Next Article in Journal
A Convolution–Non-Convolution Parallel Deep Network for Electricity Theft Detection
Previous Article in Journal
Analysis of Spatial and Temporal Variations in Ecosystem Service Functions and Drivers in Anxi County Based on the InVEST Model
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 15
Issue 13
10.3390/su151310148
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Response of Soil Microbial Community Diversity to Long-Term Cultivation of Rice (Oryza sativa L.)/Cherry Tomato (Lycopersicon esculentum Mill.) in Rotation

by
Xiao Deng
1,2,3,4,5,6,*,
Hao Yin
1,2,3,7,
Huadong Tan
1,2,3,4,5,6,
Yi Li
1,2,3,4,5,6,
Chunyuan Wu
1,2,3,4,5,6,* and
Jiancheng Su
8
1
Environmental and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
2
Hainan Danzhou Tropical Agro-Ecosystem National Observation and Research Station, Danzhou 571737, China
3
Key Laboratory of Low-Carbon Green Agriculture in Tropical Region of China, Ministry of Agriculture and Rural Affairs, Haikou 571101, China
4
Hainan Key Laboratory of Tropical Eco-Circular Agriculture, Haikou 571101, China
5
National Agricultural Experimental Station for Agricultural Environment, Danzhou 571737, China
6
National Long-Term Experimental Station for Agriculture Green Development, Danzhou 571737, China
7
College of Resource & Environment, Huazhong Agricultural University, Wuhan 430073, China
8
Hainan Star Farmer Ecological Technology Co., Ltd., Haikou 571101, China
*
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(13), 10148; https://doi.org/10.3390/su151310148
Submission received: 4 May 2023 / Revised: 21 June 2023 / Accepted: 25 June 2023 / Published: 26 June 2023
Browse Figures
Review Reports Versions Notes

Abstract

:
The crop rotation periodicity has always been a concern of agricultural researchers. This study was the first investigation on the effects of long-term continuous cultivation with rice/cherry tomato rotation on soil microbial community diversity. The main objective was to analyze the optimal rotation years of rice/cherry tomato from a micro-ecology perspective so as to provide theoretical basis for effectively avoiding continuous cropping obstacles of cherry tomato. Soil samples were collected from the surface layers with rice/cherry tomato rotations for 1 year (1a), 3 years (3a), 5 years (5a), 7 years (7a) and 10 years (10a). The microbial community diversity was determined via high-throughput sequencing. The results showed that alpha diversity of soil microbial communities was the highest at 5a and then gradually decreased during 5a to 10a. Beta diversity results revealed that microbial community structure was significantly different among 1a, 3a to 7a and 10a, but there were no clear differences among 3a, 5a and 7a. The abundances of soil beneficial bacteria Gemmatimonadetes, Bacteroidetes, Chloroflexi, Nitrospirae and beneficial fungi Mortierella, Trichoderma, Penicillium were the highest at 5a or 7a. Those of soil pathogenic fungi Fusarium and Aspergillus were the lowest at 5a and 7a, respectively. However, the relative abundances of the above-mentioned beneficial microorganisms began to decline, while those of pathogenic fungi began to increase after 5a or 7a. Soil available phosphorus, available iron and available zinc were common important factors affecting the community structure of bacteria and fungi, as indicated by significant positive correlations between the environmental factors and microbial communities. In conclusion, the soil microbial diversity began to decline and the micro-ecological balance was broken after continuously planting 5a to 7a with rice/cherry tomato rotation, which would lead to new continuous cropping obstacles.

1. Introduction

Soil is an important natural resource for agricultural production. The quality of soil for agricultural production depends on its sustainable supply of plant nutrients. Crops and soil are interconnected and subsequently exert mutual effects on one another for effectiveness of productivity [1]. Nutrient availability also regulates soil microbial effects on plant performance [2,3]. The nutrient dynamics in the soil are influenced by the available amendments of litter/organic manure and serve as one of the inputs of nutrients in agroecosystems [4,5]. The land use systems effectively influence fertility and stability of an ecosystem [6]. Agricultural trends in the last five decades have intensive production with increased exercise of commercial seeds, pesticides, fertilizers, etc. [7]. Unscientific practices have adversely affected the soil health [2]; especially, the soil quality deteriorated severely and crop yield declined sharply under the long-term single cultivation pattern [8]. The continuous cropping obstacles have significant negative impacts on plant growth and development, mainly including weakened photosynthesis, slowed growth, reduced resistance and declined yield and quality of agricultural products [9,10,11]. There are many reasons for continuous cropping obstacles, such as soil nutrient imbalance, accumulation of toxic allelochemicals, propagation of soil-born pathogen and so on, but destruction of soil microbial communities is a prime reason [9,12]. Soil microorganisms are the dominant performers of soil nutrient cycles and energy flow and play crucial roles in maintaining soil ecosystem stability and sustainable utilization [13,14,15,16]. However, continuous cropping decreases microbial activity and beneficial microbial abundance in soil but promotes the growth of soil-borne pathogens, resulting in soil microecological imbalances [12,17,18,19]. Crop rotation is one of the oldest and the most traditional farming methods, which helps to regulate nutrient and water balance, control diseases, pest insects and weeds and improve crop yield [20]. It can protect environmental health by improving functional agrobiodiversity and agricultural sustainability [21,22]. Appropriate crop rotation can alleviate continuous cropping obstacles by altering soil microorganisms [23,24].
Rice (Oryza sativa L.) is an important crop and staple food for more than half of the world’s population and globally grown on 161 million hectares, with an average annual production of 678.7 million tons [25], and cherry tomato (Lycopersicon esulentum Mill.) has become one of the most important vegetables/fruits on account of ever-growing international demands and great economic and nutritional value [26]. Since 1997, its cultivated area has been expanding, and it has become a geographical indication product of Lingshui County, Hainan Province, China. Correspondingly, cherry tomato has become the economic pillar industries of Lingshui County. However, the long-term, intensive and single cultivation patterns with rice/cherry tomato rotations have led to the gradual deterioration of the soil quality, which has become the bottleneck restricting the sustainable development of the cherry tomato industry in Lingshui County [27]. Previous studies have indicated that different crop rotation years have different effects on improving soil properties [28]. The study of the periodicity of single crop rotation patterns and determining the reasonable crop rotation years according to local conditions have been concerning. To date, no studies have been conducted on the influences of long-term rotation of rice/cherry tomato on the composition and diversity of the soil microbial community.
In this study, soils from rice/cherry tomato rotation for one year (1a), three years (3a), five years (5a), seven years (7a), and ten years (10a) were selected as study objects. The composition and diversity of soil microbial communities were determined via high-throughput sequencing of 16S rRNA and ITS genes. The main objective was to analyze the optimal rotation years for rice/cherry tomato from the micro-ecology perspective so as to provide theoretical basis for effectively avoiding continuous cropping obstacles of cherry tomato.

