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Article

Influence of Intercropping Arisaema amurense with Acanthopanax senticosus on Soil Microbial Community and the Effective Ingredients of A. senticosus

by
Jiapeng Zhu
1,2,
Yayu Zhang
1,2,3,
Cai Shao
1,2,
Bochen Lv
1,2,
Hao Liang
1,2,
Weiyu Cao
1,2,
Guojia Zhang
1,2 and
Hai Sun
1,2,*
1
Institute of Special Economic Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
2
Jilin Provincial Key Laboratory of Traditional Chinese Medicinal Materials Cultivation and Propagation, Changchun 130112, China
3
College of Pharmacy and Biological Engineer, Chengdu University, Chengdu 610106, China
*
Author to whom correspondence should be addressed.
Horticulturae 2024, 10(6), 592; https://doi.org/10.3390/horticulturae10060592
Submission received: 23 April 2024 / Revised: 26 May 2024 / Accepted: 3 June 2024 / Published: 5 June 2024
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Abstract

:
Intercropping is an effective cultivation strategy for promoting soil health, changing microbial community, reducing fertiliser application and enhancing the quality of medicinal plants. Nevertheless, the interaction effect of intercropping between Arisaema amurense and Acanthopanax senticosus remains unknown. Herein, we investigated the difference in soil properties, soil enzyme activities, microbial community diversity and active ingredients of A. senticosus in monoculturing versus intercropping of A. senticosus/A. amurense in a field experiment. High-throughput sequencing and liquid chromatography–mass spectrometry were employed to explore the growth promotion effect in the intercropping mode. Results revealed that intercropping benefitted the accumulation of ammonium nitrogen and total nitrogen in soil; total nitrogen and ammonium nitrogen increased by 33% (rhizosphere) and 65% (inter-row) and by 123% (rhizosphere) and 124% (inter-row) at 0–20 cm soil depths, respectively. Furthermore, intercropping increased the soil carbon/nitrogen ratio at the soil from 20 to 40 cm and promoted the growth of the root system of the deep-rooted plant A. senticosus. However, it exerted a certain inhibitory effect on the activities of urease, sucrase and neutral phosphatase on the soil surface. Intercropping increased bacterial diversity and inhibited fungal diversity in soil, potentially preventing the soil microflora changed from bacterial type to fungal type. In terms of community composition, intercropping exhibited a greater effect on bacteria than on fungi. At the phylum level, the relative abundance of microorganisms associated with nutrient cycling and increased ecosystem resistance increased in intercropped soils, such as those of Proteobacteria, Actinobacteriota and Bacteroidota. At the genus level, the bacterial genera that showed significantly increased relative abundance in intercropping soil included unclassified_Acidobacteriales, Sphingomonas, Gemmatimonas and Candidatus_Solibacter. Furthermore, the relative abundance of Cladosporium, a potential plant pathogen in intercropped rhizosphere soil, was 42% lower than that in monocultured rhizosphere soil. Additionally, intercropping can promote the accumulation of eleutheroside B, eleutheroside E, quercetin, protocatechuic acid and polysaccharide, which increased by 551%, 53%, 10%, 28% and 26%, respectively, compared with that after monoculturing. According to the Pearson correlation heat map, rapidly available phosphorus, rapidly available potassium, ammonium nitrogen, nitrate nitrogen, total nitrogen and urease exhibited the greatest impact on the soil microbial community and on the active ingredients of A. senticosus. In conclusion, intercropping altered the composition of the soil microbial community and increased the content of the active ingredients of A. senticosus, consequently begetting economic and ecological benefits.

