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Article

The Influence of Planting Method and Short-Term Organic Amendments on Rhizosphere Microbial Communities in Paddies: Preliminary Results

by
Ziqi Liu
1,
Zhiqiang Tang
2,
Lili Wang
2,
Li Wen
3,
Yi Liang
3,
Changhua Wang
2,* and
Hui Wang
4,*
1
Institute of Plant Nutrition and Environmental Resources, Liaoning Academy of Agricultural Sciences, Shenyang 110161, China
2
Rice Research Institute of Liaoning Province, Liaoning Academy of Agricultural Sciences, Shenyang 110101, China
3
Inner Mongolia Key Laboratory of Rice Breeding Innovation in Northern Cold Regions, Hinggan League Institute of Agricultural and Husbandry Sciences, Ulanhot 137400, China
4
Liaoning Academy of Agricultural Sciences, Shenyang 110101, China
*
Authors to whom correspondence should be addressed.
Agronomy 2025, 15(3), 540; https://doi.org/10.3390/agronomy15030540
Submission received: 24 January 2025 / Revised: 19 February 2025 / Accepted: 21 February 2025 / Published: 23 February 2025
(This article belongs to the Section Innovative Cropping Systems)
Browse Figures
Versions Notes

Abstract

:
This study assessed the impact of planting techniques and short-term organic additions on soil quality, enzyme activity, and bacterial community composition. Biochar (BC) amendment substantially enhanced the ACE, Chao 1, and Shannon indices in direct-seeded rice (DS). Principal coordinate analysis (PCoA) and dissimilarity distances confirmed significant differences in the rhizosphere bacterial community composition associated with planting methods and organic applications. At the phylum level, transplanting (TT) significantly increased the abundance of Proteobacteria, Planctomycetes, Bacteroidetes, Firmicutes, and Verrucomicrobia, whereas DS significantly reduced the abundance of Acidobacteria, Chloroflexi, Actinobacteria, Gemmatimonadetes, and WPS-2. Rice straw (RS) application was associated with increased Proteobacteria, Acidobacteria, Chloroflexi, and Gammaproteobacteria, while BC application improved Bacteroidetes, Firmicutes, and Verrucomicrobia. Planting methods and organic amendments were also observed to affect soil enzyme activities and physicochemical properties. DS was associated with an increase in microbial biomass nitrogen (MBN) and carbon (MBC), cellulase activities (CA), total phosphorus (TP), available nitrogen (AN), and available potassium (AK), while TT significantly increased urease activities (UA). Compared to BC and the control (CK), RS significantly increased CA, AN, and available phosphorus (AP). RDA ordination plots were used to examine the interactions between soil bacterial communities and soil physicochemical properties; planting techniques and organic additions had different effects on soil bacterial communities. Compared to RS and CK, BC enhanced MBN, MBC, UA, and AK. According to Pearson’s correlation analysis, Chloroflexi levels were positively associated with those of organic carbon (OC), MBN, and MBC. OC, TP, MBN, and CA positively correlated with gemmatimonadetes. In conclusion, these data reveal that planting practices and short-term organic inputs alter soil’s physicochemical parameters, enzyme activity, and microbial community composition.

1. Introduction

Oryza sativa L. is grown extensively in China, with two primary methods of production: transplanting and direct seeding. Conventional transplanting involves growing seedlings in a nursery before transferring them to the field [1]. However, this method demands substantial water, energy, and labor resources [2]. In comparison, direct seeding is a simpler strategy, wherein seeds are put directly in dry soil, removing the need for seedling nurseries and management and decreasing labor costs and resource demands [3]. Previous studies have concentrated on planting techniques’ impact on nutrient availability, soil enzyme activity, and grain output. Furthermore, they neglected the examination of soil microbial populations. This study demonstrates that planting methods significantly affect soil microorganisms.
About 30 million hectares of rice are cultivated in China, producing significant crop residual byproducts, such as rice straw [4,5]. Effectively utilizing these straw resources is a pressing challenge [6]. Returning crop straw to the field is one practical method that has been found to improve soil quality, fertility, and enzyme activity, increasing plant output [7]. Crop straw is a primary exogenous source of organic carbon and nutrients in agricultural fields [8]. It improves soil fertility by increasing the amount of carbon in the soil and mediating the availability of potassium, phosphorus, and nitrogen [9]. Furthermore, the applications of straw can alter the diversity and composition of microbial communities in the soil [10]. Straw amendments have been shown in studies to increase microbial diversity and richness, which is compatible with their capacity to increase microbial activity [11].
Another technique for managing crop waste is to make biochar (BC) from crop straws. BC is a carbon-rich substance produced by the pyrolysis of biomass leftovers under low-oxygen conditions at temperatures below 500 °C. Using BC on fields improves soil quality, nitrogen availability, and health [12]. BC increases cation exchange capacity and water retention, improving the quality of acidic soil and reducing nutrient loss. Furthermore, BC modifies soil conditions to delay nitrogen and carbon release. Its porous structure offers microorganisms a perfect habitat, which affects the compositions and activities of communities [13]. As a sustainable soil amendment, BC is widely utilized in agriculture to improve grain yields [14].
The intimate relationships between crops and soil microorganisms during plant growth have been emphasized in recent studies. To increase nutrient availability and stimulate growth, crops frequently depend on beneficial interactions between roots and root microbiomes [11]. Specifically, rhizosphere microorganisms and roots play vital roles in nutrient absorption, growth promotion, and yield improvement [10,15]. Comprehending these relationships is essential for improving agricultural output and encouraging sustainability.
The present study examined the effects of planting methods and organic amendments on soil characteristics, enzymes, and microbial populations. The specific objectives were as follows: (1) to evaluate the impact of planting type and short-term organic amendments on soil bacterial richness and diversity in the rice rhizosphere, (2) to characterize soil microbial responses to varying planting types and organic modifications, and (3) to assess the associations among microorganisms, enzymes, and the chemical properties of the rhizosphere soil.

