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We employed four Medicago sativa varieties (Aurora, Sanditi, Eureka+, Sardi), Lolium multiflorum, and three Brassica campestris varieties (Huayouza 82, Huayouza 158, Huayouza 62) in our experiment. The Medicago sativa and Lolium multiflorum seeds were provided by Zhengzhou kaiyuan Grass Industry Technology Co., Ltd (China), and Brassica campestris seeds were provided by Zhengzhou Huafeng Grass Industry Technology Co., Ltd (China), with all germination rate > 85%.
Field site description
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Our field experiment was carried out in Tiaozini, Dongtai, Jiangsu Province, China (32°51' N, 120°56' E). This region is a transition zone between subtropical and warm temperate zone with distinct seasons. The average annual temperature in this area is 15 °C, with the coldest month being January (mean monthly temperature 0.8 °C). July is the hottest month with an average monthly temperature of 27 °C. The average annual rainfall is 1,061 mm. The annual rainfall from June to September accounts for 63% of the whole year. The soil properties were as follows: pH 8.20, salt content 1.83 ‰, soil organic matter 7.92 g·kg−1, total N 0.48 g·kg−1, total P 0.65 g·kg−1, total K 18.76 g·kg−1, soil available N 45.92 mg·kg−1, available P 18.31 mg·kg−1, available K 187.07 mg·kg−1, Ca2+ content 41.84 g·kg−1, Mg2+ content 13.64 g·kg−1.
Experimental design
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The field experiment, with a random design, included eight green manure varieties. We defined each variety as a treatment and a non-cultivation as control (CK). Each treatment had three replicates (plots), and the size of each plot was 2 m × 2 m. The cultivation was performed in late October, 2021. The sowing density of Medicago sativa, Lolium multiflorum and Brassica campestris was 2.5 g·m−2, 2.5 g·m−2 and 1 g·m−2, respectively. The sowing depth was 3 cm and row spacing was 25 cm. No fertilization was applied during the growth of green manure. Irrigation and weeding were the same as in routine management.
Collection of aboveground and soil samples
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The green manure biomass was recorded at harvest (May 5, 2022). We took random subplots (0.5 × 0.5 m) within each plot and destructively harvested, and the shoots were cut at the soil surface. At the same time, we collected soil samples. Five cores (5 cm diameter and 0−15 cm depth), on the rows, were randomly sampled and sufficiently mixed to yield one representative sample. After sampling, the rest of the green manure in each plot were crushed and returned to the field with the returning depth of 20 cm. Thirty days later, soil samples were collected as previously. All collected soil samples (54 samples in total: 9 treatments × 3 replications × 2) were sieved (2.0 mm mesh) and homogenized for soil physicochemical property analysis.
Determination of aboveground samples
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The collected green manure aboveground samples were oven dried at 65 °C for 72 h to a constant weight before weighing. The shoot dry weights were expressed as total aboveground biomass per m2. Then the dry shoots were ground through 20 mesh in a Wiley mill. The prepared aboveground samples were measured by an Elementar Analyzer (Vario EL III, Germany) for total carbon (C).
Determination of soil physicochemical properties and soil fertility evaluation
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Soil pH was determined with soil-water slurry (1:5, w/v) by a PB-10 pH meter (Sartorius, Germany). Soil electrical conductivity (EC) was measured by a conductivity meter (B-173; HORIBA, Kyoto, Japan). Soil organic C (SOC) was measured by an Elementar Analyzer (Vario EL III, Germany). The total N was determined using a Kjeltec Analyser (FOSS Tecator, Hoganas, Sweden). The determination of soil available nitrogen (N) was measured according to Shi[34]. The soil fertility evaluation was calculated according to previously described methods[35, 36].
Statistical analyses
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The data in our study were log-transformed when necessary to meet the criteria for a normal distribution. We employed SPSS 22.0 (IBM, Armonk, NY, USA) software for statistical analysis of all parameters. The data from each treatment were analyzed using one-way analysis of variance (ANOVA), and Duncan’s multiple range tests (P < 0.05) were performed for multiple comparisons. The Mann-Whitney U test method was used to test soil fertility index differences between non-cultivation and cultivation groups after returning to the field.
