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Article

Differential Soil Organic Carbon Accumulation Patterns Following Cropland-to-Grassland Conversion in Non-Saline and Saline–Alkali Soils

by
Jinglei Zhang
1,2,3,
Shanshan Bai
4,
Chunlin Jia
1,
Lele Kang
5,
Yuxue Zhang
6,
Cong Guan
1,
Jinhong Zhang
1,
Daniel Horacio Basigalup
1,
Bo Wu
1 and
Guoliang Wang
1,*
1
Institute of Leisure Agriculture, Shandong Academy of Agricultural Sciences, Ji’nan 250100, China
2
Yellow River Delta Modern Agriculture Research Institute, Shandong Academy of Agricultural Sciences, Dongying 257091, China
3
National Center of Technology Innovation for Comprehensive Utilization of Saline–Alkali Land, Dongying 257347, China
4
Shandong Provincial Animal Husbandry General Station, Ji’nan 250100, China
5
College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China
6
School of Life Sciences, Hebei University, Baoding 071002, China
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(22), 2393; https://doi.org/10.3390/agriculture15222393
Submission received: 17 October 2025 / Revised: 14 November 2025 / Accepted: 17 November 2025 / Published: 19 November 2025
(This article belongs to the Section Agricultural Soils)
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Versions Notes

Abstract

Agricultural expansion and intensification generally lead to a depletion in soil organic carbon (SOC). While converting cropland to grassland is a recognized strategy for SOC accumulation, the patterns of SOC accumulation under different grassland types and soil conditions remain unclear. This study evaluated the long-term effects of two perennial grasses—alfalfa (a legume) and switchgrass (a non-legume)—on SOC composition, specifically lignin phenols and amino sugars, in non-saline and saline–alkali soils, using a conventional wheat–maize rotation as a control. Our results showed that both alfalfa and switchgrass significantly enhanced SOC content compared to a wheat–maize rotation, but their accumulation pathways differed between non-saline and saline–alkali soils. In non-saline soils, increases in both lignin phenols and amino sugars (muramic acid and glucosamine) were observed under both perennial grasses. In saline–alkali soils, however, the accumulation was primarily driven by glucosamine. While no significant difference was observed in amino sugars content between the two grasses, switchgrass showed significantly higher lignin phenols content than alfalfa under saline–alkali conditions. This indicated that litter quality regulated the accumulation of plant-derived C in saline–alkali environments, but has no significant impact on the accumulation of microbial-derived C. These findings elucidate the divergent mechanisms that drive SOC sequestration following cropland-to-grassland conversion in contrasting non-saline and saline–alkali soils, highlight the dominant role of microbial processes in SOC accumulation following such conversion.

