Phosphorus fertilizer responsive bacteria and fungi in canola (Brassica napus L.) roots are correlated with plant performance

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Kochian, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4902932/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Feb, 2025 Read the published version in Plant and Soil → Version 1 posted 6 You are reading this latest preprint version Abstract Background Canola ( Brassica napus L.) has high phosphorus demand, but its seedlings are sensitive to seed-placed phosphorus fertilizers. Optimizing phosphorus fertilizer managements (rates and placements) for canola is critical and can be aided by a better understanding of the root-associated microbiome, as it plays key roles in improving phosphorus availability through mineralization and solubilization. Methods We conducted a two-year field experiment applying monoammonium phosphate fertilizers at three rates (no addition, recommended, and high rates at 0, 17, and 32 kg P ha − 1 year − 1 ) using two opener placements (narrow at 2.5 cm vs. wide at 10 cm) which affect seedbed concentration of phosphorus. Canola performance was evaluated, and rhizosphere and root bacterial and fungal microbiomes were profiled by DNA amplicon sequencing. Results High-rate and near-seed placement of phosphorus (32 kg P ha − 1 in the 2.5 cm opener) consistently reduced canola seedling emergence but not biomass and yield, which were higher in 2020 than in 2019. Yearly variations and plant growth stages impacted both the rhizosphere and root microbiomes, while phosphorus fertilization only affected the root microbiome. Specifically, phosphorus fertilization enriched root genera Burkholderia-Caballeronia-Paraburkholderia , Luteibacter , Amaurodon , Trichoderma , and Penicillium . Conversely, Chryseobacterium , Chitinophaga , Flavobacterium and Olpidium were more prevalent in roots without phosphorus addition. Canola yield was positively correlated with the abundance of Burkholderia-Caballeronia-Paraburkholderia and Trichoderma in roots. Conclusions Phosphorus fertilizer rates and placements affect canola germination but not seed yield. Profiling of phosphorus-responsive bacteria and fungi in the roots suggests that phosphorus fertilization can have a lasting impact on the canola root microbiome, modulating plant growth responses to soil phosphorus availability. Phosphorus fertilizer management canola growth response rhizosphere and root microbiomes phosphorus responsive bacteria and fungi Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Canola ( Brassica napus . L) plants have high phosphorus demand, and early season phosphorus deficiency can restrict crop growth, potentially reducing grain yield (Grant et al. 2001 ). Granular monoammonium phosphate (MAP) (11-52-0) has been widely applied as seed-placed phosphorus fertilizer to satisfy this demand, and its efficiency depends on both phosphorus rate and placement (Malhi et al. 2008 ). The recommended rate of seed-placed phosphorus fertilizer in western Canada is7-12 kg P ha − 1 , and 12 kg P ha − 1 in Saskatchewan (Saskatchewan Ministry of Agriculture 2023 ). These rates, however, cannot compensate the phosphorus removal by canola, as optimal yields require 30–35 kg P ha − 1 (Canola Council of Canada 2023), whereas excessive rate can result in phosphorus toxicity to seedlings (Grant and Flaten 2019 ; Qian and Schoenau 2010 ). The placement of phosphorus fertilizer, particularly the width of the furrow opener in which seeds and fertilizers placed together into the soil, can impact fertilizer efficiency. For instance, a narrow opener can elevate phosphorus concentration in the seed-row, making phosphorus more accessible for the plant, but can escalates the risk of seedling damage (Lemke et al. 2009 ; Shao et al. 2023 ). Therefore, optimizing phosphorus fertilization is crucial for canola, and studies on the combinations of varied phosphorus rates and placements can fill this