2. Materials and Methods

2.1. Experiment Design

The field experiment was conducted in Guangpo Town, Lingshui County, Hainan Province, China. This region has a typical tropical maritime monsoon climate with sufficient light and heat conditions. The annual precipitation is approximately 1718 mm, and the annual average sunshine duration is approximately 2262 h. The mean annual air temperature is 25.4 °C, with a minimum temperature 20.6 °C in January and a maximum temperature 28.6 °C in June. The soil type of this region is paddy soil developed from laterite, whose texture is sandy loam.
The studied region was typical for rice/cherry tomato rotation systems (i.e., rice was cultivated from May to September and cherry tomato was cultivated from October to April in the next year). Experiment design was established through field investigation and interviewing farmers. Five treatments (three replicate plots of each treatment) were as follows: (1) 1a, cherry tomato started in rotation with rice at the first year in October 2021; (2) 3a, cherry tomato has been in rotation with rice for 3 years in October 2021; (3) 5a, cherry tomato has been in rotation with rice for 5 years in October 2021; (4) 7a, cherry tomato has been in rotation with rice for 7 years in October 2021; (5)10a, cherry tomato has been in rotation with rice for 10 years in October 2021. Additionally, the cultivation patterns of these treatments were continuous cropping of two-crop rice before the implementation of rotation. The cultivation area size per plot is about 0.2 to 0.3 ha, and the varieties of rice and cherry tomato and field management measures of each plot were basically consistent. The geographical location, planting area size, fertilization condition, etc., of 15 plots are listed in Supplementary Materials Table S1.

2.2. Soil Sample Collection and Analysis of Chemical Properties

The 0–20-cm tillage layer soils were taken during flowering fruit-bearing stage of cherry tomato in mid-January 2022. In order to avoid the influence of adjacent plots, the equidistant sampling method was used to collect soil samples from five points in the core area of each plot. These samples were well mixed into one composite sample (about 0.5 Kg per plot), sealed in a sterile bag, and then transported in an ice cube-filled box to the laboratory within two days. A total of 15 soil samples were obtained for subsequent analysis. Each soil sample was divided into two parts; the first part was air-dried and sieved with a 2 mm sieve to remove large particles and plant debris, and then used for the determination of soil pH and other physical and chemical properties. The second part was stored at −80°C and then used for the analyses of microbial diversity.
Soil pH, organic matter (OM), alkali-hydrolyzed nitrogen (AN), available phosphorus (AP) and available potassium (AK) were measured using routine methods described by Lu [29]. Soil pH was determined applying a pH electrode (Leici, Shanghai, China) at a soil: water ratio of 1: 2.5. The OM content was measured using a potassium dichromate volumetric method. The contents of AN, AP and AK were analyzed using a diffusion method, the Olsen method and ammonium acetate extraction flame photometry, respectively. The contents of exchangeable calcium (Ca) and exchangeable magnesium (Mg) were analyzed by atomic absorption spectrophotometry. The content of available sulfur (AS) was determined by phosphate–acetic acid–barium sulfate turbidimetric method. The contents of available iron (Fe), available zinc (Zn) and available copper (Cu) were determined by DTPA extraction and atomic absorption spectrophotometry. Applying ammonium acetate extraction and atomic absorption spectrophotometry to measure the content of available manganese (Mn). The available boron (B) was determined by boiling water extraction and curcumin colorimetry.

2.3. Soil DNA Extraction, PCR Amplification, and Sequencing

A Power Soil DNA Isolation Kit (MO BIO Laboratories, Carlsbad, CA, USA) was applied to extract total soil DNA from samples according to the manufacturer’s protocol. The DNA concentrations of all samples were quantified by a Qubit 3.0 Fluorometer (Invitrogen, Grand Island, NY, USA), and 16S rRNA gene sequencing was performed for bacterial profiling, in which the bacterial 16S gene V3-V4 region was amplified using the universal primers 319F (5’-ACTCCTACGGGAGGCAGCA-3’) and 806R (5’-GGACTACHVGGGTWTCTAAT-3’) and combined with adapter and bar code sequences. The ITS1 region of the fungi was amplified using the universal primers ITS1F (5’-CTTGGTCATTTAGAGGAAGTAA-3’) and ITS2R (5’-GCTGCGTTCTTCATCGATGC-3’) and combined with adapter and bar code sequences. The PCR was conducted under the conditions described by Wu et al. [30]. The amplicons were visualized using gel electrophoresis in an ethidium-bromide-stained 1.0% agarose gel to verify that they were the correct size and were no contamination, followed by gel purification using a GeneJET Gel Extraction Kit (Thermo Fisher Scientific, Waltham, MA, USA). The libraries were prepared and sequenced by Biomarker Biotechnology Co., Ltd. (Beijing, China) using the Illumina Novaseq 6000 sequencing system (Illumina, Santiago, CA, USA).

2.4. Sequence Processing and Statistical Analyses

Clean reads were obtained using the Trimmomatic v0.33 software to filter the raw reads obtained by sequencing and cutadapt 1.9.1 software to identify and remove primer sequences. Clean reads of each sample were spliced using Usearch v10 software (www.drive5.com, accessed on 10 August 2022). Chimeric sequences were identified and removed using the UCHIME v4.2 software (www.drive5.com, accessed on 12 August 2022) to obtain the final effective reads. The Quantitative Insights Into Microbial Ecology (QIIME 1.8.0) toolkit was then used to analyze the sequencing data. Clustering of the optimized sequences into operational taxonomic units (OTUs) at the 97% sequence similarity level was performed using Usearch v10 software.
Using the SILVA as the reference database, the feature sequences were annotated using naive bayes classifier to obtain the species classification information corresponding to each feature, and then the community composition of each sample was calculated and species distribution histograms at phylum and genus levels were obtained. The alpha diversity indices, including Chao1 and Shannon indices, were calculated using Mothur version v.1.30 on the BMKCloud. Non-metric multidimensional scaling (NMDS) based on Bray–Curtis dissimilarity was used to examine the beta diversity (A stress value of >0.2 indicates that this method is not appropriate). Analysis of similarities (ANOSIM) was performed to assess the significance of the differences in the beta diversities for a given combination of samples (An R value of >0 indicates that the intra-group distance is smaller than the inter-group distance, which means that the grouping is valid; a p value ≤0.05 indicated a significant difference). Redundancy analysis (RDA) and Mantel tests were performed to examine the correlation between environmental parameters and microbial communities. The alpha diversity indices, NMDS, ANOSIM, RDA analysis and Mantel tests were all performed using BMKCloud.
Data from replicates are expressed as the mean ± standard deviation (SD). The Statistical Product and Service Solutions (SPSS) v.17.0 software package (IBM Corp., Armonk, NY, USA) was used to perform the calculations and compare the treatment means of each experiment. Significant differences between the means were assessed using Duncan’s tests and one-way analysis of variance (ANOVA). Statistical significance was set at p ≤ 0.05.

