Continuous cropping of Strobilanthes sarcorrhiza drives rhizosphere bacterial community dysbiosis and growth differentiation

Continuous cropping of Strobilanthes sarcorrhiza drives rhizosphere bacterial community dysbiosis and growth differentiation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Continuous cropping of Strobilanthes sarcorrhiza drives rhizosphere bacterial community dysbiosis and growth differentiation Meifang Huang, Jiuzhou Chen, Tianchi Jiang, Kuan Xu, Xiaoxia Liu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7473669/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and aims Strobilanthes sarcorrhiza is a medicinal and edible plant of high economic value, yet its sustainable cultivation is severely constrained by continuous cropping, which reduces yield and quality. Unraveling the ecological mechanisms behind these obstacles is critical for developing effective mitigation strategies. Methods We integrated agronomic trait evaluation, soil physicochemical profiling, and 16S rRNA–based microbial community analysis to characterize rhizosphere ecological succession across successive years of S. sarcorrhiza monoculture. Results Continuous cropping obstacles progressively acidified soils and disrupted nutrient balance, with accumulation of soil carbon–nitrogen pools, ammonium enrichment, and nitrate depletion. Rhizosphere bacterial diversity, evenness, and richness declined, accompanied by intensified β-diversity. Functional prediction revealed enrichment of chemoheterotrophic taxa but loss of nitrogen-fixing and cellulose-degrading capacities. Network analysis showed a collapse of cooperative interactions, replaced by antagonistic competition. Notably, beneficial Streptomyces sharply declined, while pathogenic Ralstonia and nematode symbionts ( Xiphinematobacter) proliferated. Conclusions Continuous cropping impairs the rhizosphere soil health of S. sarcorrhiza by causing nutrient imbalances, reducing microbial diversity, and increasing pathogens, which negatively impacts its growth. These findings offer a theoretical basis for addressing continuous cropping challenges in agriculture. continuous cropping Strobilanthes sarcorrhiza soil microbiome nutrient imbalance biocontrol rhizosphere health Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Strobilanthes sarcorrhiza (C. Ling) ( S. sarcorrhiza ), a perennial herbaceous plant of the Malacca genus in the Acanthaceae family, is commonly referred Continuous cropping obstacles (CCOs) to as indigenous Radix Pseudostellariae . The tuberous roots are rich in phenolic compounds, flavonoids, and other bioactive substances, which exhibit pharmacological effects such as nourishing yin, clearing internal heat, tonifying the kidneys, and relieving pain. S. sarcorrhiza is commonly used to treat symptoms such as kidney-deficiency-related lumbago, yin-deficiency-associated toothache, hepatitis, and furunculosis (Chen et al. 2025 ; Zhu et al. 2025 ; Zhang et al. 2008 ). As part of the national strategy for the modernization of traditional Chinese medicine, S. sarcorrhiza has become a representative geo-authentic medicinal species in southeastern Zhejiang Province (Zhang et al. 2019 ). In response to rising market demand, the cultivation area of this species has expanded significantly. However, this expansion has also intensified CCOs, leading to declines in both yield and quality, and resulting in significant economic losses for growers. To date, no dedicated research has been conducted on the mechanisms underlying the CCOs of S. sarcorrhiza . Therefore, understanding the causes of these obstacles and exploring effective mitigation strategies hold both practical and scientific significance. The causes of CCOs are multifaceted, involving alterations in rhizosphere microbial communities induced by root exudates, allelopathic interactions, soil acidification, and other factors (Zhao et al. 2021 ; Li et al. 2025b ). Disruption of soil microbial community structure is considered a primary driver among these factors. Research on continuous cropping in medicinal plants shows that microbial dysbiosis—especially the enrichment of pathogenic microorganisms—plays a key role in perennial medicinal species like Panax ginseng and Panax notoginseng . In continuously cultivated soils, pathogenic fungi such as Fusarium spp. and Phytophthora spp. often become dominant, with community structures markedly distinct from those in non-continuously cropped soils (Zhang et al. 2020 ; Bao et al. 2022 ; Li et al. 2024 ). Unlike species in the genus Panax , S. sarcorrhiza —a perennial herb of the genus Strobilanthes —may shape rhizosphere microbial communities through unique mechanisms mediated by its exudate chemistry, such as phenolic compounds. However, these species-specific processes remain largely unexplored. The core manifestation of microbial imbalance is the disruption of the ecological equilibrium between beneficial and pathogenic microorganisms. Beneficial microbes help suppress soilborne diseases by enhancing ecological functions, such as producing antimicrobial metabolites. Notably, species of Bacillus and Pseudomonas are known to inhibit pathogenic fungi through such mechanisms (Mehrabi et al. 2016 ; Cheng et al. 2020 ). However, under continuous cropping systems, autotoxins (e.g., vanillin in potato monocultures) can significantly alter microbial community composition, reduce the abundance of beneficial taxa, and exacerbate cropping obstacles (Xuan et al. 2024 ; Ma et al. 2023 ; Zhou et al. 2018 ). This microbial imbalance undermines the stability of the soil micro-ecosystem. Pathogen invasion can reduce microbial diversity and disrupt microbial co-occurrence networks—as observed in banana wilt disease, where Fusarium spp. induce abnormal proliferation of rhizospheric fungi (Ma 2020 ). In contrast, biocontrol agents can promote restoration of microbial homeostasis by reshaping community structure, such as by increasing the abundance of Streptomyces spp. (Ma 2020 ; Li 2023 ). Therefore, uncovering the mechanisms of rhizosphere microbial interactions in S. sarcorrhiza , particularly the relationships between beneficial and pathogenic microorganisms, is critical for overcoming the challenges of continuous cropping and enhancing sustainable cropping of this medicinal species. Numerous studies have shown that interactions between biocontrol and pathogenic microorganisms are crucial in regulating CCOs. Pathogens can invade root systems, secrete phytotoxins that damage plant tissues, disrupt the rhizosphere microenvironment, and cause detrimental effects, including stunted growth (Ni 2024 ; Yang 2025 ). Among them, Ralstonia species, which are pathogenic bacteria, significantly disrupt soil microbial balance in continuous cropping systems through colonization and proliferation. These bacteria are highly aggressive soilborne pathogens that cause bacterial wilt in major crops such as tomato, potato, eggplant, and banana (Wang et al. 2023c ; Chachar et al. 2025 ). Under continuous cropping conditions, Ralstonia can alter the composition of root exudates, suppress the growth of beneficial microorganisms, reduce soil bacterial diversity, and decrease network complexity, ultimately leading to soil "pathogenization" (Zhang et al. 2025 ; Pan et al. 2025 ). Due to the ecological risks and potential resistance associated with chemical control, Streptomyces spp. have emerged as key microbial resources for biological control. As biocontrol agents, Streptomyces species can improve soil health and plant resistance through multiple mechanisms. At the soil level, they promote the enrichment of beneficial taxa such as Streptomyces and Nocardia , enhance the activities of key enzymes like urease and phosphatase, and increase nutrient transformation efficiency. Furthermore, they contribute to the restoration of complex, stable microbial co-occurrence networks (Fan et al. 2025 ; Li et al. 2025a ; Pan et al. 2025 ). For instance, Streptomyces sp. JL2001 produces aerugine, which compromises the membrane integrity of Ralstonia cells and directly suppresses their proliferation via the secretion of specific antimicrobial compounds (Zeng et al. 2025 ). Similarly, Streptomyces rochei can form biofilms to competitively occupy favorable ecological niches, thereby reducing Ralstonia colonization in the rhizosphere (Jegan et al. 2025 ). Collectively, investigating the antagonistic interactions between Streptomyces and Ralstonia in continuous cropping systems may offer novel strategies for microbiome-mediated soil health regulation and the mitigation of replanting obstacles. Current research on CCOs in S. sarcorrhiza has primarily focused on nutrient supply (Zhang et al. 2021b ). However, it remains unclear whether the decline in Streptomyces populations directly promotes the enrichment of Ralstonia , and whether soil acidification and nutrient shifts mediate this relationship. In this study, we examined the soil microbial community to investigate the interaction between the biocontrol genus Streptomyces and the pathogenic genus Ralstonia . By comparing microbial community structure across soils with different cultivation durations (1–3 years) and in soils without S. sarcorrhiza cultivation, we assessed how the dynamic balance between Streptomyces and Ralstonia contributes to CCOs. Our findings provide a theoretical basis for elucidating the mechanisms underlying these obstacles and for developing targeted biological control strategies. 2. Materials and methods 2.1 Study area overview The study site is located in Meifeng Village, Huangyan District, Zhejiang Province, China (654 m elevation; 28°37′N, 120°53′E). The region experiences a subtropical monsoon climate with four distinct seasons, mild temperatures, and high humidity. The mean annual temperature is approximately 17°C, with a frost-free period of ~ 250 days and an average annual precipitation of 1676 mm. The predominant soil type is red soil (Ultisol) (Wu et al. 2023 ). Meifeng Village is located in the mountainous western part of Huangyan District and features loose soil texture, good drainage, and moderate-to-low organic matter content—conditions favorable for rhizosphere ecology studies of perennial economic crops such as fruit trees and medicinal plants. S. sarcorrhiza has been cultivated in this region for many years and is regarded as an important traditional medicinal plant at the local level. Its long-term cultivation history makes this site representative for investigating soil microbial succession and functional evolution. The region’s typical topography, well-defined ecological background, and established S. sarcorrhiza cultivation history make it an ideal site for examining the effects of cultivation duration on soil physicochemical properties and microbial community composition. 2.2 Plant sampling and measurement The experiment was conducted at the S. sarcorrhiza cultivation base of Tiande Farm in Huangyan, Zhejiang Province. Field surveys and interviews with local farmers indicated that the third year of continuous cropping is a critical threshold at which replanting obstacles become apparent. At this base, 600 kg/ha of fermented rapeseed cake organic fertilizer is applied annually in June, and all other management practices are standardized. Experimental plots were categorized based on the duration of continuous cultivation: 1-year-old, 2-year-old, and 3-year-old groups. Within each group, six representative 1 m × 1 m quadrats were randomly established, totaling 18 quadrats. In each treatment, S. sarcorrhiza plants with similar growth trends, including aboveground plant height and biomass, were selected for sampling. In each quadrat, eight uniformly growing plants were randomly selected for morphological measurements. Plant height and the length of the longest leaf were measured using a ruler. Stem diameter (measured 5 cm above the soil surface) and tuber width (measured at the widest point) were recorded using a vernier caliper. All plants within each quadrat were harvested, and their aboveground and belowground biomass, along with individual tuber fresh weight, were measured using an electronic balance. 