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Article

Changes in Physicochemical Properties and Bacterial Communities of Tropical Soil in China under Different Soil Utilization Types

by
Chen He
1,2,†,
Kaikai Li
3,†,
Changli Wen
1,
Jinku Li
1,
Pingshan Fan
1,
Yunze Ruan
1,
Lei Meng
1,* and
Zhongjun Jia
4,5,*
1
College of Tropical Crops, Hainan University, Haikou 570228, China
2
Sanya Nanfan Research Institute of Hainan University, Hainan University, Sanya 572025, China
3
Hainan Research Academy of Environmental Sciences, Haikou 571126, China
4
State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
5
Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2023, 13(7), 1897; https://doi.org/10.3390/agronomy13071897
Submission received: 16 May 2023 / Revised: 30 June 2023 / Accepted: 12 July 2023 / Published: 18 July 2023
(This article belongs to the Section Soil and Plant Nutrition)
Browse Figures
Versions Notes

Abstract

:
The primary purpose of our study is to clarify the differences in physicochemical properties and microbial community composition with the continuous evolution of soil utilization types. Here, we used natural forest soil (NS), healthy banana garden soil (HS), diseased banana garden soil (DS), and paddy soil (PS) in tropical areas of Hainan Province to conduct this study. According to our research, the abundance and diversity of soil bacteria (HS/DS and PS) decrease significantly as soil utilization types evolve. In healthy banana soil, the amount of Actinobacteria and Firmicutes at the bacterial phylum level is more significant than in other soil utilization types. It was observed that the bacterial community structure in NS was notably distinct from that in HS and PS. Apart from paddy soil, the bacterial makeup of the other two soil utilization types mainly remained consistent. Pathogenic soil (DS) undergoes significant changes in its chemical properties. These changes are primarily seen as decreased pH and organic carbon content and increased C/N and inorganic nitrogen content (NH4+, NO3−). This suggests that a specific type of microorganism (Fusarium oxysporum f. sp. cubense) can cause a significant shift in the soil environment, leading to an unexpected change in soil type. Therefore, to ensure that the soil is healthy, we must balance the soil microbial community composition, promote the increase of the beneficial microbial species and quantity, and create an environment suitable for microbial growth.

1. Introduction

Soil is a crucial part of the Earth’s ecosystem, as it has the largest active carbon pool and is one of the most diverse and complex environmental matrices [1,2,3]. Small changes in soil carbon or nitrogen pools can greatly affect the concentrations of carbon dioxide (CO2) and nitrous oxide (N2O) in the atmosphere [4,5]. Land use changes can drive global change and alter ecosystem carbon and nitrogen cycles [6]. The dynamics of soil carbon (C) and nitrogen (N) under different land use changes are vital to carbon and nitrogen cycle mechanisms and have been a focal interest for research [7]. In recent years, the massive application of chemical fertilizers in agricultural production has resulted in substantial environmental risks, such as serious damage to the soil’s physicochemical properties [8], an increase in greenhouse gas emissions [9], loss of nutrients, and disturbance of the soil microbial community [10,11]. Soil degradation caused by these factors decreases soil fertility and further impacts cash crops’ production and nutritional quality, thereby threatening global food security.
Soil microorganisms are essential to the ecosystem and drive soil functional processes, such as nutrient cycling and C and N fixation [12,13]. Healthy soil and plant disease control relies on the vital biological processes facilitated by soil microorganisms. These processes include nutrient cycling, organic matter transformation, and improved plant productivity [14,15]. Soil microorganisms are susceptible to both positive and negative effects of soil management or interference, leading to changes in their taxonomy and function [16]. Because microorganisms are affected by external environmental conditions, soil utilization types may undergo different forms of evolution. Normal evolution is the process of transforming forest soil into healthy banana garden soil (low Fusarium oxysporum f. sp. cubense) or rice soil, while unusual evolution is the process of transforming forest soil into diseased banana garden soil (high Fusarium oxysporum f. sp. cubense), which is no longer suitable for sustained use. Tropical soils are a globally significant store of terrestrial carbon (C) [17], with soil microorganisms playing a key role in adjusting net soil carbon storage through the mineralization of plant residues and soil organic matter (SOM). Studies by Aparna et al. (2016) have demonstrated that fertilization can have a direct and indirect impact on soil microorganisms by altering soil properties and adding nutrients [18,19]. Bonner et al. (2018) have proven that there is a direct correlation between changes in soil microbial communities, land use, and management practices and the resulting functions of the ecosystem; these functions include nitrogen fixation, organic matter decomposition, and soil organic carbon mineralization [20]. Soil bacterial communities also play an essential role in biogeochemical cycles [21]. The decomposition of specific carbon substrates in different land use practices can determine soil bacteria’s different community composition and function [22,23]. As a result of the rapid response of bacteria to changes in the soil environment, bacterial communities were chosen as early bio-indicators of soil quality [24]. Bacterial diversity and community composition are influenced by organic matter, soil pH, soil water content, mineral substances, and fertilization management practices [25,26]. Research has shown that the bacterial community’s functional groups involved in C cycling in long-term agricultural soil differ significantly from those found in primary forest ecosystems. This difference could be attributed to fertilization, which provides microorganisms with numerous carbon sources, leading to improved assimilation and utilization of carbon and promoting an increase in chemical heterotrophic microbes [27]. Alternatively, techniques that do not rely on culture, like 16SrDNA amplicon sequencing and shotgun metagenomics, can offer a basic understanding of the variety and makeup of the entire microbial communities present within the context of environmental conditions and management practices. This ultimately contributes to our overall understanding of this field [28,29,30]. Here, we aim to study the impact of soil type development on the physical, chemical, and bacterial characteristics of tropical soils. We collected samples of various soil utilization types near one another to gain insight into how to manage soil health in tropical regions effectively. Our findings will provide both practical guidance and a theoretical framework for properly utilizing tropical soil.

