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Article

Relationships between Rhizosphere Environments and Growth of 10-Year-Old Wild-Simulated Ginseng

by
Yeong-Bae Yun
1,
Kiyoon Kim
2,
Jeong-Hoon Huh
1 and
Yurry Um
1,*
1
Forest Medicinal Resources Research Center, National Institute of Forest Science, Gyeongbuk 36040, Republic of Korea
2
National Forest Seed Variety Center, Korea Forest Service, Chungbuk 27495, Republic of Korea
*
Author to whom correspondence should be addressed.
Agronomy 2023, 13(5), 1313; https://doi.org/10.3390/agronomy13051313
Submission received: 24 March 2023 / Revised: 21 April 2023 / Accepted: 5 May 2023 / Published: 7 May 2023
(This article belongs to the Special Issue Plant-Soil-Microbe Interactions in Natural Soils - Series II)
Browse Figures
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Abstract

:
Wild-simulated ginseng (WSG, Panax ginseng C.A. Meyer) must be cultivated in mountainous forests without installation of artificial facilities or treatment of chemicals. Because cultivation of these medicinal plants requires a long-term period, soil properties and rhizobacteria are known as major factors affecting their growth. This study was aimed to investigate correlations of soil bacterial community with soil chemical properties and growth of 10-year-old WSG. Most of the growth characteristics of WSG were higher in southern region than in northern regions, while leaflet length and leaflet width of WSG were higher in northern regions. In all WSG cultivation sites, the most dominant phyla were Proteobacteria and Acidobacteria in the bacterial community. In Principal component analysis (PCA), soil bacterial community was affected by exchangeable cations (calcium, magnesium), soil pH, total nitrogen, cation exchange capacity, and organic matter. Soil pH was the most effective factor in this study because all studied sites were acidic soils. In spearman’s coefficient analysis, 9 of 13 growth characteristics of WSG showed significantly positive correlation with the relative abundance of Actinobacteria, while rhizome length and number of rootlets showed significant negative correlations with population of Acidobacteria. Therefore, growth characteristics of WSG in different cultivation sites can be affected by various soil environmental factors. These results can help foresters find suitable cultivation sites for WSG.

1. Introduction

Wild-simulated ginseng (WSG), known as Panax ginseng C.A. Meyer, belongs to the Araliaceae family [1]. In South Korea, WSG is cultivated by transplanting seedlings or sowing seeds in mountainous environments managed by the Forestry and Mountain Villages Development Promotion Act without treatment of any chemicals or installation of artificial facilities [2]. Growth, productivity, and physiological characteristics of plants can be affected by exposure to biotic and abiotic triggers [3,4] such as temperature [5], drought [6], heavy metals [7], pathogens [8], and salinity [9]. The rhizosphere is a complicated environment associated with diverse microbial communities that are responsible for affecting soil chemical properties [10]. Soil microbes living symbiotically in rhizosphere soils play a vital role in determining the quality and productivity of soil by supplying nutrients to plants, performing nutrient cycling, removing pollutants, and decomposing organic matter [11]. Furthermore, changes in soil bacterial community structures are affected not only by characteristics of plants (composition of plant species, plant functional traits) [12], but also soil properties (soil pH, organic matter, nitrogen, nutrient availability) [13].
To analyze the soil bacterial community, next generation sequencing (NGS) has been recently used to analyze gene sequences. Pyrosequencing is one of the NGS analysis methods, and is the most representative analysis method. It has been used to investigate bacterial communities in various environments [14]. Environmental factors (soil, forest physiognomy, height above sea level, and so on) might affect the growth of plants and diversity of soil bacteria [15,16]. Furthermore, because WSG is naturally cultivated without installation of artificial facilities and treatments of chemical pesticides or fertilizers, growth characteristics of WSG might be largely influenced by soil environments, forest physiognomy, and soil microbes inhabiting in rhizosphere soils. Therefore, it is necessary to analyze soil bacterial communities, environments, and growth characteristics.
Recently, with increasing national income and interest in clean forest products, studies on soil microorganisms are also increasing to enhance productivity of medicinal products [11]. Microbial communities in ginseng cultivation soils have been investigated through pyrosequencing analysis [17]. Researches on changes in soil microbial communities according to changes in forest environments using NGS are being conducted in the field of forest science [18]. However, studies on correlations of soil microbial communities with environmental factors and growth characteristics are very insufficient. In principle, WSG is cultivated for a long period (more than 7 years). Various studies have been mainly conducted on 7-year-old and 13-year-old WSG. One study has reported correlations between growth and ginsenosides of 4-year-old WSG [19]. However, no such study has been conducted on 10-year-old WSG. To find the most optimal condition for WSG cultivation, it is essential to examine the planned WSG cultivation area.
We hypothesize that the soil bacterial community of WSG cultivation sites may be significantly correlated with soil chemical properties and the growth characteristics of plants. Therefore, the purpose of this study was to understand the growth of 10-year-old WSG in different cultivation sites and to investigate environmental factors affecting their growth through principal component analysis (PCA) and Spearman’s correlation analysis. The results of this study can provide farmers with evidence of the relationship between growth of WSG and soil environments.

