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Article

Long-term Tillage Alters Soil Properties and Rhizosphere Bacterial Community in Lime Concretion Black Soil under Winter Wheat–Summer Maize Double-Cropping System

by
Qing Sun
1,
Peiyu Zhang
1,
Xiang Liu
1,
Hongsheng Zhang
1,
Shutang Liu
2,
Xuefang Sun
1 and
Wen Jiang
1,*
1
Shandong Provincial Key Laboratory of Dryland Farming Technology, College of Agronomy, Qingdao Agricultural University, Qingdao 266109, China
2
College of Resources and Environment, Qingdao Agricultural University, Qingdao 266109, China
*
Author to whom correspondence should be addressed.
Agronomy 2023, 13(3), 790; https://doi.org/10.3390/agronomy13030790
Submission received: 14 February 2023 / Revised: 2 March 2023 / Accepted: 7 March 2023 / Published: 9 March 2023
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Abstract

:
Tillage practices can directly affect soil quality, influencing soil properties, crop growth, and soil microbial community characteristics. However, the influence of long-term tillage practices on the rhizosphere bacterial community in lime concretion black soil remains largely unknown. In this study, the effects of nine-year rotary tillage (RT), no-tillage (NT), subsoiling tillage (ST), and plow tillage (PT) on soil chemical properties, microbial community structure, and correlations between bacterial communities and soil properties in the maize rhizosphere were investigated. The results revealed that the maize yield in ST and PT was higher by 10.61% and 10.26% than that in RT and by 10.25% and 9.90% than that in NT, respectively. The soil organic matter (SOM) and total nitrogen (TN) contents in NT and ST were significantly higher than those in RT and PT, whereas the available phosphorus (AP) content in ST and PT was significantly higher than that in NT and RT. The diversity and richness of the soil bacterial communities exhibited a trend of NT > RT > PT > ST. The principal component analysis revealed that the soil bacterial community differed among treatments. Linear discriminant analysis effect size (LEfSe) analysis demonstrated that Proteobacteria, Armatimonadetes, Verrucomicrobia, and Chloroflexi could serve as crucial biomarkers. Phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) results revealed that genes involved in carbon, lipid, and xenobiotic metabolism were enriched under ST and PT, whereas those involved in nitrogen and carbon fixation were enriched under NT. Besides, Proteobacteria, Verrucomicrobia, and Armatimonadetes were positively associated with AP levels and negatively associated with pH; however, Acidobacteria, Bacteroidetes, and Planctomycetes exhibited an opposite trend. Overall, ST and PT improved the soil properties and environmental suitability by increasing the bacterial keystone taxa; thus, these practices improved crop yield. These findings could enhance our understanding of the rhizosphere functional microbial community in lime concretion black soil for winter wheat–summer maize double-cropping system.