2. Materials and Methods

2.1. Experimental Design

The field experiments were performed in Shenyang City (40°57′ N, 122°14′ W), Liaoning Province, China, from 2020 to 2021. After two years of continuous application of organic amendments, the soil was examined in October 2021, when the rice matured. With mean annual temperatures of 8.3 °C, 716 mm of precipitation, and 2200 h of sunlight, the region experiences a monsoon climate. In the continuous cropping method, rice is cultivated once a year. The soil is classified as clayey loam (1:2.5 w/v), pH 5.6, with the following contents: organic carbon (OC): 13.3 g kg−1; total nitrogen (TN): 1.13 g kg−1; total phosphorus (TP): 2.32 g kg−1; total potassium (TK): 45.5 g kg−1; available nitrogen (AN): 112.6 mg kg−1; available phosphorus (AP): 23.5 mg kg−1; and available potassium (AK): 46.8 mg kg−1.
Three replicates were used in a split-plot, randomized complete block design. For two years, the experiment was conducted. Three organic treatments (RS applied at 9750 kg ha−1/Y, BC applied at 3450 kg ha−1/Y, and CK without rice straw or biochar amendment) and two rice planting techniques (TT and DS) were among the treatments. The RS application rate was based on the average regional RS yield. RS was chopped into 30–50 mm pieces and contained 34% carbon and 0.6% nitrogen. BC was produced by pyrolyzing RS at 450 °C for 1 h, yielding granular particles (diameters, 3–5 mm) with 65% carbon, 0.7% nitrogen, and a pH of 8.6 (1:2.5 H2O). The individual plots measured 360 m2. Before rice cultivation, RS and BC were manually integrated into the soil in April 2020 and 2021. The plots were fertilized with a base application of 750 kg ha−1 compound fertilizer (15% N, 15% P, 15% K) after being plowed to a depth of 200 mm. Additional urea (270 kg ha−1) was used for mid-tillering and seedling establishment. TT and DS plots used identical amounts of nitrogen, phosphorus, and potassium. Water levels, weeds, diseases, and pests were managed as needed to minimize yield losses.

2.2. Soil Sample Collection

Rhizosphere soil samples were collected when the rice reached maturity. Samples were taken from a 20 × 20 cm area to a depth of 20 cm (about 15 hills) from each plot, and five cores were merged to form a single sample. For every treatment, there were three replicates. After the excess soil was stirred off the roots, leaving about 1 mm of soil behind, it was firmly shaken again into 50 mL of sterile PBS. The suspension was then placed in 50 mL tubes. Samples were kept at 4 °C to evaluate the soil’s physicochemical characteristics, enzyme activity, and microbial biomass or at −80 °C for DNA extraction.

2.3. Analyses of Physicochemical Parameters, Enzyme Activities, and Microbial Biomass

Urease activities (UA) were measured using a sodium phenol colorimetric method, while cellulose activities (CA) were examined with carboxymethyl cellulose as substrate [16]. A soil–water suspension (1:2.5) was used when quantifying soil pH. Organic carbon (OC) levels were quantified using K2Cr2O7-H2SO4 wet oxidation. Total nitrogen (TN) was assessed via a semi-micro Kjeldahl procedure, total phosphorus (TP) using NaOH fusion and colorimetric determination, and total potassium (TK) via NaOH fusion-flame photometry [17]. Available nitrogen (AN) was measured using a NaOH diffusion approach, available phosphorus (AP) using the molybdenum blue colorimetric method, and available potassium (AK) via flame photometry [17]. Microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) were assessed via a chloroform fumigation–extraction approach [18,19].