1. Introduction

The ecological planting model of Chinese herbal medicines (CHM) has become well known in contemporary agricultural practice. This model, guided by ecological theory, aims to achieve the high-quality, safe and efficient production of CHM by combining modern scientific and technological achievements with traditional agricultural principles to regulate key ecological elements in the planting system [1]. Among these, intercropping is a sustainable agricultural cultivation technique that plays a crucial role in ecological cultivation. It can effectively solve problems caused by the monoculturing process of medicinal plants, such as rhizosphere soil microbial community disorders [2], decreased soil enzyme activity [3] and soil nutrient disorders [4]. Biodiversity is well known before being a decisive factor in maintaining the stability of field ecosystems. Intercropping enhances the diversity of biological communities in the field, thus positively affecting the direction of evolution and functioning of soil microbial clusters as well as improving the activity of soil enzymes and enabling a high yield of high-quality herbal medicines, contributing to the high-quality development of the herbal medicine industry.
In recent years, considerable attention has been paid to studying the intercropping of medicinal plants, and the development of the intercropping model has paid more and more attention to the service function of the ecosystem [5]. The structure and activity of soil microbial communities regulate nutrient turnover and transport, as well as the rate of soil organic matter decomposition. Therefore, the composition of soil microbial communities is critical for maintaining soil ecosystem services. Soil microbial communities have been identified as a key driver for the conservation of soil ecosystem services [6,7]. For example, intercropping with legumes increases the abundance of nitrogen-fixing bacteria in the soil, enhancing the ability of the crop to accept nitrogen and reducing the need for additional fertiliser application [8]. Soil enzymes are key catalysts of soil biochemical processes and are essential for maintaining and promoting soil ecosystem function. They play a role in various biogeochemical cycles, including the cycling of elements such as carbon, nitrogen, phosphorus and sulfur, and have a direct impact on the supply and transformation of plant nutrients. For instance, urease (UE) can increase the effective soil nitrogen content and participate in the soil nitrogen cycle [9]. Sucrase (SC) can hydrolyse the high molecular sucrose in soil and provide a carbon source for soil microorganisms [10]. Additionally, intercropping reportedly regulates the evolutionary direction of soil microbial clusters. Previous studies have reported that intercropping can increase the relative abundance of soil bacteria belonging to the Proteobacteria, Acidobacteriota and Actinobacteriota phyla, simultaneously reducing the relative abundance of pathogenic bacteria, such as Fusarium, in soil, to improve the inter-root micro-ecological environment [11,12,13]. This effect of intercropping on soil microbial communities may be because of the production of specific root secretions by different crops in the intercropping systems, which leads to the formation of inter-root microbial communities that are compatible with the specific crops, resulting in complex microbial communities that enhance the overall metabolic activity of soil microorganisms and promote the development of diverse soil microbial community structures [14].
Acanthopanax senticosus (Rupr. & Maxim.) harms belonging to the Araliaceae family are mainly distributed in Russia, Japan, northeastern China and Korea [15]. Studies have shown that the roots, stems, leaves and fruits of A. senticosus are rich in various active ingredients with medicinal value, such as saponins, flavonoids, phenolics, polysaccharides and coumarins [16]. Currently, the artificial cultivation industry of A. senticosus faces several challenges that have resulted in the slow development of the industry, including a long natural growth cycle, difficult cultivation, low yield and mixed quality [17]. In this regard, the introduction of A. amurense into the cultivation system of A. senticosus can effectively address the challenges caused by the monoculturing process of A. senticosus. Increasing biodiversity can enhance the stability of field ecosystems and prevent soil nutrient depletion resulting from the single nutrient demand of monoculturing. Moreover, variations in root structure, root secretion and nutrient utilisation among different plants can improve soil nutrient efficiency. A. senticosus is widely recognised to have a deeper root system than A. amurense, resulting in a difference in their below-ground ecological niche. This difference can reduce competition between the two plants for soil nutrients in the same space. Several studies have demonstrated that interspecific interactions between intercropped plant species can enhance the accumulation of active ingredients in medicinal plants, thereby improving the quality of medicinal herbs [18,19]. Therefore, intercropping offers a novel approach to promoting the healthy development of the ecological cultivation of A. senticosus while enhancing the economic and ecological benefits of the industry.
Overall, ecological planting patterns, such as intercropping, can improve resource utilisation efficiency, maintain ecosystem stability and contribute to the healthy development of the A. senticosus cultivation industry. This study examines the ecological effects of intercropping A. senticosus with A. amurense via field experiments. We hypothesised that soil properties, soil enzyme activities, soil microbial diversity and effective ingredients of A. senticosus would be significantly affected by intercropping compared with monoculturing. The objectives of this study were to determine the effect of intercropping A. senticosus with A. amurense on (1) soil properties and soil enzyme activities, (2) bacterial and fungal diversity and community composition and (3) changes in the effective ingredients of A. senticosus and (4) evaluate the relations between the soil microbial community and soil properties and enzyme activities under intercropping systems.

2. Materials and Methods

2.1. Site Description and Experimental Design

This experiment was carried out at the Zuojia Experimental Base (126°09′ E, 42°94′ N) in the Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences (CAAS), and the experimental field covers an area of about 300 square meters. It belongs to the temperate monsoon continental climate. The average annual temperature is 5.6 °C, with an average monthly maximum temperature of 22.1 °C and a minimum of −18.2 °C. The average multi-year growing accumulated temperature is 2779.8 °C, the average annual rainfall is 679 mm and the average frost-free period is 120 days. The physical and chemical characteristics of the soil before the experiments began were: pH of 6.02, total phosphorus (TP) of 0.81 g·kg−1, total potassium (TK) of 48.36 g·kg−1, total nitrogen (TN) of 1.33 g·kg−1, soil organic carbon (SOC) of 10.87 g·kg−1, rapidly available phosphorus (AP) of 46.33 mg·kg−1, rapidly available potassium (AK) of 212.48 mg·kg−1, ammonium nitrogen (AN) of 38.14 mg·kg−1 and nitrate nitrogen (NN) of 45.39 mg·kg−1.
The experiment was performed from April 2023 to September 2023. The tested plants were A. senticosus and A. amurense. Two planting modes were adopted in the experimental design, namely A. senticosus monoculturing (M) and A. senticosus and A. amurense intercropping (I). The specific planting is shown in Figure 1. The A. senticosus was planted in April 2023 with a plant spacing of 60 cm and row spacing of 80 cm. In May 2023, A. amurense was sown between rows of A. senticosus, with a plant spacing of 30 cm. Each treatment was repeated thrice. Regular manual weeding was performed depending on the weed situation, and no fertiliser was applied.

2.2. Plant and Soil Sampling

Samples were collected in September 2023 when plant growth and microbial activity were at their highest [20]. Three A. senticosus plants were randomly selected from each of the three replicates of each treatment for plant and soil sampling. First, we used a soil auger to sample the 0–20 cm and 20–40 cm soils in the rhizosphere and between the rows. The soil samples were sieved (mesh size of 2 mm) to remove stones and plant roots and then mixed well. The soil samples were divided into two parts: one half was air dried to determine the soil’s physicochemical properties, and the other half was stored at −80 °C for DNA extraction and soil enzyme activity test. Second, the whole plant of A. senticosus was sampled and dried at 40 °C to determine its active ingredients [21].

2.3. Analysis of Soil Properties and Enzyme Activities

Soil pH was measured using a Mettler SK220 pH metre with a soil/water ratio of 1:2.5.TN, and SOC were determined using an element analyser (Vario EL, Frankfurt, Germany). TP was measured using molybdenum blue via spectrophotometry at 700 nm. TK was measured using a flame photometer (6400 A, Shanghai, China). AN and NN were measured using a continuous flowing analyser (Auto analyzer 3-AA3, Hamburg, Germany) after 1 mol/L KCl extraction [22]. AP and AK were analysed using the analysis method of soil agricultural chemistry [23].
Soil enzyme activities were measured using kits from Beijing Boxbio Science and Technology Co., Ltd. (Beijing, China). Fresh soil samples were passed through the 60-mesh sieve for soil enzyme activity determination. The testing principles and units of the four soil enzymes were defined as follows: UE activity was determined on the principle of sodium hypochlorite–phenol colourimetry, with 1 μg of NH3–N generated per gram of soil sample per day defined as one unit of enzyme activity. SC activity was determined on the principle of the 3,5-dinitrosalicylic acid colourimetry, with 1 mg of reducing sugar produced per gram of soil sample per day defined as one unit of enzyme activity. Neutral phosphatase (NP) activity was determined on the principle of phenyl phosphate disodium colourimetry, with 1 μmol of phenol released per gram of soil sample per day at 37 °C defined as one unit of enzyme activity. Catalase (CAT) decomposes H2O2 so that the absorbance value of the reaction solution at 240 mm decreases with reaction time, and the activity of soil CAT can be characterised based on the rate of change in the absorbance value, with 1 mmol of H2O2 degradation catalysed per gram of soil sample per day being defined as one unit of enzyme activity.