3. Results

3.1. Effects of Cultivation Years with the Rice/Cherry Tomato Rotation on Soil Physicochemical Properties

The detailed information of soil physicochemical properties is shown in Table 1 and Table 2. Soil pH value was increased year by year from 1a to 5a, reaching the highest value of 5.32 in 5a. However, soil acidity was sharply enhanced in 7a, and the pH value dropped below 5.0. The content of soil OM was decreased year by year with the increase of crop rotation years and decreased by 11.2% to 50.4% after 3a to 10a (p ≤ 0.05). However, that of soil AN was significantly increased by 24.4% to 60.4% during 3a to 5a and began to decrease after 7a to 10a but was still at a rich level. That of soil AP was increased year by year with the increase in rotation years and increased by 110% to 173% after 3a to 10a (p ≤ 0.05). That of soil AK was increased by 1.80% to 36.1% during 3a to 7a. That of soil available Ca was increased by 27.3% to 111% during 3a to 7a, but the increase rate was reduced year by year with the increase in crop rotation years. That of soil available Mg was increased by 287% to 354% during 3a to 10a, but they were still below the critical value for crop growth (60 mg·kg−1). The contents of soil available Fe and available Zn were decreased year by year with the increase in crop rotation years and decreased by 17.2% to 53.2% and 14.9% to 23.9%, respectively, after 3a to 10a (p ≤ 0.05).

3.2. Effects of Cultivation Years with the Rice/cherry Tomato Rotation on Soil Microbial Community Composition

The soil microbial community composition was basically the same, but the relative abundance of each dominant group varied greatly among different planting years with the rice/cherry tomato rotation (Figure 1). There were nine dominant bacterial phyla (Figure 1a), namely Proteobacteria, Acidobacteria, Chloroflexi, Actinobacteria, Gemmatimonadetes, Actinobacteria, Verrucomicrobia, Bacteroidetes and Nitrospirae, already occupying 90.1% to 93.8% in different planting years of rice/cherry tomato, and Proteobacteria (34.3% to 41.6%) had the highest relative abundance, followed by Acidobacteria (21.6% to 24.7%) during different rotation years. The relative abundances of Proteobacteria and Actinobacteria were the highest at 1a and the lowest at 7a. That of Acidobacteria was the highest at 7a. Those of Chloroflexi and Nitrospirae were increased year by year during 1a to 7a and then began to decrease after 7a. Those of Gemmatimonadetes and Bacteroidetes were increased year by year during 1a to 5a but decreased year by year after 5a to 10a. For Fungi, there were five dominant phyla (Figure 1b), namely Ascomycota, Basidiomycota, Chytridiomycota, Mortierellomycota and Rozellomycota. Ascomycota (47.5%~58.1%) had the highest relative abundance, followed by the Basidiomycota (11.2%~35.1%), during different rotation years. The relative abundance of Ascomycota was the highest at 3a and the lowest at 10a. That of Basidiomycota was the highest at 1a and the lowest at 10a. That of Chytridiomycota was the highest at 1a and the lowest at 7a. That of Mortierellomycota was the highest at 5a. That of Rozellomycota was the highest at 10a and the lowest at 1a.
At the genus level (Figure 2), there were seven dominant fungi with relative abundance greater than 1%, including Aspergillus, Penicillium, Byssochlamys, Mortierella, Trichoderma, Talaromyces and Fusarium. The relative abundance of Aspergillus decreased year by year during 1a to 5a, was significantly reduced by 17.0% at 5a (p ≤ 0.05) but began to again increase gradually after 5a. That of Fusarium was the highest at 1a, decreased year by year during 1a to 7a and sharply declined by 20.2% and 27.2% at 5a and 7a (p ≤ 0.05), respectively, but began to increase obviously after 7a. The relative abundance of Mortierella increased year by year during 1a to 5a, increased by 43.6% and 31.8% at 5a and 7a (p ≤ 0.05), respectively, but began to sharply decrease after 7a. That of Trichoderma increased significantly during 5a to 10a (p ≤ 0.05), increasing by 54.4% to 103%, but its increase rate declined year by year during 5a to 10a. That of Penicillium increased obviously year by year during 1a to 7a and increased by 40.7% to 85.7% during 3a to 7a but began to sharply decrease after 7a (p ≤ 0.05).

3.3. Effects of Cultivation Years with the Rice/Cherry Tomato Rotation on Soil Microbial Diversity

Alpha diversity indices of the soil bacteria and fungi communities in the different rotation years of rice/cherry tomato are listed in Table 3. The richness and diversity of soil bacterial and fungal communities were the lowest at 1a but the highest at 5a, and those were increased gradually with the increase in crop rotation years during 1a to 5a and gradually decreased during 5a to 10a. The richness and diversity of soil bacterial communities at 3a, 5a, 7a and 10a were significantly higher than those at 1a (p ≤ 0.05), and the indices of Chao1 and Shannon were increased by 8.60% to 10.7% and 6.45% to 7.93%, respectively. However, there were no significant differences among 3a, 5a, 7a and 10a. The indices of Chao1 and Shannon of soil fungal communities at 5a were significantly higher than those at 1a, 3a and 10a (p ≤ 0.05), but there was no significant difference between 5a and 7a. However, the indices of Chao1 and Shannon of soil fungal communities at 5a and 7a were significantly higher than that at 10a (p ≤ 0.05).
The NMDS ordination revealed obvious differences in the OTU assemblages among different rotation years of rice/cherry tomato (Figure 3). The soil samples of 3a, 5a and 7a are close to each other, distributed in the same axis and not completely separated, indicating that the soil microbial community structure was very similar among 3a, 5a and 7a. However, the soil samples of 1a, 3a to 7a and 10a were distributed in different quadrants, indicating that the soil microbial community structure were obviously different among them. ANOSIM revealed that there were large differences in the compositions of microbial communities among the rotation years for 1a, 3a to 7a and 10a (R = 0.520 (bacteria)and 0.582 (fungi)), and the differences were significant (p = 0.003 (bacteria) and 0.001 (fungi)).

3.4. Effects of Soil Environmental Factors on Microbial Communities in Soil from Different Cultivation Years with the Rice/Cherry Tomato Rotation

Redundancy analysis (RDA) revealed the correlations between composition and diversity of soil microbial communities and environmental factors in different rotation years of rice/cherry tomato. Figure 4a shows that soil available P, exchangeable Mg, available Fe, available Zn and available Cu were the important environmental factors affecting the composition of soil bacterial community. Figure 4b shows that soil available P, exchangeable Mg, available Zn and available Fe were the important environmental factors affecting the composition of soil fungal community. According to the Mantel tests (Table 4), several important environmental factors affected bacterial community in soil of different rotation years of rice/cherry tomato, and the r values were in the order (from highest to lowest) were Mg > AP > Fe > Zn, as indicated by the significant positive correlations between the bacterial communities and the environmental factors. For fungi, the r values were in the order Fe > Zn > AP, as indicated by the significant positive correlations between the fungal community and the environmental factors.