gap. Soil fertilization can not only directly impact plant growth through nutrient supply, but also through the indirectly impact on the belowground bulk soil microbiome, and thus the root-associated microbiome (Zhao et al. 2020 ; Li et al. 2023a ; Gomes et al. 2018 ). Previous studies have revealed that both soil nitrogen and phosphorus fertilization can determine the relative abundance and composition of the bacterial communities in the rhizosphere of maize and wheat (Liu et al. 2020 ; Liu et al. 2023b ). The decrease in microbial richness and diversity in the bulk soil upon fertilization has also been reported (Zhou et al. 2016 ; Wang et al. 2018 ). Despite major observations of decreased microbial diversity, the increased of microbial diversity were also reported. The addition of a balanced fertilization of nitrogen-phosphorus-potassium, increased the soil microbial diversity, potentially related to the acceleration of nutrient turnover and genes involved in carbon, nitrogen, phosphorus, and sulfur cycling, which promoted rice growth (Su et al. 2014 ). Moreover, the long-term inorganic fertilization on a paddy soil increased the bacterial richness and diversity in the bulk soil (Huang et al. 2019 ). Except for the impact of the overall microbial community, specific microbes responded to fertilization. For example, nitrogen fertilization has been shown to impact the root-associated microbiome in field-grown canola, where Gammaproteobacteria, Bacteroidia, Actinobacteria, Sordariomycetes, Dothideomycetes , and Agaricomycetes from the rhizosphere soil were suggested to be the nitrogen-responding bacterial classes (Li et al. 2023a ). Currently, the root-associated microbiome of canola has been profiled and the impact of nitrogen fertilization on the microbiome has been reported (Lay et al. 2018 ; Li et al., 2023a ), however, there is limited information on the effects of phosphorus fertilization. This gap in knowledge is particularly significant because, despite the large total pool of phosphorus in soil, only a small fraction is directly available to plants, primarily bound in organic forms requiring conversion to inorganic forms for uptake (Richardson and Simpson, 2011 ). Moreover, soil phosphorus availability is further constrained by its binding to minerals such as iron, aluminum, and calcium, which limits its bioavailability (Raghothama 1999 ; Weeks and Hettiarachchi 2020 ). The root-associated microbiome plays an important role in plant phosphorus uptake. Plants can recruit these microorganisms from the bulk soil, which then influence soil phosphorus cycling and plant phosphorus acquisition. These microorganisms solubilize inorganic phosphorus by producing organic acids and phosphatases, which release phosphate from phosphorus-bound minerals (Hunter et al. 2014). Additionally, certain microorganisms mineralize organic phosphorus by producing enzymes that decompose organic matter, converting it into plant-available forms (Heuck et al. 2015 ). These processes significantly enhance plant access to soil phosphorus, thereby improving overall plant health and productivity (Heuer et al. 2017 ). Arbuscular mycorrhizal fungi (AMF) are key microbes that that enhance soil phosphorus efficiency and promote plant growth (Wahab et al. 2023 ; Hou et al. 2021 ). However, canola, being a Brassica plant, is non-mycorrhizal, necessitating the recruitment of alternative microbes to improve its phosphorus uptake. Except for AMF, various bacterial strains such as Burkholderia, Erwinia, Enterobacter, Pseudomonas, Bacillus , and Serratia , as well as fungal stains like Aspergillus , Fusarium, Mortierella, Penicillium , and Trichoderma, have been identified as potential phosphorus-solubilizing and phosphorus-mineralizing microorganisms (Alori et al. 2017 ; Elhaissoufi et al. 2022 ). Notably, some of these species have been reported in the root-associated microbiome of Brassica plants (Haney et al. 2018 ; Yu et al. 2024 ), however, their specific