2. Material and Methods

2.1. Study Sites

The soil used in this experiment is natural forest soil (NS, 19°93′, 110°24′), healthy banana soil (HS, 19°92′, 109°93′), diseased banana soil (DS, 19°93′, 109°94′), and paddy soil (PS, 19°96′, 109°93′) (Figure 1). We judge the health of a banana based on its appearance. To gather soil samples, we collect soil from the vicinity of healthy bananas to obtain healthy banana soil, and we collect soil from around diseased bananas to obtain diseased banana soil. The soil in the experiment site is classified as Ultisols base in the USDA Soil Taxonomy. All soil samples were collected from Chengmai County, Hainan Province (19°23′, 110°15′). Soil samples were drilled from the 0–20 cm soil layer at four random locations. Approximately 1 kg of soil was retained after mixing and sieving through a 2 mm mesh to remove roots, macrofauna, and rocks. Part of the soil sample was dried in the laboratory for chemical analysis, and the remainder was stored at −80 °C for soil microbial analysis.

2.2. Physical and Chemical Analyses

All soil parameters were analyzed according to the methods of Lu (2000) [31]. Soil pH was determined using a soil-to-water ratio of 1:5 (w/v). Soil bulk weight and moisture content were determined by the drying method. Soil organic carbon (SOC) was measured using the K2Cr2O7 oxidation method. A CNS elemental analyzer determined total soil nitrogen (TN). Soil ammonium (NH4+-N) and nitrate (NO3−-N) were measured by the continuous flow analyzer Skalar. Soil microbial respiration was carried out with an indoor culture method, and the amount of CO2 released by microbial decomposition per unit of time was determined by gas chromatography [32].

2.3. Microbial Analyses

The total DNA of the soil microbial genome was extracted using the Fast DNA® Spin Kit for Soil (MP Biomedicals, MP Biomedicals LLC, Santa Ana, CA, USA), following the manufacturer’s protocol. PCR amplification was performed using the 515F/907R (GTGCCAGCMGCCGCGG; CCGTCAATTCMTTTRAGTTT) universal primers. The PCR reaction (20 µL total) contained 10 µL SYBR Premix Ex TaqTM (Takara, Dalian, China), 0.25 µL of each primer, 1 µL DNA template (1–10 ng), and 8.5 µL dd H2O. PCR conditions included a temperature program of 3 min at 95 °C, followed by 39 cycles of 30 s at 95 °C, 30 s at 55 °C, and 30 s at 72 °C, and sequencing analysis was performed using the Illumina NovaSeq platform from Beijing Novogene Co., Ltd, Beijing, China.