2.4. DNA Sequencing

A Fast DNA SPIN Kit for Soil (Q-BIOgene, Carlsbad, CA, USA, CAT NO.6560200) was used as instructed to extract DNA from 0.5 g of soil. An automated microplate reader (BioTek SynergyHTX, Gene Company Limited, South San Francisco, CA, USA) was then used to measure the quality of the extracted DNA. An amplification of 16S rRNA was performed with the 338F:806R primer pair (ACTCCTACGGGAGGCAGCA/GGACTACHVGGGTWTCTAAT) using the following PCR settings: 95 °C for 5 min; 25 cycles of 95 °C for 30 s, 50 °C for 30 s, and 72 °C for 40 s; 72 °C for 7 min. Beijing Biomarker Technologies Co., Ltd. in Beijing, China used Illumina MiSeq 2500 equipment for paired-end sequencing after the resulting amplicons were separated using Agencourt AMPure XP Beads (Beckman Coulter, Indianapolis, IN USA, CAT NO. A63881). FLASH was used to merge the resulting data [20], combining merged tags and primers and eliminating tags with >6 matches to omit low-quality reads, with subsequent mass filtering [21]. After removing chimeric sequences, high-quality tagged reads were obtained [22], followed by clustering at the 97% similarity level [23], using a 0.005% OTU filtering threshold [24], yielding effective tags.

2.5. Statistical Analyses

The SAS MIXED Version 2.0 procedure was employed for data analysis [25]. A split-plot design was employed, with seeding methods and organic amendments designated as the main plots and subplots. The Shapiro–Wilk test was employed to evaluate normality and the homogeneity of variance was scrutinized, with adjustments implemented as necessary to ensure that the results were normally distributed. When ANOVAs indicated significant results (p < 0.05), extremely significant results (p < 0.01), and least significant difference (LSD) tests were conducted to clarify the impacts of treatments on enzyme activity, microbial biomass, and soil characteristics. An analysis of bioinformatics was conducted using BMK Cloud (www.biocloud.net, accessed on 15 December 2024). Alpha diversity studies were performed to assess the diversity and richness of the microbial population. Principal coordinate analyses (PCoA) and analyses of similarities (ANOSIM) based on the Jaccard distance dissimilarity matrix were used to represent the differences in bacterial communities. A redundancy analysis (RDA) was utilized to explore the associations among the activity of soil enzymes, bacterial communities, and physicochemical characteristics [26]. Pearson’s correlation coefficients were calculated to determine significant connections among predominant bacterial phyla, enzymatic activity, and soil properties.

3. Results

3.1. Microbial Community Diversity

Alpha diversity metrics, including the ACE, Chao1, Simpson, and Shannon indices, were used to evaluate bacterial diversity and richness (Table 1). The findings demonstrated that the DS group had significantly more bacterial richness and diversity than the TT group, as shown by the ACE, Chao1, and Shannon indices. Furthermore, the BC amendment resulted in significantly higher ACE, Chao1, Simpson, and Shannon indices compared to the RS and CK groups. The ACE, Chao1, and Shannon indices were markedly elevated under conditions of BC amendment in the DS treatment group.