2.3 Soil sampling and analysis Soil samples were collected from four treatment groups: unplanted soil (Unplanted) and rhizosphere soil from 1-, 2-, and 3-year S. sarcorrhiza cultivation plots. Six additional 1 m × 1 m quadrats were established for the Cultivated group, resulting in a total of 24 sampling plots across all treatments. A five-point composite sampling method was employed. In the planted plots, rhizosphere soil was collected by gently shaking off soil attached to the roots at the plot center and four corners. For the Unplanted group, bulk soil was collected from a depth of 3–5 cm to avoid root interference. All soil samples were sealed in labeled plastic bags and transported under chilled conditions. Sampling was conducted carefully to preserve soil structure and minimize disturbance, ensuring the native microbial community remained intact. Rhizosphere samples intended for microbial DNA extraction and community analysis were immediately stored at − 80°C. Remaining soil samples were divided into two portions: (1) air-dried at room temperature and sieved through a 2 mm mesh for physicochemical analysis; (2) stored at 4°C for microbial biomass carbon (MBC) and nitrogen (MBN) determination. The physicochemical properties of the soil were assessed employing various analytical techniques. The quantification of soil organic matter (OM) was conducted through external heating digestion utilizing potassium dichromate, with subsequent colorimetric detection performed at a wavelength of 580 nm. Soil pH was determined using a pH meter (PB-10, Sartorius, Germany) with a soil-water ratio of 1:5 (w/v). The cation exchange capacity (CEC) was extracted using a 1.66 c M solution of Co(NH₃)₆Cl₃ and subsequently quantified through colorimetric analysis at a wavelength of 475 nm. MBC and MBN were quantified employing the chloroform-fumigation-extraction technique (Vance et al. 1987 ). The extraction process utilized a 0.5 M K₂SO₄ solution, and the quantification was conducted using a TOC-L analyzer (CPH/CPN, Kyoto, Japan). Available nitrogen (AvN) was determined using the diffusion dish method. Ammonium nitrogen (NH₄⁺-N) and nitrate nitrogen (NO₃⁻-N) were extracted with 2 M KCl solution and measured using the indophenol blue method and dual-wavelength spectrophotometry, respectively (Zhang et al. 2021a ). Available phosphorus (AvP) was extracted with 0.5 M NaHCO₃ solution and quantified using the molybdenum-antimony colorimetric method (Wang et al. 2023b ). Available potassium (AvK) was extracted with neutral 1 M CH₃COONH₄ solution and measured with quantification by flame photometry (Xu et al. 2025 ). 2.4 Soil DNA extraction and sequencing analysis 2.4.1 DNA extraction and PCR amplification Microbial genomic DNA was extracted from soil samples using the ALFA-SEQ Magnetic Soil DNA Kit (Findrop, Guangzhou, China). DNA concentration and purity were assessed with a NanoDrop One spectrophotometer (Thermo Fisher Scientific, MA, USA). The V3–V4 hypervariable regions of the bacterial 16S rRNA gene were amplified via PCR using universal primers 338F (5′-ACTCCTACGGGAGGCAGCA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′), with the extracted DNA serving as the template. Amplification was performed using a Bio-Rad S1000 thermal cycler (Bio-Rad Laboratories, CA, USA). More details for amplicon sequencing can refer to Yabei et al. (2023). PCR products were verified by 1.5% agarose gel electrophoresis. Product concentrations were quantified using GeneTools Analysis Software (v4.03.05.0, SynGene), and equimolar pooling was carried out accordingly. 2.4.2 Sequence processing and taxonomic annotation PCR products were purified using the E.Z.N.A.® Gel Extraction Kit (Omega Bio-tek, USA) and eluted with TE buffer. Library construction was followed by paired-end (PE250) sequencing on the Illumina HiSeq 2500 platform (Guangdong Magigene Biotechnology Co., Ltd., Guangzhou, China). Raw reads were processed using Cutadapt for adapter trimming and denoised, filtered, and merged using the DADA2 algorithm within the QIIME2 platform. Amplicon sequence variants (ASVs) were generated and taxonomically annotated using the SILVA 138 database ( https://www.arb-silva.de/ ). Sequences identified as chloroplast or mitochondrial in origin were removed prior to downstream analysis. 2.4.3 Community structure and functional prediction Based on the ASV annotations obtained from 16S rRNA sequencing, microbial functional prediction was performed using the FAPROTAX (Functional Annotation of Prokaryotic Taxa) database. FAPROTAX maps bacterial taxonomic information to known ecological functions, covering nitrogen cycling (e.g., nitrogen fixation, nitrification, denitrification, ureolysis), carbon metabolism (e.g., chemoheterotrophy, facultative/aerobic/anaerobic chemoheterotrophy, cellulolysis), sulfur cycling, and other microbial ecological processes. In this study, we focused on the core functions of carbon and nitrogen metabolism and key nitrogen cycling processes in the rhizosphere. The relative abundance of each functional group was calculated and compared across different treatments, including continuous cropping for 1, 2, and 3 years, as well as the unplanted control. This allowed us to assess the effects of continuous S. sarcorrhiza cultivation on rhizosphere microbial ecological functions and the potential of soil carbon and nitrogen metabolism. 2.5 Statistical analysis All experimental data were organized and analyzed using Microsoft Excel 2019 and SPSS 26.0. One-way ANOVA was employed to assess differences among treatment groups, followed by Duncan’s multiple range test for pairwise comparisons at a significance level of P < 0.05. Graphs were generated using GraphPad Prism 9.5.1 and R software (v4.2.2). β-diversity analysis was conducted via principal coordinates analysis (PCoA), and statistical significance was tested using permutational multivariate analysis of variance (PERMANOVA), both based on normalized species-level abundance data using the vegan package in R. Microbial co-occurrence networks were constructed using R packages including dynamicTreeCut, fastcluster, WGCNA, psych, reshape2, and igraph, and visualized with Gephi. Functional annotation and visualization of FAPROTAX results were performed using tidyverse, ggplot2, and patchwork packages. Additionally, microbial community composition, correlation analyses, and LEfSe (Linear Discriminant Analysis Effect Size) significance tests were conducted using the OmicStudio platform ( https://www.omicstudio.cn/tool ). 3. Results 3.1 Effects of continuous cropping on the growth of S. sarcorrhiza Continuous cropping of S. sarcorrhiza led to a pronounced divergence between aboveground and belowground growth. As shown in Fig. 1a, aboveground growth in 3-year-old plants was notably reduced compared with earlier growth stages. ANOVA and multiple comparison tests indicated that, compared with the 2-year-old group, 3-year-old plants had significantly greater belowground biomass (Fig. 1b) and root tuber yield (Fig. 1d). However, plant height (Fig. 1e), aboveground biomass (Fig. 1f), maximum leaf length (Fig. 1g), and stem width (Fig. 1h) were all significantly lower. Specifically, relative to the 2-year-old group, these aboveground traits decreased by 35.1%, 69.9%, 18.3%, and 16.8%, respectively. Additionally, root tuber width increased with prolonged cultivation (Fig. 1c). 3.2 Effects of continuous cropping of S. sarcorrhiza on soil physicochemical properties Continuous cropping of S. sarcorrhiza significantly altered the physicochemical properties of rhizosphere soil, particularly affecting soil carbon and nitrogen pools, pH, nitrogen forms, and mineral elements (Table 1 ). The cumulative effects on carbon and nitrogen pools, as well as microbial biomass, exhibited a progressive increase with the duration of continuous cultivation. Specifically, in the 3-year-old plots, the MBC, MBN, and OM increased by 290.8%, 281.1%, and 40.0%, respectively, compared to the unplanted soils. Nitrogen forms showed inverse differentiation, with NH₄⁺-N and AvN increasing, while NO₃⁻-N levels decreased. Both AvN and NH₄⁺-N concentrations increased in the 3-year-old soils, rising by 107.6% and 52.85%, respectively, compared to the unplanted soils. In contrast, NO₃⁻-N levels showed a continuous decline, with the 3-year-old soils showing a 19.5% reduction compared to the unplanted soils. Soil acidification was most pronounced in the 2-year-old plots, with a pH of 4.76, indicating significant soil acidification. The other available soil nutrients, including AvP and AvK, were significantly higher in the later stages of continuous cropping (2- and 3-year-old plots) compared to the unplanted soils. CEC also showed a significant increase after planting S. sarcorrhiza . Table 1 Soil physicochemical and nutrient content MBC (mg kg − 1 ) MBN (mg kg − 1 ) OM (g kg − 1) ) AvN (mg kg − 1 ) NH₄⁺-N (mg kg − 1 ) NO₃⁻-N (mg kg − 1 ) AvP (mg kg − 1 ) AvK (mg kg − 1 ) CEC ( cmol + kg − 1) pH Unplanted 22.36 ± 10.53c 6.45 ± 1.8d 12.7 ± 0.84b 103.19 ± 13.66c 9.85 ± 1.09c 112.58 ± 9.47a 19.51 ± 0.34c 78.06 ± 10.78b 3.64 ± 0.81c 5.62 ± 0.36a 1-year-old 31.09 ± 5.82c 13.08 ± 3.47c 13.06 ± 1.74b 171.62 ± 11.28b 11.53 ± 2.13bc 114.62 ± 11.29a 20.2 ± 0.46bc 196.76 ± 13.54a 6.48 ± 1.07b 5.74 ± 0.14a 2-year-old 57.45 ± 13.51b 20.18 ± 3.96b 15.57 ± 1.12b 204.23 ± 17.87a 13.4 ± 2.01ab 100.98 ± 10.53ab 20.58 ± 0.27ab 182.31 ± 12.55a 5.03 ± 0.93bc 4.76 ± 0.24b 3-year-old 88.02 ± 10.93a 27.77 ± 4.64a 23.24 ± 2.83a 214.2 ± 15.17a 15.05 ± 1.98a 94.91 ± 5.57b 20.91 ± 0.6a 173.01 ± 30.87a 10.37 ± 1.45a 5.43 ± 0.27a Microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), cation exchange capacity (CEC), organic matter (OM), available nitrogen (AvN), ammonium nitrogen (NH₄⁺-N), nitrate nitrogen (NO₃⁻-N), available phosphorus (AvP), available potassium (AvK). Values are means ± SD, n = 6. Different alphabetical letters above means indicate significant differences at P < 0.05 (Tukey’s test); 3.3 Effects of continuous cropping of S. sarcorrhiza on rhizosphere bacterial community diversity and structure Continuous cropping of S. sarcorrhiza significantly influenced the diversity and structure of the rhizosphere bacterial community. Notable changes were observed in α-diversity, β-diversity, and the taxonomic composition at the phylum level. As shown in Fig. 2 a, the effect of continuous cropping on rhizosphere bacterial α-diversity was evaluated across three metrics: Pielou evenness, Shannon entropy, and Observed features. Pielou evenness consistently decreased with the duration of continuous cultivation, with a significant difference observed between the 2-year-old and unplanted soils (p < 0.05). The 3-year-old group also exhibited significant differences compared to all other treatments (p < 0.05). Both Shannon entropy and Observed features showed a declining trend, with significant differences observed between the 2-year-old and 3-year-old groups compared to the 1-year-old group. Overall, continuous cropping led to a simultaneous decrease in bacterial community evenness, diversity, and richness, with the most significant decline observed in the 3-year-old group. The Principal Coordinates Analysis (PCoA) based on Bray-Curtis distance (Fig. 2 b) showed that PCoA1 (22.60%) and PCoA2 (14.43%) together explained 37.03% of the variation in bacterial community composition. The bacterial community structure of the four treatment groups showed significant clustering, with the 3-year-old soils displaying the greatest spatial separation from the unplanted soils. Figure 2 c shows the temporal succession of rhizosphere bacterial relative abundance at the phylum level. In the 1-year-old soils, Proteobacteria surged to 39.5%, and although this decreased to 31.9% in the 3-year-old soils, it remained the dominant phylum. Acidobacteriota sharply decreased from 34.2% in the unplanted soils to 17.9% in the 1-year-old soils, and showed no significant recovery in the 2-year-old and 3-year-old soils. Verrucomicrobiota dropped to 6.1% in the 1-year-old soils, but increased to 19.1% in the 3-year-old soils, exhibiting a "decline followed by an increase" trend. Conversely, Bacteroidota increased to 12.7% in the 1-year-old soils but decreased to 9.1% in the 3-year-old soils, showing a "rise followed by a decrease" pattern. 3.4 Effects of continuous cropping of S. sarcorrhiza on the nutrient ecological niche adaptation characteristics of differential rhizosphere bacteria Continuous cropping of S. sarcorrhiza significantly regulated the nutrient ecological niche adaptation characteristics of differential rhizosphere bacteria, showing stage-specific patterns closely related to soil factors. LEfSe analysis (Fig. 3 a) identified stage-specific bacterial groups across cuitivation years, while Spearman correlation heatmaps (Fig. 3 b) were used to explore their association with soil factors, revealing significant stage-dependent differentiation. In unplanted soils, Subgroup_2 and AD3 bacteria were enriched, showing significant negative correlations with MBC, MBN, CEC, and most available nutrients (e.g., AvN, AvP), but showing no response to NO₃⁻-N. In the 1-year-old soils, Aurantisolimonas and Ferruginibacter were enriched and positively correlated with CEC, AvP, and AvK, with weak associations to carbon and nitrogen indicators. In this group, Bradyrhizobium was the only genus showing significant positive correlations with MBC, MBN, AvN, and other nutrient indicators, while the other groups showed weak associations. In the 3-year-old soils, Candidatus_Udaeobacter and Vicinamibacteraceae were enriched and strongly correlated with MBC, MBN, CEC, and most available nutrients, but negatively correlated with NO₃⁻-N. 3.5 Effects of continuous cropping of S.sarcorrhiza on the abundance succession of biocontrol and pathogenic bacterial groups Continuous cropping of S. sarcorrhiza significantly influenced the abundance succession of biocontrol bacteria, pathogens, and indirectly pathogenic groups, showing differential functional group patterns. Figure 4 illustrates the regulation of the relative abundance of Streptomyces (biocontrol), Ralstonia (direct pathogen), and Xiphinematobacter (indirect pathogen) across cultivation years, exhibiting functional differentiation. The relative abundance of Streptomyces exhibited a "rise followed by a decline" pattern (Fig. 4 a), with a more than 70% decrease in the 3-year-old soils compared to the peak at 1 year. Ralstonia abundance increased rapidly (Fig. 4 b), with the relative abundance in the 3-year-old soils being 6.3 times higher than in unplanted soils. Xiphinematobacter showed a "rise followed by a decline" fluctuation (Fig. 4 c), with abundance in unplanted soils at 6.99‰, decreasing slightly in 1-year-old soils, but increasing to 9.98‰ in 2-year-old soils, and reaching 17.65‰ in 3-year-old soils. 