4. Discussion

4.1. Response of Soil Microbial Community Diversity to Planting Years with the Rice/Cherry Tomato Rotation

Soil microbial community diversity plays crucial roles for maintaining and enhancing soil health and functional stability of the soil ecosystem [15]. Previous studies have shown that the soil amendment by crop rotation was connected with the shifts in the soil microbial community structure, for example, increasing relative abundance of beneficial microbes [31,32]. In this research, the Chao1 and Shannon indices of soil bacterial and fungal communities increased gradually with the extension of crop rotation years during 1a to 5a (Table 3), indicating continuously planting 5a with the rice/cherry tomato rotation makes for regulating the community composition of soil microbes. However, these indices began to decrease gradually after continuously planting 7a with the rice/cherry tomato rotation (Table 3). It was further confirmed that extending the monoculture period would significantly reduce soil microbial diversity [33,34]. The reason may be that soil pH significantly decreased with the extension of planting years (Table 1), which inhibited microbial growth, and it is also possible that the accumulation of autotoxic substances, which are produced by the undecomposed and aged litter of cherry tomato, affects the microbial groups and amounts [35]. Previous studies indicated that the quality and quantity of plant waste entering soil can affect soil microorganisms and microbial processes [36]. Under long-term single cultivation patterns with the rice/cherry tomato rotation, the microbial communities would be influenced because of more decomposition and other compounds (e.g., allelochemicals) in the soil [37]. Furthermore, if the litter is always the same (in case of long-term rotation of the same crop), this can create a negative feedback by affecting the microbiota negatively. The cherry tomato belongs to shrubs, while the effect of each shrub on the soil matrix depends mainly on the chemical properties of the shrub litter, which alters the chemical profile of the soil and shapes the associated microbiota [38].
The community composition of soil microbes is very complex, and microbes can interact with each other through competition, promotion, inhibition, etc., to form a complex microbial network [37,38,39,40,41,42]. In this research, the microbial community structure shifted significantly after continuously planting 5a to 7a with the rice/cherry tomato rotation (Figure 3). We found that the seven phyla of Proteobacteria, Acidobacteria, Chloroflexi, Actinobacteria, Gemmatimonadetes, Bacteroidetes and Nitrospirae were common dominant bacteria in different planting years with the rice/cherry tomato rotation (Figure 1a), and their relative abundances have already occupied 90–94% in soil, indicating they play crucial roles on maintaining the functional stability of rice/cherry tomato ecosystem. Proteobacteria can accumulate soil nutrients and promote plant growth and stress resistance [24,43]. Acidobacteria can decompose animal and plant residues and take part in the metabolism of single-carbon compounds in soils with low nutrients [44]. Chloroflexi can assimilate and absorb all kinds of organic acids from biotic and abiotic sources in the environment [45]. Actinobacteria are an important source of antibiotics, biocides and antifungal agents in agricultural production and can also promote crop growth [46]. Bacteroidetes contribute to the nitrogen cycle and nutrient turnover in soil [47]. Gemmatimonadetes can prevent and control certain plant diseases [48]. Nitrospirae play a crucial role in nitrite redox and the carbon cycle [49]. In this study, the relative abundances of Proteobacteria and Actinobacteria decreased gradually during 3a to 7a. However, those of Gemmatimonadetes, Bacteroidetes, Chloroflexi, and Nitrospirae increased year by year during 3a to 5a or 3a to 7a, while they began to decrease gradually after 5a or 7a (Figure 1a). In other words, it would break the balance of the soils’ dominant bacteria after continuously planting 5a to 7a with the rice/cherry tomato rotation.
Soil fungi are much less abundant than bacteria and are quite sensitive to the changes of soil environment [50]. Long-term continuous cropping would inhibit the growth of soil-beneficial microbes, resulting in a decrease in antagonistic microbe and a large increase in pathogenic microorganisms [51,52]. In this study, the pathogenic fungi Fusarium were detected, some of which can cause vascular wilt diseases or fruit rot of tomatoes [53,54], and its relative abundance decreased year by year during 1a to 7a (Figure 2b). Aspergillus is a conditionally pathogenic fungus widely distributed in nature [55], whose relative abundance declined year by year during 1a to 5a (Figure 2a). The abundances of Mortierella, Tichodrma and Penicillium increased gradually during 1a to 5a or 1a to 7a (Figure 2c–e); these fungi are all potential biocontrol agents [24,56,57]. It is worth noting that the relative abundances of the above-mentioned pathogenic fungi began to increase again, while beneficial fungi began to decline again after 5a or 7a. That is, it would also break the balance of soil dominant fungi after continuously planting 5a to 7a with the rice/cherry tomato rotation.

4.2. Correlation between Soil Environmental Factors and Soil Microbial Communities

In this study, the RDA results showed that the available P, available Fe and available Zn were common environmental factors affecting the soil bacteria and fungi communities in different planting years with the rice/cherry tomato rotation. Different studies have also confirmed that soil available P and microelements Fe and Zn were the important factors affecting soil microbial communities [56,57,58,59,60,61]. In recent years, the amount of compound fertilizer was increased year by year, while that of organic fertilizer was little or not used during planting cherry tomato, resulting in soil acidification and soil nutrient imbalance. The soil pH value significantly decreased when continuously planting 7a with the rice/cherry tomato rotation. However, the soil available P content increased year by year with the extension of crop rotation years during 1a to 10a (Table 1), but soil available Fe and available Zn contents declined year by year with the extension of crop rotation years (Table 2). The above results indicate that it is necessary to carry out regional soil testing and formula fertilization technology so as to avoid the aggravation of soil acidification, soil quality decline and environmental pollution caused by excessive nutrients in future fertilization practices.

5. Conclusions

After continuously planting 5a to 7a with the rice/cherry tomato rotation, the microbial community structure was changed, the microbial diversity declined in soil, and soil acidification and nutrient imbalance were aggravated. In conclusion, 5a to 7a was the appropriate rotation period for rice/cherry tomato; otherwise, the soil micro-ecological balance would break and lead to new continuous cropping obstacles of cherry tomato to a certain extent.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su151310148/s1, Table S1. Geographical location and planting area size of the study area.

