.33 bc	231 ± 2.7 bc	40.0 ± 3.60 a	69.2 ± 4.09 a
N₆₀G₄₀	7.63 ± 0.01 ab	47.7 ± 1.09 a	2.99 ± 0.01 a	1.24 ± 0.01 a	21.0 ± 0.05 c	236 ± 0.5 ab	43.0 ± 3.30 a	71.6 ± 1.63 a
N₄₀G₆₀	7.71 ± 0.05 a	46.8 ± 0.71 ab	2.72 ± 0.09 b	1.14 ± 0.02 b	22.5 ± 0.20 a	247 ± 10.8 a	36.0 ± 4.23 a	72.2 ± 1.69 a
N₂₀G₈₀	7.73 ± 0.04 a	47.3 ± 0.27 a	2.79 ± 0.13 ab	1.15 ± 0.04 ab	21.8 ± 0.67 abc	242 ± 8.5 ab	36.8 ± 1.48 a	67.8 ± 3.78 a

The relationship between SQI, grain yield and soil chemical properties.

Substituting N fertilizer with MV increased the SQI (Fig. 5a). The SQI showed an initial increase followed by a decreasing trend, with the N₆₀G₄₀ treatment exhibiting the highest SQI, which was 19.08% higher compared with the N₁₀₀ treatment. Additionally, the annual rice yield significantly increased with the improvement of SQI (Fig. 5b). Random forest model analysis integrated the prediction results of soil chemical properties for SQI (Fig. 5c) and rice yield (Fig. 5d). The results revealed that AN, TP, AP, SOM and TN were the primary predictors influencing SQI, while AK, MLOC, AP and SQI were key factors for interpreting rice yield

Figure 5 Comprehensive analysis of SQI, grain yield and soil chemical properties

The SQI across different treatments (a) and its correlation with annual rice grain yield (b), the relative influence (%) of soil chemical properties on SQI (c) and rice grain yield (d) based on a relative important model. (^*: P < 0.05; ^**: P < 0.01)

Green manure substitution improved soil aggregates stability and soil organic carbon storage

The distribution characteristics and stability of soil aggregates can be used to characterize soil quality changes under different management practices. In this research, planting MV promoting the formation of > 2mm soil aggregate, accompanied by decreasing the content of silt and clay (Fig. 1a). MV directly increased the input of organic carbon, thereby contributing to the increased SOC content (Table 3). SOC serves as the main binding agent in the formation of macroaggregates and the maintenance of their structural stability (Muhammad et al., 2021). Additionally, green manure improved the stability of SOC by enhancing the presence of recalcitrant structures such as alkyl C and aromatic C in mineral associated organic carbon fraction (Huang et al., 2022). In another aspect, the incorporation of the green manure can enhance microbial community activity, thereby contributing to the mineralization of native SOC by priming effect (Kuzyakov et al., 2000). SOC is crucial for maintaining soil structure stability (MWD and GMD) (Kemper and Rosenau, 1986), better soil structure in turn providing physical protection to the soil organic matter. The trend of LOC is consistent with SOC (Fig. 2a). The incorporation of the green manure combined with fertilization significantly improved the activity of cellulase and glucomannan enzyme. This improvement promoted the degradation of organic matter and directly increased the content of LOC (Straten et al., 2001; Quan et al., 2023). The CPI and the CPMI can response the active and the stability of SOC respectively, which can better reflect the dynamic changes in carbon pools under different management practices (Blair et al., 1995). In this research, green manure incorporation improved the CPI and CPMI (Fig. 2b). As the fresh organic matter inputs were delivered to the soil, the available part directly turned to the dissolved organic carbon. Its degradation also promoted the decomposition of the original SOC (priming effect) (Luo et al., 2015), thereby increasing the proportion of LOC. We found that the stability of soil aggregates and carbon pool peaked when incorporating 40% green manure, and decreased with higher addition rates. These findings, which indicate that increasing the substitution of N fertilizer does not necessarily lead to greater accumulation of SOC, are consistent with those of Li et al. (2019), Huang et al. (2022), and Quan et al. (2023).