roles in response to phosphorus fertilization in canola remain underexplored. This study investigates the effects of phosphorus fertilizer rate and placement on canola performance and its root-associated bacterial and fungal microbiomes. We hypothesize that i) high-rate seed-placed phosphorus fertilizer negatively affects canola seedling emergence and yield, especially when placed closer to seeds in a narrow opener, ii) phosphorus fertilizer managements impacts the diversity, composition, and structure of the canola root and rhizosphere bacterial and fungal microbiomes, iii) specific root-associated bacterial and fungal taxa are enriched in phosphorus-abundant conditions, while others thrive in phosphorus-limited conditions, iv) the abundance of specific phosphorus-responsive microorganisms in the rhizosphere and roots correlates with canola field performance. Understanding the influence of phosphorus fertilization on the overall root-associated microbial community and specific phosphorus-responsive microbes, is crucial for improving phosphorus use efficiency in canola, ultimately reducing dependency on phosphorus fertilizers while maintaining optimal crop yields. Material and Methods Site description and sampling A 2-year field experiment was conducted using a commercial canola InVigor L233P at the Agriculture and Agri-Food Canada Research Farm in Scott, Saskatchewan, Canada (52°21'38.6"nitrogen, 108°50'00.8"W) in 2019 and 2020. The Scott field site was chosen because it previously showed good phosphorus fertilizer response in canola. This canola line was chosen for its good herbicide tolerance and its wide geographic suitability. The field soil was classified as a dark brown silt loam soil at pH of 5.5-6.0, with concentrations of organic matter at 3.7%, total nitrogen at 2000 mg.kg − 1 , available nitrogen at 88 mg.kg − 1 , total phosphorus at 555 mg.kg − 1 , available Olsen phosphorus at 25 mg.kg − 1 , total potassium at 2225 mg.kg − 1 , and total sulfur at 262 mg.kg − 1 . The total growing season precipitation (May-September) was 278 mm in 2019 and 289 mm in 2020. In 2019 and 2020, the blend of urea and ammonium sulphate was banded to a depth of 7.5 cm at a rate of 156.8 kg nitrogen ha − 1 and 22.4 kg sulfur ha − 1 and mid-row-banded during the seeding operation. Six different seed-placed phosphorus fertilizer managements were supplied in combinations of three phosphorus rates: low P (LP, 0 kg P ha − 1 ), recommended P (RP, 17 kg P ha − 1 ), and high P (HP, 32 kg P ha − 1 ), and in placements of two opener widths (OW): narrower (OW1 at 2.5 cm) and wider (OW2 at 10 cm) in a replicated randomized complete block design (n = 4). In each sampling year, we randomly selected 4–6 plants per plot for microbiome studies, and obtained samples from three compartments (bulk soil, rhizosphere soil, and roots) at two growth stages, including the 4–5 leaf vegetative stage (V) and the full-flowering stage (F). In total, 288 microbiome samples were collected (2 years x 2 growth stages x 3 phosphorus rates x 2 phosphorus placements x 4 reps x 3 sample compartments = 288 samples). Detailed methods for field sampling and sample processing are provided in Method S1, and the procedures for the measurements soil traits (total and available phosphorus, total and available nitrogen, and gravimetric water content) and plant properties (biomass, seed yield, plant density, shoot total phosphorus and nitrogen concentrations, shoot phosphorus and nitrogen uptakes) can be found in Method S2. DNA Extraction and Amplicon Sequencing Total DNA from the bulk and rhizosphere soil was extracted with the DNeasy PowerSoil Pro Kit (QIAGEnitrogen, Germany), and DNA from the roots was extracted with the DNeasy Plant Mini Kit (QIAGEnitrogen, Germany). Genomic DNA in the extracts were quantified using a Qubit 4 fluorometer (Invitrogen™, CA) and standardized to 5 ng.ul − 1 prior to polymerase chain reaction (PCR). Primer pairs with Illumina adapters of 342F (5′-CTACGGGGGGCAGCAG-3′; 16 nt) and 806R (5′-GGACTACCGGGGTATCT-3′; 17 nt) (Mori et al. 2014) were used to target the 16s rRNA region of bacteria; ITS1-F_KYO1 (TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CTH GGT CAT TTA GAG GAA STA A) and ITS2-R_KYO2 (GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA GTT YRC TRC GTT CTT CAT C) were used to target the ITS region of fungi (Toju et al. 2012 ) for PCR. Detailed methods for library preparation of amplicon-based DNA Illumina sequencing are illustrated in Method S3. Sequence Data Processing and Statistical Analysis Quality-controlled sequence data of both bacteria and fungi generated from the Illumina MiSeq platform were processed using QIIME2 v2022.8 software (Bolyen et al. 2019 ), where sequence data were demultiplexed, denoised, and representative sequences were generated as Amplicon Sequence Variants (ASVs) (Callahan et al. 2017 ). Then the SILVA database (Silva_138) was trained as the classifier for 16S rRNA (Quast et al. 2013 ) and UNITE database (version 9.0) for ITS (Abarenkov et al. 2010 ), to determine the taxonomic classification of the above generated ASVs. Detailed methods for raw sequence data processing can be found in Method S4. After removing singletons and doubletons, the abundance and taxonomy tables containing the sample information were generated and imported into R software (v. 4.3.3) for downstream analyses. For analyses in R, we firstly evaluated whether plant and soil properties differed under different phosphorus fertilizer managements, using analysis of variance (ANOVA), followed by post-hoc pairwise comparisons of Tukey’s test. Plant traits included plant emergence, density, shoot biomass, grain yield, shoot phosphorus concentration (ShTP), shoot phosphorus uptake (Puptake), shoot nitrogen concentration (ShTN), shoot nitrogen uptake (Puptake). Soil properties included soil total phosphorus (STP), soil available phosphorus (SAP), soil total nitrogen (STN), soil available nitrogen (SAN), gravimetric water content (GWC). For microbial data analyses in R, Vegan (Oksanen et al. 2020) and Phyloseq (McMurdie and Holmes 2013 ) packages were used to calculate the bacterial and fungal alpha diversity (indices including Pielou’s evenness, richness of observed ASVs, and Shannon diversity) in each sample type (bulk soil, rhizosphere soil, and roots). The influence of sample type, sampling year, plant growth stage and phosphorus fertilization on the alpha diversity indices were assessed using analysis of variance (ANOVA) followed by a pairwise comparison on the results of ANOVA using false-discovery-rate-corrected (FDR) post-hoc test. Similar analyses were conducted for the root microbiome from a specific sampling event. Next, microbial relative abundance under different phosphorus fertilizer managements were calculated at the family or class level. The 20 most abundant bacterial and fungal families or classes were then visualized using “ggplot2” function (Wickham 2016 ), with less abundant ones grouped together and labelled as “Others”. To profile the bacterial and fungal community compositions (beta diversity), we used the centered log-ratio (CLR) transformation to handle compositional effects and compute the Aitchison distance. Principal component analysis (PCA) was then performed on the CLR transformed data for bacteria and fungi, respectively. The effects of sampling year, plant growth stage, and phosphorus fertilization on the microbial community structure were assessed using permutational analysis of variance (PERMANOVA) for each sample type (bulk soil, rhizosphere soil, and roots) using the "adonis2" function (McArdle BH and Anderson 2001). To investigate how phosphorus rates and placements impacted the root microbiomes, relative abundance and PCA analyses were conducted using methods similar to those described above. In addition, redundancy analysis (RDA) was performed using the “rda” function (Legendre and De Cáceres 2012) to explore the impact of soil