2.4. Determining the Active Ingredients of A. senticosus

The contents of the active ingredients of A. senticosus, including those of eleutheroside B, eleutheroside E, quercetin, isofraxidin and protocatechuic acid, were assessed based on a previous study [24]. The specific steps were as follows: the dried stems were cut into small pieces, ground using a pulveriser and the resulting mixture was passed through an 80-mesh sieve. Then, exactly 1 g of A. senticosus stem powder was weighed and placed in a conical flask. Next, 25 mL of chromatographic methanol was added to the flask and the weight of the mixture was recorded. The mixture was ultrasonicated for 30 min at 250 W and 33 kHz, following which its weight was recorded again. Chromatographic methanol was used to make up for any weight loss. Finally, the solution was filtered through a 0.45-μm membrane to obtain the test solution. The quantitative analysis of the five main target constituents in A. senticosus stems was performed via liquid chromatography–mass spectrometry. To this end, an Agilent ZORBAX Eclipse Plus C18 column (2.1 × 100 mm, 1.8 μm) was used in the analysis and testing processes. The chromatography separation of the target constituents was performed at 30 °C using deionised water containing 0.1% H3PO4 (A) and acetonitrile (B) as the mobile phase according to the following gradient elution: 0–2 min 90% (A), 2–5 min 70 (A)%, 5–7 min 10 (A)% and 7–10 min 90% (A). The flow rate of the system was 0.2 mL/min, and the injection volume was 5 μL.
The polysaccharide content was determined as follows: 1 g of A. senticosus stem powder was weighed and placed in a conical flask. Then, 30 mL of deionised water was added to the flask and ultrasonic extraction was carried out at 55 °C for 50 min at 70 W. After filtration, 5 mL of filtrate was added to 15 mL 80% ethanol and precipitated at 4 °C for 12 h. The solution was centrifuged at 6000 rpm for 5 min, and then 50 mL of deionised water ultrasonic dissolution precipitation at 55 °C was added. Finally, the polysaccharide content was determined via phenol–sulfuric acid colourimetry.

2.5. Soil Microbial Analysis

Soil DNA was extracted using the Power Soil DNA Isolation Kit (MOBIO Laboratories, Carlsbad, CA, USA) (Biomarker Technologies Co., Ltd., Beijing, China) according to the manufacturer’s instructions. DNA quantification and PCR amplification were performed as described in a previous study [25]. Each soil sample was extracted thrice and then mixed and sequenced. High-throughput sequencing analysis of bacterial/fungal rDNA was performed using the Illumina HiSeq 2500 platform (2 × 250 paired ends; Biomarker Technologies Corporation, Beijing, China).

2.6. Statistical Analysis

The data of soil physicochemical properties and soil enzyme activity in monoculturing and intercropping systems were compared using a one-way analysis of variance. Origin2021 was used to draw histograms of soil enzyme activity. The α diversity indices were calculated using QIIME2. PCA plots and correlation heatmaps were obtained using the ggplot2 package for the R4.0.5 language. The LEfSe package in Python3.8 was employed for LEfSe analysis. Microsoft Excel 2020 and IBM SPSS Statistics 23.0 software were utilised for data processing and statistical analysis. Images were retouched using Adobe Illustrator 2021 software.

3. Results

3.1. Active Ingredients of A. senticosus

Table 1 shows the changes in the active ingredients of A. senticosus when it was intercropped with A. amurense. The table indicated that intercropping promoted the accumulation of eleutheroside B, eleutheroside E, quercetin, protocatechuic acid and polysaccharide content in the stems of A. senticosus. Compared with monoculturing, the above five active ingredients showed a significant increase following intercropping of 551%, 53%, 10%, 28% and 26%, respectively. However, there was no significant difference in the isofraxidin content in the stems of A. senticosus.

3.2. Soil Properties and Soil Enzymes

Nine soil physical and chemical properties were determined, as shown in Table 2. TN was higher in intercropped soil and lower in monocultured soil at the 0–20 cm soil depth (by 33% in the rhizosphere and by 65% in the inter-row soils) but showed no significant change at the 20–40 cm soil depth. SOC and NN were significantly lower after intercropping than after monoculturing at a soil depth of 0–20 cm in the rhizosphere (SOC by 15% and NN by 43%) and inter-row (SOC by 12% and NN by 69%) soils, respectively. The AN of intercropped soil was significantly higher than that of monocultured soil at a soil depth of 0–20 cm (by 123% in the rhizosphere and by 124% in the inter-row soils). Meanwhile, there was no significant difference in SOC, NN and AN at the 20–40 cm soil depth. The contents of AK and AP in the rhizosphere and inter-row soils differed between the intercropped and monocultured soil, significantly declining in the intercropped rhizosphere soil by 34% (0–20 cm) and 23% (20–40 cm) and by 27% (0–20 cm) and 30% (20–40 cm), respectively, as well as in the inter-row soils by 51% (0–20 cm) and 49% (20–40 cm) and by 24% (0–20 cm) and 33% (20–40 cm), respectively.
In this field experiment, the activity of four soil enzymes was measured. The effect of the cultivation system on soil enzyme activities is shown in Figure 2. The results showed that UE activity significantly decreased following intercropping in the inter-row soil by 18% (0–20 cm) and 20% (20–40 cm) and in the rhizosphere soil by 18% at 0–20 cm soil depth only. SC activity increased after intercropping in the rhizosphere soil by 7% at a depth of 0–20 cm; however, the increase was not significant, whereas SC activity significantly decreased in the inter-row soil at a depth of 0–20 cm by 20%, with no significant difference from that at the 20–40 cm soil depth in the rhizosphere and inter-row soils. NP activity at a depth of 0–20 cm in the inter-row soil was significantly lower than that at the same depth in monocultured inter-row soil, with no significant change at the 20–40 cm soil depth. There was no significant change in CAT activity between intercropped and monocultured soils at depths of 0–20 and 20–40 cm.