2.4. Statistical Analyses

SPSS 24.0 software was used for the statistical analysis of the data. One-way analysis of variance (ANOVA) and least significant difference (LSD) tests (p < 0.05) were used for multiple comparison analyses. Graphs were generated in OriginPro 2018C. Pearson correlation analysis was used to compare the correlation of each index. The Shannon, Chao 1, ACE, and Simpson diversity indices were used to evaluate the diversity of each sample. The R package vegan (4.2.3) performed principal coordinate analysis (PCoA) based on Bray–Curtis distance and permutational multivariate analysis of variance (PERMANOVA). Redundancy analysis (RDA) was conducted to explore the relationships between soil chemical properties and bacteria community structure with the R package vegan (4.2.3).

3. Results

3.1. Differences in Physical and Chemical Properties of Different Utilization Types of Soil

The characteristics of soil, both physical and chemical, play a crucial role in indicating different soil utilization types and have a significant impact on the structure of microbial communities. The pH level of soil in diseased banana (DS) areas was notably lower compared to other utilization types of soil. This suggests that the soil acidity was due to increased soil pathogens, which contributed to the growth of harmful bacteria. The moisture of various soil utilization types differed significantly, with the soil of diseased bananas having a notably higher level than the others. Although the impact of soil utilization types on soil bulk density, total carbon, and total nitrogen content was not clear, the C/N ratio in DS soil was considerably higher than in other soil utilization types. This could be a contributing factor to the rise in soil-borne diseases (Table 1).

3.2. Inorganic N Content, Insoluble Organic Carbon, and Nitrogen Content in Different Utilization Types of Soil

The soil affected by disease had a much higher level of inorganic nitrogen, particularly nitrate nitrogen, than the other treatments. This suggests that a significant amount of inorganic nitrogen was needed to grow harmful bacteria. In addition, the nitrate nitrogen content in the paddy soil was noticeably lower than in the diseased soil, as shown in Figure 2a. The insoluble organic carbon and nitrogen content of the four soil utilization types were similar; however, the insoluble organic carbon and nitrogen content in natural forest soil were significantly higher than in healthy banana garden soil (Figure 2b).

3.3. Carbon Dioxide Emissions, Copy Number of 16S Gene and FOC Gene in Different Utilization Types of Soil

Soil utilization types significantly affect soil microbial populations. The bacterial copy number of natural forest soil was significantly higher than that of other soil utilization types. The bacterial copy number of the healthy banana garden soil was the lowest (Figure 3a). The carbon dioxide emissions of healthy banana garden soil were significantly higher than those of natural forest soil. Carbon dioxide emission was lowest in the diseased banana garden soil (Figure 3b). The FOC gene’s copy number in DS was notably higher than in other soil utilization types. This suggests that FOC thrived in HS, resulting in soil evolution that led to the development of diseased banana garden soil (Figure 3c).

3.4. Alpha Diversity of Bacteria in Different Utilization Types of Soil

Soil utilization types alter the diversity of bacterial communities. The results showed distinct differences in the species diversity of different utilization types of soil. The Chao 1 index and ACE index of natural forest soil were significantly higher than those of other soil utilization types, including paddy soil (Figure 4a,c). The Shannon and Simpson indexes of healthy plantation soil were significantly lower than those of other soil utilization types (Figure 4b,d).

3.5. Community Structure of Bacteria in Different Utilization Types of Soil

At the bacterial phylum level, the relative abundance of Actinobacteria and Firmicutes in healthy plantation soil was significantly higher than that of other utilization types of soil (Figure 5A). The PCoA of the bacterial community structure in different utilization types of soil shows that the first two axes explain 96.00% of the total variance (Figure 5B). In addition, the bacterial community structure of NS was significantly separated from that of HS and PS, but it was closer to DS. RDA analysis found that inorganic nitrogen content significantly affected different soil utilization types (Figure 5C).
At the bacterial genus level, the relative abundance of Bacillus and Streptomyces in healthy plantation soil was significantly higher than that of other soil utilization types (Figure 5D). The PCoA of the bacterial community structure in different soil utilization types shows that the first two axes explain 90.06% of the total variance (Figure 5E). The bacterial community structure of NS was significantly separated from that of HS and PS, but was more similar to DS. RDA analysis found that NO3−, ION, and C/N significantly affected the different soil utilization types (Figure 5F).