2. Materials and Methods

2.1. Collection of Soil Samples Cultivating WSG

Four cultivation sites of 10-year-old WSG were investigated in South Korea (Figure 1). Soil samples (five replicates) were collected from WSG cultivation sites from June to July 2021. Cultivation sites “A” and “B” were located in Gangwon province; cultivation sites “C” and “D” were located in Gyeongsangbuk-do and Jeollabuk-do province, respectively. The bedrock of the cultivation sites “A”, “C”, and “D” are granite, and that of cultivation site “B” is granite gneiss. The soil type of cultivation site “A” is Cambic Umbrisols, “B” is Lithic Leptosols, “C” and “D” are Haplic Cambisols [20]. The mean annual temperatures of the cultivation sites are 10.2 °C, 11.7 °C, 10.6 °C, and 11.7 °C. The mean annual rainfall amounts of the cultivation sites are 1166 mm, 1174.7 mm, 1404.6 mm, and 1022 mm. All WSG cultivation sites were sloped, having slope gradients ranging from 8 to 25°; slope direction was induced southwest, northeast, and southeast. The height above sea level (HASL) was 391–931 m (Table 1). Cultivation site “C” was identified as a broad-leaved forest. Other cultivation sites were shown as mixed forests consisting of both coniferous and broad-leaved trees. The proportion of broad-leaved trees in the “A” and “B” cultivation sites was much higher than that of coniferous trees. Among cultivation sites, both average tree height (TH) and diameter of breast height (DBH) were the highest in cultivation site “A” (TH: 17.95 m, DBH: 24.65 cm). The collected soil samples were collected at a depth within 20 cm and classified into rhizosphere soil and non-rhizosphere soil. For analyzing the soil bacterial community, the rhizosphere soil samples were stored at −20 °C, and for analyzing soil chemical properties, the non-rhizosphere soil samples were sieved using a 2 mm sieve and air-dried at room temperature. Features of the cultivation site of WSG were recorded by measuring the topography (slope gradient, slope direction, and height above sea level) within stipulated 10 m × 10 m plots of each cultivation site, as well as usual forest physiognomy.

2.2. Soil Analysis

After removing the surface soil, soil samples were collected at a depth within 20 cm and temporarily stored in resealable bags immediately. These collected soil samples were dried at room temperature (20 °C) and then passed through a 10-mesh (2 mm) sieve. The soil chemical properties of soil samples were analyzed following the standard analysis manual of the Rural Development Administration (RDA) in South Korea [21]. Briefly, soil pH and electroconductivity were measured in a soil–water suspension (1:5, w/v) using a digital pH meter and EC meter, respectively. Content of organic matter was measured by Walkey–Black method. Contents of total nitrogen and cation exchange capacity were measured by Kjeldhal method. Content of available phosphate was measured by Lancaster extraction method using UV/Vis spectrophotometer and 1-amino-2-naphtol-4-sulfanic acid. Exchangeable cations were measured by Inductively Coupled Plasma Optical Emission Spectrometry.

2.3. Growth Characteristics of WSG Cultivated in Different Sites

Various growth characteristics (stem diameter, stem length, number of leaflets per stem, leaflet length, leaflet width, petiole length, rhizome length, root length, root diameter, number of rootlets, root weight, total weight, and dry weight) of 10-year-old WSG samples were investigated according to the Test Guideline (ginseng) published by Korea Seed and Variety Service (KSVS) [22].