properties (including STP, SAP, STN, SAN, GWC) on the root microbial community structure. Only the soil properties that significantly explained variability in microbial community structure were fitted to the ordination and visualized with the “plot” function (p < 0.05). Differential abundance analyses were conducted using the Analysis of Compositions of Microbiomes with Bias Correction function (ANCOM-BC2) to identify ASVs that were differentially abundant under varied phosphorus rates (Lin and Peddada 2020 ). The identified ASVs were then plotted on a heatmap, using log-transformed data to illustrate their abundance. Focusing on these differentially abundant root bacterial and fungal ASVs, Spearman’s correlations between these ASVs and all soil and plant parameters (including STP, SAP, ShTP, Puptake, STN, SAN, ShTN, Nuptake, GWC, yield, biomass, and density) were calculated using the “rcorr” function from the Hmisc package (Press et al. 1998), and then visualized with the “corrplot” function (Wei and Simko, 2021 ). All detailed analysis methods in R were illustrated in Method S4. Results High-rate and more concentrated seed-placed phosphorus fertilization decreased plant density but did not affect grain yield or biomass Plant field performance was impacted by growing season conditions in 2019 and 2020. More specifically, plant emergence (on 14, 21 and 28 days after seedling (DAS)) and plant density at harvest were higher, while grain yield and plant shoot biomass were lower in 2019 compared to 2020 (Table 1 ). High-rate seed-placed phosphorus consistently decreased plant emergence and density in both 2019 and 2020. Compared to unfertilized soil (LP), plant emergence (on 14, 21 and 28 days after seedling (DAS)) and plant density at harvest decreased in phosphorus fertilized soils (recommended RP and high-rate HP), especially when applied using the narrower opener (OW1). (Table 1 ). Specifically in 2019, higher shoot biomass, grain yield, and shoot total phosphorus concentration were observed in HP-OW1 compared to LP-OW2 (p < 0.05), while no significant impact of soil phosphorus was found in either shoot phosphorus uptake, or shoot nitrogen concentration and uptake (Table 1 ). In 2020, however, no significant differences were detected in any of these traits. In addition, nutrient analyses revealed that soil total phosphorus and nitrogen, available nitrogen, nitrogen to phosphorus ratio, GWC, as well as shoot phosphorus and nitrogen uptakes were higher in 2019 compared to 2020 (Table S1 ). Apart from the impact of sampling year, plant growth stage also impacted soil and plant nutrient concentration. In both 2019 and 2020, soil available phosphorus and nitrogen, as well as shoot total phosphorus and nitrogen concentrations were higher at the early vegetative than the later flowering stage, while shoot phosphorus and nitrogen uptake were greater at flowering stage as biomass increased (Table S1 ). Table 1 Canola performance under six soil phosphorus treatments of phosphorus rates (PR) at 0 (LP), 17 (RP), and 32 kg ha − 1 (HP) in combinations of narrower (1) and wider (2) opener widths (OW) in sampling year 2019 and 2020 (pairwise comparisons were conducted within a specific sampling year, where different letters indicated statistical significance, determined using ANOVA followed by Tukey’s test, p < 0.05, n = 4) Year P treatment [PR (OW)] Plant Emergence-14DAS (plants m − 2 ) Plant Emergence-21DAS (plants m − 2 ) Plant Emergence-28DAS (plants m − 2 ) Plant Density (plants m − 2 ) Biomass (g m − 2 ) Yield (kg ha − 1 ) Shoot N concentration (mg g − 1 ) Shoot N uptake (mg) Shoot P concentration (mg g − 1 ) Shoot P uptake (mg) 2019 LP(1) 73 a 85 a 81 a 80 a 738 b 3668 ab 48.6 a 886 a 3.6 ab 65.3 a RP(1) 57 ab 79 ab 76 ab 72 ab 775 ab 3938 ab 46.0 a 811 a 4.1 ab 78.8 a HP(1) 32 b 60 c 56 b 60 b 934 a 3990 a 48.7 a 990 a 4.6 a 91.7 a LP(2) 72 a 96 a 87 a 80 a 706 b 3413 b 46.3 a 553 a 3.5 b 43.0 a RP(2) 73 a 92 a 87 a 84 a 851 ab 3654 ab 