3.6. Relationships between Bacteria Community Composition and Soil Properties

After conducting correlation analysis, it was found that NH4+ content had a significant positive correlation with Armatimonadetes and Chloroflexi at the phylum level, but a negative correlation with Firmicutes. NO3− had a significant negative correlation with Cyanobacteria and a positive correlation with AD3 (Figure 6A). At the genus level, WC, C/N, and NO3− were significantly positively correlated with Brevibacillus and O:0319-7L14, while pH was negatively correlated (Figure 6C).
At the phylum level, all soil utilization types shared 16 bacterial species, with only 4 being exclusive to paddy soil (Figure 6B). At the genus level, it was found that 123 bacterial species were common across different soil utilization types, while paddy soil had an additional 56 unique species, which was significantly higher compared to other soil utilization types (Figure 6D).

3.7. Correlation Analysis of Different Utilization Types of Soil Properties

The results showed that pH had a positive correlation with ION, NH4+, NO3−, and bacterial copy number, but a significant negative correlation with soil moisture content and C/N. Our findings suggest that TN and TC have a significant positive correlation. Additionally, TN is positively correlated with ACE, Chao1, ION, and IOC. C/N was found to be negatively correlated with ION and bacterial copy number. Furthermore, we discovered that IOC and ION have a positive correlation, and that pH has a negative correlation with FOC. These results demonstrate that pH and C/N are the main factors influencing the variety of soil properties and community composition (Figure 7).

3.8. Linear Regression Analysis of Different Utilization Types of Soil

Based on the findings presented in Figure 8B–E, it was observed that soil C/N, moisture content, bacterial copy number, and ION were all closely linked to pH levels in a linear manner. Figure 8A,F also show that bacterial copy number and ION were negatively correlated with C/N. These results suggest that soil pH and C/N are important factors that impact the properties of various soil utilization types.

4. Discussion

Various land use types influence soil physical and chemical characteristics, which determine the plant types and soil management techniques used on the field surface [33,34]. Soil’s basic chemical properties provide information about the soil’s nutrient levels. An analysis of variance (ANOVA) for soil properties revealed significant differences among various land use patterns. The presence of soil organic matter is crucial for maintaining soil quality and ecosystem services. It also affects the soil’s ability to retain nutrients [35]. Soil organic matter can also impact soil structure and aggregate distribution by acting as a cementing agent. Aggregation, in turn, physically prevents soil organic matter (SOC) from being mineralized [36] and contributes to carbon sequestration [37]. According to the results, the physical and chemical properties of soil change significantly with the evolution of soil utilization types. This includes a significant decrease in pH and a significant increase in C/N, indicating that soil utilization types have a large impact on critical physical and chemical properties of soil.
The characteristics of carbon metabolism of soil microbial communities can reflect the biological effectiveness and functional diversity of soil microorganisms [38]. The rate at which CO2 is produced is a useful way to measure soil microbial activity. It also indicates how well soil microbial communities can use carbon sources [39]. Previous research has shown that larger residue carbon inputs may result in higher carbon sequestration rates (i.e., higher SOC content) [40], and that soil respiration can be used to indicate biological activity and decomposition of organic residues [41,42]. The high respiration rate of microorganisms in soils might indicate a significant level of microbial productivity in the ecosystem [43]. Here, we demonstrate that the CO2 emissions from healthy banana garden soil and paddy soil were significantly greater than those from natural forest soil. Interestingly, the CO2 emissions from diseased banana garden soil were the lowest. These results suggest that the microbial productivity in healthy banana garden soil and paddy soil is higher, leading to a stronger respiration rate. Our findings are consistent with previous research.
Soil bacteria are important members of the soil microbial community and play a crucial role in the ecosystem. They are involved in several physiological and biochemical processes in soil, such as humus formation, soil organic matter (SOC) decomposition, and nutrient transformation and cycling [44]. Some studies demonstrate that soil bacteria can improve plant growth, resource allocation, and chemical composition using nutrient element turnover in soil [45]. Changes in agricultural management, vegetation, soil fertility, pH, temperature, precipitation, and other factors can affect the community structure and diversity of soil bacteria [46]. The composition of the soil microbial community after applying a fertilization system is primarily affected by the soil chemical properties [47,48]. Previous studies have shown that environmental factors, such as pH, organic carbon, and available phosphorus, can potentially affect soil microbial communities in different ecosystems [49,50]. Wu et al. (2020) suggest that the structure of soil bacterial communities are correlated with SOM and TN [51]. In contrast, bacteria are poorly decomposed and well-osmotic nutrients, which are related to soil solution chemistry [52]. Our results found that the bacterial composition of soil with different soil utilization types varies greatly. With increased disturbance, the bacterial copy number, the Chao 1 index, and ACE decrease significantly.
The diversity of microbes is vital to the global cycling of carbon, yet the structure of the bacterial community is often disregarded. Studies have indicated that changes in land use and the microbial composition of soil communities lead to a reduction in functional diversity. This is linked to certain environmental conditions and bacterial groups, as well as increased intensification [53,54]. For instance, a broader range of C source utilization (amines/amides guild) was related to a high abundance of specific bacterial orders, such as Actinomycetales in low-management categories. Actinomycetales typically exist in soil and serve as saprophytes, breaking down complex organic matter into more absorbable nutrients [55]. In addition, Actinomycetales order has been considered a major contributor to carbohydrate and amino acid metabolism in different environments, including cultivated soils [56,57,58]. We found that the abundance of actinomycetes increases with the evolution of soil utilization types and that the abundance of actinomycetes in banana garden soil is significantly higher than in natural forest soil.