3.3. Soil Microbial Community Structure and Diversity

A total of 1,098,030 high-quality bacterial sequences and 1,056,507 high-quality fungal sequences were obtained from the rhizosphere and inter-row areas of the monocultured and intercropped soil. These were classified into 21,421 bacterial OTUs and 12,258 fungal OTUs, respectively, with a sequence similarity cut-off value of 97%. Among them, 11,444 bacterial OTUs were unique to the intercropping system, and 7272 OTUs were unique to the monoculturing system. Additionally, 4937 fungal OTUs were unique to the intercropping system, and 5485 OTUs were unique to the monoculturing system (Figure 3).
Four α diversity indices (Simpson, Chao1, Shannon and ACE) were used to evaluate the soil microbial community richness and diversity (Figure 4). For the bacteria, the experimental results showed that the Simpson, Chao1, Shannon and ACE indices were significantly higher in the intercropped rhizosphere (IR) and inter-row (IIR) soils than in the monocultured inter-row (MIR) soil. Moreover, the Chao1 and ACE indices in IR were significantly higher than those in monocultured rhizosphere (MR) soil, with no significant differences between Simpson and Shannon with those of MR. For the fungi, the Chao1, ACE and Shannon indices in IR soil were significantly lower than those in MR soil. Overall, soil bacterial α diversity increased, and fungi α diversity decreased when A. senticosus was intercropped with A. amurense.
The principal component analysis (PCA) analysis revealed differences in soil microbial β diversity between the rhizosphere and inter-row soils of A. senticosus under different cultivation systems (Figure 3). In terms of bacteria, MR and MIR were clustered together and separated from IR and IIR, indicating that different cultivation systems had a significant effect on soil bacterial community composition. Contrary to soil bacteria, MR, MIR, IR and IIR fungal communities did not show significant segregation, suggesting that different cultivation systems may have no significant effect on soil fungal community composition. Therefore, the results of PCA revealed that the bacterial community was more sensitive to the response of different farming systems than the fungal community and that different farming systems were directly related to the bacterial community structure.

3.4. Composition of Soil Microbial Communities

The relative abundance of microbes in the intercropped and monocultured soils was first assessed at the phylum level to identify changes in the soil microbial community. The community abundance of the top 10 bacteria at the phylum level is shown in Figure 5. Proteobacteria exhibited the highest abundance, accounting for 29.19–36.13% of the total valid sequences. The dominant phyla in the soil samples were Acidobacteriota (19.30–22.75%), Gemmatimonadota (7.81–9.10%), Actinobacteriota (4.27–7.80%), Chloroflexi (4.43–5.99%), Bacteroidota (3.38–5.73%), unclassified_Bacteria (3.20–5.57%), Myxococcota (3.24–4.18%), Verrucomicrobiota (2.18–3.53%) and Firmicutes (1.82–3.14%). Furthermore, the combined relative abundance of these 10 phyla was ≥90% in each soil sample. Under the intercropping treatment, the abundance of Proteobacteria, Actinobacteriota, Bacteroidota and Patescibacteria increased significantly, while that of unclassified_Bacteria, Firmicutes, Methylomirabilota and Nitrospirota significantly decreased. At the genus level, the abundance of unclassified_Acidobacteriales, Sphingomonas, Gemmatimonas and Candidatus_Solibacter significantly increased following intercropping.
Likewise, the figure displayed the top 10 fungi in terms of community abundance at the phylum level. Ascomycota (57.15–75.00%), Basidiomycota (9.27–20.62%), unclassified_Fungi (5.96–15.65%) and Mortierellomycota (1.90–8.05%) were dominant in both the treatments, accounting for >90% of the total fungal community. Chytridiomycota was significantly lower in IR soil than in MR soil by 141%. At the genus level, intercropping significantly increased the relative abundance of Podospora in soil, and Cladosporium was lower in IR soil than in MR soil by 42%.
To further study the effect of intercropping in soil microbial abundance and composition, the linear discriminant analysis effect size (LEfSe) method was used to obtain signature microbial species between different sample groups (p < 0.05 via Wilcox test; Figure 6). There were 8 significant differences in bacterial communities and 15 significant differences in fungal communities at all the classification levels with LDA values >4.
Based on the LEfSe results, IR signature bacterial communities comprised the Proteobacteria and Acidobacteriota phyla, Alphaproteobacteria and Acidobacteriae classes, Sphingomonadales and Acidobacteriales orders, Sphingomonadaceae family and Sphingomonas genus.
The soil fungi community in MIR comprised Ascomycota, including those from the unclassified class, order, family, genus and species. The Eurotiomycetes class, Chaetothyriales and Trechisporales orders, unclassified_Chaetothyriales and Lasiosphaeriaceae families, unclassified_Chaetothyriales genus and Neocosmospora_rubicola and unclassified_Chaetothyriales species contributed to the fungal community composition characteristics in IR soil. The Podospora genus and Podospora_ellisiana species formed a characteristic fungal community in IIR soil.