1. Introduction

Soil carbon (C) dynamics, as a key component of the terrestrial C cycle, critically influence the global C balance and climate change [1,2]. Intensive agricultural practices have triggered widespread soil C depletion, threatening global soil health and agricultural sustainability [3]. In response, converting cropland to grassland—particularly perennial grassland—has emerged as a promising strategy for enhancing C sequestration [4,5,6]. This practice promotes SOC accumulation through reduced tillage disturbances, alongside increased plant residue inputs, microbial activity and residue accumulation [7].
Despite its potential, the specific sources and formation pathways of soil organic carbon (SOC) following this land use change remain inadequately understood, especially across varying environmental conditions. Recent research has increasingly highlighted the substantial contributions of plant- and microbial-derived C to the accumulation of SOC [8,9]. These two forms of SOC exhibit distinct chemical characteristics and stabilization mechanisms, and their variations critically influence SOC composition, stability, and soil C sequestration potential [10,11]. Land use and soil type exert a profound influence on these two forms of SOC [12]. Therefore, a clear understanding of the contribution and allocation of plant- and microbial-derived C is critical for unraveling the mechanisms of SOC formation in the context of land use change.
The Yellow River Basin, encompassing a vast area of approximately 79.5 × 104 km2, in northern China, serves as a critical C sink and storage for China’s terrestrial ecosystem [13]. Subject to both fragile natural conditions and long-term human activities, the SOC pool in the lower Yellow River’s alluvial area not only has a low baseline level but also faces severe risks of depletion [14]. Although the conversion of cropland to grassland enhances potential drivers of SOC accumulation, its actual effects on SOC content remain inconsistent, with studies reporting increases, decreases, or no change [15,16,17]. These findings highlight that the response of SOC to land use change varies depending on the environmental condition [18,19]. In environments characterized by salinity, abiotic stress can simultaneously limit plant productivity and microbial activity, thereby leading to differences in the plant- and microbial-derived C accumulation [20,21]. Moreover, differences in vegetation types drive variations in the quantity and quality of C input, which subsequently alter microbial community structure and activity. Plants of a high quality (low C/N) may result in microbial-derived C accumulation from enhanced soil microbial growth [22]. Therefore, studying how vegetation types affect SOC sources across varying soil environments is essential to elucidate the mechanisms of SOC formation following cropland-to-grassland conversion and to facilitate the design of regionally targeted soil C strategies.
To elucidate SOC formation mechanisms after cropland-to-grassland conversion, a comparative analysis of plant-derived (lignin phenols) and microbial-derived (amino sugars) C compounds was conducted at two contrasting sites—Dongying (saline–alkali soil) and Jinan (non-saline soil)—in the lower Yellow River region, where former cropland had been converted to alfalfa and switchgrass grasslands. These two sites share similar climatic conditions but differ in soil salinity, with Dongying exhibiting significantly higher soil electrical conductivity. Based on known differences in plant and microbial communities’ tolerance of saline–alkali conditions, we hypothesized that response of SOC components in saline–alkali and non-saline soils would be significantly different to cropland-to-grassland conversion, such that (1) compared to the wheat–corn rotation, alfalfa and switchgrass cultivation would increase the SOC both in saline–alkali and non-saline soils and (2) alfalfa and switchgrass cultivation would increase both plant- and microbial-derived C compounds in non-saline soils, (3) but there would be an increase in fungal-derived C compound in saline–alkali soils.

2. Materials and Methods

2.1. Site Description and Sampling

This study was conducted at two sites in the lower Yellow River region: Jinan, with non-saline soil, and Dongying, characterized by saline–alkaline soil (Figure S1). Although both sites share similar climatic conditions, Dongying exhibited significantly higher soil salinity (as indicated by electrical conductivity) due to its location within the Yellow River estuary (Table 1). At each site, we established experimental plots on former cropland converted to grassland. Each plot (2500 m2) contained seven-year-old stands of alfalfa and switchgrass that were maintained without regular fertilization or mowing. For comparison, an adjacent area under a conventional wheat–corn rotation was selected as a control at each location. In this rotation system, only wheat straw was incorporated back into the soil, while corn straw was removed.
Soil samples were collected at 0–10 cm depth using a soil auger (diameter: 3.8 cm) from five subplots of each crop system following the diagonal method, i.e., five soil samples per crop system. After passing the soil samples through a 2 mm sieve, one part of each sample was stored at 4 °C for later analysis of soil enzyme activity; the remainder of the sample was air-dried prior to the determination of soil physicochemical properties. The soil physicochemical properties of both study sites are presented in Table 1.

2.2. Soil Properties

Soil organic carbon (SOC) and total nitrogen (TN) were determined by dichromate oxidation and the Kjeldahl method [10], respectively. Soil total phosphorus (TP) was extracted with sodium bicarbonate and quantified using molybdenum–antimony colorimetry. The soil electrical conductivity (EC) and pH were analyzed in 1:5 (w/v) and 1:2.5 (w/v) soil-to-water suspensions, respectively [23].
The enzyme activities of acid phosphatase (AP), β-1,4-glucosidase (BG), leucine–aminopeptidase (LAP), N-acetyl-β-D-glucosaminidase (NAG), peroxidase (PER), and polyphenol oxidase (PPO) were determined spectrophotometrically in clear 96-well microplates [24]. All enzymes were quantified using commercial enzyme kits following the manufacturer’s instructions (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China). Detailed information is provided in Table S1.

