3.1 Influence of Different Treatments on Soybean Agronomic Traits and Yield
Based on Table 1, it can be observed that compared to sole fertilization, the addition of a composite microbial agent along with rhizobia significantly enhances soybean plant height, primary root length, aboveground biomass, number of branches, number of pods, number of grains, and soybean yield. Sole addition of rhizobia significantly increases total root length, main stem segments, and root volume. However, the composite microbial agent notably increases leaf area at different stages of soybean growth, facilitating the formation of photosynthetic products in plants. Additionally, the application of microbial agents reduces the impact of weed growth on soybeans, resulting in a significant increase in plant production and yield-related indicators during the harvest period, thereby enhancing soybean yield.
Table 1
Agronomic traits and yield of soybean under different treatments
Treatments
|
Plant height
(cm/plant)
|
taproot length
(cm/plant)
|
total root length
(cm/plant)
|
root volume
(cm3/plant)
|
Above ground biomass(g/plant)
|
F
|
55.44bB
|
13.79bB
|
18.77bA
|
10.34bB
|
159.93cB
|
CF
|
62.39aA
|
14.98aA
|
18.00bB
|
9.77cC
|
170.94aA
|
RF
|
59.35aA
|
14.29bA
|
19.78aA
|
15.46aA
|
165.09bB
|
CRF
|
61.22aA
|
15.12aA
|
20.03aA
|
11.47bB
|
174.38aA
|
|
main stem segments(per/plant)
|
Number of branches(per/plant)
|
Number of pods(per/plant)
|
Number of grains(per/plant)
|
Soybean yield
|
F
|
49.5bA
|
0.62cB
|
40.5eC
|
54.7bB
|
3642.04dC
|
CF
|
41.5cB
|
0.59cC
|
40.9eC
|
52.8bB
|
4347.88bB
|
RF
|
57.8aA
|
0.66bA
|
52.5aA
|
59.0aA
|
4642.86aA
|
CRF
|
54.39aA
|
0.78aA
|
48.2bA
|
62.8aA
|
4109.26cB
|
Table.1
3.2 Influence of Different Treatments on Soil Physical and Chemical Properties and Nutrients
As shown in table 2, compared to the control group F, the soil pH (5.93–6.52), organic matter content, and moisture content all significantly increase as soybeans grow, regardless of the treatment. However, the increases in pH, organic matter, and moisture content are notably smaller in the CF and RF treatments compared to the corresponding CRF treatment. Sole fertilization and the CF treatment lead to a decrease in soil aggregate stability, while the CRF and RF treatments significantly increase soil aggregate stability. Compared to the control, all treatments result in a significant increase in soil available phosphorus (AP), available potassium (AK), and available nitrogen (AN), with the CRF treatments having higher levels than other treatments. During the growth process of soybeans, the AN content reaches 1.5 times that of the sole fertilization treatment F.
Table 2
Effects of different treatments on soil physicochemical properties and nutrient content
Index
|
Treatment group
|
Emergence stage
|
Branch stage
|
Flowering stage
|
Podding stage
|
Granulation stage
|
Muturation stage
|
pH
|
F
|
5.93aA
|
5.73aA
|
5.89aA
|
6.13bA
|
6.05bA
|
6.03aA
|
CF
|
6.22bB
|
6.09cC
|
6.33bB
|
6.25cB
|
6.14cC
|
6.38cB
|
RF
|
6.23cB
|
6.19bB
|
6.43bC
|
6.30aA
|
6.21cB
|
6.40cC
|
CRF
|
6.26cC
|
6.38dD
|
6.18bC
|
6.37dA
|
6.41dC
|
6.52dC
|
organic matter
(g/kg)
|
F
|
32.8aA
|
33.4aA
|
29.03aA
|
31.5aA
|
32.0aA
|
33.5aA
|
CF
|
33.6dC
|
34.67bB
|
37.2cB
|
36.5bB
|
39.3bB
|
41.0bB
|
RF
|
36.2dC
|
37.1cB
|
35.9dC
|
41.3bB
|
40bB
|
42.4cB
|
CRF
|
35.0cB
|
37.3cB
|
39.2dD
|
41.0cB
|
44cC
|
43.6dC
|
water content
|
F
|
15.9aA
|
16.3aA
|
15.3aA
|
16.4aA
|
17.1aA