5. Conclusions

Our findings reveal a correlation between land use change and microbial composition and that soil physicochemical properties and microbial community composition undergo significant changes during the continuous evolution of soil utilization types. Over time, soil utilization types undergo changes that result in a significant decrease in the amount and diversity of HS/DS and PS bacteria, except for paddy soil, where the bacteria composition remains largely unchanged. The proliferation of pathogenic bacteria in healthy banana garden soil leads to the evolution of diseased banana garden soil, causing a notable decrease in soil pH and organic carbon content, but a marked increase in soil C/N and inorganic nitrogen content (NH4+, NO3−). Further, it has been determined that the microorganism Fusarium oxysporum f. sp. cubense can greatly impact the quality of soil in a negative way. To maintain healthy soil, it is important to maintain a balanced microbial community composition, encourage the growth of beneficial microbial species, and create a suitable environment for microbial growth. Our findings offer a theoretical foundation for better comprehension of bacterial communities in varied utilization modes.

Author Contributions

Z.J. and L.M. contributed to conceiving and designing the experiment. C.H., K.L., C.W., P.F. and J.L. contributed to performing the experiment and writing the paper. Y.R. contributed to providing materials and reagents. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Project of Sanya Yazhou Bay Science and Technology City (SCKJ-JYRC-2022-94), the Strategic Priority Research Program of Chinese Academy of Sciences (XDA28020203), the National Natural Science Foundation of China (91751204, 32160750, and 31672239), the Postgraduate Innovation Research Project of Hainan Province (Qhyb2022-67), and the PhD Scientific Research and Innovation Foundation of Sanya Yazhou Bay Science and Technology City (HSPHDSRF-2023-12-008).

Data Availability Statement

Not applicable.