3.6 Effects of continuous cropping of S. sarcorrhiza on the rhizosphere bacterial metabolic characteristics via FAPROTAX functional prediction FAPROTAX functional predictions were employed to analyze the regulatory patterns of key carbon and nitrogen metabolic functions, as well as nitrogen cycling processes, in the rhizosphere bacterial community across different cultivation years. High-abundance functional groups, including nitrogen fixation, chemoheterotrophy, and aerobic chemoheterotrophy, collectively accounted for over 70%, forming the core functional module of carbon and nitrogen metabolism in rhizosphere bacteria, exhibiting a trend of "increasing chemoheterotrophy and declining nitrogen fixation" (Fig. 5 a). The abundance of nitrification groups significantly decreased in the later years of cultivation (2- and 3-year-old treatments). Cellulolysis and ureolysis groups steadily decreased with increasing cultivation years, while animal-parasites-or-symbionts and predatory-or-exoparasitic groups significantly enriched in the 2- and 3-year-old treatments, as shown in Fig. 5 b. 3.7 Effects of continuous cropping of S. sarcorrhiza on the complexity and synergy of the microbial co-occurrence Network Microbial co-occurrence network analysis (Fig. 6 ) was performed to explore the stage-dependent regulation of rhizosphere bacterial community interaction patterns under continuous cropping. The number of nodes (species richness) in the 1-year-old soils increased compared to the unplanted soils, whereas the 2-year-old and 3-year-old soils showed a gradual decline, reflecting an initial phase of species enrichment followed by a decrease in diversity during the later stages of continuous cropping. Regarding the number of edges (indicating interactions) and positive correlations, the 1-year-old soils showed a slight decrease compared to unplanted soils, while the 2-year-old soils experienced a sharp decline. In the 3-year-old soils, a partial recovery in interactions was observed, indicating a "fine-tuning, collapse, and reorganization" pattern in synergistic interactions over time. The number of negative correlations (antagonistic interactions) showed a mild increase from Unplanted to 1-year-old soils, but dramatically surged to 13 times the level observed in unplanted soils in the 2-year-old soils. In the 3-year-old soils, antagonistic interactions decreased but still remained five times higher than in unplanted soils, highlighting the dominance of antagonistic interactions during the mid-stage of continuous cropping. Additionally, the average degree and network density (measuring connectivity) showed a slight decrease in the 1-year-old soils compared to unplanted soils. The 2-year-old soils exhibited the lowest values, while the 3-year-old soils showed a partial recovery in both metrics. This indicates a shift in the network from a phase of "high synergy" to one characterized by "low connectivity and high antagonism." 4. Discussion CCOs reflect the imbalance in plant-soil-microbe interactions. This study presents a multidimensional analysis of the ecological succession of S. sarcorrhiza under continuous cropping, focusing on agronomic traits, soil quality, and microbial community composition. The aim is to clarify the mechanisms driving the formation of CCOs. 4.1 Resource allocation strategy of S. sarcorrhiza in aboveground and belowground growth With increasing years of continuous cropping, the belowground biomass, root tuber width, and yield of S. sarcorrhiza increased progressively, while aboveground biomass, plant height, stem width, and maximum leaf length decreased. This observed inverse regulation between aboveground and belowground growth is consistent with the typical phenotypic traits associated with CCOs. A similar trend was observed in a study on buckwheat, where continuous cropping initially increased root traits, followed by a decline in the roots and a continuous deterioration of aboveground agronomic traits (Zhang et al. 2021b ). This corroborates the significant impact of continuous cropping on plant resource allocation strategies. The growth differentiation observed in S. sarcorrhiza is directly related to the accumulation of carbon and nitrogen pools in the rhizosphere, with increased ammonium (NH₄⁺) nitrogen and reduced nitrate (NO₃⁻) nitrogen. Previous studies have shown that continuous cropping leads to the overaccumulation of nitrogen and phosphorus in surface soils, resulting in soil acidification (Feng et al. 2022 ). The continuous input of root exudates under long-term monoculture drives microbial community succession, promoting the enrichment of carbon- and nitrogen-loving microorganisms, which further accelerates the directional accumulation of carbon and nitrogen pools (Wang et al. 2024 ). In this study, S. sarcorrhiza appeared to preferentially absorb ammonium nitrogen, and the hydrogen ions released by roots during ammonium uptake likely reduced soil pH, inhibiting nitrifying bacterial activity (Chen et al. 2019 ; Lee et al. 2021 ). This provides insight into the physiological basis underlying the observed growth differentiation. 4.2 Decline in rhizosphere microbial community diversity and succession of functional groups Continuous cropping resulted in a simultaneous decline in the evenness, diversity, and richness of the rhizosphere bacterial community, with the most significant reduction observed in the 3-year-old group. This suggests a continuous decrease in community stability. These findings are consistent with Chen et al.’s observation that "the α-diversity of rhizosphere bacteria in pineapple under continuous cropping is lower than that under crop rotation" (Chen et al. 2020 ). Similarly, Liu et al. reported a reduction in bacterial diversity within the rhizosphere under ginseng continuous cropping systems (Liu et al. 2021 ). Additionally, β-diversity showed a marked increase, with the 3-year-old group exhibiting the greatest spatial distance from the Unplanted control, indicating a significant ecological niche shift in the rhizosphere bacterial community after three consecutive years of cultivation. This highlights the cumulative amplifying effect of continuous cropping on disturbances to the rhizosphere microbiome. FAPROTAX functional predictions revealed functional differentiation in bacterial communities after continuous cropping. Chemoheterotrophic groups became more abundant, coupling with the accumulation of rhizosphere carbon pools, reflecting the efficient utilization of organic carbon by bacteria. Nitrogen fixation functions declined, consistent with the sustained accumulation of available nitrogen and the "nitrogen inhibition effect," suggesting that nitrogen fixation demand decreases as environmental nitrogen accumulates. This finding contrasts with results from continuous sweet potato cultivation, where nitrogen fixation in soil microbial communities was promoted (Zhang et al. 2024 ). The discrepancy may be related to soil pH; in the sweet potato study, the 1-year-old soil pH was 7.79 (Zhang et al. 2024 ), while in this study, the pH of the 1-year-old S. sarcorrhiza soil was much lower at 5.74. The cellulolysis functional group, associated with carbon degradation, showed a continuous decline, suggesting that root residue degradation efficiency decreased under continuous cropping, thereby altering the carbon cycling rhythm (Chen et al. 2024 ). This highlights that CCOs are associated with a reduction in the relative abundance of rhizosphere microbes, influenced by key ecological processes related to nitrogen cycling, antibiotic resistance, and carbon fixation (Cui et al. 2024 ; Deng et al. 2025 ). Additionally, animal parasitic/symbiotic groups significantly enriched in the 2-year-old and 3-year-old soils, reflecting a shift in functional groups toward a "parasitic" succession, which indirectly increases the risk of soilborne diseases. A study on the soil under continuous dragon fruit cultivation indicated that continuous cropping led to an increase in root-knot nematodes, which infest roots, reducing water and nutrient absorption and transport, thereby further impacting the soil ecosystem (Dou et al. 2025 ). Co-occurrence network analysis revealed a sharp decline in Edges num and positive.cor num in the 2-year-old soils, while negative.cor num surged 13-fold compared to unplanted soils. This suggests the collapse of microbial synergistic interactions, with antagonistic competition dominating the community, significantly reducing its resistance to disturbances. This further validates the conclusion that "continuous cropping disrupts microbial network stability" (Yang et al. 2024 ), providing a basis for subsequent analysis of the ecological niche competition between pathogenic and biocontrol bacteria. 4.3 Soil nutrient imbalance and the cascading effects of microbial adaptive succession The "high carbon-nitrogen, low nitrate nitrogen, and acidic" stress environment formed under continuous cropping of S. sarcorrhiza inhibits nutrient absorption and upward transport by the roots, ultimately leading to the weakening of aboveground growth (Haldar and Sengupta 2015 ; Kaysar et al. 2022 ). This nutrient imbalance selectively favors specific bacterial taxa (Zhang et al. 2024 ). In the 2-year-old soils, Bradyrhizobium was the only genus that showed a significant positive correlation with carbon, nitrogen, and available nutrient indicators, while other bacterial groups showed weak associations. This suggests that a single genus dominated the nutrient cycling, leading to a reduction in microbial functional redundancy. In the 3-year-old soils, the enriched microorganisms were predominantly negatively correlated with NO₃⁻-N, indicating that the soil microbial ecosystem had undergone substantial restructuring. When stress-adapted microbes dominate, functional redundancy decreases and pathogenic groups expand (Chen et al. 2014 ). Notably, with increasing cultivation duration, the abundance of the pathogenic bacterium Ralstonia accelerated, being 6.3 times higher in the 3-year-old soils compared to the unplanted soils. Conversely, Streptomyces abundance decreased progressively each year, which likely contributes to the accelerated increase in Ralstonia abundance. Previous studies have shown that Ralstonia infection can cause a 20%-30% decrease in leaf water content and a 30%-50% reduction in plant height in banana and Atractylodes species (Ni 2024 ; Ma 2020 ). In this study, the explosive proliferation of Ralstonia directly explains the suppressed aboveground growth phenotype of S. sarcorrhiza , highlighting the central role of this pathogen in CCOs. Research has shown that applying prebiotics to enhance the competitiveness of beneficial bacteria or introducing antimicrobial strains can effectively control soilborne diseases (Ma et al. 2025 ; Ding et al. 2024 ). This provides a feasible strategy for mitigating CCOs in S. sarcorrhiza . Streptomyces sp. 30702 possesses the ability to influence the soil microbial community, thereby reducing the prevalence of anthracnose, a major pathogen affecting yams. This reduction subsequently decreases the incidence of the disease and alleviates the challenges associated with continuous yam cropping (Fan et al. 2025 ). Furthermore, Streptomyces pactum (strain Act12) has been demonstrated to improve soil quality and enhance the efficiency of cadmium and zinc extraction in plants (Wang et al. 2023a ). The study also observed an annual increase in the abundance of bacterial-feeding nematodes, which aligns with patterns seen in short-term (≤ 5 years) continuous cropping systems where bacterial-feeding nematodes predominate, and long-term (≥ 5 years) systems where plant-parasitic nematodes become more prevalent (Wang et al. 2024 ; Tian et al. 2020 ). These findings suggest an alteration in the soil food web due to the succession of the microbial community. In conclusion, the primary mechanism underlying CCOs in S. sarcorrhiz a is attributed to nutrient imbalance, which exacerbates the decline in microbial community diversity and functional differentiation. This imbalance results in a decrease in Streptomyces biocontrol bacteria and an increase in Ralstonia pathogenic bacteria, thereby disrupting the equilibrium between biocontrol agents and pathogens. These alterations ultimately manifest as a "differentiated growth" between the aboveground and belowground plant components, exemplifying the characteristic barrier phenotype. This conclusion is intricately linked to the study's initial approach, which emphasized the role of soil microbiota, biocontrol, and pathogenic bacteria, thereby providing a theoretical foundation for the development of targeted mitigation strategies. 