|
16.5bA
|
CF
|
17.1cB
|
18.2cB
|
17.6cB
|
19.1bB
|
18.0cC
|
18.8cC
|
RF
|
21.2bA
|
20.9cC
|
19.7dC
|
21.1bB
|
20.2cB
|
22.4cA
|
CRF
|
22.3dC
|
22.1dC
|
23.2cC
|
20.7dD
|
23.6aA
|
24dC
|
water stable aggregates
|
F
|
35.6aA
|
33.4bB
|
29.2cB
|
31.7aA
|
28.8cC
|
27.7aA
|
CF
|
37.5cB
|
35.5cC
|
36.7bA
|
39aA
|
38.8dB
|
35bB
|
RF
|
33.5dC
|
36.7dC
|
35.9dD
|
39.8aA
|
41.0bB
|
39.8cC
|
CRF
|
34.2dD
|
33.5cB
|
38.9bB
|
38.7cB
|
39.8dC
|
43.0dD
|
Available phosphorus
|
F
|
14.7aA
|
15.6aA
|
17.1cB
|
16.4aA
|
15.7aA
|
18.2aA
|
CF
|
16.4dC
|
18.7cB
|
19.1aA
|
20dB
|
18.7cB
|
20.4cB
|
RF
|
15.4cB
|
16.8bB
|
17.2dC
|
19.6bB
|
18.8cB
|
21dC
|
CRF
|
17.8cB
|
21.9bB
|
20.4cB
|
21.3aA
|
22.4bB
|
21.9cB
|
Available potassium
|
F
|
143.2c
|
144.3bA
|
151.3aA
|
150.4aA
|
152.4aA
|
156aA
|
CF
|
166.0dC
|
159.4cC
|
162.5bB
|
169.3cC
|
171.6cB
|
170.9bB
|
RF
|
158.4bB
|
161.4dD
|
163.5bB
|
171.7bB
|
169.9bB
|
173.5bB
|
CRF
|
161.7dD
|
165.4dC
|
159.4cB
|
162.4bB
|
168.7cC
|
171.8dC
|
Alkaline Hydrolyzed Nitrogen
|
F
|
13.98aA
|
14.55cC
|
16.17aA
|
15.98aA
|
16.78aA
|
16.90bB
|
CF
|
12.67dC
|
14.05dC
|
16.78cC
|
15.57cB
|
18.98cB
|
17.87cC
|
RF
|
14.09cC
|
15.09aA
|
17.36cB
|
18.36dC
|
21.98dC
|
19.32dD
|
CRF
|
15.03dD
|
17.36cB
|
18.92bB
|
19.37dC
|
18.89cB
|
20.81cB
|
Table.2
3.3 Influence of Different Treatments on Soil Four Key Enzyme Activities
According to Fig. 1, as soybeans grow, the content of the four key enzymes varies in the order of CSF > RF > CF > F. Soil sucrase gradually increases with the growth and development of soybeans, with the highest content found in the CSF treatment, showing significant improvement over the control group that was solely fertilized. Urease shows relatively small changes during the growth and development process of soybeans, with the CSF treatment having significantly higher levels than other treatments during the branch stage and maturation stage. Peroxidase has the highest content in the CSF treatment during the emergence stage, showing significant differences from other treatments. Acid phosphatase has the highest content in the CSF treatment during the maturation stage, and the CSF treatment and the emergence stage CSF treatment show significant differences from other treatments.
Figure 1
3.4 Influence of Different Treatments on Soil microbial population
In this study, the influence of different treatments on soil microbial populations was investigated. The results (supplement Fig. 1) showed that in the CRF and RF treatments, the numbers of bacteria, actinomycetes, and fungi were significantly higher compared to the CF and F treatments. Specifically, in the CRF treatment, the bacterial population increased by 2.66 times compared to the F treatment, the fungal population increased by 1.36 times, and the actinomycete population increased by 1.53 times. This indicates that the use of composite microbial agents can promote an increase in soil microbial populations.
SF.1
3.5 Influence of different treatments on bacterial microbial community structure
3.5.1 Effect of different treatments on microbial diversity
The unique and shared operational taxonomic units (OTUs) of the four treatments at the location was determined via a Veen diagram (Fig. 2a). For CF and CRF, 4491 OTUs (217 + 323 + 3662 + 289) were amplified;4552 OTUs (323 + 245 + 322 + 3662) were amplified for CRF and F; F and RF were amplified 3984 OTUs (3662 + 322) and CF and F were amplified for 4234 OTUs (323 + 3662 + 249).