Acknowledgments

We would like to thank Joseph Elliot at the University of Kansas for her assistance with English language and grammatical editing of the manuscript. We thank the anonymous reviewers for reviewing our manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Soil utilization types concept map. NS: Natural forest soil; HS: Healthy banana garden soil; DS: Diseased banana garden soil; PS: Paddy soil. Normal evolution is the process of transforming forest soil into healthy banana garden soil (low Fusarium oxysporum f. sp. cubense) or rice soil, while unusual evolution is the process of transforming forest soil into diseased banana garden soil (high Fusarium oxysporum f. sp. cubense), which is no longer suitable for sustained use.
Figure 1. Soil utilization types concept map. NS: Natural forest soil; HS: Healthy banana garden soil; DS: Diseased banana garden soil; PS: Paddy soil. Normal evolution is the process of transforming forest soil into healthy banana garden soil (low Fusarium oxysporum f. sp. cubense) or rice soil, while unusual evolution is the process of transforming forest soil into diseased banana garden soil (high Fusarium oxysporum f. sp. cubense), which is no longer suitable for sustained use.
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Figure 2. Inorganic N content, insoluble organic carbon and nitrogen content in different utilization types of soil. Inorganic N (NH4+, NO3−) content (a), insoluble organic carbon and nitrogen (b) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). IOC: insoluble organic carbon; ION: insoluble organic nitrogen; NH4+: ammonium nitrogen; NO3−: nitrate nitrogen. Different letters indicate significant differences across different soil utilization types (p < 0.05).
Figure 2. Inorganic N content, insoluble organic carbon and nitrogen content in different utilization types of soil. Inorganic N (NH4+, NO3−) content (a), insoluble organic carbon and nitrogen (b) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). IOC: insoluble organic carbon; ION: insoluble organic nitrogen; NH4+: ammonium nitrogen; NO3−: nitrate nitrogen. Different letters indicate significant differences across different soil utilization types (p < 0.05).
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Figure 3. Carbon dioxide emissions, copy number of 16S gene and FOC gene in different utilization types of soil. The copy number of 16S gene (a), carbon dioxide emissions (b) and FOC copy number of 16S gene (c) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), paddy soil (PS). FOC: Fusarium oxysporum f. sp. Cubense. Different letters indicate significant differences across different soil utilization types (p < 0.05).
Figure 3. Carbon dioxide emissions, copy number of 16S gene and FOC gene in different utilization types of soil. The copy number of 16S gene (a), carbon dioxide emissions (b) and FOC copy number of 16S gene (c) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), paddy soil (PS). FOC: Fusarium oxysporum f. sp. Cubense. Different letters indicate significant differences across different soil utilization types (p < 0.05).
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Figure 4. Alpha diversity of bacteria in different utilization types of soil. Chao 1 index (a), Shannon index (b), ACE index (c), Simpson index (d) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). Different letters indicate significant differences across different soil utilization types (p < 0.05).
Figure 4. Alpha diversity of bacteria in different utilization types of soil. Chao 1 index (a), Shannon index (b), ACE index (c), Simpson index (d) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). Different letters indicate significant differences across different soil utilization types (p < 0.05).
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Figure 5. Community structure of bacteria in different utilization types of soil. The relative abundance (A), PCoA (B), and RDA (C) at the bacterial phylum level, the relative abundance (D), PCoA (E), and RDA (F) at the bacterial genus level in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). WC, water content; VW, volume weight; TC, total carbon; TN, total nitrogen; IOC, insoluble organic carbon; ION, insoluble organic nitrogen; NH4+: ammonium nitrogen, NO3−: nitrate nitrogen, CN: total organic carbon (TC)/total nitrogen (TN).
Figure 5. Community structure of bacteria in different utilization types of soil. The relative abundance (A), PCoA (B), and RDA (C) at the bacterial phylum level, the relative abundance (D), PCoA (E), and RDA (F) at the bacterial genus level in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). WC, water content; VW, volume weight; TC, total carbon; TN, total nitrogen; IOC, insoluble organic carbon; ION, insoluble organic nitrogen; NH4+: ammonium nitrogen, NO3−: nitrate nitrogen, CN: total organic carbon (TC)/total nitrogen (TN).