5. Conclusion In this study reveals that, despite the annual application of organic fertilizers to maintain nutrient supply, CCOs in S. sarcorrhiza remain unavoidable. During the later stages of continuous cropping (2- and 3-year-old), a decrease in soil pH was observed, which corresponded with a continuous decline in α-diversity, an intensification of β-diversity, and a reduction in biocontrol bacteria, specifically Streptomyces. Concurrently, there was an expansion of pathogenic bacteria, such as Ralstonia , and nematode symbionts, including Xiphinematobacter , leading to alterations in microbial metabolic functions. Co-occurrence network analysis revealed a significant increase in negative correlations, suggesting a breakdown of synergistic interactions. Ultimately, these changes culminated in the typical phenotype associated with CCOs, characterized by "compensatory increased belowground productivity and suppressed aboveground growth." This study represents the inaugural identification of microbial-driven characteristics underlying CCOs in the medicinal plant S. sarcorrhiza , thereby contributing to the theoretical framework of continuous cropping in medicinal plants. The findings furnish evidence supporting the mitigation of these obstacles through microbial management strategies, such as the inoculation of Streptomyces. This highlights the imperative of examining the microecology associated with continuous cropping in medicinal plants. Nonetheless, the current study predominantly addresses bacterial communities, necessitating further exploration into the interactions involving fungi and actinobacteria. Moreover, long-term validation at the field scale is yet to be undertaken. Abbreviations S. sarcorrhiza Strobilanthes sarcorrhiza CCOs Continuous cropping obstacles MBC microbial biomass carbon MBN microbial biomass nitrogen CEC cation exchange capacity OM organic matter AvN available nitrogen NH₄⁺-N ammonium nitrogen NO₃⁻-N nitrate nitrogen AvP available phosphorus AvK available potassium FAPROTAX Functional Annotation of Prokaryotic Taxa Declarations Author contributions Meifang Huang: Data curation, Investigation, Methodology, Software, Validation, Visualization, Writing-original draft. Jiuzhou Chen: Data curation, Investigation, Methodology, Writing—review & editing. Tianchi Jiang: Software, Writing-original draft, Writing—review & editing. Kuan Xu: Writing-original draft, Writing—review & editing. Xiaoxia Liu: Project administration, Resources. Jie Wang: Project administration, Resources. Weiying Ji: Project administration, Resources. Haizhong Lin: Project administration, Resources. Luyi Peng: Funding acquisition, Project administration, Resources, Writing-review & editing. Shengke Tian: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Writing-original draft, Writing-review & editing. Funding This work was supported by the Agricultural Science and Technology Cooperation Program of Zhejiang Province（2025SNJF099） Data availability The datasets generated during the current study are available from the corresponding author on reasonable request. 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Values are means ± SD, \u003cem\u003en\u003c/em\u003e = 8. Different alphabetical letters above means indicate significant differences at P \u0026lt; 0.05 (Tukey’s test).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7473669/v1/078f97f26cfcf8e359ba435e.png"},{"id":91210674,"identity":"71d0549c-a4f7-47d3-bb1b-d28c36350fe9","added_by":"auto","created_at":"2025-09-12 17:48:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":143863,"visible":true,"origin":"","legend":"\u003cp\u003eDiversity and composition characteristics of rhizosphere bacterial communities in \u003cem\u003eS. sarcorrhiza\u003c/em\u003e soils across different cultivation durations (a) α-diversity analysis of soil bacterial communities; (b) principal coordinates analysis (PCoA) based on Bray-Curtis distances, illustrating changes in bacterial community structure; (c) relative abundance of bacterial phyla. Values are means ± SD, \u003cem\u003en\u003c/em\u003e = 6. Different alphabetical letters above means indicate significant differences at P \u0026lt; 0.05 (Tukey’s test).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7473669/v1/78841befbcb7a839d6f379ad.png"},{"id":91210246,"identity":"17244dae-40b8-4306-a0e0-dc3731fd7176","added_by":"auto","created_at":"2025-09-12 17:40:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":407502,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential bacterial groups and their environmental associations in the rhizosphere of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e across different cultivation durations (a) LEfSe analysis (LDA ≥ 3.5) of rhizosphere bacterial communities, highlighting group-specific bacterial taxa; (b) spearman correlation heatmap of specific bacterial taxa and soil factors. In the figure, *, **, and *** represent significant differences at the P \u0026lt; 0.05, P \u0026lt; 0.01, and P \u0026lt; 0.001 levels, respectively.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7473669/v1/8290909f0e5fc1b267512c4e.png"},{"id":91210673,"identity":"46a0f175-a352-4881-9da2-5d04d388d94d","added_by":"auto","created_at":"2025-09-12 17:48:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":145088,"visible":true,"origin":"","legend":"\u003cp\u003eSuccession of the abundance of biocontrol and pathogenic bacterial groups in the rhizosphere under continuous cropping (a) biocontrol bacteria \u003cem\u003eStreptomyces\u003c/em\u003e; (b) pathogenic bacteria \u003cem\u003eRalstonia\u003c/em\u003e; (c) potential pathogenic bacteria \u003cem\u003eXiphinematobacter\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7473669/v1/df43fcdaae72d5cd6144c154.png"},{"id":91210672,"identity":"0dac1e41-4968-4502-ae5e-7e75188b4201","added_by":"auto","created_at":"2025-09-12 17:48:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":79412,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of FAPROTAX functional group proportions in the rhizosphere bacterial communities of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e across different cultivation durations (a)high-abundance functional groups (proportion \u0026gt; 10%); (b) low-abundance functional groups (proportion \u0026lt; 10%). Values are means ± SD, \u003cem\u003en\u003c/em\u003e = 6. Different alphabetical letters above means indicate significant differences at P \u0026lt; 0.05 (Tukey’s test).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7473669/v1/65d4354460b91f49eecf11a7.png"},{"id":91210254,"identity":"3756d93b-a4d9-4169-977f-016a266f0395","added_by":"auto","created_at":"2025-09-12 17:40:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":192728,"visible":true,"origin":"","legend":"\u003cp\u003eTopological structure and interaction pattern Succession of rhizosphere bacterial co-occurrence networks under continuous cropping (a-d) visualization of co-occurrence networks; (e-j) quantitative analysis of nodes num, edges num, positive.cor num, negative.cor num, average degree, and network density.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7473669/v1/429154dec08ebd075b0e5bab.png"},{"id":92310435,"identity":"d42e58f5-0192-4bb4-9989-bb60831cec68","added_by":"auto","created_at":"2025-09-27 09:51:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2032193,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7473669/v1/1b6943ea-590c-48f0-bbd4-32cd728935af.pdf"},{"id":91210250,"identity":"d270ea53-925c-4a9a-929f-d4bd360b53de","added_by":"auto","created_at":"2025-09-12 17:40:03","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":160595,"visible":true,"origin":"","legend":"\u003cp\u003eGA\u003c/p\u003e","description":"","filename":"GA.png","url":"https://assets-eu.researchsquare.com/files/rs-7473669/v1/3b18ab248b80d7a0763352aa.png"}],"financialInterests":"","formattedTitle":"Continuous cropping of Strobilanthes sarcorrhiza drives rhizosphere bacterial community dysbiosis and growth differentiation","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cem\u003eStrobilanthes sarcorrhiza\u003c/em\u003e (C. Ling) (\u003cem\u003eS. sarcorrhiza\u003c/em\u003e), a perennial herbaceous plant of the Malacca genus in the Acanthaceae family, is commonly referred Continuous cropping obstacles (CCOs) to as indigenous \u003cem\u003eRadix Pseudostellariae\u003c/em\u003e. The tuberous roots are rich in phenolic compounds, flavonoids, and other bioactive substances, which exhibit pharmacological effects such as nourishing yin, clearing internal heat, tonifying the kidneys, and relieving pain. \u003cem\u003eS. sarcorrhiza\u003c/em\u003e is commonly used to treat symptoms such as kidney-deficiency-related lumbago, yin-deficiency-associated toothache, hepatitis, and furunculosis (Chen et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Zhu et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). As part of the national strategy for the modernization of traditional Chinese medicine, \u003cem\u003eS. sarcorrhiza\u003c/em\u003e has become a representative geo-authentic medicinal species in southeastern Zhejiang Province (Zhang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In response to rising market demand, the cultivation area of this species has expanded significantly. However, this expansion has also intensified CCOs, leading to declines in both yield and quality, and resulting in significant economic losses for growers. To date, no dedicated research has been conducted on the mechanisms underlying the CCOs of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e. Therefore, understanding the causes of these obstacles and exploring effective mitigation strategies hold both practical and scientific significance.\u003c/p\u003e\u003cp\u003eThe causes of CCOs are multifaceted, involving alterations in rhizosphere microbial communities induced by root exudates, allelopathic interactions, soil acidification, and other factors (Zhao et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e). Disruption of soil microbial community structure is considered a primary driver among these factors. Research on continuous cropping in medicinal plants shows that microbial dysbiosis\u0026mdash;especially the enrichment of pathogenic microorganisms\u0026mdash;plays a key role in perennial medicinal species like \u003cem\u003ePanax ginseng\u003c/em\u003e and \u003cem\u003ePanax notoginseng\u003c/em\u003e. In continuously cultivated soils, pathogenic fungi such as \u003cem\u003eFusarium\u003c/em\u003e spp. and \u003cem\u003ePhytophthora\u003c/em\u003e spp. often become dominant, with community structures markedly distinct from those in non-continuously cropped soils (Zhang et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bao et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Unlike species in the genus \u003cem\u003ePanax\u003c/em\u003e, \u003cem\u003eS. sarcorrhiza\u003c/em\u003e\u0026mdash;a perennial herb of the genus \u003cem\u003eStrobilanthes\u003c/em\u003e\u0026mdash;may shape rhizosphere microbial communities through unique mechanisms mediated by its exudate chemistry, such as phenolic compounds. However, these species-specific processes remain largely unexplored. The core manifestation of microbial imbalance is the disruption of the ecological equilibrium between beneficial and pathogenic microorganisms. Beneficial microbes help suppress soilborne diseases by enhancing ecological functions, such as producing antimicrobial metabolites. Notably, species of \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003ePseudomonas\u003c/em\u003e are known to inhibit pathogenic fungi through such mechanisms (Mehrabi et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Cheng et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, under continuous cropping systems, autotoxins (e.g., vanillin in potato monocultures) can significantly alter microbial community composition, reduce the abundance of beneficial taxa, and exacerbate cropping obstacles (Xuan et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ma et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhou et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This microbial imbalance undermines the stability of the soil micro-ecosystem. Pathogen invasion can reduce microbial diversity and disrupt microbial co-occurrence networks\u0026mdash;as observed in banana wilt disease, where \u003cem\u003eFusarium\u003c/em\u003e spp. induce abnormal proliferation of rhizospheric fungi (Ma \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In contrast, biocontrol agents can promote restoration of microbial homeostasis by reshaping community structure, such as by increasing the abundance of \u003cem\u003eStreptomyces\u003c/em\u003e spp. (Ma \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, uncovering the mechanisms of rhizosphere microbial interactions in \u003cem\u003eS. sarcorrhiza\u003c/em\u003e, particularly the relationships between beneficial and pathogenic microorganisms, is critical for overcoming the challenges of continuous cropping and enhancing sustainable cropping of this medicinal species.