2.3. Soil Lignin Phenols and Amino Sugars Analyses

The lignin phenols were determined by using the alkaline CuO oxidation–hydrolysis method [25]. Briefly, 0.5 g of soil was mixed with 0.1 g of ammonium ferrous sulfate, 1 g of copper oxide, and 15 mL of NaOH solution (2 M) in a PTFE reaction vessel, then flushed with N2 for 15 min and heated at 170 °C for 2.5 h. After cooling, 400 μL of ethyl vanillin solution was added and the mixture was centrifuged (KH20A, Hunan Keda Scientific Instrument Co., Ltd., Changsha, China) at 4000 rpm for 3 min; the supernatant was collected, acidified with 6 mol/L HCl, and kept in the dark for 1 h. The lignin oxidation products were liquid–liquid extracted three times with ethyl acetate, concentrated under N2, and then derivatized with BSTFA and pyridine (70 °C, 3 h) to yield trimethylsilyl derivatives. Next, the phenolic oxidation products were quantified by using a gas chromatography system coupled to an ISQ mass spectrometer (ISQ7000, Thermo Fisher Scientific (China) Co., Ltd., Shanghai, China). Together, cinnamyl (i.e., ferulic acid and p-coumaric acid), syringyl (i.e., acetosyringone, syringaldehyde, and syringic acid), and vanillyl (i.e., acetovanillone, vanillic acid, and vanillin) phenols were used to quantify plant residues.
Soil amino sugars were quantified following Zhang and Amelung [26]. Briefly, ~0.5 g of air-dried soil (<2 mm) was hydrolyzed with 10 mL of 6 M HCl at 105 °C for 8 h. Two milliliters of water was added to the cooled sample, which was then dried with N2 at 40 °C, centrifuged (KH20A, Hunan Keda Scientific Instrument Co., Ltd., Changsha, China) at 8000 rpm, and filtered through a 0.45 μm membrane. After adding a quantitative standard solution, the amino sugar content was determined by using high-performance liquid chromatography (HPLC-FLD, Ultimate 3000 analytical, Thermo Fisher Scientific (China) Co., Ltd., Shanghai, China). Glucosamine (GluN) and muramic acid (MurA) were used to indicate fungal and bacterial necromass, respectively.

2.4. Statistical Analysis

All data were tested for homogeneity (Levene’s test) and normality (Shapiro–Wilk test) before the statistical analysis. Data with non-normal or unequal variances were log-transformed to improve the distribution. Differences in soil properties and biomarkers among the three land use treatments (wheat–corn rotation, alfalfa, and switchgrass cultivation) for each soil type were assessed using one-way ANOVA. Duncan’s post hoc test (p < 0.05) was used to assess the differences in the mean values of the variables between land use treatment if the one-way ANOVA results were significant. Differences in soil properties and biomarkers between the wheat–corn rotation and each grassland type (alfalfa or switchgrass) were assessed using a paired-sample t-test. A random forest (RF) analysis performed by loading the “rfPermute” R package (version 4.4.2; R Core Team, 2024) was used to identify the importances of primary soil factors to plant and microbial-derived C compounds at each site [27]. A percentage increase in the mean squared error (MSE) of variables represented the explanations of the predictors, with higher MSE% values indicating greater importance. Furthermore, the Pearson correlation was employed to explore the relationships between soil, plant, and microbial variables at each site.

3. Results

3.1. Soil Properties and Enzyme Activities

Compared to a wheat–corn rotation, cultivating alfalfa and switchgrass consistently increased SOC content while decreasing TP across both non-saline and saline–alkali soils. Additionally, alfalfa increased TN content, but this increase was significant in non-saline soils and was not significant in saline–alkali soils (Table 1).
In non-saline soils, alfalfa and switchgrass cultivation significantly increased both β-N-acetyl-glucosaminidase (NAG) and peroxidase (PER) activities compared with the wheat–corn system. In addition, switchgrass increased the polyphenol (PPO) activity. In saline–alkali soil, alfalfa increased the β-1,4-glucosidase (BG, p = 0.054) and NAG (p = 0.087) activities, and switchgrass increased BG (p = 0.055) activity (Figure 1).