For soil fertility evaluation, we employed five soil fertility evaluation parameters, including pH, EC, SOM, TN and AN. Then we chose appropriate function curves and turning points to determine values of each soil fertility parameter, according to our data characteristics. The 'optimum' curve equation is employed for pH and EC, while the 'more is better' curve equation is used for SOM, TN and AN[33, 35, 36]. The equation for the scoring curve as follows:
(a) The 'optimum' curve equation:
$ f(x)=\left\{\begin{array}{ll} 0.1 & x \leqslant L, x \geqslant U \\ 0.1+0.9(x-L) /\left(O_{1}-L\right) & L \lt x \lt O_{1} \\ 1.0 & O_{1} \leqslant x \leqslant O_{2} \\ 1.0-0.9\left(x-O_{2}\right) /\left(U-O_{2}\right) & O_{2} \lt x \lt U \end{array}\right. $ (b) The 'more is better' curve equation:
$ f(x)=\left\{\begin{array}{ll} 1.0 & x \geqslant U \\ 0.1+0.9(x-L) /(U-L) & L \lt x \lt U \\ 0.1 & x \leqslant L \end{array}\right. $ where x is the monitoring value of the parameter; f(x) is the score of the parameters ranging between 0.1 and 1.0; U and L are the upper and the lower threshold values of the parameters, respectively. O1 and O2 are the best values of the variables.
We employed partial least squares path modeling (PLS-PM), based on 'plspm' (1000 bootstraps) package in R software (v.4.0.0), to determine the complex multivariable relationships among green manure varieties, edaphic variables, plant C content, biomass and soil fertility. Then we tested the model architectures from simple to complex (direct and indirect links, previous effects)[37]. Based on the determination coefficient (R2) of the explained latent variables and goodness of fit (GoF), we selected the corresponding architecture.
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There were significant (P < 0.05) differences among Medicago sativa, Lolium multiflorum and Brassica campestris cultivation treatments for biomass at harvest (Fig. 1). In total, the largest green manure biomass was observed in Lolium multiflorum cultivation treatment (895.11 g·m−2). Lolium multiflorum cultivation treatment increased the biomass by 2.48 and 0.79 times compared with Medicago sativa and Brassica campestris cultivation treatments, respectively. Additionally, we found significant (P < 0.05) differences among the varieties of each green manure. For Medicago sativa, the biomass of Eureka+ was significantly (P < 0.05) increased by 10.38%, 8.29% and 14.88%, compared with that of Aurora, Sanditi, Sardi, respectively. For the biomass of Brassica campestris, there was no significant difference between Huayouza 82 and Huayouza 158, while they were both significantly (P < 0.05) higher than that of Huayouza 62, with increasing by 60.66% and 71.29%, respectively.
Figure 1.
The green manure biomass of different varieties cultivation at harvest in saline alkali soil field experiment. 'M1, M2, M3 and M4' represent Aurora, Sanditi, Eureka+, Sardi, respectively, which all belong to Medicago sativa. 'L' refers to Lolium multiflorum. 'B1, B2 and B3' represent Huayouza 82, Huayouza 158, Huayouza 62, respectively, which all belong to Brassica campestris. One-way analysis of variance (ANOVA) was used to assess the differences among treatments. Bars represent the mean values of three replicates ± SD. Values that do not share the same lower case letter are significantly different (P < 0.05) among green manure varieties. Values that do not share the same uppercase letter are significantly different (P < 0.05) at different green manure species (Medicago sativa, Lolium multiflorum, Brassica campestris). *** refers to P < 0.001.
Green manure carbon sequestration of different varieties cultivation
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The carbon content was lowest in Medicago sativa cultivation treatment (401.58 g·kg−1), however, no significant difference was observed among Medicago sativa, Lolium multiflorum and Brassica campestris cultivation treatments (Fig. 2a). For Medicago sativa, the carbon content of Aurora (364.25 g kg−1) was significantly (P < 0.05) lower than that of Eureka+. For Brassica campestris, the carbon content of Huayouza 82 was significantly (P < 0.05) higher than that of Huayouza 158 and Huayouza 62 by 12.55% and 12.09%, respectively. In addition, different green manure cultivation led to a significant (P < 0.05) difference in aboveground carbon store (Fig. 2b). The carbon store in Lolium multiflorum cultivation (400.58 g·m−2) was significantly (P < 0.05) higher than that of Medicago sativa and Brassica campestris cultivation treatments by 2.87 and 0.91 times, respectively. For Medicago sativa, the carbon store of Eureka+ was significantly (P < 0.05) higher by 33.88%, 25.71% and 20.36% than that of Aurora, Sanditi and Sardi, respectively. Additionally, for Brassica campestris, the carbon store of Huayouza 62 (139.41 g·m−2) was largely significantly (P < 0.05) lower than that of Huayouza 82 (251.31 g·m−2) and Huayouza 158 (237.78 g·m−2), respectively.
Figure 2.