\u003c/p\u003e\u003cp\u003eNumerous studies have shown that interactions between biocontrol and pathogenic microorganisms are crucial in regulating CCOs. Pathogens can invade root systems, secrete phytotoxins that damage plant tissues, disrupt the rhizosphere microenvironment, and cause detrimental effects, including stunted growth (Ni \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yang \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Among them, \u003cem\u003eRalstonia\u003c/em\u003e species, which are pathogenic bacteria, significantly disrupt soil microbial balance in continuous cropping systems through colonization and proliferation. These bacteria are highly aggressive soilborne pathogens that cause bacterial wilt in major crops such as tomato, potato, eggplant, and banana (Wang et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023c\u003c/span\u003e; Chachar et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Under continuous cropping conditions, \u003cem\u003eRalstonia\u003c/em\u003e can alter the composition of root exudates, suppress the growth of beneficial microorganisms, reduce soil bacterial diversity, and decrease network complexity, ultimately leading to soil \"pathogenization\" (Zhang et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Pan et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Due to the ecological risks and potential resistance associated with chemical control, \u003cem\u003eStreptomyces\u003c/em\u003e spp. have emerged as key microbial resources for biological control. As biocontrol agents, \u003cem\u003eStreptomyces\u003c/em\u003e species can improve soil health and plant resistance through multiple mechanisms. At the soil level, they promote the enrichment of beneficial taxa such as \u003cem\u003eStreptomyces\u003c/em\u003e and \u003cem\u003eNocardia\u003c/em\u003e, enhance the activities of key enzymes like urease and phosphatase, and increase nutrient transformation efficiency. Furthermore, they contribute to the restoration of complex, stable microbial co-occurrence networks (Fan et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e; Pan et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). For instance, \u003cem\u003eStreptomyces\u003c/em\u003e sp. JL2001 produces aerugine, which compromises the membrane integrity of \u003cem\u003eRalstonia\u003c/em\u003e cells and directly suppresses their proliferation via the secretion of specific antimicrobial compounds (Zeng et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Similarly, \u003cem\u003eStreptomyces rochei\u003c/em\u003e can form biofilms to competitively occupy favorable ecological niches, thereby reducing \u003cem\u003eRalstonia\u003c/em\u003e colonization in the rhizosphere (Jegan et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Collectively, investigating the antagonistic interactions between \u003cem\u003eStreptomyces\u003c/em\u003e and \u003cem\u003eRalstonia\u003c/em\u003e in continuous cropping systems may offer novel strategies for microbiome-mediated soil health regulation and the mitigation of replanting obstacles.\u003c/p\u003e\u003cp\u003eCurrent research on CCOs in \u003cem\u003eS. sarcorrhiza\u003c/em\u003e has primarily focused on nutrient supply (Zhang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e). However, it remains unclear whether the decline in \u003cem\u003eStreptomyces\u003c/em\u003e populations directly promotes the enrichment of \u003cem\u003eRalstonia\u003c/em\u003e, and whether soil acidification and nutrient shifts mediate this relationship. In this study, we examined the soil microbial community to investigate the interaction between the biocontrol genus \u003cem\u003eStreptomyces\u003c/em\u003e and the pathogenic genus \u003cem\u003eRalstonia\u003c/em\u003e. By comparing microbial community structure across soils with different cultivation durations (1\u0026ndash;3 years) and in soils without \u003cem\u003eS. sarcorrhiza\u003c/em\u003e cultivation, we assessed how the dynamic balance between \u003cem\u003eStreptomyces\u003c/em\u003e and \u003cem\u003eRalstonia\u003c/em\u003e contributes to CCOs. Our findings provide a theoretical basis for elucidating the mechanisms underlying these obstacles and for developing targeted biological control strategies.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study area overview\u003c/h2\u003e\u003cp\u003eThe study site is located in Meifeng Village, Huangyan District, Zhejiang Province, China (654 m elevation; 28\u0026deg;37\u0026prime;N, 120\u0026deg;53\u0026prime;E). The region experiences a subtropical monsoon climate with four distinct seasons, mild temperatures, and high humidity. The mean annual temperature is approximately 17\u0026deg;C, with a frost-free period of ~\u0026thinsp;250 days and an average annual precipitation of 1676 mm. The predominant soil type is red soil (Ultisol) (Wu et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Meifeng Village is located in the mountainous western part of Huangyan District and features loose soil texture, good drainage, and moderate-to-low organic matter content\u0026mdash;conditions favorable for rhizosphere ecology studies of perennial economic crops such as fruit trees and medicinal plants. \u003cem\u003eS. sarcorrhiza\u003c/em\u003e has been cultivated in this region for many years and is regarded as an important traditional medicinal plant at the local level. Its long-term cultivation history makes this site representative for investigating soil microbial succession and functional evolution. The region\u0026rsquo;s typical topography, well-defined ecological background, and established \u003cem\u003eS. sarcorrhiza\u003c/em\u003e cultivation history make it an ideal site for examining the effects of cultivation duration on soil physicochemical properties and microbial community composition.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Plant sampling and measurement\u003c/h2\u003e\u003cp\u003eThe experiment was conducted at the \u003cem\u003eS. sarcorrhiza\u003c/em\u003e cultivation base of Tiande Farm in Huangyan, Zhejiang Province. Field surveys and interviews with local farmers indicated that the third year of continuous cropping is a critical threshold at which replanting obstacles become apparent. At this base, 600 kg/ha of fermented rapeseed cake organic fertilizer is applied annually in June, and all other management practices are standardized. Experimental plots were categorized based on the duration of continuous cultivation: 1-year-old, 2-year-old, and 3-year-old groups. Within each group, six representative 1 m \u0026times; 1 m quadrats were randomly established, totaling 18 quadrats. In each treatment, \u003cem\u003eS. sarcorrhiza\u003c/em\u003e plants with similar growth trends, including aboveground plant height and biomass, were selected for sampling. In each quadrat, eight uniformly growing plants were randomly selected for morphological measurements. Plant height and the length of the longest leaf were measured using a ruler. Stem diameter (measured 5 cm above the soil surface) and tuber width (measured at the widest point) were recorded using a vernier caliper. All plants within each quadrat were harvested, and their aboveground and belowground biomass, along with individual tuber fresh weight, were measured using an electronic balance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Soil sampling and analysis\u003c/h2\u003e\u003cp\u003eSoil samples were collected from four treatment groups: unplanted soil (Unplanted) and rhizosphere soil from 1-, 2-, and 3-year \u003cem\u003eS. sarcorrhiza\u003c/em\u003e cultivation plots. Six additional 1 m \u0026times; 1 m quadrats were established for the Cultivated group, resulting in a total of 24 sampling plots across all treatments. A five-point composite sampling method was employed. In the planted plots, rhizosphere soil was collected by gently shaking off soil attached to the roots at the plot center and four corners. For the Unplanted group, bulk soil was collected from a depth of 3\u0026ndash;5 cm to avoid root interference. All soil samples were sealed in labeled plastic bags and transported under chilled conditions. Sampling was conducted carefully to preserve soil structure and minimize disturbance, ensuring the native microbial community remained intact. Rhizosphere samples intended for microbial DNA extraction and community analysis were immediately stored at \u0026minus;\u0026thinsp;80\u0026deg;C. Remaining soil samples were divided into two portions: (1) air-dried at room temperature and sieved through a 2 mm mesh for physicochemical analysis; (2) stored at 4\u0026deg;C for microbial biomass carbon (MBC) and nitrogen (MBN) determination.\u003c/p\u003e\u003cp\u003eThe physicochemical properties of the soil were assessed employing various analytical techniques. The quantification of soil organic matter (OM) was conducted through external heating digestion utilizing potassium dichromate, with subsequent colorimetric detection performed at a wavelength of 580 nm. Soil pH was determined using a pH meter (PB-10, Sartorius, Germany) with a soil-water ratio of 1:5 (w/v). The cation exchange capacity (CEC) was extracted using a 1.66 c\u003cem\u003eM\u003c/em\u003e solution of Co(NH₃)₆Cl₃ and subsequently quantified through colorimetric analysis at a wavelength of 475 nm. MBC and MBN were quantified employing the chloroform-fumigation-extraction technique (Vance et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). The extraction process utilized a 0.5 \u003cem\u003eM\u003c/em\u003e K₂SO₄ solution, and the quantification was conducted using a TOC-L analyzer (CPH/CPN, Kyoto, Japan). Available nitrogen (AvN) was determined using the diffusion dish method. Ammonium nitrogen (NH₄⁺-N) and nitrate nitrogen (NO₃⁻-N) were extracted with 2 \u003cem\u003eM\u003c/em\u003e KCl solution and measured using the indophenol blue method and dual-wavelength spectrophotometry, respectively (Zhang et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). Available phosphorus (AvP) was extracted with 0.5 \u003cem\u003eM\u003c/em\u003e NaHCO₃ solution and quantified using the molybdenum-antimony colorimetric method (Wang et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). Available potassium (AvK) was extracted with neutral 1 \u003cem\u003eM\u003c/em\u003e CH₃COONH₄ solution and measured with quantification by flame photometry (Xu et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Soil DNA extraction and sequencing analysis\u003c/h2\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.4.1 DNA extraction and PCR amplification\u003c/h2\u003e\u003cp\u003eMicrobial genomic DNA was extracted from soil samples using the ALFA-SEQ Magnetic Soil DNA Kit (Findrop, Guangzhou, China). DNA concentration and purity were assessed with a NanoDrop One spectrophotometer (Thermo Fisher Scientific, MA, USA). The V3\u0026ndash;V4 hypervariable regions of the bacterial 16S rRNA gene were amplified via PCR using universal primers 338F (5\u0026prime;-ACTCCTACGGGAGGCAGCA-3\u0026prime;) and 806R (5\u0026prime;-GGACTACHVGGGTWTCTAAT-3\u0026prime;), with the extracted DNA serving as the template. Amplification was performed using a Bio-Rad S1000 thermal cycler (Bio-Rad Laboratories, CA, USA). More details for amplicon sequencing can refer to Yabei et al. (2023). PCR products were verified by 1.5% agarose gel electrophoresis. Product concentrations were quantified using GeneTools Analysis Software (v4.03.05.0, SynGene), and equimolar pooling was carried out accordingly.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.4.2 Sequence processing and taxonomic annotation\u003c/h2\u003e\u003cp\u003ePCR products were purified using the E.Z.N.A.\u0026reg; Gel Extraction Kit (Omega Bio-tek, USA) and eluted with TE buffer. Library construction was followed by paired-end (PE250) sequencing on the Illumina HiSeq 2500 platform (Guangdong Magigene Biotechnology Co., Ltd., Guangzhou, China). Raw reads were processed using Cutadapt for adapter trimming and denoised, filtered, and merged using the DADA2 algorithm within the QIIME2 platform. Amplicon sequence variants (ASVs) were generated and taxonomically annotated using the SILVA 138 database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arb-silva.de/\u003c/span\u003e\u003cspan address=\"https://www.arb-silva.