3.5. Correlation Analysis

Changes in soil properties may lead to alterations in the structure of the rhizosphere microbial community. To study the key factors that affect rhizosphere soil microorganisms, we conducted correlation analyses of rhizosphere soil properties and microorganisms, showing correlations between species diversity, environmental factors and α indices (Figure 7). Mantel test with network combination diagram revealed that the Shannon, Simpson, Chao1 and ACE indices of the bacteria were significantly correlated with rhizosphere SOC and UE. The species diversity of the bacterial genera showed significant correlations with the abundance of TP, AP, TK, AK, AN, NN, TN, UE, SC and CAT in inter-root soil. Additionally, the Shannon and Simpson indices of fungi were significantly correlated with the abundance of TK. Fungal genus diversity was significantly correlated with the abundance of TP, TK, AN, NN and UE. The correlation between soil properties and bacterial and fungal communities was further demonstrated via Pearson correlation coefficient analysis (Figure 8).
The Pearson correlation heat map revealed a connection between the active ingredients of A. senticosus and abiotic factors such as soil physical and chemical properties and soil enzyme activities and biotic factors such as soil microorganisms (Figure 9). The results showed that protocatechuic acid, eleutheroside E, eleutheroside B and polysaccharides were considerably positively correlated with AP, AK, NN, SOC and UE but significantly negatively correlated with AN and TN. Furthermore, quercetin was significantly positively correlated with AP, AK, NN, SOC and UE but significantly negatively correlated with TN and AN.
Likewise, the correlation between soil microbial genera and the six active ingredients of A. senticosus was represented using a heat map (Figure 10). The bacterial genera Sphingomonas and Gemmatimonas showed a significant positive correlation with protocatechuic acid, eleutheroside E, eleutheroside B and polysaccharide. RB41, unclassified_Vicinamibacterales and MND1 showed a significant negative correlation with protocatechuic acid, eleutheroside E and polysaccharide. Quercetin was significantly negatively correlated with Sphingomonas, Gemmatimonas, unclassified_Acidobacteriales and Candidatus_Solibacter but significantly positively correlated with RB41 and MND1.
Among the fungal genera, unclassified_Ascomycota was significantly negatively correlated with protocatechuic acid, eleutheroside E and polysaccharide but significantly positively correlated with quercetin. Unclassified_Chaetothyriales was significantly positively correlated with eleutheroside B but significantly negatively correlated with quercetin. Podospora was significantly positively correlated with echinacoside B and polysaccharide but significantly negatively correlated with quercetin, while Cladosporium was negatively correlated with eleutheroside B and polysaccharide.

4. Discussion

4.1. Effect of Intercropping on Soil Properties and Soil Enzyme Activities

Most intercropping systems can enhance the use of soil nutrients by plants effectively, but differences in soil properties were observed among intercropping practices. Herein, TN and AN were significantly higher following intercropping than after monoculturing at the soil depth of 0–20 cm. This may be due to the increased expression of genes associated with the nitrogen cycle and the enhanced availability of mineral nitrogen by intercropping [26]. At the same time, SOC and NN were significantly lower following intercropping than after monoculturing at a soil depth of 0–20 cm. AP and AK were significantly lower following intercropping than after monoculturing at the soil depth of 0–40 cm, which did not agree with the results of the previous study [27]. This could be because of two reasons: first, A. senticosus and A. amurense were in a vigorous growth phase in this study and intercropping can improve the uptake of phosphorus and potassium nutrients by A. senticosus, resulting in lower levels of AP and AK at a soil depth of 0–40 cm. Second, the effectiveness of phosphorus and potassium may be influenced by the root secretions of different plants [28,29]. Hence, appropriate supplementation of phosphorus and potassium fertiliser should be ensured during this cultivation process to avoid soil nutrient depletion. Furthermore, SOC was lower in the intercropped soil than in the monocultured soil, suggesting a higher rate of decomposition by the soil microbial community in the intercropping treatment [30]. Combined with changes in soil organic carbon and total nitrogen, the results showed that intercropping significantly increased the C/N ratio of soil at depths of 20–40 cm (by 18% in the rhizosphere and by 65% in the inter-row soils). This increase in the C/N ratio at deeper soil levels favours the growth of deep-rooted plants [31]. Therefore, intercropping A. amurense can improve the nutrient structure of the soil, which can help the growth of the root system of A. senticosus. This, in turn, leads to the formation of a below-ground ecological niche complementary to the growth and improvement in nutrient use efficiency.
Field experiments revealed that intercropping affected soil enzyme activities at the rhizosphere and inter-row levels. Soil enzymes are a crucial factor in maintaining soil ecosystem function. They promote various soil processes and play a crucial role in regulating plant growth, nutrient cycling, soil structure and ecological balance [32]. According to Chen, continuous cropping adversely affects soil enzyme activities, including those of soil urease, catalase, sucrase acid phosphatase, alkaline phosphatase and polyphenol oxidase [33]. By contrast, intercropping increased soil enzyme activities [34]. Contrary to previous studies, intercropping A. amurense significantly reduced UE activities (in IR and IIR soils), SC activities (in IIR soil) and NP activities (in IR soil) at a soil depth of 0–20 cm. The cause of this phenomenon may be the varying response of soil enzymes to intercropped plants. Sun [35] summarised that A. amurense contains compounds with antimicrobial activity and that they inhibit the growth of Cytospora chrysosperma [36]. We speculate that these compounds were also present in the root secretion of A. amurense, and owing to the shallower distribution of A. amurense roots, there was a certain inhibition of UE and NP activities at a soil depth of 0–20 cm. However, further experiments are warranted to confirm this hypothesis.