3.2. Lignin Phenols and Amino Sugars: Contents and Contributions to SOC

In the non-saline soils, the cultivation of alfalfa and switchgrass significantly increased the soil lignin phenols content compared to the wheat–corn rotation system, particularly enhancing the levels of vanillyl (V) and syringyl (S) units (Figure 2). In the saline–alkali soils, alfalfa was the only crop that significantly reduced the soil lignin phenols, with a more pronounced decrease observed in syringyl (S) units (Figure 2). Alfalfa had lower lignin phenols content than switchgrass in saline–alkali soils (p < 0.05), but not in non-saline soils (Figure 2).
The acid-to-aldehyde (Ad/Al) ratios for S and V phenols were used to evaluate the extent of lignin degradation. In non-saline soils, both alfalfa and switchgrass cultivation showed lower values of [Ad/Al]S and [Ad/Al]V than the wheat–corn rotation, but this phenomenon was not seen in saline–alkali soils (Figure 3).
Alfalfa and switchgrass significantly increased soil amino sugars content compared with the wheat–corn rotation in two soil types (Figure 4), particularly the GluN content (Figure 4c). However, there was no significant difference in MurA content among wheat–corn rotation, alfalfa, and switchgrass systems in saline–alkali soil (Figure 4b).
In non-saline soils, alfalfa and switchgrass significantly enhanced the relative contribution of lignin phenols and amino sugars to SOC compared with the wheat–corn system (specifically through an increase in GluN). Conversely, in saline–alkali soils, these two cropping systems decreased the contribution of lignin phenols and MurA to SOC (Figure 5). Both alfalfa and switchgrass cultivation decreased the ratio of amino sugars to lignin phenols in non-saline soils, but increased it in saline–alkali soils (Figure S2).

3.3. Relationships Between Soil Properties and Organic C Components

Correlation analysis showed that most of the soil properties were closely related to lignin phenols and amino sugars (Figure 6). The relative importance of abiotic (chemical properties) and biotic (enzyme activities) factors on lignin phenols and amino sugars were estimated using a random forest model. For alfalfa cultivated in non-saline soils, C/P, N/P, TN and NAG were significant predictors of the increase in lignin phenols and amino sugars. The main drivers of lignin phenols and amino sugars accumulation in switchgrass cultivation soils were NAG, C/P, PPO, and PER (Figure 6).
In saline–alkali soils, the accumulation of amino sugars was predominantly predicted by BG, C/P, and C/N in alfalfa cultivation soils, whereas in switchgrass soils, it was mainly associated with N/P, C/P, and BG (Figure 6).

4. Discussion

4.1. The Influence of Cropland-to-Grassland Conversion on Plant-Derived C

Our study revealed a divergence in the accumulation of plant-derived C (lignin phenols) between non-saline and saline–alkali soils following cropland-to-grassland conversion. In non-saline soils, compared to the wheat–corn rotation, the cultivation of alfalfa and switchgrass markedly increased lignin phenols content. Microbial metabolic activity, particularly through the action of extracellular enzyme activity (Figure 6), appeared to mediate lignin phenols accumulation [17]. The observed positive correlation between NAG or PPO and lignin phenols suggested stimulated microbial catabolism, presumably driven by sustained plant C input under alfalfa and switchgrass cultivation [8,28]. Additionally, the perennial nature of alfalfa and switchgrass cultivation substantially minimized soil disturbance relative to annual cropping systems, leading to reduced rates of lignin phenols decomposition and oxidation [29,30]. This protective effect was quantitatively demonstrated by lower (Ad/Al)S and (Ad/Al)V ratios (Figure 3), indicating enhanced preservation of lignin phenols [31].
In saline–alkali soils, lignin phenols accumulation decreased under alfalfa cultivation compared to the wheat–corn rotation, whereas switchgrass had no significant effect. This reduction in the alfalfa system can be attributed to two key factors: first, the constrained growth of alfalfa (Table S2) led to lower plant C input relative to the wheat–corn system with wheat straw return; and second, the adverse edaphic conditions suppressed microbial metabolic activity [32,33,34,35,36]. In contrast to alfalfa, switchgrass exhibited superior salt tolerance [37]. Although its biomass in saline–alkali soil was lower than in non-saline–alkali soil, the difference was not significant (Table S3). This ability to maintain relatively stable biomass ultimately explained the stable lignin phenols content observed under saline–alkali conditions compared to the wheat–corn rotation.