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Figure 6. Relationships between bacteria community composition and soil properties at the bacterial phylum level (A,B), at the bacterial phylum level (C,D) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). WC: water content, VW: volume weight, TC: total organic carbon, TN: total nitrogen, IOC: insoluble organic carbon, ION: insoluble organic nitrogen, NH4+: ammonium nitrogen, NO3−: nitrate nitrogen, CN: total organic carbon (TC)/total nitrogen (TN).
Figure 6. Relationships between bacteria community composition and soil properties at the bacterial phylum level (A,B), at the bacterial phylum level (C,D) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). WC: water content, VW: volume weight, TC: total organic carbon, TN: total nitrogen, IOC: insoluble organic carbon, ION: insoluble organic nitrogen, NH4+: ammonium nitrogen, NO3−: nitrate nitrogen, CN: total organic carbon (TC)/total nitrogen (TN).
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Figure 7. Correlation analysis of different utilization types of soil properties in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). SMC, soil moisture content; SBD, soil bulk density; TC, total carbon; TN, total nitrogen; IOC, insoluble organic carbon; ION, insoluble organic nitrogen; 16S, bacterial gene copy number; CO2, carbon dioxide emissions; FOC: FOC gene copy number; C/N: total organic carbon (TC)/total nitrogen (TN); *, p < 0.05.
Figure 7. Correlation analysis of different utilization types of soil properties in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). SMC, soil moisture content; SBD, soil bulk density; TC, total carbon; TN, total nitrogen; IOC, insoluble organic carbon; ION, insoluble organic nitrogen; 16S, bacterial gene copy number; CO2, carbon dioxide emissions; FOC: FOC gene copy number; C/N: total organic carbon (TC)/total nitrogen (TN); *, p < 0.05.
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Figure 8. Linear regression analysis of 16S and C/N (A), pH and C/N (B), pH and SMC (C), pH and 16S (D), pH and ION (E), C/N and ION (F) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). 16S, bacterial gene copy number; SMC, soil moisture content; ION, insoluble organic nitrogen; C/N: total organic carbon (TC)/total nitrogen (TN); **, p < 0.05.
Figure 8. Linear regression analysis of 16S and C/N (A), pH and C/N (B), pH and SMC (C), pH and 16S (D), pH and ION (E), C/N and ION (F) in natural forest soil (NS), healthy banana soil (HS), diseased banana soil (DS), and paddy soil (PS). 16S, bacterial gene copy number; SMC, soil moisture content; ION, insoluble organic nitrogen; C/N: total organic carbon (TC)/total nitrogen (TN); **, p < 0.05.
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Table
Table 1. Physical and chemical analyses in soil and organic materials.
Table 1. Physical and chemical analyses in soil and organic materials.
Soil Utilization
Types		pHWc
(%)		Vw
(g/cm3)		TC
(g/kg)		TN
(g/kg)		C/N
NS5.92 a44.04 c1.32 a20.17 a1.78 a11.34 b
HS5.14 b47.00 b1.28 a18.90 a1.54 a12.27 a
DS4.91 b51.63 a1.20 a18.93 a1.49 a12.67 a
PS5.32 b47.40 b1.25 a19.12 a1.57 a12.22 a
The various soil utilization types include Natural Forest soil (NS), Healthy banana soil (HS), Diseased banana soil (DS), and Paddy soil (PS). Each soil type was analyzed for specific physical and chemical properties, including water content (Wc), volume weight (Vw), total organic carbon (TC), and TN: total nitrogen (TN), C/N: total organic carbon (TC)/total nitrogen (TN). Different letters indicate significant differences across soil utilization types (p < 0.05).
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He, C.; Li, K.; Wen, C.; Li, J.; Fan, P.; Ruan, Y.; Meng, L.; Jia, Z. Changes in Physicochemical Properties and Bacterial Communities of Tropical Soil in China under Different Soil Utilization Types. Agronomy 2023, 13, 1897. https://doi.org/10.3390/agronomy13071897

AMA Style

He C, Li K, Wen C, Li J, Fan P, Ruan Y, Meng L, Jia Z. Changes in Physicochemical Properties and Bacterial Communities of Tropical Soil in China under Different Soil Utilization Types. Agronomy. 2023; 13(7):1897. https://doi.org/10.3390/agronomy13071897

Chicago/Turabian Style

He, Chen, Kaikai Li, Changli Wen, Jinku Li, Pingshan Fan, Yunze Ruan, Lei Meng, and Zhongjun Jia. 2023. "Changes in Physicochemical Properties and Bacterial Communities of Tropical Soil in China under Different Soil Utilization Types" Agronomy 13, no. 7: 1897. https://doi.org/10.3390/agronomy13071897

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