3.2. Soil Bacterial Community Structure and Composition

A PCoA analysis of rhizosphere microbial communities based on Jaccard distances revealed clear distinctions among planting methods and organic amendments at the OTU level (Figure 1). Significant differences existed in the microbial community structures between RS, BC, and CK treatments and between TT and DS. Further, the microbial communities under RS, BC, and CK amendments were significantly distinct for the TT and DS planting techniques.
Variations in bacterial community structures among treatments were validated by dissimilarity distances (Figure 2). These analyses revealed that the bacterial community structures in TT soil showed higher distance values than DS, while TT differences in the rhizosphere bacterial communities exhibited higher distance values with DS. Under the TT, the CK-treated rhizosphere bacterial communities of exhibited greater distance values than RS and BC. Under the DS, the RS-treated rhizosphere bacterial communities exhibited greater distance values than BC and CK.
Concerning the type of planting and the organic ingredients, the composition of the bacterial communities was further evaluated (Figure 3). For every treatment, different distributions were observed at the phylum level. Among the 25 phyla (Figure 3), 67 classes, 249 families, the most abundant phyla (>1% relative abundance) across all depths included Proteobacteria (35.0–41.8%), Acidobacteria (24.8–30.0%), Chloroflexi (4.5–9.0%), Actinobacteria (5.3–7.0%), Planctomycetes (3.8–4.9%), Bacteroidetes (3.0–6.1%), Firmicutes (1.0–5.4%), Gemmatimonadetes (2.0–3.1%), Verrucomicrobia (2.0–3.0%), and WPS-2 (2.0–2.9%). The predominant classes (>1% relative abundance) throughout all depths were Acidobacteria (10.8–29.8%), Alphaproteobacteria (16.8–21.5%), Gammaproteobacteria (10.5–24.4%), Bacteroidetes (1.9–8.1%), Planctomycetacia (2.4–6.2%), Actinobacteria (1.8–5.5%), and Deltaproteobacteria (1.9–3.8%) (Figure S1). Uncultured_bacterium_o_Acidobacteriales (3.6–11.9%), Burkholderiaceae (3.9–12.6%), uncultured_bacterium_o_Subgroup_2 (2.5–7.4%), Xanthobacteraceae (2.6–7.7%), Solibacterace-ae_Subgroup_3 (2.6–7.0%), uncultured_bacterium_o_Gammaproteobacteria_Incertae_S (1.2–4.0%), Acidobacteriaceae_Subgroup_1 (1.4–4.2%), and Isosphaeraceae (1.8–4.5%) were the most abundant families (>1% relative abundance) across all depths (Figure S2). At the phylum level, relative to DS, TT was linked to significant increases in Proteobacteria, Planctomycetes, Bacteroidetes, Firmicutes, and Verrucomicrobia abundance, together with significantly reduced Acidobacteria, Chloroflexi, Actinobacteria, Gemmatimonadetes, and WPS-2 abundances. RS application was linked to increases in Proteobacteria, Acidobacteria, Chloroflexi, and Gammaproteobacteria levels, whereas BC application improved rhizosphere soil Bacteroidetes, Firmicutes, and Verrucomicrobia.

3.3. Activities of Soil Enzymes and Microbial Biomass

Significant variations in UA, CA, MBN, and MBC were observed among the groups (Table 2), signifying changes in nutrient concentrations and organic matter degradation. MBN, MBC, and CA levels significantly decreased under TT conditions compared to DS conditions, although UA increased. The implementation of BC was associated with higher MBN, MBC, and UA compared to RS or CK treatments. Compared to BC and CK, the use of RS improved CA.

3.4. Soil Physicochemical Properties

Regarding the various soil treatments and plantings, there were significant differences in soil pH, OC, TN, TP, TK, AN, AP, and AK (p < 0.05) (Table 3). In comparison to TT planting, it was discovered that DS planting techniques produced significantly higher quantities of TP, AN, and AK. Compared to BC or CK treatment, RS application was associated with higher levels of AN and AP. The BC amendment elevated soil pH and AK levels compared to the RS and CK treatments. The RS and BC amendments were associated with elevated rhizosphere soil OC, TN, TP, and TK levels compared to the CK. The application of RS was associated with an increase in rhizosphere soil AN under TT conditions and an increase in rhizosphere soil AP under DS conditions. On the other hand, the application of BC enhanced AK levels in the rhizosphere soil. Under DS conditions, the RS and BC treatments enhanced the rhizosphere soil’s AN and AK levels.

3.5. Associations Between Microbial Communities and Physiochemical Parameters in the Soil

At the genus level, RDA was used to assess the relationships between microbial communities and soil physicochemical characteristics (Figure 4). The compositions of the bacterial communities were significantly impacted by the type of planting and the organic amendment. Bacterial communities associated with RS and BC amendments were comparable under DS conditions, but CK communities were distinct. RS, BC, and CK changes produced different bacterial community structures under TT conditions. Under the BC amendment, there was a substantial correlation between the structure of the bacterial population and soil characteristics such as pH, OC, TN, TP, AN, AP, and AK. In DS, TK was similarly strongly associated with RS and BC treatments (Figure 4).

3.6. Associations Between Enzyme Activities, Physicochemical Parameters, and Abundant Phyla

Pearson’s correlation analysis revealed significant relationships between soil characteristics, bacterial populations, and soil enzyme activities (Table 4 and Table 5). TN, TP, TK, AN, AP, AK, and pH were all positively correlated with MBN, whereas OC, TN, TP, TK, AN, AP, and AK were all positively correlated with MBC. UA showed positive links with pH, OC, TN, TK, and AP, while CA similarly demonstrated positive associations with OC, TN, TP, AN, and AP. Among the bacterial phyla, Chloroflexi showed positive correlations with OC, MBN, and MBC, while Firmicutes displayed negative correlations with OC, AN, UA, and CA. Gemmatimonadetes showed positive correlations with OC, TP, MBN, and CA.