The results showed that different treatments could affect the richness and diversity of bacteria, but CRF treatment had the greatest effect
The principal coordinate analyses (PCoA) of Phylum and genus classified the microbial communities according to the four treatments (Fig. 2b and c). A community structure based on the Bray-Curtis distance was built to determine whether the observed differences in microbial structure and composition were correlated with restoration practice. In phylum, PCoA1 and PCoA1explained 59.3% and 19.9% respectively. In genus, PCoA1 and PCoA1explained 54.5% and 16.5% respectively. In two PCoA, CF and RF flora are separated, and CRF about covers CF and RF flora.
Figure 2
3.5.2 Effect of different treatments on bacterial community composition
The impact of different fertilization treatments on the composition of bacterial communities at the phylum level is shown in Fig. 3a. The most abundant phylum in all treatments was acidobacteria, accounting for 30–40% of the relative abundance. Other dominant phyla were Proteobacteria, Chloroflexi, and Bacteroidetes. The CF treatment had the highest relative abundance of acidobacteria and Chloroflexi, while the SF treatment had the highest relative abundance of Proteobacteria. At the genus level, the relative abundance of Candidatus_solibacter, sphingomonas, and Bryobacter was highest, as shown in Fig. 3b.
Figures 3c and 3d represent phylogenetic trees of species, primarily used to showcase differential species and their evolutionary relationships. Acidobacteria was the dominant species at the phylum level, while Candidatus_solibacter was the dominant species at the genus level, with more pronounced differences observed at the phylum level.
Figure 3
3.6 Relationships between soil physicochemical properties and bacterial community under different fertilization treatments
The RDA analysis demonstrated the factors influencing microbial community structure and function (Fig. 4a and b). At the phylum level, pH had the most significant impact on bacterial community structure, explaining 22.6% of the community variation, followed by soil AK, explaining 12.62% of the variation. The overall effect of all physicochemical factors explained % of the variation, with the order of influence being pH > AK > SOC > AN > AP. The first two axes of the RDA analysis explained a total of 90.4% of the community variation, with the first axis explaining 63.1% and the second axis explaining 37.3%. At the genus level, pH had the most significant impact on bacterial community structure, explaining 23.2% of the variation, followed by soil AK, explaining 10% of the variation. The overall effect of all physicochemical factors explained 36.78% of the variation, with the order of influence being pH > AK > SOC > AN > AP. The first two axes of the RDA analysis explained a total of 90.4% of the community variation, with the first axis explaining 63.1% and the second axis explaining 27.3%.Examining the first axis, the bacterial communities under the three fertilization treatments clustered together, while being separate from the F treatment group, indicating significant impact of different treatments on bacterial community structure.
The heatmap provided detailed information under each treatment (Fig. 4c and d). At the phylum level, physicochemical factor AN showed a significant relationship with Luteibacter. Acidothermus showed a highly significant relationship with SOC and SOM. Among these factors, pH had the highest relative abundance at the phylum level. At the genus level, physicochemical factor Nitrospirae showed a highly significant relationship with SOC and SOM, while AN showed a highly significant relationship with Latescibacteria and FCPU426. Among these factors, AN had the highest relative abundance at the genus level.
Figure 4
3.7 Effect of different treatments on Co-network analysis
Based on the data and Fig. 5, it can be seen that at the bacterial phylum level, the highest correlation was observed between the Proteobacteria phylum and the species (27.8%), with the order of correlation coefficient between different fertilization treatments and bacteria being CRF > RF ≈ CF > F, indicating that different treatments have different effects on the bacterial community.
At the bacterial genus level, the highest correlation was observed between the Ascomycota and the species (21.9%), explaining the variation of 21.9 percent of the bacterial community. The order of correlation coefficient between different fertilization treatments and bacterial genera was CRF > RF > CF > F, indicating that different treatments have different effects on the bacterial genus community. These results suggest that different fertilization treatments have a significant impact on the community structure of soil bacteria, and that different bacterial phyla and genera respond differently to each treatment.
Figure 5