4.2. The Influence of Cropland-to-Grassland Conversion on Microbial-Derived C

Our research demonstrated that the cultivation of both alfalfa and switchgrass elevated the levels of microbial-derived C (amino sugars) in non-saline and saline–alkali soils. The perennial growth habit of alfalfa and switchgrass facilitated a continuous and stable input of photosynthetic C via root-derived processes [38]. Unlike systems that depended mainly on the decomposition of aboveground crop residues (e.g., wheat–corn rotations), this sustained C flow more effectively promoted the formation of stable soil organic carbon, particularly microbial-derived C [39,40]. In addition, alfalfa and switchgrass systems reduced soil disturbance by eliminating frequent tillage, thereby minimizing SOC mineralization and microbial-derived C persistence [41,42].
However, the composition of microbial-derived C varied substantially across different soil types. In non-saline soils, alfalfa and switchgrass cultivation simultaneously increased both bacterial-derived C (MurA) and fungal-derived C (GluN), whereas in saline–alkali soils, only fungal-derived C showed a significant increase. The mechanisms underlying this divergence were closely related to soil characteristics. In non-saline soils, the increased C- and N- acquiring enzyme activities (Figure 6)—direct indicators of microbial metabolic activity—drove the co-accumulation of bacterial and fungal residues [17]. In addition, soil chemical properties (e.g., C/P, C/N) directly or indirectly regulated the C accumulation process through their effects on organo-mineral interactions and microbial activities [43]. In contrast, the unique environment of saline–alkali soils inhibited bacterial growth, while this selective pressure promoted the development of more tolerant fungal communities [44,45], ultimately leading to a fungal-dominated residue accumulation pattern [46,47].
Notably, higher-quality (low C/N) plant litter facilitated the accumulation of microbial-derived C [48,49]. However, we found that alfalfa and switchgrass had a comparable effect, universally increasing the content of microbial-derived C (amino sugars) in both saline–alkali and non-saline–alkali soils. This indicated that the accumulation of microbial-derived C following the conversion of croplands to grasslands depended on litter quantity rather than litter quality. Research indicates that the influence of plant litter quality on the composition and stability of SOC was short-lived [50]. This transient influence thus led to the lack of a difference in amino sugars content between switchgrass and alfalfa observed in this study.

4.3. The Contributions of Plant- and Microbial-Derived C to SOC

Under alfalfa and switchgrass cultivation, both plant- and microbial-derived C increased with SOC in non-saline soils, whereas plant- and bacterial-derived C decreased with SOC in saline–alkali soils (Figure 5). Alfalfa and switchgrass, as perennial crops, continuously supplied abundant C and N sources to soil microorganisms (Table 1). Under suitable environmental conditions, such as in non-saline–alkali soils, these nutrients significantly enhanced microbial proliferation and metabolic activity. Through the dual mechanisms of the “Microbial Carbon Pump” (MCP)—facilitating the rapid transformation of plant residues while promoting the conversion of microbial necromass into stable organic carbon—the active microbial community effectively established long-term stable pools of both plant- and microbial-derived C [8]. However, the unique environment of saline–alkali soils not only inhibited the normal growth of plants but also significantly restricted the proliferation and activity of microorganisms, particularly bacteria. These stressful conditions led to a notable reduction in the production and accumulation of lignin phenols and bacterial-derived C, thereby diminishing their contribution to the SOC pool.
Notably, our findings reveal that alfalfa and switchgrass cultivation increased the ratio of amino sugars to lignin phenols in saline–alkali soils (Figure S2). This suggested that amino sugars (particularly GluN) played a crucial role in facilitating the accumulation of SOC under such conditions. In addition, we found a significant positive correlation between SOC and amino sugars in both non-saline and saline–alkali soils (Figure 6), indicating that the “MCP” pathway played a pivotal role in SOC formation under alfalfa and switchgrass cultivation. Microbial-derived C may be more stable and persistent than plant-derived C, as it is more readily protected by soil minerals [51,52].