4. Discussion

The two main techniques for growing rice are direct seeding and transplanting. To support sustainable agriculture, rice cultivation produces a significant amount of crop residue, such as rice straw, which is increasingly used in fields in northeast China [2,26]. Previous studies have highlighted the considerable impact of straw and BC treatment on soil’s chemical parameters, enzymes, and microbial communities [27,28]. However, the effects of planting techniques and short-term organic compounds on soil microbial communities are still poorly investigated. This study evaluated the impact of these variables on the microbial diversity, soil properties, and enzyme activities of paddy soils. The results elucidate the relationships among microbial communities, soil characteristics, and planting practices, providing valuable insights for improving agricultural productivity and sustainability.
Soil microbial richness and diversity are key indicators of both soil ecosystem stability and fertility [29], and they play a vital role in supporting robust and sustainable agronomic productivity [30]. BC, characterized by high porosity and abundant functional groups, provides biogeochemical interfaces that diversify niche microhabitats, thereby fostering the growth of diverse bacterial communities [31,32]. These characteristics most likely account for the observed increases in bacterial diversity and richness after BC treatment, which aligns with the current findings. The ACE and Chao1 indices were used to measure richness in this work, while the Simpson and Shannon indices were used to define the diversity of the microbial community (Table 1). Compared to RS and CK treatments, the results revealed significantly higher BC ACE, Chao1, Simpson, and Shannon indices. This rise might be explained by the BC amendment’s increased habitat availability, which encourages microbial growth.
At the OTU level, PCoA revealed significant impacts of the type of planting and organic amendment on soil microbial community composition (Figure 1). The current results support the findings of the previous research studies, showing that organic amendments can significantly affect the α-diversity of soil microorganisms [27,33,34]. When using the TT and DS planting techniques, there were significant variations in the community α-diversity between the RS, BC, and CK treatments (Figure 2). Furthermore, the compositions of the rhizosphere microbial communities were changed by the type of planting, as well as the short-term organic amendment used (Figure 3). Proteobacteria, Planctomycetes, Bacteroidetes, Firmicutes, and Verrucomicrobia were significantly more abundant in TT than in DS. Variations in soil nutrients and the moisture content of paddy soil may have been the cause of these alterations [2,35]. Proteobacteria, ubiquitous in soil, play critical roles in nutrient cycling, particularly nitrogen and sulfur metabolism, and in organic matter mineralization [36,37,38]. The application of RS increased the abundance of Proteobacteria, corresponding to higher AN and AP levels in the soil. Gemmatimonas, a common bacterial genus connected with RS treatment, most likely developed because of the breakdown of straw, which supplies cellulose as a substrate [39,40]. However, the abundance of Gemmatimonadetes was significantly lower under TT conditions relative to DS, aligning with the findings published by Wang et al. [41], who reported that flooded environments inhibit Gemmatimonadetes growth, favoring Pseudomonas instead. Bacteroidetes, often used as an indicator of soil health [42], produce antibiotics and other compounds that suppress pathogens, contributing to soil health and nutrient balance. In this study, the application of BC increased the abundance of Bacteroidetes and elevated soil AK levels, consistent with the findings of previous research [43]. Acidobacteria, known for their adaptation to acidic environments and role in plant residue decomposition [32,44], were more abundant in BC-treated soils, possibly due to improvements in soil pH. The microporous structure of BC provides additional habitats for microbes, further enhancing bacterial richness and diversity [45,46].
Soil enzyme activity levels, which are crucial indicators of nutrient cycling and the decomposition of organic material [47,48], were significantly influenced by planting type and the addition of organic material. MBN, MBC, and CA increased significantly after DS treatment, most likely due to an increase in AN, AK, and TP levels, which were positively connected with microbial biomass and enzyme activity [49]. The RS amendment elevated CA levels, possibly due to the decomposition of cellulose and hemicellulose in rice straw, releasing carbohydrates and organic nutrients into the soil [8]. The soil’s nutritional content was further enhanced by the RS application, which significantly raised AN and AP levels. BC contains both micropores (<2 nm) and mesopores, stores dissolved substances, and retains moisture, thereby supporting microbial growth [50,51,52]. Its alkaline nature can enhance soil pH, creating favorable conditions for specific microbial populations [53,54]. Consistent with previous findings [51], BC application significantly increased soil MBC, MBN, and UA, highlighting its ability to enhance microbial biomass and enzyme activity compared to RS and CK treatments. In this study, the DSRS approach is more conducive to increasing soil AN, while the DSBC is more beneficial for increasing MBC, AK, and soil’s microbial diversity and richness. Therefore, under the DS planting condition, BC application to the soil can further increase the soil’s MBC and AK contents, improve the soil microbial community structure, enhance soil quality, and thereby potentially lead to an increase in grain yield. The DSBC approach may be better for soil nutrient content, enzyme activity, soil health, and productivity. Therefore, the DSBC method may be more beneficial to soil health and productivity, and is a suitable rice production method.
The RDA offered further insights into the relationships between the physicochemical properties of the soil and the architecture of the microbial communities (Figure 4). BC-amended soils demonstrated strong relationships between microbial communities and pH, OC, TN, TP, AN, AP, and AK. These data indicate that BC enhances nitrogen uptake by enhancing soil nutrient retention and offering habitats for microbial communities [55]. The composition and abundance of the bacterial population were shaped by short-term organic amendments that affected the soil’s physicochemical characteristics and enzymatic activities. For instance, in line with previous findings, Gemmatimonadetes levels positively correlated with OC, TP, MBN, and CA [56]. Gemmatimonas, a genus within this phylum, utilizes rice straw as a carbon source and indirectly facilitates cellulose degradation [57,58]. This functional role underscores the importance of RS in fostering bacterial communities that enhance soil quality.