1. Introduction

Lime concretion black soil, or the Shajiang black soil, is a main soil type in the Huang-Huai-Hai Plain in China, accounting for approximately four million hm2. Crop production in lime concretion black soil is normally limited because it is characterized by heavy texture and low physical soil quality [1]. Numerous studies have shown that soil quality is closely related to tillage practices, which have an impact on soil’s physical, chemical, and biological properties [2,3]. For instance, no-tillage (NT) and rotary tillage (RT) contributed to reducing soil erosion and runoff, protecting soil aggregates, and increasing microbial diversity [4,5]; subsoiling tillage (ST) can improve soil properties and enrich nitrogen-cycling bacterial communities [6]. However, the choice of an appropriate tillage is primarily determined by soil conditions and the type of crops [7]. The application of suitable tillage practices on arable land contributes to soil productivity and fertility [8]. Therefore, it is of great significance to identify effective tillage measures to improve soil quality and fertility to increase crop yield for the security and stability of grain production in this region.
An RT system is considered highly ecofriendly, as it reduces soil erosion and runoff, protects soil aggregates, and increases microbial diversity [5,9]. However, continuous RT will reduce the pores in the soil, resulting in poor soil ventilation and water permeability, temperature increase, and soil compaction [10]. No-tillage (NT) can reduce soil disturbance, improve soil pore connectivity, and increase soil organic matter content and soil agglomeration ability, thus combating soil degradation [11]. However, long-term NT can increase soil bulk density in the top soil layer and lead to soil stiffness and other adverse consequences, limiting the growth of roots [12]. Subsoiling tillage (ST) involves breaking the plough bottom, reducing the soil bulk density and compactness, and expanding the soil reservoir without reversing the original soil layer [13]. ST exhibits a good effect on expanding, storing, increasing capacity, and increasing yield; however, soil water holding capacity is relatively weak in drought, and soil clods are large and elastic in the surface layer. This adversely affects the growth and development of crops. Plow tillage (PT) can effectively reduce soil bulk density and increase macropore content [14]. However, for areas with poor levels of soil nutrients, deep digging can bring the core soil layer with low nutrients to the surface layer, which can aggravate the surface soil fertility and even lead to yield reduction. Therefore, scientists are developing efficient ways to improve the fertility of lime concretion black soil with poor levels of nutrients [1,15,16].
In agroecosystems, rhizosphere microorganisms play an important role in improving soil fertility and aeration, which are considered the drivers of nutrient cycling [17,18]. It is critical to understand how soil microbial communities respond to tillage practices. Liu et al. reported that NT increased bacterial diversity and richness; however, no significant differences were observed between RT and PT [19]. Sun et al. reported that NT exhibited the lowest bacterial richness compared with PT and RT [20]. Recent studies that investigated the effects of tillage practices on soil microbial abundance, diversity, and composition have not reached a consensus [21,22]. Despite research for decades on microorganisms in various agricultural systems, the responses of the rhizosphere microbial community to various tillage practices in lime concretion black soil are still not well understood.
The objective of this study was to reveal how long-term tillage practices influence the soil properties, rhizosphere bacterial community, and maize yield in lime concretion black soil under the winter wheat–summer maize double-cropping systems. We used 16S rDNA amplicon sequencing to evaluate the effect of nine-year tillage practices (i.e., conventional rotary tillage [RT], no-tillage [NT], subsoiling tillage [ST], and plow tillage [PT]) in the wheat season on the structure and function of the soil bacterial community in the maize rhizosphere. We hypothesized that bacterial community composition and diversity would differ among various tillage practices and that soil bacterial microbial community and soil chemical properties might be related. This study could provide guidance in farmland tillage management, particularly in lime concretion black soil.

2. Materials and Methods

2.1. Experimental Site and Design

The nine-year tillage experiment was conducted in 2009 at Jiaozhou Modern Agricultural Science and Technology Demonstration Station of Qingdao Agricultural University (35.53° N, 119.58° E), Qingdao City, Shandong Province, China. The climate in this region is temperate, continental monsoon, semi-humid, and prone to drought. The soil type is lime concretion black soil; soil permeability is relatively poor, and drought and flood disasters occur frequently. Before commencing the experiment, the 0–20 cm of mixed-soil layer contained 13.5 g kg−1 organic matter (SOM), 101.4 mg kg−1 alkaline nitrogen, 24.6 mg kg−1 available phosphorus (AP), and 128 mg kg−1 available potassium (AK). During the maize season, the popular cultivar Zhengdan 958 was used, and approximately 675 kg hm−2 of controlled-release fertilizer (N: P2O5:K2O = 25:12:8) was applied. Each experimental plot was subjected to identical irrigation and other agricultural management strategies.
For the experiment, a randomized complete block design was used with the four tillage treatments (i.e., conventional rotary tillage [RT], no-tillage [NT], subsoiling tillage [ST], and plow tillage [PT]) during the wheat season. For RT, the soil was tilled twice to a 15 cm depth with a rotary tiller. For NT, sowing and repressing operations were simultaneously conducted using a no-till seeder. For ST, a subsoiler was used to subsoil to a depth of 35 cm. For PT, the soil was tilled to a depth of 30 cm using a moldboard plough. Further, a shallow rotary tillage (15 cm) was used for breaking up large clods before sowing wheat. Winter wheat was sown in October and harvested in June. Summer maize was sown after the harvest of wheat, and the crop residues of both crops were completely returned to the field. All treatments were performed with three replicates, and the plot size was 325 m2 (5 m wide × 65 m long).

2.2. Soil Sampling and Chemical Analysis

Soil samples were collected at the maturity stage of maize in 2018. Soil from the 0–20 cm layer in the maize rhizosphere was collected from five points on each plot and mixed thoroughly to form a composite sample. The sampling and storage of rhizosphere soil were performed as described in a previous report [23]. Soil pH was measured in a soil-to-water ratio of 1:2.5 (weight/volume) by using a pH meter. The SOM content was determined via the dichromate oxidation method. The TN content was measured by the Kjeldahl method. The AK content was measured by the ammonium acetate oscillation extraction and flame photometry methods. The AP content was extracted with NaHCO3 (0.5 M) and measured using the molybdenum blue method [24].