2.4. Extraction of Soil DNA and Polymerase Chain Reaction (PCR) Amplification

Total DNA of each collected soil sample was extracted using a DNeasy Power Soil kit (QIAGEN, Hilden, Germany). After extraction, quality and quantity of DNA were measured with PicoGreen and Nanodrop (Thermo Scientific, Rockford, IL, USA). Each sequenced sample was investigated according to Illumina 16S Metagenomics Sequencing Library protocols (Macrogen, Seoul, Republic of Korea). For amplicon PCR, the V3–V4 region of the 16S rRNA gene of bacteria was targeted using 16S V3–V4 primers [23], including 16S amplicon PCR forward primer (5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGC WGCAG-3′) and 16S amplicon PCR reverse primer (5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGTATCTAATCC-3′). Input gDNA was amplified with 16S V3-V4 primers. A subsequent limited-cycle amplification step was performed to add multiplexing indices and Illumina sequencing adapters. Amplicon PCR conditions were as follows: initial denaturation at 95 °C for 3 min, followed by denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s, and a final extension at 72 °C for 5 min (25 cycles). Conditions for index PCR were as follows: initial denaturation at 95 °C for 3 min, followed by denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s, and a final extension at 72 °C for 5 min (8 cycles). Using PicoGreen, final products were normalized and pooled. Library sizes were verified using a TapeStation DNA screentape D100 (Agilent, Santa Clara, CA, USA).

2.5. Pyrosequencing and Data Processing

The Illumina MiSeq™ sequencing system (Illumina Inc., San Diego, CA, USA) was used to perform bacterial DNA sequencing. Mothur pipeline was used to process raw sequences of bacterial DNA (version 1.43.0, The University of Michigan, Ann Arbor, MI, USA) [24]. Forward and reverse reads obtained from the Illumina platform were assembled. Sequences with a quality score less than 20 (<20) and ambiguous nucleotides were discarded before performing downstream analysis. Resulting sequences spanning the V3–V4 region were measured for presence of chimera using the function chimera.uchime. Taxonomic classification was performed using ‘Greengenes reference database’ for bacteria. Greengenes were used to make the best combination of speed and quality [25]. Sequences were clustered into operational taxonomic units (OTUs) at 97% similarity level using distance-based greedy clustering method (DGC) in Mothur. OTUs with less than 10 sequences were discarded to reduce false diversity.

2.6. Data Analysis and Principal Coordinate Analysis

To investigate the significance of soil properties and growth characteristics of samples in different cultivation sites, all data are expressed as means ± standard error (SE). Statistical Analysis System (SAS) version 9.4 was used to perform statistical analyses (SAS Institute, Cary, NC, USA) for one-way analysis of variance (ANOVA) and Duncan’s test, with statistical significance set at p < 0.05 [25]. Data analysis and processing of 16S rRNA amplicon data were performed following the guidelines [26]. Principal component analysis (PCA) was performed using Mothur to visualize the relationship with soil chemical properties based on soil bacterial community. Differences in the soil bacterial community were tested using Bray–Curtis dissimilarity values with permutational analysis of variance (PERMANOVA), a nonparametric technique used to differentiate groups based on dissimilarity matrix [27]. Correlations between various growth characteristics of WSG and rhizospheric environmental factors were analyzed using Pearson’s coefficient analysis (IBM SPSS Statistics, version 25, IBM Corp., Armonk, NY, USA).