(a) Carbon content and (b) carbon store of different varieties cultivated at harvest in saline alkali soil field experiment. 'M1, M2, M3 and M4' represent Aurora, Sanditi, Eureka+, Sardi, respectively, which all belong to Medicago sativa. 'L' refers to Lolium multiflorum. 'B1, B2 and B3' represent Huayouza 82, Huayouza 158, Huayouza 62, respectively, which all belong to Brassica campestris. One-way analysis of variance (ANOVA) was used to assess the differences among treatments. Bars represent the mean values of three replicates ± SD. Values that do not share the same lower case letter are significantly different (P < 0.05) among green manure varieties. Values that do not share the same uppercase letter are significantly different (P < 0.05) at different green manure species (Medicago sativa, Lolium multiflorum, Brassica campestris). * refers to P < 0.05; ** refers to P < 0.01; *** refers to P < 0.001.
Soil physicochemical properties in different cultivation treatment at green manure harvest
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The green manure cultivation generated significantly different physicochemical properties in saline alkali soil (Table 1, Supplemental Table S1). The cultivation of Medicago sativa (Aurora, Sanditi, Eureka+) and Lolium multiflorum resulted in a significant (P < 0.05) lower pH by 6.32%, 3.67%, 1.69% and 4.03% than that of CK. Moreover, compared with CK, the EC in Medicago sativa (except for Sanditi) and Brassica campestris were also significantly (P < 0.05) declined. For soil organic matter, only Eureka+ and Huayouza 62 were significantly (P < 0.05) higher than that of CK. Additionally, soil total N in Sardi and Huayouza 62 were significantly (P < 0.05) lower than that of CK. For available N, Aurora, Sanditi, Sardi and Lolium multiflorum were significantly (P < 0.05) higher by 33.08%, 27.53%, 29.70%, 38.49%, when compared with CK.
Table 1. Soil properties measured under different treatment at green manure harvest in saline alkali soil field experiment.
Green manure cultivation Treatment pH EC
(us·cm−1)Soil organic matter
(g·kg−1)Total N
(g·kg−1)Available N
(mg·kg−1)No-cultivation CK 9.04 ± 0.16abc 496.33 ± 19.50b 5.27 ± 0.14bc 0.58 ± 0.05abc 38.76 ± 2.03bc Medicago sativa M1 8.50 ± 0.13f 429.00 ± 26.21cd 4.41 ± 0.78c 0.58 ± 0.01ab 51.58 ± 2.66a M2 8.72 ± 0.02e 470.33 ± 13.32bc 5.11 ± 0.42bc 0.54 ± 0.01cd 49.43 ± 4.35a M3 8.89 ± 0.03d 356.67 ± 6.43ef 5.63 ± 0.66a 0.54 ± 0.02bcd 41.89 ± 4.57b M4 8.93 ± 0.03cd 391.00 ± 4.36de 4.33 ± 0.24c 0.53 ± 0.02d 50.27 ± 1.61a Lolium multiflorum L 8.69 ± 0.04e 567.67 ± 52.88a 5.33 ± 0.46bc 0.60 ± 0.01a 53.68 ± 3.79a Brassica campestris B1 9.02 ± 0.04bc 363.00 ± 26.91ef 5.13 ± 0.11bc 0.51 ± 0.01de 37.53 ± 3.16bc B2 9.11 ± 0.02ab 330.67 ± 12.66f 5.07 ± 1.32bc 0.51 ± 0.02de 38.87 ± 2.33bc B3 9.17 ± 0.01a 328.00 ± 28.69f 6.00 ± 0.21a 0.49 ± 0.01e 34.97 ± 5.50c CK: no cultivation. 'M1, M2, M3 and M4' represent Aurora, Sanditi, Eureka+, Sardi, respectively, which all belong to Medicago sativa. 'L' refers to Lolium multiflorum. 'B1, B2 and B3' represent Huayouza 82, Huayouza 158, Huayouza 62, respectively, which all belong to Brassica campestris. Data are the mean values of three replicates. Numbers followed by '±' are the standard deviations (SDs). Within a column, values that do not share the same letter are significantly different (P < 0.05). Variation of soil physicochemical properties in different treatment after green manure returning to field for 30 days
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The soil properties were measured after green manure was returned to the saline alkali soil field for 30 d. In general, the soil properties after green manure return (Table 2, Supplemental Table S2) were generally improved when compared with previous (Table 1). The returning of Medicago sativa (only Sardi), Lolium multiflorum and Brassica campestris (Huayouza 82, Huayouza 158, Huayouza 62) had significant (P < 0.05) reduction effects on soil pH, which reduced by 2.04%, 8.30%, 4.90%, 4.77% and 4.17%, respectively, when compared to no-returning (CK). Moreover, as compared with CK, only returning of Sanditi and Eureka+ significantly (P < 0.05) decreased soil EC content. In addition, the green manure return led to significant (P < 0.05) improvement on soil organic matter. Similarly, significant (P < 0.05) promoting effects on soil total N were also observed, expect for Sanditi, as compared to CK. The soil available N in Sardi, Lolium multiflorum, and Brassica campestris (Huayouza 82) were significantly (P < 0.05) increased by 30.55%, 57.24%, 23.22% than that of CK.