4.2. Effect of Intercropping on Soil Microorganisms

Rhizosphere microorganisms play a crucial role in the plant life cycle. They possess a greater number of genes than the plant genome, earning them the title of the ‘second genome’ of plants [37]. To study the biotic effects of intercropping patterns, changes in the relative abundance of soil microorganisms are important. Soil microbial diversity and community composition play an important role in soil health and the formation of medicinal plant quality. Therefore, in order to study the effect of intercropping model, the changes in soil microorganisms should be paid much attention.
Overall, in the intercropped soil, the bacterial α diversity indices were significantly higher than that in the monocultured soil. Nevertheless, the fungal diversity indices were lower in the intercropped soil compared with the monocultured soil. The number of bacterial OTUs increased, while the number of fungal OTUs decreased in the intercropped soil. Moreover, the shift from bacterial to fungal soil is a sign of soil fertility failure [38]. Intercropping A. amurense may help prevent a shift towards a fungal-dominated soil and avoid soil fertility failure. Furthermore, the bacterial α diversity was significantly affected by SOC and UE activities (Figure 7). This was because of increased carbon utilisation and metabolic activity in the soil, which in turn led to an increase in the microbial diversity and species richness in the intercropping systems [39]. Additionally, UE activity influenced SOC storage and decomposition. The interactions between these factors significantly impacted soil carbon cycling and nutrient transformation. Intercropping can increase farm diversification compared with monoculturing, which can enrich the sources of soil organic matter and promote soil microbial growth by increasing apoplastic biomass, root secretions and nutrient availability [40]. This study found that this change had an effect only on soil bacterial composition, consistent with the findings of Diakhaté et al. [41].
Soil microbial community composition has a strong impact on soil nutrient composition and structural characteristics [42]. The analysis of bacterial community composition revealed no changes in the dominant bacterial phyla in the rhizosphere and inter-row soils in the monoculturing and intercropping systems. However, there were differences in their relative abundance. Intercropping systems can enhance soil nutrient accumulation and nutrient use efficiency by promoting the growth of microorganisms closely associated with nitrogen fixation or other nutrient cycling processes. Herein, the abundance of the bacterial phyla Proteobacteria, Actinobacteriota, Bacteroidota and Patescibacteria was significantly higher in the intercropping system than in the monoculturing system.
Research has shown that Actinobacteria produce a range of extracellular hydrolytic enzymes that break down soil organic matter and enhance the cycling of elements such as carbon and nitrogen [43]. Bacteroidota is abundant in bacteria related to the transformation of biomolecules [44]. These changes in the soil bacterial community structure improved the soil nutrient status after intercropping. LEfSe analysis revealed that Proteobacteria were the signature community of IR, while Proteobacteria were oligotrophic bacteria, which can better predict the multifunctional resistance of ecosystems [45]. Therefore, the changes in the soil bacterial community structure after intercropping can likewise enhance soil resistance and ecosystem stability. The MR signature community, Sphingomonas, showed significant negative correlations with UE, AK and NN and significant positive correlations with AN and TN. These results suggest that such soil properties and enzymes play a crucial role in determining the relative abundance of Sphingomonas.
The dominant phyla in the intercropping and monoculturing systems were the same in terms of fungal community composition. This is consistent with descriptions of arid agricultural lands globally [46]. At the genus level, intercropping significantly increased the relative abundance of Podospora and decreased the relative abundance of Cladosporium, a potential plant pathogen [47]. Therefore, intercropping plays an important role in improving the soil environment and reducing the content of plant pathogens. The study revealed a significant positive correlation between the relative abundance of the unclassified_Chaetothyriales genus in the IR soil signature community and AN content. Likewise, the study found a significant positive correlation between the abundance of the Podospora genus in the IIR soil fungal signature community and AN and TN and a significant negative correlation with NN. The study revealed a significant correlation between alterations in fungal communities and variations in soil N effectiveness, which is consistent with the results of Fontaine [48].

4.3. Effect of Intercropping on the Active Ingredients of A. senticosus

The synthesis and accumulation of secondary metabolites in medicinal plants are regulated by complex interactions in the soil environment, which include influences from biotic and abiotic factors [49]. Studying and revealing these regulatory mechanisms is essential to increase the content of secondary metabolites in medicinal plants and improve the quality of medicinal herbs.
The study found significant correlations between most soil properties and the active ingredients of A. senticosus. Specifically, the contents of protocatechuic acid, eleutheroside E, eleutheroside B and polysaccharides were positively correlated with AN and TN. This suggested that A. senticosus may require high nitrogen for growth. During cultivation, the appropriate application of nitrogen fertiliser can enhance the synthesis and accumulation of active ingredients in A. senticosus. Additionally, controlling the content of AP, AK, NN, SOC and UE in the soil may induce a defence response and increase the accumulation of secondary metabolites in A. senticosus. This is because, under nutrient-limited conditions, the plant produces additional secondary metabolites to adapt to this abiotic stress [50,51].
Microorganisms can affect the accumulation of active ingredients in medicinal plants by improving their nutrition, regulating growth and resisting pests, diseases and drought, which in turn affects their quality. For instance, beneficial microorganisms in the rhizosphere of Hypericum perforatum can stimulate the secondary metabolism of the plant and increase the content of hypericin and pseudohypericin [52]. Herein, intercropping significantly increased the relative abundance of bacterial genera such as unclassified_Acidobacteriales, Sphingomonas, Gemmatimonas and Candidatus_Solibacter and of the fungal genus Podospora. At the same time, these genera were significantly positively correlated with the content of active ingredients in A. senticosus. Furthermore, a signature bacterial genus, Sphingomonas, screened in the IR was significantly and positively correlated with protocatechuic acid, eleutheroside E, eleutheroside B and polysaccharides. Additionally, a signature fungal genus, unclassified_Chaetothyriales, was positively correlated with the content of eleutheroside B. The soil microflora of IIR was screened for the fungal genus Podospora, which was significantly and positively correlated with eleutheroside B and polysaccharide. These microflorae may be the key genera in improving the quality of A. senticosus herbs.