Green manure substitution improved soil nutrients in aggregates

Soil nitrogen, phosphorus and potassium are important component of the soil fertility. More than 95 percent of soil N is found in organic matter and positively correlated with the content of SOC (Bi et al., 2023). Consistent with the content of SOC, the incorporation of the MV increased soil nitrogen level (Fig. 3a). As a kind of legume green manure, MV can assimilate large amounts of atmospheric N and take up inorganic N from the soil. It converted this N into organic forms within the plants and then reintroduced it to the soil, thereby contributing to soil nitrogen replenishment. (Cao et al., 2009; Coombs et al., 2017; Yang et al., 2022). On the other hand, the incorporation of MV may inhibit nitrification by suppressing the abundance of ammonia oxidizers, and thus reducing the risk of nitrogen leaching loss (Paungfoo-Lonhienne et al., 2017; Gao et al., 2020). Previous researches have indicated that incorporating MV leads to a significant increase in soil AP content in double rice cropping systems. (Li et al., 2020; Xie et al., 2022). In our research, the incorporation of MV had little effect on the soil TP in aggregates (Fig. 3a). However, the soil AP content significantly increased by an average of 19.56% in the 1-2mm aggregate and 15.30% in the 0.5-1mm aggregate (Fig. 3b). Green manure can provide a substantial carbon source, altering the soil carbon-to-phosphorus ratio. Microorganisms, in response, promoted the mineralization of soil organic P to maintain stoichiometric balance. Additionally, the abundant organic carbon supports microbial growth and enhances mineralization through the secretion of phosphatase. (Bergkemper et al., 2016; Luo et al., 2017). Furthermore, approximately 28% of the green manure converted into the microbial biomass phosphorus within a week after ploughing. Microbial biomass phosphorus constitutes a crucial component of the soil P pool and is a key factor of soil AP (Peng et al., 2021). The incorporation of MV positively impacts the K supply capacity in paddy soil. By activating non-exchangeable and lattice K, it directly enhances soil AK. Moreover, non-legume green manure has shown superior performance (Wen et al., 2020; Ma et al., 2021). Contrary to previous researches, we found that the incorporation of MV led to a decrease in AK levels in the whole soil and in soil aggregates (Fig. 3b, Table 3). Most of the K nutrient from MV were released within 15 days of its applications and completely decomposed within 90 days (Wang et al., 2012; Huang et al., 2016). In this research, soil sample were collected in March. Late rice took plenty of potassium, and during its flowering phase, green manure requires nutrient for growth. Zhang et al. (2017) demonstrated that soil AK level remained unchanged during early rice but decreased significantly during late rice when MV was incorporated, consistent with our findings. Previous studies have indicated higher nutrient levels in macro-aggregates, potentially contributing to increased aggregate stability (Wei et al., 2013; Ge et al., 2017). In our study, the contents of SOC, TN and TP decreased with decreasing aggregate size (Fig. 3a). Aggregates formation is considered the primary mechanism for soil carbon sequestration (Six et al., 2000). Recent research has shown that organic matter can reduce the hydrolysis rate of soil aggregates by increasing their water repellency and slowing their wetting rate (Xue et al., 2019). Formation of aggregates helps to shield nutrients from atmospheric influences and microorganisms, thereby reducing nutrient loss. In our study, the incorporation of MV increased the contributions of total nutrients(TN、TP、TK) in aggregates larger than 2mm, while decreasing them in aggregates smaller than 0.25mm (Fig. 4). This indicated that MV utilization enhances the transformation of nutrient into macro-aggregates, where organic matter from microbial decomposition is preferentially distributed. In conclusion, incorporating MV enhanced soil aggregate stability, which can promote the physical protection of soil nutrients. Further research is needed to understand the relationships among organic carbon, nitrogen, and phosphorus within soil aggregates.