5. Conclusions

Converting wheat–corn rotations to perennial grasslands (alfalfa and switchgrass) consistently increased total SOC in both non-saline and saline–alkali soils, but differentially influenced its composition. In non-saline soils, both plant- (lignin phenols) and microbial-derived (amino sugars) C components increased, suggesting synergistic plant-microbial enhancement. In saline–alkali soils, however, only fungal-derived C accumulated, likely due to the suppressive effects of salinity on bacterial activity. Our findings reveal distinct C sequestration mechanisms governed by soil type, highlighting the vital role of microbial-derived C in SOC accumulation following the conversion of cropland to grassland.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agriculture15222393/s1, Figure S1: The locations of two different study sites in Shandong Province; Table S1: The substrates of soil enzymes; Table S2: The aboveground dry biomass (t/hm2) of alfalfa in Jinan and Dongying in 2019; Table S3: The aboveground dry biomass (t/hm2) of switchgrass in Jinan and Dongying in 2020; Figure S2: The ratio of amino sugars (including MurA and GluN) to lignin phenols in different cropping systems across two soil types.

Author Contributions

J.Z. (Jinglei Zhang) and G.W. contributed to the writing of the original draft. S.B., C.J., L.K., Y.Z., C.G., J.Z. (Jinhong Zhang), D.H.B. and B.W. were responsible for conducting the experimental operations. G.W. was responsible for the review and editing of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was jointly supported and funded by the National Natural Science Foundation of China (32503284), Earmarked Fund for CARS (CARS-34), Key R&D Program of Shandong Province, China (2024SFGC0403, 2023LZGCQY022), Shandong Province Base and Talent Program (WSR2023050), and Science Research Project of Hebei Education Department (BJ2025095).

Data Availability Statement

The original contributions presented in this study are included in the article; further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
SOCSoil organic carbon.
MurAMuramic acid.
GluNGlucosamine

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Agriculture 15 02393 g001
Figure 1. The activities of soil enzymes in different cropping systems across two soil types. Jinan and Dongying represent non-saline and saline–alkali soil, respectively. (a) polyphenol oxidase; (b) peroxidase; (c) β-1,4-glucosidase; (d) acid phosphatase; (e) leucine–aminopeptidase; (f) N-acetyl-β-D-glucosaminidase. ** p < 0.01.
Figure 1. The activities of soil enzymes in different cropping systems across two soil types. Jinan and Dongying represent non-saline and saline–alkali soil, respectively. (a) polyphenol oxidase; (b) peroxidase; (c) β-1,4-glucosidase; (d) acid phosphatase; (e) leucine–aminopeptidase; (f) N-acetyl-β-D-glucosaminidase. ** p < 0.01.
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Figure 2. The contents of soil lignin phenols in different cropping systems across two soil types. V, S, and C represent the vanillyl, syringyl, and cinnamyl, respectively. (a) lignin phenols; (b) V phenols; (c) S phenols; (d) C phenols. * p < 0.05, ** p < 0.01.
Figure 2. The contents of soil lignin phenols in different cropping systems across two soil types. V, S, and C represent the vanillyl, syringyl, and cinnamyl, respectively. (a) lignin phenols; (b) V phenols; (c) S phenols; (d) C phenols. * p < 0.05, ** p < 0.01.
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Figure 3. The (a) acid-to-aldehyde ratio of syringyl phenols, (Ad/Al)S; (b) the acid-to-aldehyde ratio of vanillyl phenols, (Ad/Al)V in different cropping systems across two soil types. * p < 0.05, ** p < 0.01.
Figure 3. The (a) acid-to-aldehyde ratio of syringyl phenols, (Ad/Al)S; (b) the acid-to-aldehyde ratio of vanillyl phenols, (Ad/Al)V in different cropping systems across two soil types. * p < 0.05, ** p < 0.01.
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Figure 4. The content of soil amino sugars in different cropping systems across two soil types. MurA and GluN represent muramic acid and glucosamine, respectively. (a) amino sugars; (b) MurA; (c) GluN. * p < 0.05, ** p < 0.01.
Figure 4. The content of soil amino sugars in different cropping systems across two soil types. MurA and GluN represent muramic acid and glucosamine, respectively. (a) amino sugars; (b) MurA; (c) GluN. * p < 0.05, ** p < 0.01.
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Figure 5. The relative contribution of lignin phenols and amino sugars to SOC in different crop systems across two soil types. (a) lignin phenols/ SOC; (b) amino sugars /SOC; (c) MurA/SOC; (d) GluN/SOC. * p < 0.05, ** p < 0.01.
Figure 5. The relative contribution of lignin phenols and amino sugars to SOC in different crop systems across two soil types. (a) lignin phenols/ SOC; (b) amino sugars /SOC; (c) MurA/SOC; (d) GluN/SOC. * p < 0.05, ** p < 0.01.
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Figure 6. Relative importance (percentage of increase of the mean square error, MSE) of soil properties for predicting the lignin phenols and amino sugars from random forest analysis combined with Spearman correlations. * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 6. Relative importance (percentage of increase of the mean square error, MSE) of soil properties for predicting the lignin phenols and amino sugars from random forest analysis combined with Spearman correlations. * p < 0.05, ** p < 0.01, *** p < 0.001.
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Table 1. The effect of alfalfa cultivation on soil properties in two different soil types.
Table 1. The effect of alfalfa cultivation on soil properties in two different soil types.
Study SitesCropsSOC (g/kg)TN (g/kg)TP (g/kg)pHEC (µs/cm)
JinanWheat–corn11.30 ± 0.76 b1.17 ± 0.03 b1.27 ± 0.03 a8.38 ± 0.06117.32 ± 5.94
Alfalfa17.62 ± 0.64 a1.92 ± 0.11 a1.16 ± 0.04 b8.27 ± 0.05118.02 ± 2.50
Switchgrass20.08 ± 1.65 a1.39 ± 0.18 b1.01 ± 0.06 b8.42 ± 0.01127.90 ± 5.66
DongyingWheat–corn11.17 ± 0.96 b1.38 ± 0.131.26 ±0.07 a8.48 ± 0.02154.10 ± 12.59
Alfalfa16.36 ± 1.30 a1.62 ± 0.100.99 ± 0.04 b8.42 ± 0.05138.14 ± 7.53
Switchgrass15.82 ± 1.54 a1.35 ± 0.101.08 ± 0.03 b8.56 ± 0.08129.0 ± 64.44
Notes: Jinan and Dongying represent non-saline and saline–alkali soil, respectively; different lowercase letters indicate significant differences among different cropping systems. Values = mean ± SEM (n = 5). The same applies below.
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MDPI and ACS Style