2.3. Yield

At the maturity stage, 20 consecutive plants with uniform growth were harvested from three rows of maize. The grains were air-dried and weighed, and the yield was recorded at 14% grain moisture.

2.4. DNA Isolation from Soil and High-Throughput Sequencing

The genomic DNA of the sample was extracted using the CTAB method. Further, DNA purity and concentration were determined using agarose gel electrophoresis. The 16S rDNA V4 region was amplified using the primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) to assess bacterial diversity. The PCR products were mixed according to the required concentration. Subsequently, the PCR product mixture was run on 2% agarose gel for the separation. The PCR products were isolated using the Gene JET Gel Extraction Kit. The qualified product was used to construct a library using the Ion Plus Fragment Library (Thermo Scientific, Waltham, MA, USA). The library was sequenced on an Illumina Ion S5TMXL (Illumina, San Diego, CA, USA).

2.5. Statistical Analysis of Sequencing Data

Raw data were processed using the Cutadapt program to remove low-quality reads. Further, barcode and primer sequences were cut off to produce raw reads. In the NCBI database, raw sequences were deposited under SRA accession number: PRJNA587371. Clean reads were obtained after removing the chimeras. Further, OTU clustering was performed on the basis of 97% identity using the UPARSE program. R software (version 2.15.3) was used to draw dilution curves. Taxonomic annotation was performed using the Mothur method and the SSU rRNA database. Additionally, QIIME was used to calculate the alpha diversity indexes (ACE and Shannon). A Wilcox test was performed to study the variances of the α-indexes among various groups. The principal component analysis (PCoA) was performed using the R package vegan based on the UniFrac distance. The linear discriminant analysis (LDA) and effect size (LEfSe) analyses were conducted using the Galaxy web application via the LEfSe algorithm, with LDA > 3.0 indicating important biomarkers. PICRUSt was used based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to predict bacterial metabolic potential.

2.6. Statistical Analysis

The maize yield, soil properties, and relative abundance of the most abundant bacteria under various treatments were compared using ANOVA followed by Duncan’s test (p < 0.05). Spearman’s correlation coefficient was used to determine the relationship between microbial parameters and soil characteristics. All statistical analyses were conducted using SPSS version 20.0 software.

3. Results

3.1. Maize Yield and Soil Properties

Under various tillage practices for 9 years, significant differences in crop yields were observed (Figure 1). The yield in ST and PT was higher by 10.61% and 10.26% than that in RT and by 10.25% and 9.90% than that in NT, respectively (p < 0.05). However, no significant difference in yield was observed between ST and PT, as well as NT and RT.
In the 0–20 cm soil layer of the maize root rhizosphere, the basic chemical properties differed significantly under the four tillage practices (p < 0.05; Table 1). The pH values under the four tillage practices were in the following order: NT > RT > PT > ST. The SOM and TN contents under NT and ST were higher by 18.45–34.15% and 21.32–27.14% than those under RT and PT (p < 0.05). The AP content under ST and PT was higher by 47.06% and 50.37% than that under NT and by 42.71% and 46.21% than that under RT, respectively (p < 0.05). However, the pH values exhibited an opposite trend (p < 0.05). The AK content was higher by 15.97% under NT, ST, and RT than that under PT (p < 0.05).