Green manure substitution improved soil quality index to maintain grain yield

In our study, substitution CF with MV primarily increased soil total nutrient content (Table 3), MV shows significant potential for reducing N fertilizer use by enhancing carbon storage and expanding N and P pools (Gao et al., 2013; Yang et al., 2019). Numerous studies have used pH、SOM、AP and other available nutrients to evaluate soil quality (M. Ghaemi et al., 2014 ; Shang et al., 2014; Xie et al., 2016). Following previous recommendation (Zhang et al., 2022), we selected pH, SOM, TN, AN, AP, and AK as our minimum dataset. Our findings indicate that replacing 40% of N fertilizer with MV optimizes soil quality (Fig. 5a), crucial for increasing rice yield and maintaining stability, consistent with earlier researches (Xie et al., 2016; Li et al., 2020). However, higher substitution rates do not lead to a better result. The SQI significantly decreased at 60% substitution, similarly, the grain yield significantly decreased at 80% substitution (Table 2). The decreased in SQI directly correlates with reduced rice yield (Fig. 5b). Previous studies have indicated that the ability of MV to replace CFs is limited (Zhang et al., 2020; Liang et al., 2021), as CFs provide nutrients quickly and MV supplies them slowly and continuously. AP strongly influenced both SQI and grain yield (Fig. 5c, Fig. 5d). Incorporating MV enhances phosphorus accumulation and its availability, thereby enhancing soil fertility and its contribution to grain yield (Mitran and Mani, 2017; Zhang et al., 2022). We have to point out that we only used soil chemical properties to evaluate SQI, while further research should incorporate physical factors (such as soil bulk density), and biological conditions (such as soil animals), consider more on the soil ecosystem's ability to provide multiple functions to better assess soil health.

Continuously field experiment over ten years have confirmed that substituting chemical N fertilizer with MV increased the proportion of soil macroaggregates (> 0.25mm), enhanced soil aggregate stability, and also elevated the content of active organic carbon components, thereby significantly improving the soil CMI and CPMI. The incorporation of MV promoted nutrient transformation into macroaggregates, while enhancing soil physical structure provides better physical protection for nutrients. Substituting 20–40% of N fertilizer with MV not only enhanced soil fertility but also stabilized rice grain yield. However, there is a potential risk of yield reduction when the substitution rate reached 80%.

Authors' contributions

Haoliang Yuan: Writing – original draft. Jianglin Zhang: Writing – review & editing and Funding acquisition. Peng Li, Software. Jun Nie, Weidong Cao, Yanhong Lu, Yulin Liao Conceptualization, Supervision, Funding acquisition. All the authors contributed critically to the drafts and approved the final manuscript for publication.

ACKNOWLEDGEMENTS

This work was financially supported by the National Natural Science Foundation of China (32202607), the National Key Research and Development Program of China (2021YFD1700200), the Hunan Provincial Natural Science Foundation (2023JJ40391, 2023JJ40392), the Innovative Research Groups of the Natural Science Foundation of Hunan Province (2023CX47, 2023CX45); and the earmarked fund for CARS-Green manure (CARS-22).

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Sustainable Rice Farming: The Benefits of Substituting Fertilizer-N with Milk Vetch for Improved Soil Structure and Quality

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Abstract

Purpose

Method

Result

Conclusions

Figures

INTRODUCTION

MATERIALS AND METHODS

Experimental description

Soil sampling and measurements

Statistical analysis

MWD=\(\:{\sum\:}_{i=1}^{n}{W}_{i}\stackrel{-}{{X}_{i}}\) (1)

CPMI = CPI×AI×100 (3)

RESULTS

Grain yield

Distribution of soil aggregates and their stability indices

SOC density fractions

Soil aggregate nutrients and its distribution

SQI and rice grain yield

DISCUSSION

Green manure substitution improved soil aggregates stability and soil organic carbon storage

Green manure substitution improved soil nutrients in aggregates

Green manure substitution improved soil quality index to maintain grain yield

CONCLUSION

Declarations

Authors' contributions

ACKNOWLEDGEMENTS

References

Supplementary Files

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