Table 2. Soil properties measured under different treatment after green manure return to saline alkali soil field for 30 d.
Green manure return Treatment pH EC
(us·cm−1)Soil organic matter
(g·kg−1)Total N
(g·kg−1)Available N
(mg·kg−1)No-returning CK 9.00 ± 0.14ab 591.00 ± 56.45bcd 5.84 ± 0.74b 0.52 ± 0.01c 39.80 ± 1.88d Medicago sativa M1 8.89 ± 0.07bc 536.33 ± 32.59d 7.92 ± 1.24a 0.60 ± 0.01b 41.99 ± 4.37cd M2 9.11 ± 0.03a 407.33 ± 43.25e 8.55 ± 0.80a 0.54 ± 0.05c 45.70 ± 4.68bcd M3 9.00 ± 0.02ab 438.33 ± 49.08e 8.36 ± 0.59a 0.60 ± 0.02b 47.24 ± 4.26bcd M4 8.82 ± 0.02c 549.67 ± 15.28cd 7.76 ± 0.55a 0.63 ± 0.02b 51.96 ± 1.87b Lolium multiflorum L 8.31 ± 0.12e 519.00 ± 14.53d 7.72 ± 0.88a 0.71 ± 0.02a 62.58 ± 5.98a Brassica campestris B1 8.58 ± 0.05d 621.67 ± 5.13bc 7.75 ± 0.44a 0.62 ± 0.02b 49.04 ± 8.57bc B2 8.59 ± 0.07d 701.33 ± 71.44a 7.30 ± 0.46a 0.61 ± 0.01b 42.43 ± 3.22cd B3 8.64 ± 0.01d 627.67 ± 35.53b 7.61 ± 0.28a 0.68 ± 0.03a 48.57 ± 3.73bcd CK: no cultivation. 'M1, M2, M3 and M4' represent Aurora, Sanditi, Eureka+, Sardi, respectively, which all belong to Medicago sativa. 'L' refers to Lolium multiflorum. 'B1, B2 and B3' represent Huayouza 82, Huayouza 158, Huayouza 62, respectively, which all belong to Brassica campestris. Data are the mean values of three replicates. Numbers followed by '±' are the standard deviations (SDs). Within a column, values that do not share the same letter are significantly different (P < 0.05). Effects of different returning treatment to improve soil quality in saline alkali field experiment
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The descriptions of detailed scoring function values and weights assigned to the selected soil fertility parameters are available in Table 3. The weights of pH, EC, soil organic matter, total N and available N were 0.25, 0.23. 0.07, 0.23 and 0.22, respectively. Based on these, the soil fertility index in each returning treatment was calculated. As shown in Fig. 3, we observed significant (P < 0.001) difference between the non-cultivation and cultivation group. In the cultivation group, returning Lolium multiflorum to the field had the best soil fertility enhancing effect (0.56), which significantly (P < 0.05) improved soil fertility by 55.56% and 33.33% compared with Medicago sativa and Brassica campestris. For Medicago sativa, the soil fertility index of Sardi was significantly (P < 0.05) higher than that of the other three varieties. However, there was no significant difference among Brassica campestris varieties.
Table 3. Scoring function values and weights assigned to selected soil fertility parameters.
pH (H2O) EC
(us·cm−1)Soil organic matter
(SOM, g·kg−1)Total nitrogen
(TN, g·kg−1)Available nitrogen
(AN, mg·kg−1)Scoring curve# a a b b b Turning point U 9 1,500 15 1.2 120 L 6.0 100 5 0.5 30 O1 6.5 300 O2 8 400 weight 0.25 0.23 0.07 0.23 0.22 'a' Refers to the 'optimum' curve equation; 'b' refers to the 'more is better' curve equation. Figure 3.
Soil fertility index of different treatment that returning to the field in saline alkali soil experiment. One-way analysis of variance (ANOVA) was used to assess the differences among treatments. Bars represent the mean values of three replicates ± SD. Values that do not share the same lower case letter are significantly different (P < 0.05) among green manure varieties. Values that do not share the same uppercase letter are significantly different (P < 0.05) at different green manure species (Medicago sativa, Lolium multiflorum, Brassica campestris). ** refers to P < 0.01; *** refers to P < 0.001.