3.2. The Bacterial Composition of Rhizosphere Soil under Various Tillage Practices

A total of 7883 OTUs were obtained in this study. Among them, 3467 OTUs were shared among the four tillage practices, and 417, 246, 287, and 235 unique OTUs were obtained under NT, ST, RT, and PT, respectively (Figure S1). The soil bacterial community composition and relative abundance under various tillage practices are given in Figure 2. At the phylum level, Proteobacteria, Actinobacteria, Acidobacteria, and Bacteroidetes were the dominant microorganisms, accounting for up to 75% of the total microorganisms, with a relative abundance of 39.21–44.68%, 12.36–14.91%, 11.09–14.13%, and 8.25–9.76%, respectively. In addition, Chloroflexi (3.36–4.72%), Planctomycetes (2.71–4.24%), Gemmatimonadetes (3.47–4.17%), and Verrucomicrobia (2.80–3.73%) all accounted for more than 1% of total microorganisms (Figure 2A). Compared with RT, NT significantly increased the relative abundance of Planctomycetes (p < 0.05) (Figure S2A). ST significantly enriched Proteobacteria and Verrucomicrobia but decreased the relative abundance of Bacteroidetes, Chloroflexi, and Thaumarchaeota compared with RT (p < 0.05) (Figure S2B). In addition, PT markedly increased the relative abundance of Actinobacteria, Chloroflexi, and Verrucomicrobia and notably decreased the relative abundance of Planctomycetes and Thaumarchaeota relative to RT (p < 0.05) (Figure S2C).
The predominant genera under the four tillage practices included Sphingomonas (3.06–5.66%), unidentified_Acidobacteria (1.48–43.08%), Pseudomonas (0.15–2.87%), Haliangium (1.85–2.61%), unidentified_Gammaproteobacteria (0.94–2.15%), Gemmatimonas (0.60–1.93%), Dongia (0.86–1.92%), Sphingobium (0.79–1.60%), Flavisolibacter (0.50–1.17%), and Nocardioides (0.65–1.37%) (Figure 2B). Compared with RT, NT significantly decreased the relative abundance of Dongia, Sphingobium, and Flavisolibacter (p < 0.05) (Figure S3A). ST significantly enriched Haliangium, unidentified_Gammaproteobacteria, Gemmatimonas, and Nocardioides but decreased the relative abundance of unidentified_Acidobacteria and Pseudomonas compared with RT (p < 0.05) (Figure S3B). In addition, PT markedly increased the relative abundance of Haliangium, Gemmatimonas, and Nocardioides and notably decreased the relative abundance of unidentified_Acidobacteria relative to RT (p < 0.05) (Figure S3C).
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Figure 2. The bacterial community composition under various tillage practices. The relative abundance at the phylum level (A) and genus level (B). RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, and PT: plow tillage.
Figure 2. The bacterial community composition under various tillage practices. The relative abundance at the phylum level (A) and genus level (B). RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, and PT: plow tillage.
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3.3. Response of Alpha and Beta Diversity to Long-Term Tillage Practices

The richness and diversity of the bacteria in the rhizosphere soil were assessed by the alpha diversity. The ACE index revealed that NT and RT exhibited the highest bacterial richness compared to PT and ST (p < 0.05), and a significant difference was observed between PT and ST (p < 0.05) (Figure 3A). The Shannon index indicated that the diversity of soil bacteria exhibited the following trend: NT > RT > PT > ST (p < 0.05), indicating different bacterial diversity among the tillage practices (Figure 3B).
The beta diversity indicated the bacterial community structure in the soil under various tillage practices. According to the PCoA results, the bacterial communities were completely dissimilar among the tillage treatments. Based on the weighted UniFrac distance, PCo1 and PCo2 explained 66.73% and 15.9% of the variance in bacterial community structure, respectively (Figure 4A). Based on the unweighted UniFrac distance, PCo1 and PCo2 explained 28.4% and 13.85% of the variance, respectively (Figure 4B). The results demonstrated that all tillage practices had a strong impact on the soil bacterial community composition.
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Figure 3. The difference in the alpha diversity indexes under long-term tillage practices. (A) ACE index; (B) Shannon index. RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, and PT: plow tillage.
Figure 3. The difference in the alpha diversity indexes under long-term tillage practices. (A) ACE index; (B) Shannon index. RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, and PT: plow tillage.
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Figure 4. Principal coordinate analysis of soil bacterial composition as affected by tillage practices based on (A) the weighted UniFrac distance and (B) unweighted UniFrac distance. RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, PT: plow tillage.
Figure 4. Principal coordinate analysis of soil bacterial composition as affected by tillage practices based on (A) the weighted UniFrac distance and (B) unweighted UniFrac distance. RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, PT: plow tillage.
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3.4. Identification of Keystone Taxa under Different Tillage Practices

The LefSe analysis revealed that bacterial communities were significantly distinct under the four tillage practices (Figure 5). Bacterial phyla Thaumarchaeota and Bacteroidetes were significantly enriched under RT; Planctomycetes and Rokubacteria were significantly enriched under NT; Proteobacteria, Armatimonadetes, and Verrucomicrobia were significantly enriched under ST, and Chloroflexi was enriched under PT. At the genus level, Sphingobium, Agromyces, Terrimonas, Sphingoblum, and Lysobacter were enriched under RT; Galella, Stenotrophobacter, Adhaeribacter, Chryseolinea, Ohtaekwangia, Planctomycetes, Altererythrobacter, and Rokubacteria were enriched under NT; Kribbella, Flavitalea, Dongia, Haliangium, Pseudoduganella, and Steroidobacter were significantly enriched under PT; and Bryobacter, Nocardioides, Gemmatimonas, Flavisolibacter, Pseudolabrys, and 18 other phyla were enriched under ST.