3. Results and Discussion

3.1. Information of Various WSG Cultivation Sites

In soil chemical properties, cation exchange capacity (CEC), organic matter (OM), total nitrogen (TN), electrical conductivity (EC), and exchangeable potassium (Ex. K) contents were significantly higher in cultivation site “A” (Table 2). Gruba and Mulder [28] have reported that the content of OM is the major contributor to CEC. The content of available phosphate (Avail. P2O5) was significantly higher in “A” and “D” cultivation sites than in other cultivation sites. Mixed-species forests might improve soil microbial diversity, plant residue compositions, and root distribution patterns [29]. Therefore, mixed forests could stimulate phosphate cycling by increasing plant uptake and mobilizing soil-fixed phosphate [30]. Previous studies have shown that coniferous forests may help to acidify the soil more than mixed forest [31,32]. Soil pH values of WSG cultivation sites in this study were similar, ranging from 4.18 to 4.84. This result suggested that soil pH could change depending on the physiognomy of the forest, other nutrient cycles (N, C, P), and soil microbial structure. The growth of WSG cultivated in mountainous forests can also be affected by various forest environments, soil properties, and soil bacterial communities [33]. Therefore, forest vegetation can be significantly varied through difference in the presence of particular tree species [34]. Because the OM content of cultivation sites is affected by the accumulation of fallen leaves from trees, the OM content in forest soil is higher in mixed forests than in coniferous forests [35]. This means that mixed forests composed of broad-leaved and coniferous trees contain more organic carbon sources than only coniferous forests because OM in a coniferous forest is slowly decomposed [36]. The diversity of soil bacterial communities inhabiting forest soils composed of mixed forests was much higher than those of forest soils composed of coniferous forests [37]. Therefore, due to the diverse bacterial community, nutrient cycling will also proceed more rapidly in mixed-forests than in coniferous forests. Both biological and non-biological factors are influencing the decomposition of organic matter. Soil microorganisms are able to produce various enzymes to degrade organic matter (hydrolyze, oxidize) [38].

3.2. Growth Characteristics of 10-Year-Old WSG Cultivated in Different Sites

Growth characteristics of 10-year-old WSG are shown in Figure 2. For the above-ground part, stem length and petiole length did not show any significant differences among cultivation sites. Stem diameter and the number of leaflets per stem were higher in cultivation sites “C” and “D”, while leaflet length and leaflet width were higher in cultivation site “A” than in other sites (Figure 2A). For the root part, rhizome length and root diameter in cultivation site “C” and “D” were significantly higher than in other cultivation sites (Figure 2B). In particular, the number of rootlets in cultivation site “C” have the highest value among various cultivation sites. Furthermore, results of total weight and dry weight in cultivation site “C” were significantly higher than in other cultivation sites (Figure 2C). Optimal soils for the production of WSG are slightly acidic, with relatively high calcium content [39]. In previous studies, growth characteristics of WSG cultivated in coniferous forests are better than those in broad-leaved forests [40,41]. However, in results of this study, cultivation site “C” was composed of only broad-leaved forests, with growth characteristics of WSG being significantly higher than those in other cultivation sites. It is difficult to determine the ideal WSG site that endures various soil physical and chemical attributes. Furthermore, a cultivation site composed of only coniferous stand might not be suited because soils are acidic and nutrient depleted in many of these sites [35]. This means that WSG growth characteristics can be influenced by various factors, including physiognomy of cultivation site, soil properties, soil bacterial community structure, endophytes, and symbiotic microorganisms [42,43]. Microorganisms collected from forest soils, as biocontrol agents and bacterial antagonists, are able to decrease the harmful effects of pathogens [44]. These microorganisms belong to the plant growth-promoting bacteria, which is composed of bacteria that exert beneficial effects on plants [45]. They are able to facilitate the acquisition of nutrients by plants, including biological nitrogen fixation and mobilization of immobilized nutrients as phosphorus (organic acids) and iron (siderophores), respectively [46].