5. Conclusions

The results show that both planting type and short-term organic amendment significantly impact the richness and variety of rice rhizosphere soil microbial community structures. Applying rice straw and biochar to the field considerably affects the root growth environment, enhances nutrient availability and soil enzyme activities, and modifies bacterial community structures, which can indirectly augment grain yield. These studies make sustainable agricultural practices possible, advancing our knowledge of how different planting and organic amendment types affect microbial communities, soil enzyme activity, and soil’s physicochemical characteristics.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15030540/s1, Figure S1: Class-level bacterial community composition as affected by each treatments; Figure S2: Family-level bacterial community composition as affected by each treatments.

Author Contributions

Conceptualization, Z.L. and H.W.; methodology, Z.T. and C.W.; software, L.W. (Lili Wang); validation, Y.L., Z.L. and C.W.; formal analysis, Z.T., L.W. (Li Wen) and C.W.; investigation, L.W. (Lili Wang) and Z.L.; resources Z.L. and Y.L.; data curation, Z.T. and L.W. (Lili Wang); writing—original draft preparation, Z.L., C.W. and H.W.; writing—review and editing, H.W. and Z.L.; visualization, L.W. (Li Wen); supervision, Y.L.; project administration, L.W. (Li Wen); funding acquisition, Z.T. and. C.W. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by a study on monitoring, evaluation, and early warning prediction of low-temperature chilling damage of maize and rice in Northeast China (2022YFD2300201), Construction project of Key Laboratory of rice Breeding Innovation in northern cold region of Inner Mongolia Autonomous Region, the earmarked fund for China Agriculture Research System (CARS-01), Liaoning Province agriculture major project (2022JH1/10200003).

Data Availability Statement

The data presented in this study are included within the article.

Conflicts of Interest

The authors declare that the research was conducted without any commercial or financial relationship that could be construed as a potential conflict of interest.