3.5. Soil Bacteria’s Metabolic Responses to Long-Term Tillage

A KEGG-based bacterial functional profile was predicted with PICRUSt2 using 16S rRNA sequence datasets. According to the KEGG level 2 GO analysis, differentially abundant protein-coding genes could be mapped to 41 pathways. According to Welch’s t-test, NT and RT exhibited enrichment in 10 and 5 functional categories, respectively (p < 0.05). Genes associated with replication and repair; translation; cell motility; nucleotide metabolism; transcription; folding, sorting, and degradation; signal transduction; glycan biosynthesis and metabolism; enzyme families; and environmental adaptation were predicted to be more abundant under NT. Meanwhile, genes related to amino acid metabolism, xenobiotic biodegradation and metabolism, membrane transport, and the metabolism of other amino acids were more abundant under RT (Figure 6A). Under ST, genes related to amino acid metabolism, carbohydrate metabolism, lipid metabolism, xenobiotic biodegradation and metabolism, cellular processes and signaling, metabolism, transcription, and the metabolism of other amino acids were enriched (Figure 6B). Under PT, the genes related to membrane transport, carbohydrate metabolism, xenobiotic biodegradation and metabolism, transcription, and the metabolism of other amino acids were enriched (Figure 6C). Compared with ST and PT, genes related to energy metabolism; replication and repair; translation; metabolism of cofactors and vitamins; cell motility; nucleotide metabolism; genetic information processing; and folding, sorting, and degradation were more abundant under RT.

3.6. Relationships between Soil Bacterial Communities and Soil Chemical Properties

Figure 7A shows the relationship between bacterial communities and soil properties. Soil bacterial communities were significantly affected by AP, AK, SOM, TN, and pH, with the first axis of the RDA plot explaining 47.43% of the variation. As shown in the second axis, which explained 29.23% of the variation, SOM and AP strongly correlated with bacterial communities. pH displayed a trend opposite that of SOM, AP, TN, and AK. Importantly, the soil properties described in Figure 7A are mostly indicated by arrows pointing to NT and ST, suggesting that their explanatory power for reduced tillage was stronger than that for RT and PT. This indicated that the rhizosphere bacteria were more closely related to the soil environment under reduced tillage conditions.
To study the relationship between the abundance of bacterial phyla and environmental factors, Spearman’s correlation heat map was conducted (Figure 7B). The relative abundance of Proteobacteria, Verrucomicrobia, and Armatimonadetes was negatively correlated with soil pH but positively correlated with AP. The relative abundance of Acidobacteria, Bacteroidetes, and Planctomycetes was positively correlated with soil pH but negatively correlated with AP. Moreover, significant positive correlations were observed between the relative abundance of Gemmatimonadetes and TN, as well as between Actinobacteria and AP. However, the relative abundance of Chloroflexi and soil nutrients (TN and SOM) exhibited a negative correlation. The results indicated that soil chemical properties could affect microbial community richness and composition.