Author Contributions

Funding acquisition, X.D.; Investigation, H.Y. and J.S.; Methodology, Y.L.; Resources, C.W.; Writing—original draft, X.D.; Writing—review & editing, H.Y., H.T. and C.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Hainan Province Science and Technology Special Fund of China, grant number “ZDYF2021XDNY137”.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Padalia, K.; Bargali, S.S.; Bargali, K.; Khulbe, K. Microbial biomass carbon and nitrogen in relation to cropping systems in Central Himalaya, India. Curr. Sci. 2018, 115, 1741–1750. [Google Scholar] [CrossRef]
  2. Padalia, K.; Bargali, S.S.; Bargali, K.; Manral, V. Soil microbial biomass phosphorus under different land use systems. Trop. Ecol. 2022, 63, 30–48. [Google Scholar] [CrossRef]
  3. Manral, V.; Bargali, K.; Bargali, S.S.; Karki, H.; Chaturvedi, R.K. Seasonal dynamics of soil microbial biomass C, N and P along an altitudinal gradient in Central Himalaya, India. Sustainability 2023, 15, 1651. [Google Scholar] [CrossRef]
  4. Pant, M.; Negi, G.C.S.; Kumar, P. Macrofauna contributes to organic matter decomposition and soil quality in Himalayan agroecosystems, India. Appl. Soil Ecol. 2017, 120, 20–29. [Google Scholar] [CrossRef]
  5. Bargali, S.S.; Padalia, K.; Bargali, K. Effects of tree fostering on soil health and microbial biomass under different land use systems in central Himalaya. Land Degrad. Dev. 2019, 30, 1984–1998. [Google Scholar] [CrossRef]
  6. Karki, H.; Bargali, K.; Bargali, S.S. Dynamics of fine root and soil nitrogen in Mangifera indica based agroforestry systems in Central Himalaya, India. Land Degrad. Dev. 2022, 33, 3523–3538. [Google Scholar] [CrossRef]
  7. Shahi, C.; Bargali, S.S.; Bargali, K.; Vibhuti. Dry matter dynamics and CO2 mitigation in the herb layer of Central Himalayan agroecosystems along an altitudinal gradient, India. Trop. Ecol. 2023, 64, 180–192. [Google Scholar] [CrossRef]
  8. Zhu, S.W.; Gao, T.P.; Liu, Z.; Ning, T.Y. Rotary and subsoiling tillage rotations influence soil carbon and nitrogen sequestration and crop yield. Plant Soil Environ. 2022, 68, 89–97. [Google Scholar] [CrossRef]
  9. Ma, Z.M.; Guan, Z.J.; Liu, Q.C.; Hu, Y.Y.; Liu, L.F.; Wang, B.Q.; Huang, L.F.; Li, H.F.; Yang, Y.F.; Han, M.K.; et al. Chapter Four—Obstacles in continuous cropping: Mechanisms and control measures. Adv. Agron. 2023, 179, 205–256. [Google Scholar]
  10. Ali, A.; Ghani, M.I.; Ding, H.; Iqbal, M.; Cheng, Z.; Cai, Z. Arbuscular mycorrhizal inoculum coupled with organic substrate induces synergistic effects for soil quality changes, and rhizosphere microbiome structure in long-term monocropped cucumber planted soil. Rhizosphere 2021, 20, 100428. [Google Scholar] [CrossRef]
  11. Chen, P.; Wang, Y.Z.; Liu, Q.Z.; Zhang, Y.T.; Li, X.Y.; Li, H.Q.; Li, W.H. Phase changes of continuous cropping obstacles in strawberry (Fragaria × ananassa Duch.) production. Appl. Soil Ecol. 2020, 155, 103626. [Google Scholar] [CrossRef]
  12. Zhao, F.; Zhang, Y.; Li, Z.; Shi, J.; Zhang, G.; Zhang, H.; Yang, L. Vermicompost improves microbial functions of soil with continuous tomato cropping in a greenhouse. J. Soil Sediment. 2020, 20, 380–391. [Google Scholar] [CrossRef]
  13. Cardinale, B.J.; Srivastava, D.S.; Duffy, J.E.; Wright, J.P.; Downing, A.L.; Sankaran, M.; Jouseau, C. Effects of biodiversity on the functioning of trophic groups and ecosystems. Nature 2006, 443, 989–992. [Google Scholar] [CrossRef] [PubMed]
  14. Zhou, X.; Tian, L.; Zhang, J.F.; Ma, L.N.; Li, X.J.; Tian, C.J. Rhizospheric fungi and their link with the nitrogen-fixing Frankia harbored in host plant Hippophae rhamnoides L. J. Basic Microb. 2017, 57, 1055–1064. [Google Scholar] [CrossRef] [PubMed]
  15. Huang, X.; Zhao, J.; Zhou, X.; Han, Y.X.; Zhang, J.B.; Cai, Z.C. How green alternatives to chemical pesticides are environmentally friendly and more efficient. Eur. J. Soil Sci. 2019, 70, 518–529. [Google Scholar] [CrossRef]
  16. Liu, Z.X.; Liu, J.J.; Yu, Z.H.; Li, Y.S.; Hu, X.J.; Gu, H.D.; Li, L.J.; Jin, J.; Liu, X.B.; Wang, G.H. Archaeal communities perform an important role in maintaining microbial stability under long term continuous cropping systems. Sci. Total Environ. 2022, 838, 156413. [Google Scholar] [CrossRef]
  17. Jaiswal, A.K.; Elad, Y.; Paudel, I.; Graber, E.R.; Cytryn, E.; Frenkel, O. Linking the belowground microbial composition, diversity and activity to soil borne disease suppression and growth promotion of tomato amended with biochar. Sci. Rep. 2017, 7, 44382. [Google Scholar] [CrossRef] [Green Version]
  18. Sui, J.; Wang, X.; Liu, Z.; Sa, R.; Hu, Y.; Wang, C. A plant growth promoting bacterium alters the microbial community of continuous cropping poplar trees’rhizosphere. J. Appl. Microbiol. 2019, 126, 1209–1220. [Google Scholar] [CrossRef]
  19. Li, J.; Cheng, X.Y.; Chu, G.X.; Hu, B.W.; Tao, R. Continuous cropping of cut chrysanthemum reduces rhizospheric soil bacterial community diversity and co-occurrence network complexity. Appl. Soil Ecol. 2023, 185, 104801. [Google Scholar] [CrossRef]
  20. Chongtham, I.R.; Bergkvist, G.; Watson, C.A.; Sandström, E.; Bengtsson, J.; Öborn, I. Factors influencing crop rotation strategies on organic farms with different time periods since conversion to organic production. Biol. Agric. Hortic. 2016, 33, 14–27. [Google Scholar] [CrossRef]
  21. Wright, P.J.; Falloon, R.E.; Hedderley, D. A long-term vegetable crop rotation study to determine effects on soil microbial communities and soil borne diseases of potato and onion. N. Z. J. Crop Hortic. Sci. 2017, 45, 29–54. [Google Scholar] [CrossRef]
  22. Pretty, J.; Bharucha, Z.P. Sustainable intensification in agricultural systems. Ann. Bot. 2014, 114, 1571–1596. [Google Scholar] [CrossRef] [PubMed]
  23. Wang, F.Y.; Zhang, X.M.; Wei, M.T.; Wang, Y.; Liang, Z.S.; Xia, P.G. Appropriate crop rotation alleviates continuous cropping barriers by changing rhizosphere microorganisms in Panax notoginseng. Rhizosphere 2022, 23, 100568. [Google Scholar] [CrossRef]