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Figure 1. Principle coordinates analysis (PCoA) of the bacterial communities in rhizosphere samples. PCoA distances were based on the Jaccard distance algorithm at the OTU level. TT, transplanting; DS, direct seeding; RS, rice straw; BC, biochar; CK, no RS or BC.
Figure 1. Principle coordinates analysis (PCoA) of the bacterial communities in rhizosphere samples. PCoA distances were based on the Jaccard distance algorithm at the OTU level. TT, transplanting; DS, direct seeding; RS, rice straw; BC, biochar; CK, no RS or BC.
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Figure 2. Dissimilarity distances show the differences in bacterial communities in rhizosphere samples. Dissimilarity distances were based on the Jaccard distance algorithm at the OTU level. TT, transplanting; DS, direct seeding; RS, rice straw; BC, biochar; CK, no RS or BC.
Figure 2. Dissimilarity distances show the differences in bacterial communities in rhizosphere samples. Dissimilarity distances were based on the Jaccard distance algorithm at the OTU level. TT, transplanting; DS, direct seeding; RS, rice straw; BC, biochar; CK, no RS or BC.
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Figure 3. Phylum-level bacterial community composition is affected by each treatment. TT, transplanting; DS, direct seeding; RS, rice straw; BC, biochar; CK, no RS or BC.
Figure 3. Phylum-level bacterial community composition is affected by each treatment. TT, transplanting; DS, direct seeding; RS, rice straw; BC, biochar; CK, no RS or BC.
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Figure 4. Redundancy analysis of rhizosphere bacterial genera and physicochemical characteristics.
Figure 4. Redundancy analysis of rhizosphere bacterial genera and physicochemical characteristics.
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Table 1. Richness and diversity of bacterial communities in the rhizosphere samples.
Table 1. Richness and diversity of bacterial communities in the rhizosphere samples.
Planting MethodsOrganic AmendmentsACE IndexChao 1 IndexSimpson IndexShannon Index
Transplanting (TT)RS133313660.998.14
BC139614110.9948.75
CK133213550.9777.34
Direct seeding (DS)RS143414590.9948.78
BC162916370.9958.88
CK155615710.9938.56
LSD(0.05)91.8120.9<0.010.65
Planting methods
TT 1354 ± 41.2 b1377 ± 43.9 b0.987 ± 0.018.07 ± 0.67 b
DS 1539 ± 88.8 a1556 ± 83.7 a0.994 ± 0.018.74 ± 0.15 a
Organic amendments
RS 1383 ± 60.6 c1413 ± 60.5 c0.992 ± 0.002 a8.45 ± 0.37 b
BC 1512 ± 129.4 a1524 ± 128.1 a0.995 ± 0.001 a8.81 ± 0.12 a
CK 1444 ± 126.5 b1463 ± 124.0 b0.985 ± 0.010 b7.95 ± 0.74 c
Analysis of variance
Planting methods (PM) **NS*
Organic amendments (OA) ********
PM × OA *******
Different letters indicate statistical significance within planting and application methods at the p < 5% level. * Significant at 0.05 level; ** significant at 0.01 level; NS, not significant at 0.05 level. TT, transplanting; DS, direct seeding; RS, rice straw; BC, biochar; CK, no RS or BC.
Table 2. Soil enzyme activity and microbial biomass under different planting methods and organic amendment treatments.
Table 2. Soil enzyme activity and microbial biomass under different planting methods and organic amendment treatments.
Planting MethodsOrganic AmendmentsMicrobial
Biomass N
(mg kg−1)		Microbial
Biomass C
(g kg−1)		Urease
Activity
(mg g−1day−1)		Cellulase Activity (mg g−1day−1)
Transplanting (TT)RS132.91.48.41.2
BC134.91.48.61.1
CK129.11.37.91.0
Direct seeding (DS)RS138.51.48.11.3
BC141.41.48.21.1
CK134.91.37.91.1
LSD(0.05)1.63<0.010.10.02
Planting methods
TT 132.3 ± 2.64 b1.36 ± 0.02 b8.3 ± 0.31 a1.1 ± 0.08 b
DS 138.3 ± 2.86 a1.38 ± 0.03 a8.1 ± 0.11 b1.6 ± 0.08 a
Organic amendments
RS 135.7 ± 3.12 b1.38 ± 0.01 b8.3 ± 0.19 b1.23 ± 0.03 a
BC 138.1 ± 3.63 a1.39 ± 0.01 a8.4 ± 0.24 a1.10 ± 0.01 b
CK 132.0 ± 3.23 b1.34 ± 0.01 c7.9 ± 0.01 c1.06 ± 0.03 c
Analysis of variance
Planting methods (PM) ********
Organic amendments (OA) ********
PM × OA NS****NS
Different letters indicate statistical significance for planting and application methods at the p < 5% level. ** Significant at 0.01 level; NS, not significant at 0.05 level. TT, transplanting; DS, direct seeding; RS, rice straw; BC, biochar; CK, no RS or BC.
Table 3. Soil physicochemical characteristics under different treatments, planting methods, and organic amendments.