4. Discussion

4.1. Effects of Tillage Practices on Yield and Soil Properties

This study was conducted on typical lime concretion black soil with a heavy texture and low physical quality. In the present study, the maize yield under ST and PT was higher than that under RT and NT. This is consistent with many previous studies, which reported that ST with straw incorporation resulted in higher maize yields than the other tillage treatments [6,25]. This may be attributed to the fact that the soil surface under NT was relatively compact, making it unsuitable for root growth. Conversely, the soil under ST and PT was less compact, resulting in increased root biomass and nutrient uptake [26]. However, previous studies reported that conservation tillage practices such as NT enhanced maize yield [27]. These differences may depend on soil type, physicochemical properties, weather conditions, and cultivation years.
Tillage practices have important effects on soil biological, physical, and chemical properties [28,29,30]. Our study demonstrated that tillage practices have a significant effect on soil chemical properties. NT and ST had relatively high SOM and TN contents, which is consistent with many previous studies [31,32]. A possible explanation is that NT and ST practices could reduce soil disturbance, preserve the soil aggregate structure, and reduce the exogenous SOM decomposition rate [33,34]. However, the AP content under ST and PT was significantly higher than that under NT and RT; however, the pH exhibited the opposite trend. This is consistent with recent studies reporting that soils with NT contained decreased amounts of P below 10 cm, whereas P levels were more homogenized throughout the tilled layer in soils with PT [35]. Plant roots in soils with ST might have benefited from the higher P availability via phosphate-absorbing bacteria. Furthermore, our study indicated that soils with ST contained a higher abundance of bacteria associated with AP. Additionally, we observed that the soils with NT and RT had a significantly higher pH, which could be a contributing factor to bacterial growth [36].

4.2. Response of Microbial Community Composition to Tillage Practices

In this study, Proteobacteria, Actinobacteria, Acidobacteria, and Bacteroidetes were the dominant bacterial phyla in all tillage practices. This was consistent with previous studies reporting that the same bacteria were globally and widely distributed throughout the soil under various tillage practices [31,37]. In previous studies, various tillage practices resulted in different rhizosphere microbial compositions [27,36]. In this study, compared with RT, NT significantly increased the relative abundance of Planctomycetes; ST significantly enriched Proteobacteria and Verrucomicrobia, and PT markedly increased the relative abundance of Actinobacteria, Chloroflexi, and Verrucomicrobia. A higher abundance of Proteobacteria under ST can be explained by the preference of Proteobacteria for environments with high nutrient availability. In general, the Proteobacteria are considered copiotrophs, which means they tend to proliferate under nutrient-rich conditions [17]. This phylum consists of numerous genera of important bacteria, such as those with the ability to biologically fix nitrogen [38]. At the rhizosphere interface, Verrucomicrobia are widespread and can produce beneficial substances for plants [39]. This study demonstrated that bacteria from the phyla Proteobacteria and Verrucomicrobia could more readily establish under ST. Several studies have reported that Actinobacteria can degrade cellulose and chitin as the main resources for soil nutrient supply under C-limited conditions [40]. Actinobacteria and Chloroflexi are considered oligotroph-associated phyla [41], which can be confirmed by the relatively limited nutrient status in the 0–20 cm soil layer in PT. In addition, Chloroflexi can fix inorganic CO2 as well as aerobically oxidize carbon monoxide and nitrite and reduce ferric iron and nitrate [42]. Thus, these bacterial keystone taxa played an important role in increasing maize yield.

4.3. Effects of Tillage on Microbial Alpha and Beta Diversity

Our results revealed that bacterial community structures were significantly influenced by tillage practices, which was supported by previous studies suggesting that bacterial alpha or beta diversity varies greatly under various tillage practices [5,20]. In this study, NT and RT increased the alpha diversity of rhizosphere bacteria compared with PT or ST, which was consistent with previous studies reporting that bacterial alpha diversity decreased under PT compared with that under NT and RT [19,43]. Studies reported that NT increased soil microbial diversity via increasing soil moisture and reducing temperature fluctuation [44]. However, Liu et al. reported that ST with straw incorporation increased bacterial diversity compared with PT [6]. These inconsistent observations may be attributed to various soil types and years of tillage practice. In addition, no significant differences in bacterial richness were observed under NT and RT, which may be because tillage functions for winter wheat are consolidated under RT and specific issues are managed with respect to NT practices for summer maize [45]. However, we observed that the maize yield was higher under ST and PT than under RT and NT. This may be attributed to the number of pathogenic bacteria in the soil. Wang et al. reported that long-term NT combined with residue amounts changed soil microbial communities and increased maize root rot risks in northeast China [31].