  24. Feng, C.; Yi, Z.W.; Jiang, X.S. Rotations improve the diversity of rhizosphere soil bacterial communities, enzyme activities and tomato yield. PLoS ONE 2023, 18, e0270944. [Google Scholar] [CrossRef]
  25. Vibhuti, C.S.; Bargali, K.; Bargali, S.S. Bargali Seed germination and seedling growth parameters of rice (Oryza sativa L.) varieties as affected by salt and water stress. Indian J. Agr. Sci. 2015, 85, 102–108. [Google Scholar]
  26. Dai, Y.Q.; Wang, Z.; Li, J.; Xu, Z.; Qian, C.; Xia, X.D.; Liu, Y.; Feng, Y.F. Tofu by-product soy whey substitutes urea: Reduced ammonia volatilization, enhanced soil fertility and improved fruit quality in cherry tomato production. Environ. Res. 2023, 226, 115662. [Google Scholar] [CrossRef]
  27. Zhu, Q.S. Grafting culture technology of cherry tomato in Lingshui County. China Agric. Technol. Ext. 2017, 33, 32–33. (In Chinese) [Google Scholar]
  28. Liu, H.F.; Han, H.W.; Wang, Q.; Zhuang, H.M.; Wang, H. Effect of vegetables-tomato rotation on soil microbial diversity, enzyme activity and physicochemical properties of vegetables in greenhouse. Acta Microbiol. Sinica 2021, 61, 167–182. (In Chinese) [Google Scholar]
  29. Lu, R.K. Analytical Methods of Soil and Agro-Chemistry; China Agricultural Science and Technology Press: Beijing, China, 2000. (In Chinese) [Google Scholar]
  30. Wu, X.Y.; Shan, Y.; Li, Y.; Wu, C.Y. The soil nutrient environment determines the strategy by which bacillus velezensis HN03 suppresses Fusarium wilt in banana plants. Front. Plant Sci. 2020, 11, 599904. [Google Scholar] [CrossRef] [PubMed]
  31. Hu, Y.T.; Wang, Y.N.; Cui, L. Effects of crop rotation and continuous cropping on the bacterial diversity of carrot rhizosphere and non-rhizosphere. Genomics Appl. Biol. 2019, 38, 2078–2085. (In Chinese) [Google Scholar]
  32. Jiao, X.L.; Zhang, X.S.; Lu, X.H.; Qin, R.; Gao, W.W. Effects of maize rotation on the physicochemical properties and microbial communities of American ginseng cultivated soil. Sci. Rep. 2019, 9, 9–99. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Tian, Y.Q.; Zhang, X.Y.; Wang, J.G.; Gao, L.H. Soil microbial communities associated with the rhizosphere of cucumber under different summer cover crops and residue management: A 4-year field experiment. Sci. Hortic. 2013, 150, 100–109. [Google Scholar] [CrossRef]
  34. Zhao, Q.; Xiong, W.; Xing, Y.Z.; Sun, Y.; Lin, X.J.; Dong, Y.P. Long-term coffee monoculture alters soil chemical properties and microbial communities. Sci. Rep. 2018, 8, 6116. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Mazzoleni, S.; Bonanomi, G.; Incerti, G.; Chiusano, M.L.; Termolino, P.; Mingo, A.; Senatore, M.; Giannino, F.; Carteni, F.; Rietkerk, M.; et al. Inhibitory and toxic effects of extracellular self-DNA in litter: A mechanism for negative plant-soil feedbacks? New Phytol. 2015, 205, 1195–1210. [Google Scholar] [CrossRef] [Green Version]
  36. Bini, D.; dos Santos, C.A.; Bouillet, J.P.; de Morais Goncalves, J.L.; Nogueira Cardoso, E.J.B. Eucalyptus grandis and Acacia mangium in monoculture and intercropped plantations: Evolution of soil and litter microbial and chemical attributes during early stages of plant development. Appl. Soil Ecol. 2013, 63, 57–66. [Google Scholar] [CrossRef]
  37. Bonanomi, G.; Zotti, M.; Idbella, M.; Mazzoleni, S.; Abd-ElGawad, A.M. Microbiota modulation of allelopathy depends on litter chemistry: Mitigation or exacerbation? Sci. Total Environ. 2021, 776, 145942. [Google Scholar] [CrossRef]
  38. Idbellaa, M.; De Filippis, F.; Zotti, M.; Sequino, G.; Abd-ElGawad, A.M.; Fechtali, T.; Mazzoleni, S.; Bonanomi, G. Specific microbiome signatures under the canopy of Mediterranean shrubs. Appl. Soil Ecol. 2022, 173, 104407. [Google Scholar] [CrossRef]
  39. Banerjee, S.; Walder, F.; Büchi, L.; Meyer, M.; Held, A.Y.; Gattinger, A.; Keller, T.; Charles, R.; van der Heijden, M.G.A. Agricultural intensification reduces microbial network complexity and the abundance of keystone taxa in roots. ISME J. 2019, 13, 1722–1736. [Google Scholar] [CrossRef] [Green Version]
  40. Ma, B.; Wang, H.; Dsouza, M.; Lou, J.; He, Y.; Dai, Z.M.; Brookes, P.C.; Xu, J.M.; Gilbert, J.A. Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China. ISME J. 2016, 10, 1891–1901. [Google Scholar] [CrossRef]
  41. Morriën, E.; Hannula, S.E.; Snoek, L.B.; Helmsing, N.R.; Zweers, H.; De Hollander, M.; Soto, R.L.; Bouffaud, M.L.; Buée, M.; Dimmers, W. Soil networks become more connected and take up more carbon as nature restoration progresses. Nat. Commun. 2017, 8, 14349. [Google Scholar] [CrossRef] [Green Version]
  42. Shi, S.J.; Nuccio, E.E.; Shi, Z.J.; He, Z.L.; Firestone, M.K. The interconnected rhizosphere: High network complexity dominates rhizosphere assemblages. Ecol. Lett. 2016, 19, 926–936. [Google Scholar] [CrossRef] [Green Version]
  43. Ling, N.; Wang, T.; Kuzyakov, Y. Rhizosphere bacteriome structure and functions. Nat. Commun. 2022, 13, 836. [Google Scholar] [CrossRef] [PubMed]
  44. Fierer, N.; Lauber, C.L.; Ramirez, K.S.; Zaneveld, J.; Bradford, M.A.; Knight, R. Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients. ISME J. 2012, 6, 1007–1017. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Samaddar, S.; Truu, J.; Chatterjee, P.; Truu, M.; Kim, K.; Kim, S.; Seshadri, S.; Sa, T. Long-term silicate fertilization increases the abundance of Actinobacterial population in paddy soils. Biol. Fertil. Soils 2019, 55, 109–120. [Google Scholar] [CrossRef]
  46. Barka, E.A.; Vatsa, P.; Sanchez, L. Taxonomy, physiology and natural products of Actinobacteria. Microbiol. Mol. Biol. R. 2016, 80, 1–43. [Google Scholar] [CrossRef] [Green Version]
  47. Yousuf, B.; Keshri, J.; Mishra, A.; Jha, B. Application of targeted metagenomics to explore abundance and diversity of CO2-fixing bacterial community using cbbL gene from the rhizosphere of Arachis hypogaea. Gene 2012, 506, 18–24. [Google Scholar] [CrossRef]