5. Conclusions

In conclusion, the intercropping system markedly improved the content of protocatechuic acid, eleutheroside E, eleutheroside B, quercetin and polysaccharides in the stems of A. senticosus compared to monocropping, which contributed to the stability of the quality of A. senticosus herbs. The results also indicated that introduced A. amurense into A. senticosus traditional monoculture system significantly increased soil nitrogen supply levels but was unfavourable to soil enzyme activities. The intercropping system not only increased bacterial alpha diversity and decreased fungal alpha diversity but also improved the structure of the soil bacterial community and enriched more beneficial bacteria involved in soil nutrient cycling and enhancing soil resistance. The changes in soil AP, AK, NN, AN, TN and UE induced by intercropping were important potential factors for the prediction of microbial diversity and the active ingredients of A. senticosus.

Author Contributions

Conceptualization, J.Z. and H.S.; Data curation, C.S.; Formal analysis, H.L.; Investigation, G.Z.; Methodology, J.Z., H.S. and Y.Z.; Software, W.C. and C.S.; Validation, B.L.; Visualization, B.L.; Writing—original draft, J.Z. and H.S.; Writing—review and editing, H.S.; Financial support, H.S. All authors have read and agreed to the published version of the manuscript.

Funding

This study received funding from National Key R&D Program of China (2021YFD1600902).