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Sequences identified as chloroplast or mitochondrial in origin were removed prior to downstream analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.4.3 Community structure and functional prediction\u003c/h2\u003e\u003cp\u003eBased on the ASV annotations obtained from 16S rRNA sequencing, microbial functional prediction was performed using the FAPROTAX (Functional Annotation of Prokaryotic Taxa) database. FAPROTAX maps bacterial taxonomic information to known ecological functions, covering nitrogen cycling (e.g., nitrogen fixation, nitrification, denitrification, ureolysis), carbon metabolism (e.g., chemoheterotrophy, facultative/aerobic/anaerobic chemoheterotrophy, cellulolysis), sulfur cycling, and other microbial ecological processes. In this study, we focused on the core functions of carbon and nitrogen metabolism and key nitrogen cycling processes in the rhizosphere. The relative abundance of each functional group was calculated and compared across different treatments, including continuous cropping for 1, 2, and 3 years, as well as the unplanted control. This allowed us to assess the effects of continuous \u003cem\u003eS. sarcorrhiza\u003c/em\u003e cultivation on rhizosphere microbial ecological functions and the potential of soil carbon and nitrogen metabolism.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e\u003cp\u003eAll experimental data were organized and analyzed using Microsoft Excel 2019 and SPSS 26.0. One-way ANOVA was employed to assess differences among treatment groups, followed by Duncan\u0026rsquo;s multiple range test for pairwise comparisons at a significance level of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Graphs were generated using GraphPad Prism 9.5.1 and R software (v4.2.2).\u003c/p\u003e\u003cp\u003eβ-diversity analysis was conducted via principal coordinates analysis (PCoA), and statistical significance was tested using permutational multivariate analysis of variance (PERMANOVA), both based on normalized species-level abundance data using the vegan package in R. Microbial co-occurrence networks were constructed using R packages including dynamicTreeCut, fastcluster, WGCNA, psych, reshape2, and igraph, and visualized with Gephi. Functional annotation and visualization of FAPROTAX results were performed using tidyverse, ggplot2, and patchwork packages. Additionally, microbial community composition, correlation analyses, and LEfSe (Linear Discriminant Analysis Effect Size) significance tests were conducted using the OmicStudio platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.omicstudio.cn/tool\u003c/span\u003e\u003cspan address=\"https://www.omicstudio.cn/tool\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Effects of continuous cropping on the growth of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e\u003c/h2\u003e\n \u003cp\u003eContinuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e led to a pronounced divergence between aboveground and belowground growth. As shown in Fig. 1a, aboveground growth in 3-year-old plants was notably reduced compared with earlier growth stages. ANOVA and multiple comparison tests indicated that, compared with the 2-year-old group, 3-year-old plants had significantly greater belowground biomass (Fig. 1b) and root tuber yield (Fig. 1d). However, plant height (Fig. 1e), aboveground biomass (Fig. 1f), maximum leaf length (Fig. 1g), and stem width (Fig. 1h) were all significantly lower. Specifically, relative to the 2-year-old group, these aboveground traits decreased by 35.1%, 69.9%, 18.3%, and 16.8%, respectively. Additionally, root tuber width increased with prolonged cultivation (Fig. 1c).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Effects of continuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e on soil physicochemical properties\u003c/h2\u003e\n \u003cp\u003eContinuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e significantly altered the physicochemical properties of rhizosphere soil, particularly affecting soil carbon and nitrogen pools, pH, nitrogen forms, and mineral elements (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The cumulative effects on carbon and nitrogen pools, as well as microbial biomass, exhibited a progressive increase with the duration of continuous cultivation. Specifically, in the 3-year-old plots, the MBC, MBN, and OM increased by 290.8%, 281.1%, and 40.0%, respectively, compared to the unplanted soils. Nitrogen forms showed inverse differentiation, with NH₄⁺-N and AvN increasing, while NO₃⁻-N levels decreased. Both AvN and NH₄⁺-N concentrations increased in the 3-year-old soils, rising by 107.6% and 52.85%, respectively, compared to the unplanted soils. In contrast, NO₃⁻-N levels showed a continuous decline, with the 3-year-old soils showing a 19.5% reduction compared to the unplanted soils.\u003c/p\u003e\n \u003cp\u003eSoil acidification was most pronounced in the 2-year-old plots, with a pH of 4.76, indicating significant soil acidification. The other available soil nutrients, including AvP and AvK, were significantly higher in the later stages of continuous cropping (2- and 3-year-old plots) compared to the unplanted soils. CEC also showed a significant increase after planting \u003cem\u003eS. sarcorrhiza\u003c/em\u003e.\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSoil physicochemical and nutrient content\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMBC\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMBN\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOM\u003c/p\u003e\n \u003cp\u003e(g kg\u003csup\u003e\u0026minus;\u0026thinsp;1)\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAvN\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNH₄⁺-N\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNO₃⁻-N\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAvP\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAvK\u003c/p\u003e\n \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCEC\u003c/p\u003e\n \u003cp\u003e( cmol\u003csup\u003e+\u003c/sup\u003ekg\u003csup\u003e\u0026minus;\u0026thinsp;1)\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnplanted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.36\u0026thinsp;\u0026plusmn;\u0026thinsp;10.53c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103.19\u0026thinsp;\u0026plusmn;\u0026thinsp;13.66c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112.58\u0026thinsp;\u0026plusmn;\u0026thinsp;9.47a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78.06\u0026thinsp;\u0026plusmn;\u0026thinsp;10.78b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year-old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.09\u0026thinsp;\u0026plusmn;\u0026thinsp;5.82c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.08\u0026thinsp;\u0026plusmn;\u0026thinsp;3.47c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e171.62\u0026thinsp;\u0026plusmn;\u0026thinsp;11.28b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e114.62\u0026thinsp;\u0026plusmn;\u0026thinsp;11.29a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e196.76\u0026thinsp;\u0026plusmn;\u0026thinsp;13.54a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2-year-old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.45\u0026thinsp;\u0026plusmn;\u0026thinsp;13.51b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.18\u0026thinsp;\u0026plusmn;\u0026thinsp;3.96b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e204.23\u0026thinsp;\u0026plusmn;\u0026thinsp;17.87a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.01ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.98\u0026thinsp;\u0026plusmn;\u0026thinsp;10.53ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e182.31\u0026thinsp;\u0026plusmn;\u0026thinsp;12.55a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3-year-old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.02\u0026thinsp;\u0026plusmn;\u0026thinsp;10.93a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.77\u0026thinsp;\u0026plusmn;\u0026thinsp;4.64a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e214.2\u0026thinsp;\u0026plusmn;\u0026thinsp;15.17a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.91\u0026thinsp;\u0026plusmn;\u0026thinsp;5.57b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e173.01\u0026thinsp;\u0026plusmn;\u0026thinsp;30.87a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\"\u003eMicrobial biomass carbon (MBC), microbial biomass nitrogen (MBN), cation exchange capacity (CEC), organic matter (OM), available nitrogen (AvN), ammonium nitrogen (NH₄⁺-N), nitrate nitrogen (NO₃⁻-N), available phosphorus (AvP), available potassium (AvK). Values are means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6. Different alphabetical letters above means indicate significant differences at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Tukey\u0026rsquo;s test);\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Effects of continuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e on rhizosphere bacterial community diversity and structure\u003c/h2\u003e\n \u003cp\u003eContinuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e significantly influenced the diversity and structure of the rhizosphere bacterial community. Notable changes were observed in \u0026alpha;-diversity, \u0026beta;-diversity, and the taxonomic composition at the phylum level. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea, the effect of continuous cropping on rhizosphere bacterial \u0026alpha;-diversity was evaluated across three metrics: Pielou evenness, Shannon entropy, and Observed features. Pielou evenness consistently decreased with the duration of continuous cultivation, with a significant difference observed between the 2-year-old and unplanted soils (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The 3-year-old group also exhibited significant differences compared to all other treatments (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Both Shannon entropy and Observed features showed a declining trend, with significant differences observed between the 2-year-old and 3-year-old groups compared to the 1-year-old group. Overall, continuous cropping led to a simultaneous decrease in bacterial community evenness, diversity, and richness, with the most significant decline observed in the 3-year-old group.\u003c/p\u003e\n \u003cp\u003eThe Principal Coordinates Analysis (PCoA) based on Bray-Curtis distance (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb) showed that PCoA1 (22.60%) and PCoA2 (14.43%) together explained 37.03% of the variation in bacterial community composition. The bacterial community structure of the four treatment groups showed significant clustering, with the 3-year-old soils displaying the greatest spatial separation from the unplanted soils. Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec shows the temporal succession of rhizosphere bacterial relative abundance at the phylum level. In the 1-year-old soils, Proteobacteria surged to 39.5%, and although this decreased to 31.9% in the 3-year-old soils, it remained the dominant phylum. Acidobacteriota sharply decreased from 34.2% in the unplanted soils to 17.9% in the 1-year-old soils, and showed no significant recovery in the 2-year-old and 3-year-old soils. Verrucomicrobiota dropped to 6.1% in the 1-year-old soils, but increased to 19.1% in the 3-year-old soils, exhibiting a \u0026quot;decline followed by an increase\u0026quot; trend. Conversely, Bacteroidota increased to 12.7% in the 1-year-old soils but decreased to 9.1% in the 3-year-old soils, showing a \u0026quot;rise followed by a decrease\u0026quot; pattern.\u003c/p\u003e\n \u003cp\u003e3.4 Effects of continuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e on the nutrient ecological niche adaptation characteristics of differential rhizosphere bacteria\u003c/p\u003e\n \u003cp\u003eContinuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e significantly regulated the nutrient ecological niche adaptation characteristics of differential rhizosphere bacteria, showing stage-specific patterns closely related to soil factors. LEfSe analysis (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea) identified stage-specific bacterial groups across cuitivation years, while Spearman correlation heatmaps (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb) were used to explore their association with soil factors, revealing significant stage-dependent differentiation.\u003c/p\u003e\n \u003cp\u003eIn unplanted soils, Subgroup_2 and AD3 bacteria were enriched, showing significant negative correlations with MBC, MBN, CEC, and most available nutrients (e.g., AvN, AvP), but showing no response to NO₃⁻-N. In the 1-year-old soils, \u003cem\u003eAurantisolimonas\u003c/em\u003e and \u003cem\u003eFerruginibacter\u003c/em\u003e were enriched and positively correlated with CEC, AvP, and AvK, with weak associations to carbon and nitrogen indicators. In this group, \u003cem\u003eBradyrhizobium\u003c/em\u003e was the only genus showing significant positive correlations with MBC, MBN, AvN, and other nutrient indicators, while the other groups showed weak associations. In the 3-year-old soils, \u003cem\u003eCandidatus_Udaeobacter\u003c/em\u003e and \u003cem\u003eVicinamibacteraceae\u003c/em\u003e were enriched and strongly correlated with MBC, MBN, CEC, and most available nutrients, but negatively correlated with NO₃⁻-N.