Table 3. Soil physicochemical characteristics under different treatments, planting methods, and organic amendments.
Planting MethodsOrganic AmendmentspHOC
(g kg−1)		TN
(g kg−1)		TP
(g kg−1)		TK
(g kg−1)		AN
(mg kg−1)		AP
(mg kg−1)		AK
(mg kg−1)
Transplanting (TT)RS5.813.11.361.2922.5127.334.4136
BC6.013.51.371.2422.5120.630.2137.4
CK5.812.21.241.1621.8119.625.5129.8
Direct seeding (DS)RS5.913.41.391.3522.5130.733.8140.1
BC6.012.81.411.3422.9124.934.8149.2
CK5.712.41.281.2321.2119.725.2131.6
LSD(0.05)0.070.740.060.060.910.931.555.32
Planting methods
TT 5.8 ± 0.0912.9 ± 0.691.36 ± 0.071.23 ± 0.06 b22.3 ± 0.42122.5 ± 3.67 b31.3 ± 3.85134.4 ± 3.85 b
DS 5.8 ± 0.1012.9 ± 0.521.32 ± 0.061.31 ± 0.06 a22.2 ± 0.82125.1 ± 4.78 a30.0 ± 4.59140.3 ± 7.77 a
Organic amendments
RS 5.8 ± 0.03 b13.2 ± 0.29 a1.37 ± 0.02 a1.32 ± 0.04 a22.5 ± 0.29 a129.0 ± 1.86 a34.1 ± 0.48 a138.1 ± 2.46 b
BC 6.0 ± 0.04 a13.2 ± 0.42 a1.39 ± 0.03 a1.29 ± 0.06 a22.7 ± 0.27 a122.8 ± 2.50 b32.5 ± 2.56 b143.3 ± 6.83 a
CK 5.7 ± 0.03 c12.2 ± 0.45 b1.26 ± 0.03 b1.20 ± 0.04 b21.5 ± 0.49 b119.6 ± 0.38 c25.4 ± 0.41 c130.7 ± 1.73 c
Analysis of variance
Planting methods (PM) NSNSNS*NS**NS**
Organic amendments (OA) ****************
PM × OA NSNSNSNSNS******
Different letters indicate statistical significance for the planting and application methods at the p < 5% level. * Significant at 0.05 level; ** Significant at 0.01 level; NS, not significant at 0.05 level. TT, transplanting; DS, direct seeding; RS, rice straw; BC, biochar; CK, no RS or BC.
Table 4. Pearson’s correlation coefficients of soil’s physicochemical properties with different enzyme activities.
Table 4. Pearson’s correlation coefficients of soil’s physicochemical properties with different enzyme activities.
p HOCTNTPTKANAKAP
MBN0.612 **0.3870.772 **0.837 **0.495 *0.496 *0.873 **0.636 **
MBC0.862 **0.619 **0.926 **0.795 **0.835 **0.557 *0.935 **0.860 **
UA0.651 **0.682 **0.577 *0.2450.565 *0.1520.3070.51 *
CA0.2190.546 *0.591 **0.753 **0.380.937 **0.3490.734 **
Asterisks indicate significance level; * p < 0.05 and ** p < 0.01.
Table 5. Pearson’s correlation coefficients among enzyme activities, soil physicochemical properties, and abundant bacterial phyla.
Table 5. Pearson’s correlation coefficients among enzyme activities, soil physicochemical properties, and abundant bacterial phyla.
pHOCTNTPTKANAKAPMBNMBCUACA
Acidobacteria0.0580.0610.1630.2610.0110.0880.2670.2490.4280.360.1310.252
Actinobacteria0.0810.4320.1170.117−0.135−0.0530.143−0.2050.3090.1850.3050.124
Bacteroidetes0.145−0.131−0.025−0.1830.009−0.251−0.02−0.135−0.059−0.094−0.307−0.387
Chloroflexi0.3840.641 **0.370.3350.0420.230.385−0.0510.54 *0.470 *0.2750.35
Firmicutes−0.156−0.635 **−0.163−0.271−0.162−0.484 *−0.168−0.2630.022−0.193−0.692 **−0.534 *
Gemmatimonadetes0.2070.595 **0.2990.492 *0.0750.4410.3460.160.474 *0.3830.2490.585 *
Planctomycetes−0.0210.0940.140.1850.0130.0240.1740.2240.2860.1760.2310.169
Proteobacteria0.019−0.131−0.032−0.0030.2010.158−0.0710.257−0.348−0.1890.10.044
Asterisks indicate significance level; * p < 0.05 and ** p < 0.01.
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Liu, Z.; Tang, Z.; Wang, L.; Wen, L.; Liang, Y.; Wang, C.; Wang, H. The Influence of Planting Method and Short-Term Organic Amendments on Rhizosphere Microbial Communities in Paddies: Preliminary Results. Agronomy 2025, 15, 540. https://doi.org/10.3390/agronomy15030540

AMA Style

Liu Z, Tang Z, Wang L, Wen L, Liang Y, Wang C, Wang H. The Influence of Planting Method and Short-Term Organic Amendments on Rhizosphere Microbial Communities in Paddies: Preliminary Results. Agronomy. 2025; 15(3):540. https://doi.org/10.3390/agronomy15030540

Chicago/Turabian Style

Liu, Ziqi, Zhiqiang Tang, Lili Wang, Li Wen, Yi Liang, Changhua Wang, and Hui Wang. 2025. "The Influence of Planting Method and Short-Term Organic Amendments on Rhizosphere Microbial Communities in Paddies: Preliminary Results" Agronomy 15, no. 3: 540. https://doi.org/10.3390/agronomy15030540

APA Style

Liu, Z., Tang, Z., Wang, L., Wen, L., Liang, Y., Wang, C., & Wang, H. (2025). The Influence of Planting Method and Short-Term Organic Amendments on Rhizosphere Microbial Communities in Paddies: Preliminary Results. Agronomy, 15(3), 540. https://doi.org/10.3390/agronomy15030540

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