4.4. Potential Bacterial Functions in Response to Tillage Practices

Metabolic and functional profiling of bacterial communities was investigated using PICRUSt2. At level 2, the genes involved in secondary metabolism (amino acid metabolism, carbohydrate metabolism, and lipid metabolism) and degradation of complex compounds and soil pollutants (xenobiotic biodegradation and metabolism) were enriched in soils with ST and PT compared with those with RT. This was consistent with previous studies reporting that PT enriched the bacterial genera involved in C metabolism, including amino acid, lipid, and carbohydrate metabolism, compared with RT [19]. Soils with ST and PT exhibited pathways characteristic of fitness responses to environmental stress. For instance, the higher abundance of genes related to lipid metabolism results in increased production of fatty acids, which are crucial for the survival of microorganisms in strenuous conditions [35]. The enriched defense pathways (i.e., xenobiotic biodegradation and metabolism) in ST and PT indicated a buildup of toxic compounds and an increase in microbial competition in soil, which leads to an increase in antibiotic production and resistance. Compared with RT, genes involved in nucleotide metabolism, transcription, glycan biosynthesis and metabolism, enzyme families, and environmental adaptation were predicted to be more prevalent in NT. This indicated that soils with NT had a greater potential for microbial nitrogen and carbon fixation than soils with other tillage practices.

4.5. Differential Bacteria and Their Relationship with Soil Properties

Related studies have reported that the topsoil’s chemical properties are closely related to soil microbial communities [5,20]. In this study, the soil AP and pH had a great impact on the structure of the bacterial community, as demonstrated by both the RDA and Spearman’s correlation heat map. Previous studies have reported that pH plays a universal role in predicting bacterial composition [46]. The relative abundance of Proteobacteria, Verrucomicrobia, and Armatimonadetes negatively correlated with soil pH, while that of Acidobacteria, Bacteroidetes, and Planctomycetes positively correlated with soil pH. This is consistent with previous studies reporting that Proteobacteria and pH have a significant negative correlation. However, Acidobacteria have a significant positive correlation with pH [36]. Microorganisms in the soil affect root growth and soil phosphorus transformation, affecting phosphorus uptake [47]. In this study, the abundance of Proteobacteria, Verrucomicrobia, Actinobacteria, and Armatimonadetes positively correlated with AP content. Thus, these phyla may play a role in the transformation of phosphorus. In addition, a significant positive correlation was observed between the relative abundance of Gemmatimonadetes and TN, and a negative correlation was observed between the relative abundance of Chloroflexi and soil nutrients (TN and SOM). Consequently, Chloroflexi are generally considered oligotrophic [41]. Therefore, it can be concluded that various tillage practices could mediate the associations between keystone taxa and soil properties to alter soil quality.

5. Conclusions

In summary, long-term tillage practices in the wheat season affected the maize yield in the summer wheat–winter maize double-cropping system. The maize yield was significantly higher under ST and PT than under RT and NT in both years. NT and ST significantly increased soil SOC and TN contents compared with RT and PT, whereas ST and PT significantly increased AP content. The tillage practices changed bacterial diversity and richness, exhibiting the order of NT > RT > PT > ST. Several keystone bacterial phyla, such as Proteobacteria, Verrucomicrobia, Chloroflexi, and Armatimonadetes, emerged as important biomarkers that could affect soil fertility and crop yield. In addition, PICRUSt results revealed that soils with ST and PT have the characteristics of a fitness response to environmental stress. However, the potential for microbial nitrogen and carbon fixation was greater in soils with NT. Therefore, this study underlined that various tillage practices affected keystone taxa by changing soil properties, thus reshaping the bacterial community composition. This could further affect crop yield. Future studies should adopt metagenomic and metabolomic strategies to investigate the microbial mechanisms of keystone taxa for improving soil quality.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy13030790/s1. Figure S1: OTU Venn diagram of soil bacteria in the soil samples under different long-term tillage treatments; Figure S2: Relative abundances of the bacterial phyla under various tillage practices compared with RT; Figure S3: Relative abundances of the bacterial genera under various tillage practices compared with RT.