  48. Shen, C.; Liang, W.; Shi, Y.; Lin, X.G.; Zhang, H.Y.; Wu, X.; Xie, G.; Chain, P.; Grogan, P.; Chu, H.Y. Contrasting elevational diversity patterns between eukaryotic soil microbes and plants. Ecology 2014, 95, 3190–3202. [Google Scholar] [CrossRef] [Green Version]
  49. Pachiadaki, M.G.; Sintes, E.; Bergauer, K.; Brown, J.M.; Record, N.R.; Swan, B.K.; Mathyer, M.E.; Hallam, S.J.; Lopaz-Garcla, P.; Takaki, Y.; et al. Major role of nitrite-oxidizing bacteria in dark ocean carbon fixation. Science 2017, 358, 1046–1051. [Google Scholar] [CrossRef] [Green Version]
  50. Wakelin, S.A.; Macdonald, L.M.; Rogers, S.L. Habitat selective factors influencing the structural composition and functional capacity of microbial communities in agricultural soils. Soil Biol. Biochem. 2008, 40, 803–813. [Google Scholar] [CrossRef]
  51. Gao, Z.Y.; Han, M.K.; Hu, Y.Y.; Li, Z.Q.; Ma, Z.M. Effects of continuous cropping of sweet potato on the fungal community structure in rhizospheric soil. Front. Microbiol. 2019, 10, 2269. [Google Scholar] [CrossRef]
  52. Liu, Z.X.; Liu, J.J.; Yu, Z.H.; Yao, Q.; Li, Y.S.; Liang, A.Z.; Zhang, W.; Mi, G.; Jin, J.; Liu, X.B.; et al. Long-term continuous cropping of soybean is comparable to crop rotation in mediating microbial abundance, diversity and community composition. Soil Till. Res. 2020, 197, 104503. [Google Scholar] [CrossRef]
  53. Gordon, T.R. Fusarium oxysporum and the Fusarium Wilt Syndrome. Annu. Rev. Phytopathol. 2017, 55, 23–39. [Google Scholar] [CrossRef] [PubMed]
  54. Wang, J.H.; Feng, Z.H.; Han, Z.; Song, S.Q.; Lin, S.H.; Wu, A.B. First report of pepper fruit rot caused by Fusarium concentricum in China. Plant Dis. 2013, 97, 1657. [Google Scholar] [CrossRef] [PubMed]
  55. Jin, L.Y.; Guo, N.; Shi, J.; Zhang, H.J.; Liu, S.S.; Zhang, J.Q. Detection and analysis of fungi carried by maize grain in Huang-Huai-Hai summer maize region. Scientia Agric. Sinica. 2018, 51, 3508–3519. (In Chinese) [Google Scholar]
  56. Zapata-Sarmiento, D.H.; Palacios-Palaa, E.F.; Rodríguez-Hernándezb, A.A.; Melchora, D.L.M.; Rodríguez-Monroya, M.; Sepúlveda-Jiménez, M. Trichoderma asperellum, a potential biological control agent of Stemphylium vesicarium, on onion (Allium cepa L.). Biol. Control 2020, 140, 104105. [Google Scholar] [CrossRef]
  57. Enebe, M.C.; Babalola, O.O. Effects of inorganic and organic treatments on the microbial community of maize rhizosphere by a shotgun metagenomics approach. Ann. Microbiol. 2020, 70, 49. [Google Scholar] [CrossRef]
  58. Ding, L.J.; Su, J.Q.; Xu, H.J.; Jia, Z.J.; Zhu, Y.G. Long-term nitrogen fertilization of paddy soil shifts iron-reducing microbial community revealed by RNA-13C-acetate probing coupled with pyrosequencing. ISME J. 2015, 9, 721–734. [Google Scholar] [CrossRef] [Green Version]
  59. Muehe, E.M.; Weigold, P.; Adaktylou, I.J.; Planer-Friedrich, B.; Kraemer, U.; Kappler, A.; Behrens, S. Rhizosphere microbial community composition affects cadmium and zinc uptake by the metal-hyper accumulating plant Arabidopsis halleri. Appl. Environ. Microbiol. 2015, 81, 2173–2181. [Google Scholar] [CrossRef] [Green Version]
  60. Sheremet, A.; Jones, G.M.; Jarett, J.; Bowers, R.M.; Bedard, I.; Culham, C.; Eloe-Fadrosh, E.A.; Ivanova, N.; Malmstrom, R.R.; Grasby, S.E.; et al. Ecological and genomic analyses of candidate phylum WPS-2 bacteria in an unvegetated soil. Environ. Microbiol. 2020, 22, 3143–3157. [Google Scholar] [CrossRef]
  61. Xu, J.S.; Gao, W.; Zhao, B.Z.; Chen, M.Q.; Ma, L.; Jia, Z.J.; Zhang, J.B. Bacterial community composition and assembly along natural sodicity/salinity gradient in surface and subsurface soils. Appl. Soil Ecol. 2021, 157, 103731. [Google Scholar] [CrossRef]
Sustainability 15 10148 g001 550
Figure 1. Composition of microbial communities at phylum level in soils from different planting years with rice/cherry tomato rotation. (a) Bacteria. (b) Fungi. 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively.
Figure 1. Composition of microbial communities at phylum level in soils from different planting years with rice/cherry tomato rotation. (a) Bacteria. (b) Fungi. 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively.
Sustainability 15 10148 g001
Sustainability 15 10148 g002 550
Figure 2. Soils’ predominant fungi at genus level in different planting years with rice/cherry tomato rotation. (a) Aspergillus; (b) Fusarium; (c) Mortierella; (d) Trichoderma; (e) Penicillum. 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively. Different lowercase letters a,b,c,d above the bars indicate significant differences among all the rotation years according to one-way ANOVA with Duncan’s multiple range tests (p ≤ 0.05).
Figure 2. Soils’ predominant fungi at genus level in different planting years with rice/cherry tomato rotation. (a) Aspergillus; (b) Fusarium; (c) Mortierella; (d) Trichoderma; (e) Penicillum. 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively. Different lowercase letters a,b,c,d above the bars indicate significant differences among all the rotation years according to one-way ANOVA with Duncan’s multiple range tests (p ≤ 0.05).
Sustainability 15 10148 g002
Sustainability 15 10148 g003 550
Figure 3. Beta diversity of bacteria and fungi communities in soils from different planting years with the rice/cherry tomato rotation. Non-metric multidimensional scaling (NMDS) ordination based on operational taxonomic units for (a) bacteria and (b) fungi. (A stress value > 0.2 indicates that this method is not appropriate; an R value > 0 indicates that the intra-group distance is smaller than the inter-group distance, which means that the grouping is valid; a p value ≤ 0.05 indicates a significant difference). 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively.
Figure 3. Beta diversity of bacteria and fungi communities in soils from different planting years with the rice/cherry tomato rotation. Non-metric multidimensional scaling (NMDS) ordination based on operational taxonomic units for (a) bacteria and (b) fungi. (A stress value > 0.2 indicates that this method is not appropriate; an R value > 0 indicates that the intra-group distance is smaller than the inter-group distance, which means that the grouping is valid; a p value ≤ 0.05 indicates a significant difference). 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively.