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Schematic diagram of the planting pattern. (a): A. senticosus monoculture, (b): A. senticosus intercropped with A. amurense. Note: The triangle represents A. senticosus, the circle represents A. amurense, and the square represents the sampling point between the rows.
Figure 1. Schematic diagram of the planting pattern. (a): A. senticosus monoculture, (b): A. senticosus intercropped with A. amurense. Note: The triangle represents A. senticosus, the circle represents A. amurense, and the square represents the sampling point between the rows.
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Figure 2. Results of soil urease activity (a), sucrase invertase activity (b), neutral phosphatase activity (c), and catalase activity (d) under treatments of monoculture and intercropping systems. Different alphabetical letters indicate significant differences at p < 0.05 (n = 4).
Figure 2. Results of soil urease activity (a), sucrase invertase activity (b), neutral phosphatase activity (c), and catalase activity (d) under treatments of monoculture and intercropping systems. Different alphabetical letters indicate significant differences at p < 0.05 (n = 4).
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Figure 3. OTU differences and principal component analysis (PCA) analysis between soil bacteria (a,c) fungal (b,d) in monoculture (M) and intercropping (I) level of field soil.
Figure 3. OTU differences and principal component analysis (PCA) analysis between soil bacteria (a,c) fungal (b,d) in monoculture (M) and intercropping (I) level of field soil.
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Figure 4. The index of Simpson, Shannon, ACE and Chao1 of the bacteria (a–d) and fungal (e–h) in monoculture rhizosphere (MR), monoculture inter-row (MIR), intercropping rhizosphere (IR) and intercropping inter-row (IIR) systems. The symbols *, ** and *** were used only to indicated significantly with p < 0.5, p < 0.01 and p < 0.001, respectively.
Figure 4. The index of Simpson, Shannon, ACE and Chao1 of the bacteria (a–d) and fungal (e–h) in monoculture rhizosphere (MR), monoculture inter-row (MIR), intercropping rhizosphere (IR) and intercropping inter-row (IIR) systems. The symbols *, ** and *** were used only to indicated significantly with p < 0.5, p < 0.01 and p < 0.001, respectively.
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Figure 5. Relative abundance of bacterial (a,c) and fungal (b,d) at the phylum and genus level. Only the top 10 abundance phyla and top 15 abundance genus are shown in this figure.
Figure 5. Relative abundance of bacterial (a,c) and fungal (b,d) at the phylum and genus level. Only the top 10 abundance phyla and top 15 abundance genus are shown in this figure.
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Figure 6. LEfSe analysis of soil bacterial and fungal community. (a): Bacterial LEfSe evolutionary branching diagram. (b): Bacterial LDA histogram. (c): Fungal evolutionary branching diagram. (d): Fungal LDA histogram. LDA > 4. Yellow color is for microorganisms with no significant difference.
Figure 6. LEfSe analysis of soil bacterial and fungal community. (a): Bacterial LEfSe evolutionary branching diagram. (b): Bacterial LDA histogram. (c): Fungal evolutionary branching diagram. (d): Fungal LDA histogram. LDA > 4. Yellow color is for microorganisms with no significant difference.
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Figure 7. Network diagram of species, alpha index and environmental factors. And a heat map of Pearson correlation between environmental factors and environmental factors. (a): Bacterial. (b): Fungal.
Figure 7. Network diagram of species, alpha index and environmental factors. And a heat map of Pearson correlation between environmental factors and environmental factors. (a): Bacterial. (b): Fungal.
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Figure 8. Heat map of the correlation between bacterial (a) and fungal (b) genera and soil physicochemical properties and soil enzyme activity. The symbols *, ** and *** were used only to indicated significantly with p < 0.5, p < 0.01 and p < 0.001, respectively.
Figure 8. Heat map of the correlation between bacterial (a) and fungal (b) genera and soil physicochemical properties and soil enzyme activity. The symbols *, ** and *** were used only to indicated significantly with p < 0.5, p < 0.01 and p < 0.001, respectively.
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Figure 9. Heat map of the correlation between soil physicochemical properties, soil enzyme activity and the active ingredients of A. senticosus. The symbols * and ** were used only to indicated significantly with p < 0.5 and p < 0.01, respectively.
Figure 9. Heat map of the correlation between soil physicochemical properties, soil enzyme activity and the active ingredients of A. senticosus. The symbols * and ** were used only to indicated significantly with p < 0.5 and p < 0.01, respectively.
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Figure 10. Heat map of Pearson’s rank correlation coefficients between the active ingredients of A. senticosus and the relative abundance of bacterial (a) and fungal (b) communities at the genus level, respectively. The symbols *, ** and *** were used only to indicated significantly with p < 0.05, p < 0.01 and p < 0.001, respectively.
Figure 10. Heat map of Pearson’s rank correlation coefficients between the active ingredients of A. senticosus and the relative abundance of bacterial (a) and fungal (b) communities at the genus level, respectively. The symbols *, ** and *** were used only to indicated significantly with p < 0.05, p < 0.01 and p < 0.001, respectively.
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Table 1. Active ingredients of A. senticosus.
Table 1. Active ingredients of A. senticosus.
TreatmentProtocatechuic Acid μg/gEleutheroside E μg/gIsofraxidin μg/gQuercetin
μg/g		Eleutheroside B μg/gPolysaccharide mg/g
monoculture103.23 ± 0.42 b36.92 ± 0.84 b21.07 ± 0.13 a0.135 ± 0.004 b0.79 ± 0.05 b11.27 ± 0.34 b
intercropping131.84 ± 0.64 a56.38 ± 0.36 a21.08 ± 0.41 a0.148 ± 0.001 a5.14 ± 0.05 a14.20 ± 0.73 a
Note: Different letters in the same column indicate significant differences, p < 0. 05, (n = 4).
Table 2. Soil properties in monoculture and intercropping systems.
Table 2. Soil properties in monoculture and intercropping systems.
0–20 cm Soil
A. senticosus Monocropping		A. senticosus/A. amurense Intercropping20–40 cm Soil
A. senticosus Monocropping		A. senticosus/A. amurense Intercropping
RhizosphereInter-RowRhizosphereInter-RowRhizosphereInter-RowRhizosphereInter-Row
pH6.23 ± 0.26 cd6.62 ± 0.14 a6.38 ± 0.15 abc6.50 ± 0.14 ab6.16 ± 0.07 d6.25 ± 0.02 cd6.31 ± 0.04 bcd6.42 ± 0.02 abc
TN (g/kg)1.54 ± 0.06 b1.39 ± 0.01 b2.05 ± 0.25 a2.29 ± 0.59 a1.26 ± 0.03 b1.26 ± 0.04 b1.35 ± 0.01 b1.18 ± 0.01 b
TP (g/kg)0.92 ± 0.07 ab1.04 ± 0.03 a0.93 ± 0.01 ab0.89 ± 0.04 ab0.90 ± 0.10 ab0.87 ± 0.08 b0.88 ± 0.09 ab0.84 ± 0.08 b
TK (g/kg)51.41 ± 1.94 ab52.27 ± 1.96 ab48.74 ± 2.16 b49.57 ± 2.38 ab53.46 ± 2.11 a51.60 ± 2.02 ab49.29 ± 2.11 ab49.92 ± 1.21 ab
SOC (g/kg)15.10 ± 0.66 a12.66 ± 0.34 b13.13 ± 0.37 b10.91 ± 1.34 c10.73 ± 0.48 c10.60 ± 0.58 c10.22 ± 0.09 c9.30 ± 0.03 d
AK (mg/kg)301.69 ± 5.43 b350.31 ± 3.73 a199.75 ± 2.02 e169.95 ± 5.94 f214.97 ± 6.59 d264.15 ± 6.05 c166.59 ± 5.22 f134.86 ± 4.12 e
AP (mg/kg)73.07 ± 4.30 a69.47 ± 1.29 a53.07 ± 3.07 cd52.53 ± 6.05 cd64.80 ± 5.00 ab58.47 ± 2.00 bc45.20 ± 6.63 de38.93 ± 1.40 e
AN (mg/kg)9.44 ± 1.66 cd6.61 ± 1.32 d21.07 ± 0.95 a14.81 ± 1.73 b14.73 ± 1.22 b7.15 ± 1.01 d12.62 ± 2.08 bc21.54 ± 2.48 a
NN (mg/kg)35.52 ± 2.34 b42.73 ± 1.26 a20.14 ± 0.81 d13.31 ± 1.95 e28.65 ± 0.68 c28.83 ± 0.82 c27.73 ± 0.42 c13.11 ± 0.30 e
Note: Different letters in the same line indicate significant differences, p < 0.05, (n = 4). pH: soil pH; TN: total nitrogen; TP: total phosphorus; TK: total potassium; SOC: soil organic carbon; AK: rapidly available potassium; AP: rapidly available phosphorus; AN: ammonium nitrogen; NN: nitrate nitrogen.
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Zhu, J.; Zhang, Y.; Shao, C.; Lv, B.; Liang, H.; Cao, W.; Zhang, G.; Sun, H. Influence of Intercropping Arisaema amurense with Acanthopanax senticosus on Soil Microbial Community and the Effective Ingredients of A. senticosus. Horticulturae 2024, 10, 592. https://doi.org/10.3390/horticulturae10060592

AMA Style

Zhu J, Zhang Y, Shao C, Lv B, Liang H, Cao W, Zhang G, Sun H. Influence of Intercropping Arisaema amurense with Acanthopanax senticosus on Soil Microbial Community and the Effective Ingredients of A. senticosus. Horticulturae. 2024; 10(6):592. https://doi.org/10.3390/horticulturae10060592

Chicago/Turabian Style

Zhu, Jiapeng, Yayu Zhang, Cai Shao, Bochen Lv, Hao Liang, Weiyu Cao, Guojia Zhang, and Hai Sun. 2024. "Influence of Intercropping Arisaema amurense with Acanthopanax senticosus on Soil Microbial Community and the Effective Ingredients of A. senticosus" Horticulturae 10, no. 6: 592. https://doi.org/10.3390/horticulturae10060592

APA Style

Zhu, J., Zhang, Y., Shao, C., Lv, B., Liang, H., Cao, W., Zhang, G., & Sun, H. (2024). Influence of Intercropping Arisaema amurense with Acanthopanax senticosus on Soil Microbial Community and the Effective Ingredients of A. senticosus. Horticulturae, 10(6), 592. https://doi.org/10.3390/horticulturae10060592

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