3.3. Bacterial Community Profiles

Microbial resources are more than 10 times richer in rhizosphere soil than in bulk soil [47]. Rhizospheric soil bacterial communities are represented by diverse bacterial taxa, although their abundance varies across the root system depending on soil and plant types [48]. Changes in soil bacterial community abundance and structure may influence flowering and fruiting, plant interaction with phytophagous insects, and plant growth and development, which can be of great significance for plant growth and yield [49,50].
Soil bacterial community compositions varied among the collected soil samples. Soil bacterial communities were grouped according to cultivation sites (Figure 3). Proteobacteria (31.58%) and Acidobacteria (29.19%) were the most dominant phyla, followed by Verrucomicrobia (9.35%), Actinobacteria (7.07%), Chloroflexi (6.65%), and Planctomycetes (4.06%). These results are identical to those of previous studies, where Proteobacteria, Acidobacteria, Verrucomicrobia, and Actinobacteria are major bacterial communities at the phylum level in WSG cultivation soils [1,43,51]. Proteobacteria and Acidobacteria were the most dominant phylum in cultivation sites “A” and “B” and cultivation sites “C” and “D”, respectively. Of Proteobacteria in cultivation sites “A” and “B”, α-proteobacteria had the highest relative abundance. The order of classes was α-proteobacteria > β-proteobacteria > δ-proteobacteria > γ-proteobacteria (Table S1). Soil bacterial communities can be affected by soil properties in mountainous environments, such as soil pH and electrical conductivity [52]. In Arabidopsis thaliana, Proteobacteria have the highest relative abundance in rhizospheric soil bacterial communities [53,54]. This result suggests that Proteobacteria is the main component of rhizosphere environments regardless of plant species. It is well known that Proteobacteria are related to common contaminant removal [55], are very common in soil environments, and are related to a wide range of functions involved in carbon, nitrogen, and sulphur cycling [56]. Alpha-proteobacteria plays fundamental roles in the degradation of inorganic compounds and nitrogen fixation [57], and it has excellent removal activity of chromium in contaminated soils [58]. Therefore, the risk of exposure to contaminants that may impede growth of WSG grown in cultivation sites “A” and “B” will be low [59,60]. Cultivation sites “C” and “D” showed low soil pH, with the relative abundance of Acidobacteria being slightly higher than in other cultivation sites. Acidobacteria have dynamic roles in soil environments, such as plant growth promotion, exopolysaccharide secretion, decomposition of biopolymers, and regulation of biogeochemical cycles [61,62,63]. Therefore, in cultivation sites “C” and “D”, the growth of both the above-ground part and root part of WSG would be better because Acidobacteria could promote the growth of WSG. Fu et al. [64] reported that the soil microbial community in mountainous environments showed a seasonal variation (dry and rainy) according to land restoration types in the subtropical region. Soil microbial community composition in WSG cultivation sites can also change depending on the season. Therefore, soil bacterial communities in WSG cultivation sites should be continuously investigated.

3.4. Correlation Analyses between Soil Chemical Properties and Bacterial Community

To investigate the correlation between soil chemical properties and soil bacterial community, principal component analysis (PCA) was performed. The total variation in the bacterial community was 75.7%, explaining two axes of PCA (Figure 4). Soil properties placed in the abscissa showed higher correlation with soil bacterial communities than those located in the ordinate coordinate because PC1 variation (57.8%) was much higher than PC2 variation (17.9%). This means that Ca, Mg, soil pH, TN, CEC, and OM may be major effective factors to soil bacterial clustering. Correlation analyses between soil properties and soil bacterial communities have been carried out in many studies [65,66,67]. Previous studies have also suggested that the soil bacterial community is significantly correlated with soil pH, TN, CEC, and OM [1,67]. Therefore, it might have significant correlations with growth of WSG. Cation exchange capacity is a great indicator of soil productivity and fertility. It is involved in supplying nutrients, enhancing nutrient holding capacity, and enhancing soil buffer capacity [68]. Soil microorganisms are essential factors affecting soil fertility. They have important relationships with soil productivity and quality including organic matter decomposition and nutrient cycling [69]. Furthermore, nitrogen mineralization and decomposition of organic matter in the soil will proceed through a complex interaction between soil physiochemical properties, nutrient demand, and microbial population [70,71]. Generally, TN, CEC, and OM have high correlations in natural mountainous vegetation [72]. The soil bacterial community had significant correlations with Ca, Mg, soil pH, TN, CEC, and OM.

3.5. Correlation Analysis between Growth Characteristics of WSG and Soil Bacterial Community

Spearman’s coefficient analysis was performed to investigate the correlation between growth characteristics and the soil microbial community. The relative abundance of Proteobacteria showed significant positive correlations with the number of leaflets per stem, root diameter, root weight, total weight, and dry weight. The relative abundance of Actinobacteria was correlated with most growth characteristics of WSG (stem diameter, number of leaflets per stem, rhizome length, root diameter, root length, number of rootlets, total weight, root weight, and dry weight) (Table S2). Actinobacteria are known as plant-growth-promoting microorganisms with an antibacterial activity. They live as endophytes in various medicinal crops, such as horopito (Pseudowintera colorata), lucerne (Medicago sativa L), and Glycyrrhiza inflata Bat., and play a role in reducing environmental risks [73,74,75,76]. However, the relative abundance of Acidobacteria showed significant negative correlations with rhizome length and the number of rootlets. Wang et al. [50] reported that the population of Acidobacteria is significantly higher in cultivated soil of P. ginseng than in bulk soil. Kim et al. [43] also reported that the relative abundance of Acidobacteria shows a negative correlation with soil pH in WSG cultivation sites. Therefore, rhizome length and the number of rootlets were positively correlated with soil pH. Among Acidobacteria, the relative abundance of Koribacteraceae showed a significant negative correlation with soil pH (r = −0.762, p = 0.028). Therefore, it will be possible to confirm differences in soil properties and the bacterial community of soils between the WSG cultivation site and non-cultivated site. In particular, because WSG requires long-term cultivation of more than 7 years without any artificial facilities, chemical pesticides, or fertilizers, results of this study could be used as important basic data for investigating correlations between soil bacterial communities and growth characteristics of WSG. In addition, they could be used to select a suitable cultivation site for WSG by investigating soil bacterial community.

4. Conclusions

Mountainous forest soils and the growth of plants grown in these soils can be affected by biotic and abiotic factors in its environments. This study investigated various soil chemical properties, including soil pH, OM, TN, exchangeable cations, and CEC, that had significant correlations with the soil bacterial community of WSG cultivation sites. Relative abundances of Proteobacteria and Acidobacteria in all WSG cultivation sites were the highest. In addition, the soil bacterial community of WSG cultivation sites was significantly correlated with various growth characteristics of WSG. Therefore, this study may able to provide the optimum condition for WSG cultivation in natural vegetation. The optimum conditions deduced by this study were weakly acid soil and high relative abundance of Proteobacteria and Acidobacteria in the WSG cultivation site.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy13051313/s1, Table S1 shows relative abundance of classes in Proteobacteria phylum of cultivation sites “A” and “B”. Table S2 shows relationships between relative abundance of soil bacterial communities and growth characteristics of WSG using Spearman’s rank correlation analysis.

Author Contributions

Y.-B.Y., K.K. and Y.U. conceptualized and Y.-B.Y. wrote the original draft. J.-H.H. and Y.-B.Y. carried out the experimental section under supervision from Y.U. and K.K. Y.U. critically reviewed the draft. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Institute of Forest Science, grant number FP0802-2022-03-2023.

Data Availability Statement

Data will be made available on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Sampling locations of 10-year-old WSG cultivation soil in South Korea. A and B were located in Gangwon-do province, C was located in Gyeongsangbuk-do province, and D was located in Jeollabuk-do province.
Figure 1. Sampling locations of 10-year-old WSG cultivation soil in South Korea. A and B were located in Gangwon-do province, C was located in Gyeongsangbuk-do province, and D was located in Jeollabuk-do province.
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Figure 2. Growth characteristics of 10-year-old WSG cultivated in different sites. (A) above-ground part, (B) root part, and (C) weights. Each column shows the means of five replicates ± standard error (SE). Values in each column with different letters mean statistically significant differences (p < 0.05) among the treatments according to Duncan’s Multiple Range Test (DMRT) (p < 0.05).
Figure 2. Growth characteristics of 10-year-old WSG cultivated in different sites. (A) above-ground part, (B) root part, and (C) weights. Each column shows the means of five replicates ± standard error (SE). Values in each column with different letters mean statistically significant differences (p < 0.05) among the treatments according to Duncan’s Multiple Range Test (DMRT) (p < 0.05).
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Figure 3. Relative abundance of the taxonomic profile at the phylum level for bacteria in rhizospheric soils of 10-year-old WSG cultivation sites.
Figure 3. Relative abundance of the taxonomic profile at the phylum level for bacteria in rhizospheric soils of 10-year-old WSG cultivation sites.
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Figure 4. Correlation analysis between soil properties and microbial community obtained from principal component analysis (PCA) based on Bray–Curtis dissimilarity matrix generated using Mothur platform.
Figure 4. Correlation analysis between soil properties and microbial community obtained from principal component analysis (PCA) based on Bray–Curtis dissimilarity matrix generated using Mothur platform.
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Table
Table 1. Information of location environments of various 10-year-old WSG cultivation sites.
Table 1. Information of location environments of various 10-year-old WSG cultivation sites.
Cultivation SiteSand
(%)		Loam
(%)		Clay
(%)		Soil TextureTopographySpecies of TreeForest Physiognomy
SlopeHASL aAveragePercentage
TH bDBH c
°Directionmmcm%
A67.518.014.5Sandy loam25Southwest931ConiferPinus koraiensis18.529.015.4
Broad-leavedBetula dahurica Pall.
Ulmus davidiana var. japonica		17.420.384.6
Total17.9524.65100
B35.532.432.1Loamy sand22Southwest615ConiferLarix kaempferi10.026.06.3
Broad-leavedPrunus sect. Cerasus11.2620.3693.7
Total10.6323.18100
C65.912.621.5Sandy clay loam8Southeast391Conifer----
Broad-leavedRobinia pusedoacacia9.5713.57100
Total9.5713.57100
D84.85.110.1Clay loam18Northeast717ConiferLarix kaempferi21.628.455.6
Broad-leavedFraxinus rhynchophylla
Morus alba		8.09.044.4
Total14.818.7100
a HASL: height above sea level; b TH: tree height; c DBH: diameter of breast height.
Table
Table 2. Soil chemical properties of soil samples collected from four WSG cultivation sites.
Table 2. Soil chemical properties of soil samples collected from four WSG cultivation sites.
pHECOM zTN yAvail. P2O5 xExchangable CationsCEC s
K wCa vMg uNa t
(1:5)dS/m (1:5)%%mg/kg-------------------------------------- cmol+/kg --------------------------------------
A4.57 ± 0.04b0.31 ± 0.02a20.25 ± 0.69a0.65 ± 0.02a231.55 ± 11.36a0.46 ± 0.04a7.12 ± 0.45a0.93 ± 0.09a0.07 ± 0.02a46.31 ± 0.31a
B4.84 ± 0.04a0.21 ± 0.02b9.81 ± 0.95b0.35 ± 0.04b134 ± 15b0.22 ± 0.02bc5.88 ± 0.84a0.77 ± 0.10a0.04 ± 0.01ab27.14 ± 2.25b
C4.25 ± 0.03c0.15 ± 0.01c5.27 ± 0.23c0.23 ± 0.02c144.8 ± 44.4b0.26 ± 0.02b0.60 ± 0.09b0.16 ± 0.02b0.03 ± 0.00b18.02 ± 1.54c
D4.18 ± 0.02c0.17 ± 0.01bc10.63 ± 0.47b0.39 ± 0.03b232.18 ± 14.59a0.17 ± 0.01c0.88 ± 0.11b0.21 ± 0.02b0.02 ± 0.00b26.59 ± 1.25b
Each column shows the means of five replicates ± standard error (SE). Values in each column with different letters mean statistically significant differences (p < 0.05) among the treatments according to Duncan’s Multiple Range Test (DMRT) (p < 0.05). z OM: organic matter; y TN: total nitrogen; x Avail. P2O5: available phosphate; w K: exchangeable potassium; v Ca: exchangeable calcium; u Mg: exchangeable magnesium; t Na: exchangeable sodium; s CEC: cation exchange capacity.
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Yun, Y.-B.; Kim, K.; Huh, J.-H.; Um, Y. Relationships between Rhizosphere Environments and Growth of 10-Year-Old Wild-Simulated Ginseng. Agronomy 2023, 13, 1313. https://doi.org/10.3390/agronomy13051313

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Yun Y-B, Kim K, Huh J-H, Um Y. Relationships between Rhizosphere Environments and Growth of 10-Year-Old Wild-Simulated Ginseng. Agronomy. 2023; 13(5):1313. https://doi.org/10.3390/agronomy13051313

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Yun, Yeong-Bae, Kiyoon Kim, Jeong-Hoon Huh, and Yurry Um. 2023. "Relationships between Rhizosphere Environments and Growth of 10-Year-Old Wild-Simulated Ginseng" Agronomy 13, no. 5: 1313. https://doi.org/10.3390/agronomy13051313

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