Zhang, J.; Bai, S.; Jia, C.; Kang, L.; Zhang, Y.; Guan, C.; Zhang, J.; Basigalup, D.H.; Wu, B.; Wang, G. Differential Soil Organic Carbon Accumulation Patterns Following Cropland-to-Grassland Conversion in Non-Saline and Saline–Alkali Soils. Agriculture 2025, 15, 2393. https://doi.org/10.3390/agriculture15222393

AMA Style

Zhang J, Bai S, Jia C, Kang L, Zhang Y, Guan C, Zhang J, Basigalup DH, Wu B, Wang G. Differential Soil Organic Carbon Accumulation Patterns Following Cropland-to-Grassland Conversion in Non-Saline and Saline–Alkali Soils. Agriculture. 2025; 15(22):2393. https://doi.org/10.3390/agriculture15222393

Chicago/Turabian Style

Zhang, Jinglei, Shanshan Bai, Chunlin Jia, Lele Kang, Yuxue Zhang, Cong Guan, Jinhong Zhang, Daniel Horacio Basigalup, Bo Wu, and Guoliang Wang. 2025. "Differential Soil Organic Carbon Accumulation Patterns Following Cropland-to-Grassland Conversion in Non-Saline and Saline–Alkali Soils" Agriculture 15, no. 22: 2393. https://doi.org/10.3390/agriculture15222393

APA Style

Zhang, J., Bai, S., Jia, C., Kang, L., Zhang, Y., Guan, C., Zhang, J., Basigalup, D. H., Wu, B., & Wang, G. (2025). Differential Soil Organic Carbon Accumulation Patterns Following Cropland-to-Grassland Conversion in Non-Saline and Saline–Alkali Soils. Agriculture, 15(22), 2393. https://doi.org/10.3390/agriculture15222393

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