Author Contributions

Conceptualization, Q.S. and W.J.; methodology, Q.S.; software, P.Z.; validation, X.L. and P.Z.; formal analysis, H.Z. and S.L.; investigation, Q.S., P.Z., X.L. and X.S.; data curation, X.S.; writing—original draft preparation, Q.S.; writing—review and editing, Q.S. and W.J.; visualization, Q.S. and W.J.; supervision, H.Z.; project administration, S.L.; funding acquisition, W.J. and Q.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Shandong Modern Agricultural Industrial Technology System Construction Fund, grant number SAIT-02-06, National Key Research and Development Program, grant number 2016YFD0300803, and the Qingdao Agricultural University High-Level Talents Research Foundation, grant number 663/1119023.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Agronomy 13 00790 g001 550
Figure 1. Comparison of maize yield under various tillage treatments. NT: no-tillage, RT: rotary tillage, ST: subsoiling tillage, and PT: plow tillage. Different letters above columns signified statistically significant difference (p < 0.05).
Figure 1. Comparison of maize yield under various tillage treatments. NT: no-tillage, RT: rotary tillage, ST: subsoiling tillage, and PT: plow tillage. Different letters above columns signified statistically significant difference (p < 0.05).
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Figure 5. Linear discriminant analysis of the effect of tillage practices on bacterial species (LDA > 3.0). The phylum and genus levels are listed in order from the inside to the outside of the cladogram with various colored dots. Taxa that were significantly abundant in ST, PT, NT, and RT plots are indicated in red, green, blue, and orange, respectively. RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, PT: plow tillage.
Figure 5. Linear discriminant analysis of the effect of tillage practices on bacterial species (LDA > 3.0). The phylum and genus levels are listed in order from the inside to the outside of the cladogram with various colored dots. Taxa that were significantly abundant in ST, PT, NT, and RT plots are indicated in red, green, blue, and orange, respectively. RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, PT: plow tillage.
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Figure 6. Prediction of altered KEGG pathways in response to various tillage treatments using PICRUSt2 analysis. (A) NT vs. RT treatments; (B) ST vs. RT treatments; (C) PT vs. RT treatments. RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, PT: plow tillage.
Figure 6. Prediction of altered KEGG pathways in response to various tillage treatments using PICRUSt2 analysis. (A) NT vs. RT treatments; (B) ST vs. RT treatments; (C) PT vs. RT treatments. RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, PT: plow tillage.
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Figure 7. Correlation between soil chemical properties and rhizosphere bacterial community composition. (A) A redundancy analysis of the distance between bacteria communities and five soil properties. (B) The Spearman’s correlation heat map between the soil properties and the abundance of bacterial phyla. The asterisks indicate statistical significance (*, p < 0.05; **, p < 0.01). RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, PT: plow tillage.
Figure 7. Correlation between soil chemical properties and rhizosphere bacterial community composition. (A) A redundancy analysis of the distance between bacteria communities and five soil properties. (B) The Spearman’s correlation heat map between the soil properties and the abundance of bacterial phyla. The asterisks indicate statistical significance (*, p < 0.05; **, p < 0.01). RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, PT: plow tillage.
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Table
Table 1. Chemical characteristics of root rhizosphere soil under various long-term tillage treatments.
Table 1. Chemical characteristics of root rhizosphere soil under various long-term tillage treatments.
TreatmentpHSOM (g/kg)TN (g/kg)AP (mg/kg)AK (mg/kg)
RT7.37 b18.88 c1.53 b23.83 b144.92 a
NT7.83 a23.26 b2.10 a21.99 b144.85 a
ST6.39 d28.67 a1.97 a41.54 a144.86 a
PT6.71 c18.96 c1.55 b44.31 a121.57 b
Values are means ± standard deviation (n = 3). Means within a column followed by various letters are significantly different (p < 0.05). RT: rotary tillage, NT: no-tillage, ST: subsoiling tillage, PT: plow tillage.
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Sun, Q.; Zhang, P.; Liu, X.; Zhang, H.; Liu, S.; Sun, X.; Jiang, W. Long-term Tillage Alters Soil Properties and Rhizosphere Bacterial Community in Lime Concretion Black Soil under Winter Wheat–Summer Maize Double-Cropping System. Agronomy 2023, 13, 790. https://doi.org/10.3390/agronomy13030790

AMA Style

Sun Q, Zhang P, Liu X, Zhang H, Liu S, Sun X, Jiang W. Long-term Tillage Alters Soil Properties and Rhizosphere Bacterial Community in Lime Concretion Black Soil under Winter Wheat–Summer Maize Double-Cropping System. Agronomy. 2023; 13(3):790. https://doi.org/10.3390/agronomy13030790

Chicago/Turabian Style

Sun, Qing, Peiyu Zhang, Xiang Liu, Hongsheng Zhang, Shutang Liu, Xuefang Sun, and Wen Jiang. 2023. "Long-term Tillage Alters Soil Properties and Rhizosphere Bacterial Community in Lime Concretion Black Soil under Winter Wheat–Summer Maize Double-Cropping System" Agronomy 13, no. 3: 790. https://doi.org/10.3390/agronomy13030790

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