Contributions of green manure varieties, soil physicochemical properties, plant C, green manure biomass on soil fertility improvement
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PLS-PM analysis was employed to identify direct and indirect effects of different green manure cultivation and returning to the field on saline alkali soil fertility improvement (Fig. 4a). Green manure varieties significantly (P < 0.05) positively affected biomass (0.76 of the direct effects) and then positively (P < 0.001) affected soil fertility (0.72). Similarly, green manure varieties significantly (P < 0.001) positively affected slow-changing soil properties (0.78), then positively (P < 0.05) affected plant C (0.81), followed with affecting biomass (0.55), and finally affected soil fertility. Furthermore, we observed fast-changing soil properties could significantly (P < 0.01) and directly affect biomass (0.91), while slow-changing soil properties had no significant effect on biomass.
Figure 4.
Cascading relationships of soil fertility with green manure and soil physicochemical properties. (a) Partial least squares path modelling (PLS-PM) disentangling major pathways of the influences of green manure varieties, soil physicochemical properties, plant C, green manure biomass on soil fertility. Red and blue arrows indicate positive and negative flows of causality, respectively. Solid and dashed lines indicate significant (*, P < 0.05; **, P < 0.01; ***, P < 0.001) and nonsignificant (P > 0.05) levels, respectively. Values on arrows indicate significant standardized path coefficients. R2 indicates the variance of dependent variable explained by the model. (b) Total effects of soil fertility in the PLSPM models for green manure varieties, fast-changing soil properties, slow-changing soil properties, plant C, and green manure biomass.
Overall, we found that all variates (green manure varieties, slow-changing soil properties, fast-changing soil properties, plant C and biomass) had positive impacts on soil fertility improvement. Among these, both fast-changing soil properties and biomass exhibited the greatest positive impacts (0.72 of the total effects). In addition, the total effects of fast-changing soil properties (0.552) was greater than slow-changing soil properties (0.55). Plant C also largely contribute to saline alkali soil fertility improvement (0.60). Green manure varieties had the lowest but also positive impact (0.07) (Fig. 4b).
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We employed different green manure variates to measure the effects of cultivation for aboveground carbon sequestration and returning to the field to ameliorate soil quality in saline alkali soil, based on a field experiment. We determined that plant carbon store was positively correlated with aboveground biomass. Green manure varieties, slow-changing soil properties, fast-changing soil properties, plant C and biomass all contributed to soil fertility improvement after aboveground returning to the field. The biomass production was a determining factor contributing to soil fertility, and variety with higher biomass production would more effectively improve soil quality in saline alkali soil. Our study can provide crucial theoretical support and a feasible way for green and sustainable development of saline-alkali agriculture.
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About this article
Cite this article
Zhang F, Han Y, Shang H, Ding Y. 2023. Effects of green manure cultivation for aboveground carbon store and returning to the field to ameliorate soil quality in saline alkali soil. Grass Research 3:1 doi: 10.48130/GR-2023-0001
Effects of green manure cultivation for aboveground carbon store and returning to the field to ameliorate soil quality in saline alkali soil
- Received: 15 November 2022
- Accepted: 27 December 2022
- Published online: 18 January 2023
Abstract: The utilization of saline-alkali land together with the consideration of the productive value (improving soil productivity) and ecological value (increasing carbon store ability) has rarely been reported. We conducted a field experiment to investigate the impact of green manure cultivation for aboveground carbon (C) store and then returning this to field to improve soil quality in saline alkali soil. The biomass in Lolium multiflorum cultivation treatment was significantly (P < 0.05) higher than that of Medicago sativa and Brassica campestris cultivation. A similar tendency was observed in aboveground C store. Green manure cultivation resulted in largely different physicochemical properties at time of harvest. Returning the green manure to the field could significantly (P < 0.001) improve soil fertility. Moreover, the soil fertility index of Lolium multiflorum treatment was significantly (P < 0.05) enhanced by 55.56% and 33.33%, as compared with Medicago sativa and Brassica campestris treatments. Based on PLS-PM analysis, both fast-changing soil properties and biomass exhibited the greatest positive impacts (0.72 of the total effects) on soil fertility improvement after aboveground returning to the field. Our research provides evidence that Lolium multiflorum is the best potential variety to improve saline alkali soil fertility. Additionally, green manure cultivation in saline-alkali soil is an important way to store carbon in plants, then returning to the field is a feasible approach to improve saline alkali soil quality, which is beneficial for the green and sustainable development of saline-alkali agriculture.