\u003c/p\u003e\n \u003cp\u003e3.5 Effects of continuous cropping of \u003cem\u003eS.sarcorrhiza\u003c/em\u003e on the abundance succession of biocontrol and pathogenic bacterial groups\u003c/p\u003e\n \u003cp\u003eContinuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e significantly influenced the abundance succession of biocontrol bacteria, pathogens, and indirectly pathogenic groups, showing differential functional group patterns. Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e illustrates the regulation of the relative abundance of \u003cem\u003eStreptomyces\u003c/em\u003e (biocontrol), \u003cem\u003eRalstonia\u003c/em\u003e (direct pathogen), and \u003cem\u003eXiphinematobacter\u003c/em\u003e (indirect pathogen) across cultivation years, exhibiting functional differentiation.\u003c/p\u003e\n \u003cp\u003eThe relative abundance of \u003cem\u003eStreptomyces\u003c/em\u003e exhibited a \u0026quot;rise followed by a decline\u0026quot; pattern (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea), with a more than 70% decrease in the 3-year-old soils compared to the peak at 1 year. \u003cem\u003eRalstonia\u003c/em\u003e abundance increased rapidly (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb), with the relative abundance in the 3-year-old soils being 6.3 times higher than in unplanted soils. \u003cem\u003eXiphinematobacter\u003c/em\u003e showed a \u0026quot;rise followed by a decline\u0026quot; fluctuation (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ec), with abundance in unplanted soils at 6.99\u0026permil;, decreasing slightly in 1-year-old soils, but increasing to 9.98\u0026permil; in 2-year-old soils, and reaching 17.65\u0026permil; in 3-year-old soils.\u003c/p\u003e\n \u003cp\u003e3.6 Effects of continuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e on the rhizosphere bacterial metabolic characteristics via FAPROTAX functional prediction\u003c/p\u003e\n \u003cp\u003eFAPROTAX functional predictions were employed to analyze the regulatory patterns of key carbon and nitrogen metabolic functions, as well as nitrogen cycling processes, in the rhizosphere bacterial community across different cultivation years. High-abundance functional groups, including nitrogen fixation, chemoheterotrophy, and aerobic chemoheterotrophy, collectively accounted for over 70%, forming the core functional module of carbon and nitrogen metabolism in rhizosphere bacteria, exhibiting a trend of \u0026quot;increasing chemoheterotrophy and declining nitrogen fixation\u0026quot; (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea).\u003c/p\u003e\n \u003cp\u003eThe abundance of nitrification groups significantly decreased in the later years of cultivation (2- and 3-year-old treatments). Cellulolysis and ureolysis groups steadily decreased with increasing cultivation years, while animal-parasites-or-symbionts and predatory-or-exoparasitic groups significantly enriched in the 2- and 3-year-old treatments, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb.\u003c/p\u003e\n \u003cp\u003e3.7 Effects of continuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e on the complexity and synergy of the microbial co-occurrence Network\u003c/p\u003e\n \u003cp\u003eMicrobial co-occurrence network analysis (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e) was performed to explore the stage-dependent regulation of rhizosphere bacterial community interaction patterns under continuous cropping. The number of nodes (species richness) in the 1-year-old soils increased compared to the unplanted soils, whereas the 2-year-old and 3-year-old soils showed a gradual decline, reflecting an initial phase of species enrichment followed by a decrease in diversity during the later stages of continuous cropping.\u003c/p\u003e\n \u003cp\u003eRegarding the number of edges (indicating interactions) and positive correlations, the 1-year-old soils showed a slight decrease compared to unplanted soils, while the 2-year-old soils experienced a sharp decline. In the 3-year-old soils, a partial recovery in interactions was observed, indicating a \u0026quot;fine-tuning, collapse, and reorganization\u0026quot; pattern in synergistic interactions over time.\u003c/p\u003e\n \u003cp\u003eThe number of negative correlations (antagonistic interactions) showed a mild increase from Unplanted to 1-year-old soils, but dramatically surged to 13 times the level observed in unplanted soils in the 2-year-old soils. In the 3-year-old soils, antagonistic interactions decreased but still remained five times higher than in unplanted soils, highlighting the dominance of antagonistic interactions during the mid-stage of continuous cropping.\u003c/p\u003e\n \u003cp\u003eAdditionally, the average degree and network density (measuring connectivity) showed a slight decrease in the 1-year-old soils compared to unplanted soils. The 2-year-old soils exhibited the lowest values, while the 3-year-old soils showed a partial recovery in both metrics. This indicates a shift in the network from a phase of \u0026quot;high synergy\u0026quot; to one characterized by \u0026quot;low connectivity and high antagonism.\u0026quot;\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eCCOs reflect the imbalance in plant-soil-microbe interactions. This study presents a multidimensional analysis of the ecological succession of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e under continuous cropping, focusing on agronomic traits, soil quality, and microbial community composition. The aim is to clarify the mechanisms driving the formation of CCOs.\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Resource allocation strategy of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e in aboveground and belowground growth\u003c/h2\u003e\u003cp\u003eWith increasing years of continuous cropping, the belowground biomass, root tuber width, and yield of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e increased progressively, while aboveground biomass, plant height, stem width, and maximum leaf length decreased. This observed inverse regulation between aboveground and belowground growth is consistent with the typical phenotypic traits associated with CCOs. A similar trend was observed in a study on buckwheat, where continuous cropping initially increased root traits, followed by a decline in the roots and a continuous deterioration of aboveground agronomic traits (Zhang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e). This corroborates the significant impact of continuous cropping on plant resource allocation strategies.\u003c/p\u003e\u003cp\u003eThe growth differentiation observed in \u003cem\u003eS. sarcorrhiza\u003c/em\u003e is directly related to the accumulation of carbon and nitrogen pools in the rhizosphere, with increased ammonium (NH₄⁺) nitrogen and reduced nitrate (NO₃⁻) nitrogen. Previous studies have shown that continuous cropping leads to the overaccumulation of nitrogen and phosphorus in surface soils, resulting in soil acidification (Feng et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The continuous input of root exudates under long-term monoculture drives microbial community succession, promoting the enrichment of carbon- and nitrogen-loving microorganisms, which further accelerates the directional accumulation of carbon and nitrogen pools (Wang et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this study, \u003cem\u003eS. sarcorrhiza\u003c/em\u003e appeared to preferentially absorb ammonium nitrogen, and the hydrogen ions released by roots during ammonium uptake likely reduced soil pH, inhibiting nitrifying bacterial activity (Chen et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lee et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This provides insight into the physiological basis underlying the observed growth differentiation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Decline in rhizosphere microbial community diversity and succession of functional groups\u003c/h2\u003e\u003cp\u003eContinuous cropping resulted in a simultaneous decline in the evenness, diversity, and richness of the rhizosphere bacterial community, with the most significant reduction observed in the 3-year-old group. This suggests a continuous decrease in community stability. These findings are consistent with Chen et al.\u0026rsquo;s observation that \"the α-diversity of rhizosphere bacteria in pineapple under continuous cropping is lower than that under crop rotation\" (Chen et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, Liu et al. reported a reduction in bacterial diversity within the rhizosphere under ginseng continuous cropping systems (Liu et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, β-diversity showed a marked increase, with the 3-year-old group exhibiting the greatest spatial distance from the Unplanted control, indicating a significant ecological niche shift in the rhizosphere bacterial community after three consecutive years of cultivation. This highlights the cumulative amplifying effect of continuous cropping on disturbances to the rhizosphere microbiome.\u003c/p\u003e\u003cp\u003eFAPROTAX functional predictions revealed functional differentiation in bacterial communities after continuous cropping. Chemoheterotrophic groups became more abundant, coupling with the accumulation of rhizosphere carbon pools, reflecting the efficient utilization of organic carbon by bacteria. Nitrogen fixation functions declined, consistent with the sustained accumulation of available nitrogen and the \"nitrogen inhibition effect,\" suggesting that nitrogen fixation demand decreases as environmental nitrogen accumulates. This finding contrasts with results from continuous sweet potato cultivation, where nitrogen fixation in soil microbial communities was promoted (Zhang et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The discrepancy may be related to soil pH; in the sweet potato study, the 1-year-old soil pH was 7.79 (Zhang et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), while in this study, the pH of the 1-year-old \u003cem\u003eS. sarcorrhiza\u003c/em\u003e soil was much lower at 5.74. The cellulolysis functional group, associated with carbon degradation, showed a continuous decline, suggesting that root residue degradation efficiency decreased under continuous cropping, thereby altering the carbon cycling rhythm (Chen et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This highlights that CCOs are associated with a reduction in the relative abundance of rhizosphere microbes, influenced by key ecological processes related to nitrogen cycling, antibiotic resistance, and carbon fixation (Cui et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Deng et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAdditionally, animal parasitic/symbiotic groups significantly enriched in the 2-year-old and 3-year-old soils, reflecting a shift in functional groups toward a \"parasitic\" succession, which indirectly increases the risk of soilborne diseases. A study on the soil under continuous dragon fruit cultivation indicated that continuous cropping led to an increase in root-knot nematodes, which infest roots, reducing water and nutrient absorption and transport, thereby further impacting the soil ecosystem (Dou et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Co-occurrence network analysis revealed a sharp decline in Edges num and positive.cor num in the 2-year-old soils, while negative.cor num surged 13-fold compared to unplanted soils. This suggests the collapse of microbial synergistic interactions, with antagonistic competition dominating the community, significantly reducing its resistance to disturbances. This further validates the conclusion that \"continuous cropping disrupts microbial network stability\" (Yang et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), providing a basis for subsequent analysis of the ecological niche competition between pathogenic and biocontrol bacteria.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Soil nutrient imbalance and the cascading effects of microbial adaptive succession\u003c/h2\u003e\u003cp\u003eThe \"high carbon-nitrogen, low nitrate nitrogen, and acidic\" stress environment formed under continuous cropping of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e inhibits nutrient absorption and upward transport by the roots, ultimately leading to the weakening of aboveground growth (Haldar and Sengupta \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Kaysar et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This nutrient imbalance selectively favors specific bacterial taxa (Zhang et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In the 2-year-old soils, \u003cem\u003eBradyrhizobium\u003c/em\u003e was the only genus that showed a significant positive correlation with carbon, nitrogen, and available nutrient indicators, while other bacterial groups showed weak associations. This suggests that a single genus dominated the nutrient cycling, leading to a reduction in microbial functional redundancy. In the 3-year-old soils, the enriched microorganisms were predominantly negatively correlated with NO₃⁻-N, indicating that the soil microbial ecosystem had undergone substantial restructuring.