Sustainability 15 10148 g003
Sustainability 15 10148 g004 550
Figure 4. Redundancy analysis (RDA) of bacteria (a) and fungi (b) in the soils from different rotation years of rice/cherry tomato. 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively.
Figure 4. Redundancy analysis (RDA) of bacteria (a) and fungi (b) in the soils from different rotation years of rice/cherry tomato. 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively.
Sustainability 15 10148 g004
Table
Table 1. Basic physicochemical properties in soils from different planting years with rice/cherry tomato rotation.
Table 1. Basic physicochemical properties in soils from different planting years with rice/cherry tomato rotation.
Planting
Years		pHOM
(g·kg−1)		AN
(mg·kg−1)		AP
(mg·kg−1)		AK
(mg·kg−1)		Ca
(mg·kg−1)		Mg
(mg·kg−1)		S
(mg·kg−1)
1a4.99 ± 0.14 b24.0 ± 1.35 a107 ± 13.3 c26.7 ± 0.79 c160 ± 9.32 b321 ± 38.5 d13.3 ± 2.67 b0.38 ± 0.05 b
3a5.03 ± 0.05 b21.3 ± 1.03 b171 ± 5.15 a56.2 ± 4.44 b163 ± 20.4 b677 ± 71.6 a60.4 ± 9.97 a0.51 ± 0.04 a
5a5.32 ± 0.07 a18.4 ± 0.81 c133 ± 14.5 b59.7 ± 4.50 b166 ± 8.42 b570 ± 41.7 b59.2 ± 5.41 a0.28 ± 0.05 c
7a4.79 ± 0.16 c17.4 ± 1.90 c112 ± 5.76 c61.5 ± 4.73 b218 ± 14.7 a408 ± 36.1 c54.2 ± 6.16 a0.26 ± 0.04 c
10a4.48 ± 0.16 d12.0 ± 1.17 d107 ± 11.4 c73.0 ± 4.11 a168 ± 21.3 b268 ± 22.7 d51.5 ± 4.44 a0.26 ± 0.05 c
OM—organic matter, AN—alkali-hydrolyzed nitrogen, AP—available phosphorus, AK—available potassium, Ca—exchangeable calcium, Mg—exchangeable magnesium, S—available sulfur. 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively. Values are the mean ± standard error (n = 3). Different lowercase letters a,b,c,d in each column indicate significant differences among all the rotation years according to one-way ANOVA with Duncan’s multiple range tests (p ≤ 0.05).
Table
Table 2. Micronutrients in soils from different planting years with rice/cherry tomato rotation.
Table 2. Micronutrients in soils from different planting years with rice/cherry tomato rotation.
Planting YearsFe (mg·kg−1)Mn (mg·kg−1)Zn (mg·kg−1)Cu (mg·kg−1)B (mg·kg−1)
1a19.8 ± 2.54 a5.88 ± 0.38 c0.67 ± 0.04 a0.20 ± 0.02 a0.05 ± 0.01 a
3a16.4 ± 0.62 b6.95 ± 0.43 ab0.57 ± 0.04 b0.19 ± 0.05 a0.04 ± 0.00 a
5a14.6 ± 1.20 b7.39 ± 0.51 a0.55 ± 0.08 b0.17 ± 0.02 ab0.05 ± 0.02 a
7a11.4 ± 0.89 c6.31 ± 0.90 bc0.54 ± 0.06 b0.14 ± 0.02 ab0.04 ± 0.01 a
10a9.26 ± 0.83 c5.31 ± 0.35 c0.51 ± 0.02 b0.12 ± 0.01 b0.06 ± 0.00 a
Fe—available iron, Mn—available manganese, Zn—available zinc, Cu—available copper, B—available boron. 1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively. Values are the mean ± standard error (n = 3). Different lowercase letters a,b,c,d in each column indicate significant differences among all the rotation years according to one-way ANOVA with Duncan’s multiple range tests (p ≤ 0.05).
Table
Table 3. Alpha diversity indices of bacteria and fungi community in soils from different planting years with rice/cherry tomato rotation.
Table 3. Alpha diversity indices of bacteria and fungi community in soils from different planting years with rice/cherry tomato rotation.
Planting YearsBacterial α-Diversity IndicesFungal α-Diversity Indices
Chao1ShannonChao1Shannon
1a1877.5 ± 64.3 b8.7179 ± 0.3770 b650.0 ± 36.7 c6.4210 ± 0.2702 d
3a2071.3 ± 76.5 a9.2812 ± 0.1062 a701.7 ± 84.8 b6.8260 ± 0.0766 bc
5a2078.9 ± 107 a9.4095 ± 0.1736 a767.2 ± 78.8 a7.2901 ± 0.3152 a
7a2052.4 ± 65.2 a9.3541 ± 0.1964 a754.3 ± 23.8 a7.0088 ± 0.1273 ab
10a2038.0 ± 101 a9.2806 ± 0.1781 a701.9 ± 41.0 b6.5542 ± 0.1958 cd
1a, 3a, 5a, 7a and 10a represent rice/cherry tomato rotation for 1, 3, 5, 7 and 10 years, respectively. Values are the mean ± standard error (n = 3). Different lowercase letters a,b,c,d in each column indicate significant differences among all the rotation years according to one-way ANOVA with Duncan’s multiple range tests (p ≤ 0.05).
Table
Table 4. Correlations according to Mantel tests between microbial community composition at the phylum level and soil environmental factors for different rotation year of rice/cherry tomato. p value ≤ 0.05 indicates a significant correlation.
Table 4. Correlations according to Mantel tests between microbial community composition at the phylum level and soil environmental factors for different rotation year of rice/cherry tomato. p value ≤ 0.05 indicates a significant correlation.
Environmental FactorsBacterial Community CompositionFungal Community Composition
rprp
pH−0.03010.555−0.12680.781
OM0.09390.2580.18720.178
AN−0.01040.4720.01480.336
AP0.39890.0300.33590.042
AK−0.23020.956−0.04390.539
Ca−0.06940.702−0.15060.903
Mg0.48890.010.18750.197
S−0.01050.454−0.07240.612
Fe0.37610.0110.40640.028
Mn0.00650.4280.03930.312
Zn0.27080.0430.40310.026
Cu0.14780.1350.15780.112
B−0.02480.5000.06050.301
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Deng, X.; Yin, H.; Tan, H.; Li, Y.; Wu, C.; Su, J. Response of Soil Microbial Community Diversity to Long-Term Cultivation of Rice (Oryza sativa L.)/Cherry Tomato (Lycopersicon esculentum Mill.) in Rotation. Sustainability 2023, 15, 10148. https://doi.org/10.3390/su151310148

AMA Style

Deng X, Yin H, Tan H, Li Y, Wu C, Su J. Response of Soil Microbial Community Diversity to Long-Term Cultivation of Rice (Oryza sativa L.)/Cherry Tomato (Lycopersicon esculentum Mill.) in Rotation. Sustainability. 2023; 15(13):10148. https://doi.org/10.3390/su151310148

Chicago/Turabian Style

Deng, Xiao, Hao Yin, Huadong Tan, Yi Li, Chunyuan Wu, and Jiancheng Su. 2023. "Response of Soil Microbial Community Diversity to Long-Term Cultivation of Rice (Oryza sativa L.)/Cherry Tomato (Lycopersicon esculentum Mill.) in Rotation" Sustainability 15, no. 13: 10148. https://doi.org/10.3390/su151310148

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop