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Article

Dynamics of Arbuscular Mycorrhizal Fungi in the Rhizosphere of Medicinal Plants and Their Promotion on the Performance of Astragalus mongholicus

by
Wanyi Zhang
1,2,
Chao He
3,
Yuli Lin
1,2,
Shenghui Qin
1,2,
Duo Wang
1,2,
Chunmiao Li
1,2,
Min Li
4,
Xiang Sun
1,2 and
Xueli He
1,2,*
1
School of Life Sciences, Hebei University, Baoding 071002, China
2
Key Laboratory of Microbial Diversity Research and Application of Hebei Province, No. 180, Wusidong Rd., Baoding 071002, China
3
Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China
4
College of Biology and Food, Shangqiu Normal University, Shangqiu 476000, China
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(11), 2695; https://doi.org/10.3390/agronomy14112695
Submission received: 22 October 2024 / Revised: 14 November 2024 / Accepted: 14 November 2024 / Published: 15 November 2024
(This article belongs to the Section Horticultural and Floricultural Crops)
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Abstract

:
Arbuscular mycorrhizal fungi (AMF) act as intermediaries between the root systems of host plants and the surrounding soil, offering various benefits to medicinal plants, such as promoting growth and enhancing quality. However, the host range of AMF in medicinal plants and the characteristics of plant–AMF networks in farmland ecosystems remain insufficiently studied. In the present study, we measured AMF colonization, species diversity, and soil properties of 31 medicinal plants at the Anguo Medicine Planting Base in Northwest China. The medicinal plant–AMF network was subsequently analyzed, and the growth-promoting effects of AMF on Astragalus mongholicus were examined. Spore density, species richness, and total colonization exhibited significant variation across different medicinal plant species. Glomus melanosporum, G. claroideum, and Septoglomus constrictum were the dominant species among 61 AMF species. Soil organic matter, phosphatase, available nitrogen, and glomalin-related soil proteins (GRSPs) were the main factors affecting the AMF composition. Structural equation models and a variation partitioning analysis suggested a highly plant species-specific pattern of AMF distribution patterns, where the host identities explained 61.4% of changes in spore density and 48.2% of AMF colonization. The soil nutrient availability and phosphatase activity also influenced AMF colonization. Our results confirmed glomalin as an important contributor to the soil carbon in farmland for cultivating medicinal plants. The medicinal plant–AMF symbiotic network exhibited highly nested patterns, a low specialized structure, high connectance, and low modularity, which suggested saturated AMF colonization and symbiosis stability provided by redundant plant–AMF associations. Despite the wide host range among medicinal plants, AMF inoculation revealed species-specific effects on the growth performance and active ingredient content levels in A. mongholicus, G. claroideum and Sep. constrictum induced the highest biomass and active ingredient content accumulation in A. mongholicus. These findings advance our understanding of AMF community dynamics in the rhizosphere of medicinal plants and offer valuable insights for optimizing medicinal plant cultivation practices.

1. Introduction

Medicinal plants provide a source of bioactive compounds that are widely used in the treatment of various diseases [1]. Astragalus membranaceus Bunge var. mongholicus (Bge.) Hsiao., as a commonly used medicinal plant, is rich in astragalussaponins, formononetin, and calycos in its roots [2]. These compounds are known to protect the vascular endothelium, mitigate hypertension symptoms, enhance hematopoiesis, and treat leukemia. A. membranaceus is widely cultivated in regions such as Gansu, Shanxi, and Hebei in China [3]. However, the cultivation of medicinal plants is often challenged by pests, diseases, the excessive use of chemical fertilizers, and soil pollution [4]. One potential strategy to improve both the quality and quantity of medicinal plant materials is through the utilization of arbuscular mycorrhizal fungi (AMF).
AMF are obligate symbiotic fungi that form symbiotic relationships with plant roots [5] and are widely found in association with medicinal plants [6]. AMF symbiosis has been shown to upregulate gene transcription-encoding enzymes involved in isopren-like biosynthesis, thereby increasing terpenoid concentrations in host plants [7]. AMF have been reported to colonize Panax notoginseng and improve its accumulation of active ingredients [8]. Additionally, AMF enhance plants to access soil mineral nutrients in exchange for photosynthates [9]. Given the positive effect of AMF on the growth of medicinal plants, studying the colonization and ecological distribution of AMF in medicinal plants would provide valuable insights into the application of mycorrhizal biotechnology in the cultivation of medicinal plants [10].
Although only 332 AMF species have been reported worldwide [11], a high degree of species diversity in AMF is often observed at a small regional scale. For instance, Piszczek et al. [12] investigated the root colonization of AMF in 40 plant species from a garden of medicinal plants and identified 22 AMF species, with significant differences in distribution among plant species. Similarly, Zubek and Blaszkowski [13] conducted a study on 31 medicinal plants, and the spores of 15 species of AMF were discovered in these plants. Since medicinal plants in cultivation gardens are typically grown with dozens of different species intensively in limited areas, the close proximity of root systems with different origins results in complex AMF communities and AMF–plant symbiotic networks within the garden.
By elucidating the structure of plant–AMF networks, we can understand the underlying mechanisms of species coexistence and ecosystem stability [14]. AMF are usually characterized by being highly nested, lowly specialized, highly connected, and having a low modularity of generalization. For example, the networks between AMF and 17 woody plants have been shown to be anti-modular and anti-specialized in subtropical forest ecosystems, revealing a complex yet uniform pattern in the distribution of AMF [15]. Lin et al. [16] examined the structure of AMF networks among eight common herbaceous plants in rural and urban areas. Their findings indicated that urban areas exhibited higher connectivity and lower specificity, suggesting that AMF share a highly overlapping ecological niche. The plant–AMF network in a Tibetan alpine meadow was found to have high nestedness, high connectance, and low modularity, which may imply a high level of stability [17]. However, in tropical forests in Africa, the plant–AMF symbiotic network exhibits a highly modular, highly interconnected, and highly nested pattern [18]. In temperate forests in Japan, plant–AMF showed insignificant nesting, specificity, and modularity, which may imply a symbiotic relationship group formed between plants and AMF, with specific ecological functions and adaptations [19]. Hence, understanding the network structures can be informative about how bipartite communities respond to different ecosystems and can help detect the state of AMF–plant communities in the field, allowing for more accurate and efficient cultivating management. However, medicinal plant–AMF network characteristics in a garden of medicinal plants remain poorly understood.
The Anguo Medicinal Planting Base cultivates over 400 species of medicinal plants, with an annual transaction volume of approximately USD 57 thousand [20]. As one of the largest gardens for traditional medicinal herbs in China, several economically valuable endemic Chinese species, such as Scrophularia ningpoensis, Notopterygium incisum, Rehmannia glutinosa, and Angelica dahurica are cultivated. These species are renowned for their abundant bioactive ingredients and have substantial market demand. This study aimed to obtain insights into the ecological roles of AMF in farmland ecosystems and to explore their potential for the cultivation of medicinal plants. Morphological methods were used to characterize AMF communities living in each plant root to address the following questions: (1) are there differences in AMF colonization and spore density associated with medicinal plant spices and soil factors in farmland? (2) What are the nested, connected, specialized, and modular patterns of the medicinal plant–AMF network structure, and what is the meaning behind them? (3) Could inoculation with the dominant AMF facilitate the growth of medicinal plants?

2. Materials and Methods

2.1. Study Sites and Sampling

All medicinal plant samples were collected at the Anguo Medicine Planting Base (38°43′ N, 115°33′ E), located in Anguo City, Hebei Province, China. The region experiences a typical temperate continental climate, with an average annual temperature of 12.2 °C and an average annual precipitation of 505.3 mm. The soils in the area consist of Xeralf, Durixeralf, and Alfisols. A total of 230 species of medicinal plants were cultivated at the Anguo Medicine Planting Base, which received biannual irrigation during their growing season. The plants were fertilized annually with 180 kg/ha of universal fertilizer (N: P2O5: K2O = 2:1:2), 90 kg/ha of P2O5, and 180 kg/ha of K2O.
In June 2022, samples from 31 medicinal plants representing 11 different families were collected (Table 1). To sample each species, quadrats within farmland areas were randomly established away from roads. Within each quadrat, three 0.5 × 0.5 m plots located at the center and opposite ends were selected, and five soil cores (21 cm in diameter and 17 cm in height) were randomly collected from each plot, excluding any damaged or diseased plants. The samples were packaged and transported to the laboratory for further analysis. Soil samples were sieved through a 2 mm mesh, air-dried at room temperature, and stored at 4 °C until enzymatic analysis was performed. The root samples were washed thoroughly under tap water to remove any remaining soil particles and stored at 4 °C. The remaining samples were used for the determination of soil factors.

2.2. AMF Spore Density and Morphological Characteristics

The AMF spores were isolated from the soil with wet sieving and decanting techniques [21]. All the contents retained on a 45 μm sieve were collected and mixed with water. Then, sucrose density centrifugation was performed centrifuged at 4500 rpm for 15 min [22]. Spores were counted and identified with morphological characteristics under a microscope (MODEL BX53F, Olympus, Tokyo, Japan), in accordance with morphology identifiable criteria (INVAM website, https://invam.ku.edu/, accessed on 17 June 2024). The relative abundance (RA, %) of each AMF species was calculated as the percentage of spores in a given species relative to the total spore count [23]. The relative frequency (F, %) of each species was calculated as the percentage of samples in which the species appeared across three sampling plots [23]. The dominance candidate index (DCi, %) of each species was derived from the average of RA and F [23]. Based on their DCi, AMF species were categorized into four groups, namely (1) dominant species with DCi > 55%; (2) subdominant species with 55% ≥ DCi > 41%; (3) moderately abundant species with 41% ≥ DCi > 21%; and (4) rare species with DCi ≤ 21%.

2.3. Dominant AMF Spore Propagation

Trifolium repens was used as a host plant for AMF spore propagation. The propagation substrate consisted of a soil and sand mixture in a volume ratio of 1:1, autoclaved at 120 °C for 30 min. The autoclaved substrate was left to rest for seven days, then filled to one-third of the pots, which were sprayed and wiped with 75% ethanol prior. The seeds of T. repens with consistent sizes were selected and disinfected with 4% NaClO for 10 min and washed five times with sterile water. AMF spores were evenly flushed into the pots with sterile water, sterilized T. repens seeds were spread on top, and then they were covered with the autoclaved substrate. After four months of growth, the plants were cut and three pots containing the dominant AMF inoculum were harvested. The AMF inoculum consisted of a mixture of spores, mycelium, plant roots, and soil, with an approximate concentration of 10 spores/g of inoculum.

2.4. Pot Experiments and Plant Growth Parameters

The experiment examined the effects of different AMF inoculations on A. mongholicus growth, with four replicates for each treatment. The treatments comprised a non-inoculated control (CK) and inoculations with Glomus melanosporum (GM), G. claroideum (GC), or Septoglomus constrictum (SC), resulting in a total of 16 experimental pots. A. mongholicus seeds were immersed in water for 12 h at 4 °C to break the dormancy period before sowing. At sowing, 50g of AMF inoculum was evenly sprinkled in the soil. The pots were placed in an incubator with a photoperiod of 14 h light/10 h dark at a constant temperature of 27 °C and watered every two days. Plant growth parameters were measured 120 days after sowing.

2.5. Determination of Plant Growth Parameter and Active Ingredient Content

The plant height and branch numbers of the A. mongholicus in each pot were recorded before harvest. The shoots and roots from each pot were separately harvested. The roots were washed with clean water to remove the soil from the surface. The root samples were laid flat in a plexiglass tray and scanned using a scanner (EPSON V800; Seiko Epson Inc., NKS, Tokyo, Japan). The root morphological indexes were analyzed by the WinRHIZO image analysis system. The fresh shoots and roots were dried at 70 °C for over 72 h to determine biomass.
The determination of medicinal ingredients of A. mongholicus by high-performance liquid chromatography (HPLC) was performed according to the Chinese Pharmacopoeia. A total of 0.5 g of A. mongholicus root powder was weighed into a 50 mL volumetric flask, and 50 mL of methanol was added. The sample was sonicated using an ultrasonic instrument for 3 h (KH-250; Kunshan Hechuang Ultrasonic Instruments Factory, Kunshan, China), then filtered. The filtrate was concentrated by rotary evaporation at 45 °C under reduced pressure until no organic phase remained. The residue was dissolved in 1.25 mL of methanol, thoroughly mixed, and filtered through a 0.22 μm microporous filter. Silica gel bonded with octadecyl silane was used as the filler, acetonitrile as mobile phase A, and a 2% formic acid solution served as mobile phase B. The gradient elution conditions were divided into two parts, at 0–20 min (A changed from 20% to 40% while B changed from 80% to 60%) and 20–30 min (A was 40% and B was 60%). The flow rate was maintained at 1 mL/min and the detection wavelength was 286 nm. The results included Calycosin-7-glucoside and formononetin.

2.6. Soil Analysis

Soil organic carbon (SOC) content was estimated through dichromate oxidation in the presence of H2SO4 [24]. Soil pH was measured using a digital pH meter (PHS-3C; Shanghai Lida Instrument Factory, Shanghai, China) with a 1:2.5 soil-to-water suspension. Available phosphorus (P) was determined using the extraction and molybdenum–antimony anti-colorimetric method [25], the soil samples were extracted with NaHCO3 for 30 min, filtered, and then the molybdenum–antimony anti-reagent was added, and the absorbance was measured at 700 nm. using a spectrophotometer (model 752 N, Shanghai INESA Instrument Analytical Instruments Co., Ltd., Shanghai, China). The alkaline hydrolysis diffusion method was used to determine soil available nitrogen (N); after incubating the diffusion dish at 40 °C for 24 h, titration was performed using H2SO4. Soil available potassium (K) was determined using a turbidimetric method [26]; the soil was extracted with NaNO3 for 5 min and then filtered, a sodium tetraphenylboron solution was added, followed by shaking, measured the absorbance at wavelengths of 410 nm. Soil alkaline phosphatase activity was determined by the disodium p-nitrophenyl phosphate method [27]; the soil was extracted with NaHCO3 for 50 min, then disodium p-nitrophenyl phosphonate was added and the mixture was shaken well after filtration, measured the absorbance at wavelengths of 410 nm. The total extractable glomalin-related soil protein (T-GRSP, TG) and easily extractable glomalin-related soil protein (EE-GRSP, EEG) were quantified following Rillig’s method [28].

2.7. AMF Colonization Rate

The root samples were stored at 4 °C. Thirty fresh root segments were randomly selected from each plant, thoroughly washed with tap water, and cut into 1 cm sections. After washing off any remaining soil, the root segments were placed in a water bath at 100 °C for 1 h with 10 mL of 10% KOH solution. The roots were then rinsed several times with clean water and stained with 0.5% acid fuchsin, following the method of McGonigle et al. [29]. After staining, the roots were decolorized for 48 h before microscopic examination. The total colonization rate of AMF was calculated as the ratio of infected root segments to the total number of root segments.

2.8. Statistical Analysis

Sample differences in soil parameters, AMF colonization, and spore density were determined by one-way analysis of variance (ANOVA) with post hoc comparisons using Duncan’s test. The effects of soil parameters and plant species on AMF colonization and spore density were further assessed using variation partitioning analysis (VPA). Correlation analyses were conducted to evaluate the relationship between soil factors and AMF colonization or spore density. The Simpson indices of diversity were calculated using the function diversity from the R package “vegan”. The AMF diversity index box plots were drawn using the R package “ggplot2”. The effects of plant species and soil parameters on the AMF community were tested using the Mantel test and structural equation modeling (SEM) in R-4.3.3 with the ecodist and AMOS 21.0 packages, respectively (using maximum likelihood estimation).
For network analysis, data from each plant species sample were combined, with each row corresponding to a plant species and the number of spores listed. A dichotomous network using the R package “bipartite” was constructed and the network-level weighted nestedness metric based on overlap and decreasing fill (WNODF), connectance, specialization, and modularity was computed. A 1000-replicate Patefield’s null model was generated using the “bipartite” package, and the significance of network metrics was assessed using a two-tailed test. Plant growth parameters and the active ingredient content in A. mongholicus were analyzed using ANOVA with Duncan’s post hoc test.

3. Results

3.1. Soil Factors and Glomalin-Related Soil Protein

Soil chemical properties and enzyme activities varied significantly among the rhizospheres of the 31 medicinal plant species studied (Table 2). Soil pH was in the range of 6.0–7.6, available K content was 41.0–90.4 μg/g, available P content ranged between 2.4 and 5.3 μg/g, available N content was 42.7–94.5 μg/g, SOC content was 6.9–11.1 mg/g, and alkaline phosphatase activity ranged between 52.0 and 116.8 μg/g/h. The value of pH of the soil of Tussilago farfara was lower than that of other medicinal plants. The available K content of the soil of Atractylodes macrocephala and Aconitum carmichaeli was higher than that of other medicinal plants. The highest levels of available P were found in the soils with Aristolochia contorta, Pericallis hybrida, Sedum sarmentosum, and Hemerocallis fulva. The lowest available K, available P, and available N levels were measured for the soils with Hylotelephium erythrostictum, respectively. Alkaline phosphatase activity was higher in the rhizosphere of Scutellaria baicalensis than the other plants. Minimum SOC levels were determined for the soils with Notopterygium incisum.
There were notable variations between plants in the contents of the two GRSPs (Table 1). EEG content was 1.1–1.7 mg/g and TG content was 3.3–4.7 mg/g. EEG levels were higher in the rhizosphere of Scutellaria baicalensis than the other plants. Minimum TG levels were determined for Notopterygium incisum. The highest levels of EEG/SOC were found in the soils of Notopterygium incisum. TG/SOC was higher in the rhizosphere of Paeonia lactiflora. Minimum EEG/SOC and TG/SOC levels were determined for the soils of Glechoma longituba.

3.2. AMF Colonization

AMF colonization was observed in the roots of all 31 medicinal plant species through tissue staining and microscopic examination. It can form typical intermediate-type AM structures (Figure 1), where hyphae form intercellularly between host root cells (Figure 1a,f,h,k,l), with the hyphal tips inside the cells swelling to form vesicles (Figure 1b–e,g,i,j).
The AMF total colonization of 31 medicinal plants is shown in Table 3. The total colonization rate varied from 42.2% (Pericallis hybrida) to 94.4% (Scutellaria baicalensis), and differences among plants species were significant (F = 24.016, p < 0.001). All 11 of the families under investigation had plants that were colonized by AMF (Aristolochiaceae, Compositae, Crassulaceae, Labiatae, Leguminosae, Liliaceae, Linaceae, Ranunculaceae, Stemonaceae, Scrophulariaceae, and Umbelliferae). The total colonization rate was 57.4–83.3% (Figure 2). The total colonization rate of Aristolochiaceae was significantly higher than other medicinal plants; the lowest total colonization rate was observed in Umbelliferae (F = 24.016, p < 0.01).

3.3. AMF Composition and Diversity

The AMF spores recovered in the present study were identified to seven genera and 61 species according to morphological characteristics, including 34 species in Glomus, 15 in Acaulospora, five in Scutellospora, three in Rhizophagus, two in Septoglomus, one in Pacispora, and one in Funneliformis. The genus Glomus predominated all 31 medicinal plants, followed by Acaulospora and Septoglomus (Figure 3a). G. melanosporum (accounted for 35.54% of RA), G. claroideum (23.0% of RA), and Sep. constrictum (12.4% of RA) were the dominant species among the 31 medicinal plants (Figure 3b). The isolation rate and dominance candidate index of S. deserticola of medicinal plant Hylotelephium erythrostictum were higher than other plants (Table S1, Figure 3b), and G. caledonium was discovered to have exclusively colonized of Hylotelephium erythrostictum.
The AMF spore densities varied between 112 and 383/10 g soil among the 31 medicinal plants, with a statistical significance of difference (F = 108.483, p < 0.001). Minimum spore density occurred in Coreopsis tinctori (112/10 g soil). Hosta plantaginea had the highest spore density of 383 spores/10 g soil. The species richness of AMF in the 31 medicinal plants ranged from 26 to 49. The minimal AMF richness was found in Glechoma longituba with 26 AMF species, while Angelica sinensis had a maximum AMF richness of 49 species. Simpson indices differed significantly among different medicinal plants, where the highest indices occurred to Hylotelephium erythrostictum and the lowest to Glechoma longituba (F = 16.603, p < 0.001). In the case of the AMF richness parameter, there were also statistically significant differences between families (F = 45.881, p < 0.001), which varied from 24.6 (Stemonaceae) to 50 (Ranunculaceae, Figure 4a). The ANOVA showed that there were significant differences in the Simpson index for 11 families (F = 2.705, p < 0.05), where Crassulaceae was significantly higher than Aristolochiaceae, Compositae, Leguminosae, Liliaceae, Linaceae, Stemonaceae, and Umbelliferae (Figure 4b).

3.4. Influence of Soil Factors on AMF Distribution and GRSP

The AMF total colonization was significantly and positively correlated with SOC, alkaline phosphatase, available N, available K, EEG, and TG (Table 4, p < 0.05). Spore density was significantly affected by SOC, alkaline phosphatase, available N, EEG, and TG (Table 4, p < 0.05). Overall, SOC, alkaline phosphatase, available N, EEG, and TG were the main soil factors affecting AMF distribution. The contents of EEG and TG were significantly affected by SOC, alkaline phosphatase, and available N (Table 4, p < 0.05). There was a highly significant correlation between EEG and TG (Table 4, p < 0.01).
The VPA employed plant species and soil properties as explanatory variables and employed AMF colonization (Figure 5a) and spore density (Figure 5b) as response variables. The findings revealed that these two explanatory factors accounted for 87.2% of the variance in total colonization, with plant species alone explaining 48.2%. Although soil characteristics individually contributed little to the variation, their interaction with plant species explained 38.9%. Similarly, the analysis showed that the two variables accounted for 96.4% of the variance in spore density, with plant species explaining 61.4%. The soil interaction with plant species accounted for 34.6% of the variation.
The structural equation model (SEM) was used to illustrate the effects of plant species on the soil parameters and AMF community (x2 = 35.667, df = 13, p = 0.01, RMSEA = 0.138, GFI = 0.918, AIC = 81.667, CFI = 0.905; Figure 6). Our findings demonstrated that plant species had notable direct impacts on organic carbon, available phosphorus, spore density, and AMF colonization (Figure 6). Plant species indirectly influenced AMF spore density via available P and available K content. Plant species indirectly influenced AMF colonization through pH, organic C, available P, and available K. Organic C and available K content significantly directly influenced AMF colonization.

3.5. Structural Features of Medicinal Plant–AMF Symbiotic Networks

Compared with the predicted value of the null model, the characteristics of the plant–AMF network, such as high nestedness, low specialized structure, high connectance, and low modularity, were obtained (Table 5, Figure 7). The observed values of WNODF were significantly higher than the predicted values (p < 0.05). In terms of specificity, the observed value of the medicinal plant–AMF symbiotic network specificity was significantly higher than the predicted value of the null model (p < 0.001). The observed connectance value of the symbiotic network was significantly lower than predicted value of the null model (p < 0.001). In terms of modularity, the observed value was significantly higher than the predicted value of the null model (p < 0.001).

3.6. Plant Growth Parameters and Active Ingredient Content

Inoculation with dominant AMF had significant effects on plant growth (Figure 8a). Specifically, seedlings inoculated with GM, GC, and SC exhibited increases in plant height by 22.6%, 29.7%, and 56.4%, respectively, compared to the control (CK, Figure 8b). GC and SC increased the branch number by 56.2% and 39.7% compared to the control, respectively, while GM had no effect on the branch number (Figure 8c). Seedlings inoculated with three AMF strains demonstrated a notable increase in the number of blades, achieving 15.9%, 39.3%, and 61.6% enhancement, separately (Figure 8e). Inoculation with GC and SC strains significantly promoted the root growth of A. mongholicus seedlings, as evidenced by significant increases in their root biomass and root length (Figure 8a,d,f). Inoculation with GM, GC, and SC strains all significantly affected the total biomass of A. mongholicus seedlings compared to CK; however, there were no significant differences between the different AMF inoculations (Figure 8d). Regarding the active ingredient, SC significantly increased the accumulation of Calycosin-7-glucoside in A. mongholicus seedlings, achieving 46.3% enhancement compared to CK. All three AMF increased the accumulation of formononetin by 63.3%, 100.7%, and 51.9%, respectively, compared with CK.

4. Discussion

4.1. Association Between AMF and Medicinal Plants

Although AMF were associated with a large range of medicinal plants [5], approximately 300 medicinal plants colonized by AMF have been studied to date, representing less than 1% of their global total. In this study, we detected AMF colonization in the roots of 31 medicinal plants, with AMF colonization being reported for the first time in 15 of these species (Aristolochia contorta, Coreopsis tinctoria, Pericallis hybrida, Sedum sarmentosum, Glechoma longituba, Nepeta cataria, Scutellaria barbata, Lespedeza bicolor, Hemerocallis fulva, Polygonatum odoratum, Linum perenn, Aconitum carmichaeli, Stemona japonica, Scrophularia ningpoensis, and Notopterygium incisum). In addition, the AMF colonization status of Tussilago farfara has only been previously reported under saline–alkaline conditions [30]. The new information about the AMF colonization and species composition in these 31 medicinal plants is valuable for further clarifying the associations between AMF and their host plants.
Plants are keen to interact with AMF to enhance their survival [31,32]. Numerous studies have confirmed the beneficial effects of AMF on their plant hosts [33,34]. For example, Dai et al. [8] found that inoculation with AMF associated with Panax notoginseng successfully formed AMF structures in the roots of their seedlings and enhanced their growth performance. Similarly, Helianthus tuberosus has been shown to benefit from AMF colonization, with improvements in plant height, biomass, and leaf area [35]. In this investigation, we observed AMF colonization in the roots of 31 medicinal plant species, supporting the idea that AMF are vital components for the successful cultivation of medicinal plants. AMF colonization is likely to allow plants access to additional nutrient sources. In addition to growing within the root, AMF extend extra-radical hypha into the soil to further enhance the function of plant roots [36]. Zhang et al.’s [37] study showed that AMF improve the stress resistance of host plants and were associated with a higher mycorrhizal colonization and consumption of lipids. Toxic substances can be stored in vesicles of hyphal cells, and AMF hyphae are probably the transport pathway that allowed for the excretion of toxic substances through glomalin and spores [38]. Therefore, high colonization rates help host plants to improve growth, development, and nutritional status in host plants.
There was a significant difference in the total AMF colonization rate between the 31 plants. The AMF colonization rates in Aristolochia contorta, Scutellaria baicalensis, Aconitum carmichaeli, Paeonia lactiflora, and Scrophularia ningpoensis were significantly higher than other medicinal plants. Previous studies have reported that plant species leads to differences in AMF colonization [39]. Our VPA results demonstrated that plant species alone explained 48.2% of the variation in AMF colonization and 61.4% of the variation in spore density, highlighting the crucial role of plant species in determining AMF colonization levels. The 31 medicinal plants used in this investigation belonged to 11 families, and a distinct colonization pattern at the family level was observed. Aristolochiaceae plants were significantly higher in total colonization than other plant families. AMF colonization varying among host families has been reported in previous studies. For example, the AMF colonization rates of 13 plant species from plant communities at 3700 m elevation above in Bolivian Andes were investigated, and the highest CRs were found in Verbenaceae, Compositae, and Leguminosae, followed by Solanaceae, with the lowest in Gramineae and Chenopodiaceae [40]. The variation in AMF colonization across plant families may be attributed to differences in root structure and root exudates, which influence AMF colonization [41]. In addition, AMF act as a bridge between the root system and the soil environment, and different host plants have different degrees of influence on the community structure of AMF [42]. The Simpson index of Crassulaceae was significantly higher than other families in our study, which may be due to their succulent nature, with thick root hairs that may form a stronger symbiotic relationship with AMF [43].
The distribution of AMF is different significantly among plant species and is closely related to the phylogenetic relationships of host plants [44]. AMF also have host species preferences [45]. In this study, there were significant differences among AMF colonization, spore density, and the Simpson index. A total of seven genera of AMF were identified, namely Glomus, Acaulospora, Scutellospora, Rhizophagus, Septoglomus, Pacispora, and Funneliformis. Among them, Glomus is the dominant genus, which aligns with previous studies that have shown Glomus to be globally distributed and dominant in AMF communities [9]. The adaptability of Glomus to a wide range of ecosystems and its ability to form a mycorrhizal symbiosis with wide range of plants may be related to its high spore production and dispersal capacity, where species in the genus produce a large number of smaller spores in a short period of time and are easily dispersed [46]. AMF species co-occurring in different host plants varied; however, Glomus caledonium was found only in a single host plant. The separation rate and dominance candidate index of Sep. deserticola of Hylotelephium erythrostictum were higher than other medicinal plants, which is consistent with previous studies of AMF host species preference.

4.2. AMF and Soil Factors

Previous studies have shown a significant correlation between AMF colonization and soil factors [47]. In the present study, strong positive correlations were found between AMF total colonization, spore density, SOC, available N, alkaline phosphatase, and GRSPs. AMF enhanced host plant stress tolerance, and photosynthesis and supply of photosynthetically produced products affected AMF community composition and increased soil carbon accumulation [48]. Plants can also influence the connection between the host and the fungus through the allocation and regulation of carbon [20]. Soil enzymes are active organic components which reflect soil microbial metabolic processes. AMF hyphal exudates stimulate soil enzymes released by microbes, indirectly influence soil enzymes, GRSPs, soil available N, P dynamics, and decomposition [49]. In the present study, the dominance candidate index of Sep. deserticola of Hylotelephium erythrostictum was higher than other medicinal plants, the soil available P, K, and N contents of Hylotelephium erythrostictum were significantly lower than those of other medicinal plants, and the soil nutrient contents of rhizospheres were lower. It may lead to host preferences of Sep. deserticola for medicinal plants Hylotelephium erythrostictum, and Sep. deserticola may affect the absorption of nutrient elements such as N, P, and K by host plants in low-nutrient environments. The VPA results showed that the effect of soil factors on the distribution of AMF was largely dependent on plant species, which was consistent with the conclusion of Han et al. [20]. Abundant nutrients and metabolic resources in the rhizosphere facilitate the proliferation of microorganisms. In turn, these microorganisms regulate the fungal community structure in the host plant’s roots [50]. Therefore, rhizosphere environments among different plant hosts may largely account for the differences in rhizosphere microbial characteristics.

4.3. Glomalin-Related Soil Protein and Soil Factors

The glomalin-related soil proteins produced by AMF can promote the formation of soil aggregates through the entanglement of extra-radical hypha and soil particles, thereby improving soil structure, water retention and permeability, and enhancing the resistance of plants to unfavorable environments [51,52]. The indirect contribution of GRSP to the carbon pools is crucial. Averagely, EEG and TG accounted for 1.7% and 9.6% of SOC, respectively, in tropical forests, and up to 60.28% of SOC is conserved in GRSPs in desert soil [53]. High ratios of both GRSP fractions to SOC in this study confirmed the contribution of glomalin to the soil carbon stocks in farmland. GRSP increases microbial activity by promoting carbon pool activity and helps AMF host plants grow better [47]. Furthermore, EEG and TG were highly correlated with SOC, as found in various ecosystems, such as pastures [54], tropical coastal forests [55], the Loess Plateau [56], etc. Soil factors are important in determining GRSP content. GRSP was observed to be higher in soils with high C and N content and phosphatase activity [57]. In this case, organic matter supports the production of AMF proteins, which promotes GRSP accumulation [58]. In this study, EEG and TG were significantly and positively correlated with available N and phosphatase. This may be due to the increase in the organic carbon mineralization rate under high soil enzyme activity and nutrient-rich conditions, which expands the release of GRSPs.

4.4. Structure of Medicinal Plant–AMF Symbiotic Networks

The network structure of medicinal plants and AMF had high nestedness and connectance and a low specialization and modularity based on the dataset pooled from 31 plants and 61 AMF species tested against multiple null models. High connectance is generally accompanied by high nestedness and low modularity [17], which is consistent with the results of our study. The highly nested and connected network patterns suggest that species coexistence may be facilitated by enhanced robustness against random extinctions and a reduction in interspecific competition [15]. The low modularity of the network indicates that certain AMF may interact with multiple plant species, implying that the ecosystem exhibits redundancy and stability [59]. These network characteristics improved community stability within the mutually beneficial network, a crucial factor in promoting species coexistence in the mutualistic system [17]. However, further research involving larger sample sizes is needed to determine whether high nestedness, high connectance, low specialization, and low modularity are consistent features of medicinal plant–AMF networks more broadly.

4.5. AMF Growth Promotion of A. mongholicus and Its Potential Applications

Plant growth and reproduction are influenced by many factors such as heredity, environment, individual size, and soil nutrient conditions [60]. In this study, we found that AMF inoculation improved the total biomass, branch number, blade number, and active ingredient content compared with non-AMF plants, which confirmed the effects of AMF on mediating plant survival and reproduction strategies. Different AMF strains have different beneficial effects on plants [61,62]; some AMF can expand the root range of host plants [63] and some AMF can significantly increase fresh/dry herbal and leaf yields [64]. Our results suggest that different AMF strains confer different degrees of growth-promoting effects on their host plants. For instance, in pot experiments, G. claroideum and Sep. constrictum promoted the root growth of A. mongholicus, while inoculation with Sep. constrictum promoted shoot growth. Secondary metabolites produced by plant–environment interactions are the main components of medicinal plant efficacy. AMF are intimately involved in the physiological and biochemical processes of plants, promoting the synthesis and accumulation of active ingredients such as terpenes, phenols, and alkaloids [65]. AMF inoculation significantly alters the content and composition of secondary metabolites in aromatic plants [66]. In our study, Sep. constrictum significantly increased the accumulation of Calycosin-7-glucoside in A. mongholicus seedlings. All three AMF increased the accumulation of formononetin, with the effect of G. claroideum being the most pronounced, increasing formononetin content by 100.7% compared to the control. Both G. claroideum and Sep. constrictum inoculations significantly promoted the accumulation of medicinal constituents, making them the most effective AMF strains for A. mongholicus.
Medicinal plants are important sources of bioactive compounds used to treat a wide range of diseases [67]. Despite the rapid development in the cultivation of medicinal plants, challenges such as pest infestations, excessive use of chemical fertilizers, and soil contamination pose significant hurdles to their cultivation and sustainable development [68]. This study focused on the colonization and species composition of AMF in the roots of particular medicinal plants within an agricultural setting and their growth-promoting effects on A. mongholicus. Our results offer novel insights into leveraging AMF for enhancing the growth of medicinal plants. Assessing the AMF colonization status across various medicinal plants offers guidance for the selection of representative species for forming mutually beneficial relationships with AMF. It is crucial to identify additional AMF species and evaluate their potential applications in medicinal plants.

5. Conclusions

Mutualistic symbiosis between 31 medicinal plants and arbuscular mycorrhizal fungi (AMF) were found in the farmland of Northern China. The distribution of AMF was highly correlated with plant species and further showed correlations with soil nutrients, GRSP content, and enzyme activities. High contributions of GRSP to soil organic carbon were present, indicating that GRSP might be useful indicators for evaluating soil quality and function. G. melanosporum, G. claroideum, and Sep. constrictum were the dominant species. Aristolochia contorta, Coreopsis tinctoria, Pericallis hybrida, Sedum sarmentosum, Glechoma longituba, Nepeta cataria, Scutellaria barbata, Lespedeza bicolor, Hemerocallis fulva, Polygonatum odoratum, Linum perenn, Aconitum carmichaeli, Stemona japonica, Scrophularia ningpoensis, and Notopterygium incisum were the first reported case of AMF colonization in medicinal plants. The medicinal plant–AMF symbiotic network exhibited highly nested patterns, a low specialized structure, high connectance, and low modularity. All three tested AMF could promote the growth of A. mongholicus, while G. claroideum and Sep. constrictum could promote the accumulation of the active ingredient in A. mongholicus; thus, it was considered to be the best fungus for A. mongholicus.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy14112695/s1, Table S1: The dominance candidate index for AMF communities in the rhizosphere soil of 31 species of medicinal plants collected from the Anguo Medicinal Plant Planting Base in Hebei Province, China.

Author Contributions

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

Funding

This research was supported by the Natural Science Foundation of Hebei Province (no. H2022201056), the Central Guidance for Local Scientific and Technological Development Funding Projects (no. 236Z2904G), and the Postgraduate’s Innovation Fund Project of Hebei University (no. HBU2024BS004).

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding authors.

Acknowledgments

The authors are grateful to the students Wanyun Li, Yali Xie, Ling Li, and Feng Gong for laboratory work.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Arbuscular mycorrhizal fungal (AMF) colonization in roots of medicinal plants. H = AMF hyphae; V = AMF vesicular. (a) Aristolochia contorta, (b) Atractylodes macrocephala, (c) Sedum sarmentosum, (d) Scutellaria barbata, (e) Mimosa pudica, (f) Hosta plantaginea, (g) Lilium davidii, (h) Linum perenne, (i) Paeonia suffruticosa, (j) Stemona japonica, (k) Rehmannia glutinosa, (l) Angelica dahurica.
Figure 1. Arbuscular mycorrhizal fungal (AMF) colonization in roots of medicinal plants. H = AMF hyphae; V = AMF vesicular. (a) Aristolochia contorta, (b) Atractylodes macrocephala, (c) Sedum sarmentosum, (d) Scutellaria barbata, (e) Mimosa pudica, (f) Hosta plantaginea, (g) Lilium davidii, (h) Linum perenne, (i) Paeonia suffruticosa, (j) Stemona japonica, (k) Rehmannia glutinosa, (l) Angelica dahurica.
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Agronomy 14 02695 g002
Figure 2. Arbuscular mycorrhizal fungal (AMF) total colonization rate (%) in medicinal plant roots. Different letters above the error bars indicate significant differences.
Figure 2. Arbuscular mycorrhizal fungal (AMF) total colonization rate (%) in medicinal plant roots. Different letters above the error bars indicate significant differences.
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Agronomy 14 02695 g003
Figure 3. Relative abundance (%) of arbuscular mycorrhizal fungal (AMF) genus (a) and species (b) level in rhizosphere soil of medicinal plants.
Figure 3. Relative abundance (%) of arbuscular mycorrhizal fungal (AMF) genus (a) and species (b) level in rhizosphere soil of medicinal plants.
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Agronomy 14 02695 g004
Figure 4. Differences in arbuscular mycorrhizal fungal (AMF) spore richness ((a), number of species) and the Simpson index (b) at the family level of medicinal plants. Different letters indicate significant differences.
Figure 4. Differences in arbuscular mycorrhizal fungal (AMF) spore richness ((a), number of species) and the Simpson index (b) at the family level of medicinal plants. Different letters indicate significant differences.
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Agronomy 14 02695 g005
Figure 5. The relative contributions of plant species and soil factors were evaluated using a variation partitioning analysis on arbuscular mycorrhizal fungal (AMF) total colonization (a) and spore density (b). Values < 0 are not shown.
Figure 5. The relative contributions of plant species and soil factors were evaluated using a variation partitioning analysis on arbuscular mycorrhizal fungal (AMF) total colonization (a) and spore density (b). Values < 0 are not shown.
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Agronomy 14 02695 g006
Figure 6. Structural equation model illustrating the causal connections between plant species, arbuscular mycorrhizal fungal (AMF) communities, and soil parameters. The final model fitted the data well, with the maximum likelihood, x2 = 35.667, df = 13, p = 0.01, RMSEA = 0.138, GFI = 0.918, AIC = 81.667, and CFI = 0.905. Solid lines represent significant pathways, while dashed lines denote nonsignificant ones. The thickness of the solid lines corresponds to the strength of the causal effect, and the numbers adjacent to the arrows show the standardized path coefficients. “e” represents the residual values. TG: total extractable glomalin-related soil protein.
Figure 6. Structural equation model illustrating the causal connections between plant species, arbuscular mycorrhizal fungal (AMF) communities, and soil parameters. The final model fitted the data well, with the maximum likelihood, x2 = 35.667, df = 13, p = 0.01, RMSEA = 0.138, GFI = 0.918, AIC = 81.667, and CFI = 0.905. Solid lines represent significant pathways, while dashed lines denote nonsignificant ones. The thickness of the solid lines corresponds to the strength of the causal effect, and the numbers adjacent to the arrows show the standardized path coefficients. “e” represents the residual values. TG: total extractable glomalin-related soil protein.
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Agronomy 14 02695 g007
Figure 7. The bipartite interaction network formed by medicinal plants (lower boxes) and arbuscular mycorrhizal fungal (AMF) spores. The colors of the different lower boxes represent different medicinal plants.
Figure 7. The bipartite interaction network formed by medicinal plants (lower boxes) and arbuscular mycorrhizal fungal (AMF) spores. The colors of the different lower boxes represent different medicinal plants.
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Agronomy 14 02695 g008
Figure 8. The impacts of arbuscular mycorrhizal fungi (AMF) on the growth parameters of Astragalus mongholicus seedlings. Growth diagram (a), plant height (b), branch number (c), plant biomass (d), blade number (e), root length (f), Calycosin-7-glucoside (g), and formononetin (h). Different letters above the error bars indicate significant differences. CK, inoculated control; GM, Glomus melanosporum; GC, Glmous. claroideum; SC, Septoglomus constrictum.
Figure 8. The impacts of arbuscular mycorrhizal fungi (AMF) on the growth parameters of Astragalus mongholicus seedlings. Growth diagram (a), plant height (b), branch number (c), plant biomass (d), blade number (e), root length (f), Calycosin-7-glucoside (g), and formononetin (h). Different letters above the error bars indicate significant differences. CK, inoculated control; GM, Glomus melanosporum; GC, Glmous. claroideum; SC, Septoglomus constrictum.
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Table 1. Glomalin-related soil proteins and their contribution to the soil carbon pool for 31 medicinal plants.
Table 1. Glomalin-related soil proteins and their contribution to the soil carbon pool for 31 medicinal plants.
Plant FamiliesPlant SpeciesEEG (mg/g)TG (mg/g)EEG/SOC (%)TG/SOC (%)
AristolochiaceaeAristolochia contorta1.57 b4.67 a14.65 ghijklmn43.57 defgh
CompositaeArtemisia argyi1.34 def3.86 fghijk16.59 bcdef47.76 bcd
Atractylodes macrocephala1.34 def3.93 defghi15.10 defghijkl44.37 cdefg
Coreopsis tinctoria1.28 fgh3.40 mno15.54 defghij41.24 ghij
Pericallis hybrida1.28 fgh3.59 jklmno16.42 cdefg46.02 cdef
Tussilago farfara1.20 ghi3.54 klmno13.37 lmno39.36 ijk
CrassulaceaeHylotelephium erythrostictum1.14 i3.47 lmno15.23 defghijk46.21 cdef
Sedum aizoon1.32 defg4.20 bcde13.01 no41.29 ghij
Sedum sarmentosum1.36 cdef3.70 ijklm15.09 defghijkl41.03 ghijk
LabiataeGlechoma longituba1.37 cdef4.08 defg12.46 o37.08 k
Nepeta cataria1.37 cdef4.05 defgh16.19 cdefgh47.69 bcd
Scutellaria baicalensis1.71 a4.48 ab16.33 cdefg42.79 fghij
Scutellaria barbata1.20 hi3.73 hijklm13.70 klmno42.56 fghij
LeguminosaeGlycine soja1.20 ghi3.32 no14.81 fghijklm40.94 ghijk
Lespedeza bicolor1.26 fgh3.89 efghij14.47 hijklmn44.54 cdefg
Mimosa pudica1.20 ghi3.64 ijklm15.74 defghi47.67 bcd
LiliaceaeHemerocallis fulva1.35 cdef4.05 defgh13.88 jklmno41.63 ghij
Hosta plantaginea1.31 defg4.21 bcde14.29 ijklmn46.05 cdef
Lilium davidii1.42 cd3.76 ghijkl17.80 bc47.17 bcde
Polygonatum odoratum1.28 fgh3.84 fghijk16.84 bcd50.55 ab
LinaceaeLinum perenne1.30 defg3.91 defghij15.53 defghij46.83 bcde
RanunculaceaeAconitum carmichaeli1.41 cde4.22 bcd14.25 ijklmn42.79 fghij
Clematis florida1.41 cde3.66 ijklm14.96 efghijklm38.77 jk
Paeonia lactiflora1.19 hi3.69 ijklm16.71 bcde51.93 a
Paeonia suffruticosa1.27 fgh3.81 fghijk14.84 fghijklm44.64 cdefg
StemonaceaeStemona japonica1.47 c4.40 abc13.19 mno39.59 hijk
ScrophulariaceaeRehmannia glutinosa1.29 efgh3.60 ijklmn18.29 b51.11 ab
Scrophularia ningpoensis1.38 cdef3.73 hijklm17.68 bc47.82 bc
UmbelliferaeAngelica dahurica1.30 defg3.60 ijklmn15.62 defghij43.31 efghi
Angelica sinensis1.30 defg4.11 cdef13.98 ijklmno44.03 cdefg
Notopterygium incisum1.41 cd3.28 o20.41 a47.3 bcde
Significant (p < 0.05) variations between various plant species are displayed vertically down the column, denoted by different lettering. EEG: easily extractable glomalin-related soil protein; TG: total extractable glomalin-related soil protein.
Table 2. Soil factors of 31 medicinal plants at Anguo Medicinal Plant Planting Base in Hebei Province, China.
Table 2. Soil factors of 31 medicinal plants at Anguo Medicinal Plant Planting Base in Hebei Province, China.
Plant SpeciespHAvailable K (μg/g)Available P (μg/g)Available N (μg/g)SOC (mg/g)Alkaline Phosphatase (μg/g/h)
Aristolochia contorta7.38 a86.11 ab5.25 a82.13 b10.72 ab100.33 bc
Artemisia argyi7.35 a70.27 fgh4.21 cdefg56.93 ijk8.08 lmn64.29 lmn
Atractylodes macrocephala7.32 a88.70 a4.31 cdefg56.00 jk8.86 ghij69.40 kl
Coreopsis tinctoria7.39 a74.17 cdefg3.20 lmn50.40 lm8.25 klm64.38 lmn
Pericallis hybrida7.29 a49.20 i5.22 a45.97 mn7.80 mno70.38 jkl
Tussilago farfara6.02 b72.63 defg4.65 cd52.97 kl9.00 fghi72.73 ijk
Hylotelephium erythrostictum7.58 a40.98 m2.35 p43.17 n7.50 opq68.69 kl
Sedum aizoon7.33 a77.35 cdef4.62 bcd93.80 a10.18 cd104.96 b
Sedum sarmentosum7.36 a50.90 i5.24 a70.23 de9.02 fghi96.69 cde
Glechoma longituba7.36 a73.00 defg4.09 efghi82.60 b10.99 ab82.96 gh
Nepeta cataria7.33 a76.27 cdef4.16 defgh66.27 efg8.48 ijkl70.78 jkl
Scutellaria baicalensis7.33 a80.91 bc3.94 ghij79.57 bc10.48 bc116.82 a
Scutellaria barbata7.39 a67.77 ghi3.31 klm62.30 ghi8.75 hijk95.53 cde
Glycine soja7.41 a52.24 ki3.65 ijkl57.87 ijk8.11 lmn77.13 hij
Lespedeza bicolor7.37 a77.84 cde2.87 mno64.63 fgh8.72 hijk90.38 def
Mimosa pudica7.39 a76.47 cdef4.45 cdef62.07 ghi7.64 nop80.07 h
Hemerocallis fulva7.40 a71.55 efg5.23 a65.10 efg9.73 de84.29 fgh
Hosta plantaginea7.29 a48.32 i2.83 no74.67 cd9.13 fgh82.11 h
Lilium davidii7.36 a58.47 jk3.01 mno53.43 kl7.97 lmno69.89 jkl
Polygonatum odoratum7.31 a67.71 ghi2.76 nop63.93 fgh7.60 nop61.09 mn
Linum perenne7.29 a74.45 cdefg3.70 hijk56.70 ijk8.36 jklm67.80 klm
Aconitum carmichaeli7.32 a90.35 a4.57 bcde75.37 cd9.87 de97.84 bcd
Clematis florida7.41 a51.25 i2.64 op59.27 hij9.44 ef60.07 n
Paeonia lactiflora7.31 a63.50 hij4.96 ab45.27 mn7.11 pqr78.47 hi
Paeonia suffruticosa7.40 a75.34 cdef3.92 ghij57.17 ijk8.54 ijkl58.11 no
Stemona japonica7.40 a62.03 ij3.23 lmn94.50 a11.12 a100.78 bc
Rehmannia glutinosa7.29 a59.72 jk3.59 jkl46.43 mn7.05 qr52.02 o
Scrophularia ningpoensis7.36 a70.33 fgh4.02 fghij64.40 fgh7.79 mno89.58 efg
Angelica dahurica7.31 a67.37 ghi2.82 no42.70 n8.31 jklm69.62 jkl
Angelica sinensis7.38 a79.63 bcd3.10 mno68.60 ef9.33 def91.98 de
Notopterygium incisum7.49 a48.91 i4.30 cdefg47.37 mn6.93 r60.47 mn
Significant differences among different plant species (p < 0.05) are denoted by different letters shown vertically down the column. K: available potassium; available P: available phosphorus; available N: available nitrogen; available SOC: soil organic carbon.
Table 3. Mean diversity indices and total colonization of arbuscular mycorrhizal fungi (AMF) in the rhizosphere soil of 31 medicinal plants.
Table 3. Mean diversity indices and total colonization of arbuscular mycorrhizal fungi (AMF) in the rhizosphere soil of 31 medicinal plants.
Plant FamiliesPlant SpeciesTotal Colonization (%)Spore Density (nu./10 g Soil)Species Richness (No. of Species)Simpson
AristolochiaceaeAristolochia contorta83.30 ± 3.30 bc344340.76 ghijk
CompositaeArtemisia argyi57.77 ± 1.93 ij180290.74 kl
Atractylodes macrocephala82.22 ± 1.92 bc214280.75 ijk
Coreopsis tinctoria65.56 ± 1.93 fghi112370.82 bcd
Pericallis hybrida42.22 ± 1.92 l214360.78 efghi
Tussilago farfara81.11 ± 1.93 bc202400.78 fghij
CrassulaceaeHylotelephium erythrostictum49.10 ± 3.33 k204360.87 a
Sedum aizoon76.67 ± 3.33 cd258350.76 hijk
Sedum sarmentosum57.78 ± 1.92 ij278340.82 bcd
LabiataeGlechoma longituba75.56 ± 1.92 cde228260.69 m
Nepeta cataria68.89 ± 8.38 efgh245330.78 efghi
Scutellaria baicalensis94.44 ± 1.92 a360370.82 bcd
Scutellaria barbata63.33 ± 3.33 ghij294360.84 bc
LeguminosaeGlycine soja67.78 ± 1.92 fgh160330.78 efghij
Lespedeza bicolor79.10 ± 6.67 bc204280.72 lm
Mimosa pudica66.67 ± 6.67 fgh173340.81 cde
LiliaceaeHemerocallis fulva75.56 ± 1.92 cde225300.80 def
Hosta plantaginea64.44 ± 1.92 fghi383380.80 cdef
Lilium davidii61.11 ± 9.62 hij177330.75 ijk
Polygonatum odoratum55.56 ± 3.85 jk233290.75 ijk
LinaceaeLinum perenne66.67 ± 3.33 fgh302380.79 defg
RanunculaceaeAconitum carmichaeli85.56 ± 6.94 b294370.79 defg
Clematis florida62.22 ± 3.85 ghij219410.81 cdef
Paeonia lactiflora83.33 ± 3.33 bc320340.81 cde
Paeonia suffruticosa81.11 ± 1.92 bc285330.73 kl
StemonaceaeStemona japonica70.00 ± 3.33 defg329320.75 ijk
ScrophulariaceaeRehmannia glutinosa62.22 ± 3.85 ghij299390.84 ab
Scrophularia ningpoensis83.33 ± 3.33 bc287310.75 jk
UmbelliferaeAngelica dahurica72.21 ± 7.69 def251310.75 ijk
Angelica sinensis64.44 ± 1.92 fghi279490.79 defgh
Notopterygium incisum55.56 ± 1.92 jk195320.71 lm
Significant (p < 0.05) variations between various plant species are displayed vertically down the column, denoted by different lettering.
Table 4. Correlation relationship among arbuscular mycorrhizal fungal (AMF) colonization, spore density, and soil factors.
Table 4. Correlation relationship among arbuscular mycorrhizal fungal (AMF) colonization, spore density, and soil factors.
ItempHOrganic Carbon (mg/g)Alkaline Phosphatase (μg/g/h)Available N (μg/g)Available K (μg/g)Available P (μg/g)EEG (mg/g)TG (mg/g)
Total colonization (%)−0.2280.479 **0.494 **0.398 *0.714 **0.2620.370 *0.503 **
Spore density (nu./10g soil)0.0720.386 *0.500 **0.449 *0.1750.0240.355 *0.647 **
EEG (mg/g)0.1650.576 **0.455 *0.535 **0.2850.177——0.655 **
TG (mg/g)0.0910.789 **0.665 **0.814 **0.547 **0.1760.655 **——
* p < 0.05. ** p < 0.01. EEG: easily extractable glomalin-related soil protein; TG: total extractable glomalin-related soil protein.
Table 5. Structural features of medicinal plant–arbuscular mycorrhizal (AMF) fungal symbiotic networks.
Table 5. Structural features of medicinal plant–arbuscular mycorrhizal (AMF) fungal symbiotic networks.
Network FeaturesObserved ValueThe Predicted Value of the Null Modelp
WNODF34.8431.37*
Specialization0.080.01***
Connectance0.500.64***
Modularity0.120.03***
* p < 0.05; *** p < 0.001.
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Zhang, W.; He, C.; Lin, Y.; Qin, S.; Wang, D.; Li, C.; Li, M.; Sun, X.; He, X. Dynamics of Arbuscular Mycorrhizal Fungi in the Rhizosphere of Medicinal Plants and Their Promotion on the Performance of Astragalus mongholicus. Agronomy 2024, 14, 2695. https://doi.org/10.3390/agronomy14112695

AMA Style

Zhang W, He C, Lin Y, Qin S, Wang D, Li C, Li M, Sun X, He X. Dynamics of Arbuscular Mycorrhizal Fungi in the Rhizosphere of Medicinal Plants and Their Promotion on the Performance of Astragalus mongholicus. Agronomy. 2024; 14(11):2695. https://doi.org/10.3390/agronomy14112695

Chicago/Turabian Style

Zhang, Wanyi, Chao He, Yuli Lin, Shenghui Qin, Duo Wang, Chunmiao Li, Min Li, Xiang Sun, and Xueli He. 2024. "Dynamics of Arbuscular Mycorrhizal Fungi in the Rhizosphere of Medicinal Plants and Their Promotion on the Performance of Astragalus mongholicus" Agronomy 14, no. 11: 2695. https://doi.org/10.3390/agronomy14112695

APA Style

Zhang, W., He, C., Lin, Y., Qin, S., Wang, D., Li, C., Li, M., Sun, X., & He, X. (2024). Dynamics of Arbuscular Mycorrhizal Fungi in the Rhizosphere of Medicinal Plants and Their Promotion on the Performance of Astragalus mongholicus. Agronomy, 14(11), 2695. https://doi.org/10.3390/agronomy14112695

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