\u003c/p\u003e\u003cp\u003eWhen stress-adapted microbes dominate, functional redundancy decreases and pathogenic groups expand (Chen et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Notably, with increasing cultivation duration, the abundance of the pathogenic bacterium \u003cem\u003eRalstonia\u003c/em\u003e accelerated, being 6.3 times higher in the 3-year-old soils compared to the unplanted soils. Conversely, \u003cem\u003eStreptomyces\u003c/em\u003e abundance decreased progressively each year, which likely contributes to the accelerated increase in \u003cem\u003eRalstonia\u003c/em\u003e abundance. Previous studies have shown that \u003cem\u003eRalstonia\u003c/em\u003e infection can cause a 20%-30% decrease in leaf water content and a 30%-50% reduction in plant height in banana and Atractylodes species (Ni \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ma \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In this study, the explosive proliferation of \u003cem\u003eRalstonia\u003c/em\u003e directly explains the suppressed aboveground growth phenotype of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e, highlighting the central role of this pathogen in CCOs.\u003c/p\u003e\u003cp\u003eResearch has shown that applying prebiotics to enhance the competitiveness of beneficial bacteria or introducing antimicrobial strains can effectively control soilborne diseases (Ma et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Ding et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This provides a feasible strategy for mitigating CCOs in \u003cem\u003eS. sarcorrhiza\u003c/em\u003e. \u003cem\u003eStreptomyces\u003c/em\u003e sp. 30702 possesses the ability to influence the soil microbial community, thereby reducing the prevalence of anthracnose, a major pathogen affecting yams. This reduction subsequently decreases the incidence of the disease and alleviates the challenges associated with continuous yam cropping (Fan et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Furthermore, \u003cem\u003eStreptomyces pactum\u003c/em\u003e (strain Act12) has been demonstrated to improve soil quality and enhance the efficiency of cadmium and zinc extraction in plants (Wang et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). The study also observed an annual increase in the abundance of bacterial-feeding nematodes, which aligns with patterns seen in short-term (\u0026le;\u0026thinsp;5 years) continuous cropping systems where bacterial-feeding nematodes predominate, and long-term (\u0026ge;\u0026thinsp;5 years) systems where plant-parasitic nematodes become more prevalent (Wang et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Tian et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These findings suggest an alteration in the soil food web due to the succession of the microbial community.\u003c/p\u003e\u003cp\u003eIn conclusion, the primary mechanism underlying CCOs in \u003cem\u003eS. sarcorrhiz\u003c/em\u003ea is attributed to nutrient imbalance, which exacerbates the decline in microbial community diversity and functional differentiation. This imbalance results in a decrease in \u003cem\u003eStreptomyces\u003c/em\u003e biocontrol bacteria and an increase in \u003cem\u003eRalstonia\u003c/em\u003e pathogenic bacteria, thereby disrupting the equilibrium between biocontrol agents and pathogens. These alterations ultimately manifest as a \"differentiated growth\" between the aboveground and belowground plant components, exemplifying the characteristic barrier phenotype. This conclusion is intricately linked to the study's initial approach, which emphasized the role of soil microbiota, biocontrol, and pathogenic bacteria, thereby providing a theoretical foundation for the development of targeted mitigation strategies.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn this study reveals that, despite the annual application of organic fertilizers to maintain nutrient supply, CCOs in \u003cem\u003eS. sarcorrhiza\u003c/em\u003e remain unavoidable. During the later stages of continuous cropping (2- and 3-year-old), a decrease in soil pH was observed, which corresponded with a continuous decline in α-diversity, an intensification of β-diversity, and a reduction in biocontrol bacteria, specifically Streptomyces. Concurrently, there was an expansion of pathogenic bacteria, such as \u003cem\u003eRalstonia\u003c/em\u003e, and nematode symbionts, including \u003cem\u003eXiphinematobacter\u003c/em\u003e, leading to alterations in microbial metabolic functions. Co-occurrence network analysis revealed a significant increase in negative correlations, suggesting a breakdown of synergistic interactions. Ultimately, these changes culminated in the typical phenotype associated with CCOs, characterized by \"compensatory increased belowground productivity and suppressed aboveground growth.\" This study represents the inaugural identification of microbial-driven characteristics underlying CCOs in the medicinal plant \u003cem\u003eS. sarcorrhiza\u003c/em\u003e, thereby contributing to the theoretical framework of continuous cropping in medicinal plants. The findings furnish evidence supporting the mitigation of these obstacles through microbial management strategies, such as the inoculation of Streptomyces. This highlights the imperative of examining the microecology associated with continuous cropping in medicinal plants. Nonetheless, the current study predominantly addresses bacterial communities, necessitating further exploration into the interactions involving fungi and actinobacteria. Moreover, long-term validation at the field scale is yet to be undertaken.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cem\u003eS. sarcorrhiza\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003e\u003cem\u003eStrobilanthes sarcorrhiza\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eCCOs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003eContinuous cropping obstacles\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eMBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003emicrobial biomass carbon\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eMBN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003emicrobial biomass nitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eCEC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003ecation exchange capacity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eOM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003eorganic matter\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eAvN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003eavailable nitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNH₄⁺-N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003eammonium nitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNO₃⁻-N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003enitrate nitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eAvP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003eavailable phosphorus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eAvK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003eavailable potassium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eFAPROTAX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003eFunctional Annotation of Prokaryotic Taxa\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeifang Huang: Data curation, Investigation, Methodology, Software, Validation, Visualization, Writing-original draft.\u003c/p\u003e\n\u003cp\u003eJiuzhou Chen: Data curation, Investigation, Methodology, Writing\u0026mdash;review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eTianchi Jiang: Software,\u0026nbsp;Writing-original draft, Writing\u0026mdash;review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eKuan Xu:\u0026nbsp;Writing-original draft, Writing\u0026mdash;review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eXiaoxia Liu:\u0026nbsp;Project administration, Resources.\u003c/p\u003e\n\u003cp\u003eJie Wang:\u0026nbsp;Project administration, Resources.\u003c/p\u003e\n\u003cp\u003eWeiying Ji: Project administration, Resources.\u003c/p\u003e\n\u003cp\u003eHaizhong Lin:\u0026nbsp;Project administration, Resources.\u003c/p\u003e\n\u003cp\u003eLuyi Peng:\u0026nbsp;Funding acquisition, Project administration, Resources,\u0026nbsp;Writing-review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eShengke Tian: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Writing-original draft, Writing-review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Agricultural Science and Technology Cooperation Program of Zhejiang Province（2025SNJF099）\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBao L, Liu Y, Ding Y, et al (2022) Interactions between phenolic acids and microorganisms in rhizospheric soil from continuous cropping of \u003cem\u003ePanax notoginseng\u003c/em\u003e. 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Breit. on soil physicochemical properties, enzyme activities, microbial communities and functional genes. Chem Biol Technol Agric 8:43. https://doi.org/10.1186/s40538-021-00243-6\u003c/li\u003e\n\u003cli\u003eZhou X, Jia H, Ge X, Wu F (2018) Effects of vanillin on the community structures and abundances of \u003cem\u003eFusarium\u003c/em\u003e and \u003cem\u003eTrichoderma\u003c/em\u003e spp. in cucumber seedling rhizosphere. J Plant Interact 13:45\u0026ndash;50. https://doi.org/10.1080/17429145.2017.1414322\u003c/li\u003e\n\u003cli\u003eZhu S, Yuan S, Wang C, et al (2025) Effects of different pretreatments on the drying and quality characteristics of \u003cem\u003eStrobilanthes sarcorrhiza (C. Ling)\u003c/em\u003e by hot-air drying. Ind Crops Prod 227:120759. https://doi.org/10.1016/j.indcrop.2025.120759\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"continuous cropping, Strobilanthes sarcorrhiza, soil microbiome, nutrient imbalance, biocontrol, rhizosphere health","lastPublishedDoi":"10.21203/rs.3.rs-7473669/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7473669/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and aims Strobilanthes sarcorrhiza\u003c/h2\u003e\u003cp\u003eis a medicinal and edible plant of high economic value, yet its sustainable cultivation is severely constrained by continuous cropping, which reduces yield and quality. Unraveling the ecological mechanisms behind these obstacles is critical for developing effective mitigation strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe integrated agronomic trait evaluation, soil physicochemical profiling, and 16S rRNA\u0026ndash;based microbial community analysis to characterize rhizosphere ecological succession across successive years of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e monoculture.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eContinuous cropping obstacles progressively acidified soils and disrupted nutrient balance, with accumulation of soil carbon\u0026ndash;nitrogen pools, ammonium enrichment, and nitrate depletion. Rhizosphere bacterial diversity, evenness, and richness declined, accompanied by intensified β-diversity. Functional prediction revealed enrichment of chemoheterotrophic taxa but loss of nitrogen-fixing and cellulose-degrading capacities. Network analysis showed a collapse of cooperative interactions, replaced by antagonistic competition. Notably, beneficial \u003cem\u003eStreptomyces\u003c/em\u003e sharply declined, while pathogenic \u003cem\u003eRalstonia\u003c/em\u003e and nematode symbionts (\u003cem\u003eXiphinematobacter)\u003c/em\u003e proliferated.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eContinuous cropping impairs the rhizosphere soil health of \u003cem\u003eS. sarcorrhiza\u003c/em\u003e by causing nutrient imbalances, reducing microbial diversity, and increasing pathogens, which negatively impacts its growth. These findings offer a theoretical basis for addressing continuous cropping challenges in agriculture.\u003c/p\u003e","manuscriptTitle":"Continuous cropping of Strobilanthes sarcorrhiza drives rhizosphere bacterial community dysbiosis and growth differentiation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-12 17:39:58","doi":"10.21203/rs.3.rs-7473669/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6a5e1af7-6e83-470c-bbbf-1b63f9e49e30","owner":[],"postedDate":"September 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-27T09:43:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-12 17:39:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7473669","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7473669","identity":"rs-7473669","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}