45.5 a 789 a 4.1 ab 71.5 a HP(2) 50 ab 82 ab 76 ab 70 ab 941 a 3871 ab 45.4 a 647 a 4.0 ab 61.2 a 2020 LP(1) 54 a 85 a 77 a 70 a 983 a 4861 a 43.4 a 533 a 4.6 a 63.6 a RP(1) 27 b 52 b 48 b 43 b 1019 a 4689 a 40.9 a 665 a 4.6 a 81.0 a HP(1) 33 b 50 b 48 b 44 b 1044 a 4723 a 40.1 a 1102 a 4.9 a 160.2 a LP(2) 44 ab 65 ab 62 ab 57 ab 1098 a 4563 a 42.8 a 814 a 4.4 a 105.0 a RP(2) 48 ab 65 ab 59 ab 54 ab 998 a 4598 a 41.5 a 1043 a 4.6 a 136.4 a HP(2) 36 ab 52 a 49 b 44 b 956 a 4536 a 41.3 a 1001 a 4.7 a 137.4 a Phosphorus fertilization impacted only the root bacterial and fungal diversity and community structure A total of 10,176 unique bacterial ASVs and 3,599 unique fungal ASVs were identified in 288 samples (ninety-six samples each of bulk soil, rhizosphere soil, and root). The alpha diversity (observed richness, Pielou’s evenness, and Shannon diversity) of both bacteria and fungi was the highest in the bulk soil, followed by the rhizosphere soil, and was the lowest in the root (Fig. S1 , Table S2). Notably, only the root bacterial and fungal diversity in 2019 were impacted by phosphorus treatments (Fig. 1 , Table S3). At the early vegetative stage, lower root bacterial alpha diversity was found in RP compared to both LP and HP, for OW1 (p < 0.05). Comparable patterns were observed in the root fungal community but were not statistically significant. Instead, phosphorus placement rather than rate, impacted root fungal diversity, with higher diversity observed in OW1 compared to OW2 (p < 0.05). At the flowering stage, the root bacterial and fungal diversities showed no significant differences between phosphorus treatments. In terms of microbial community structure, the greatest separation occurred in the three sample types under investigation, and this separation was greater in the bacterial compared to the fungal community (Fig. S2, Table S3). In the bulk soil, sampling year had a major impact on both bacterial and fungal community structure, with a minor impact of plant growth stage on the fungal community. In the rhizosphere soil and roots, both sampling year and plant growth stage contributed to separations in bacterial and fungal communities. Specifically for the root microbiome, in 2019, the root bacterial community structures were significantly influenced by phosphorus treatments. The root fungal community structure was affected by phosphorus rate (PR), particularly when supplied with a specific OW, across all sampling events except at the flowering stage in 2020 (Table 2 ). Despite these inconsistent impacts from PR and OW, soil available phosphorus (SAP) was consistently correlated with the bacterial community of the canola roots across all sampling events (Fig. 2 ). The impact of additional soil factors on root fungal community was only observed at the early vegetative stage (e.g., SAP, total nitrogen, and GWC) (Fig. S3). Table 2 PERMANOVA of the effect of phosphorus rate (PR) and opener width (OW) on root bacterial and fungal communities in 2019 and 2020 at the 4–5 leaf vegetative stage (V) and the full-flowering (F) stages Bacteria Fungi R 2 Pr(> F) R 2 Pr(> F) 2019V PR 0.133 0.001 0.103 0.001 OW 0.057 0.023 0.057 0.001 PR x OW 0.103 0.015 0.099 0.004 2019F PR 0.110 0.005 0.084 0.264 OW 0.059 0.011 0.049 0.059 PR x OW 0.083 0.264 0.102 0.006 2020V PR 0.076 0.174 0.085 0.086 OW 0.038 0.232 0.047 0.010 PR x OW 0.065 0.788 0.088 0.030 2020F PR 0.068 0.579 0.079 0.367 OW 0.039 0.155 0.041 0.268 PR x OW 0.076 0.124 0.084 0.086 Note: Bold values denote statistical significance at the p < 0.05 level Phosphorus fertilization affected the abundance of root bacteria and fungi Sampling year and plant growth stage influenced the bacterial and fungal compositions in canola roots. For instance, the abundance of Streptomycetaceae was higher in the vegetative stage (12%-15%), compared to the flowering stage (2%-3%), while the abundance of Olpidiaceae was higher in the flowering stage (60%-70%), compared to the vegetative stage (2%-20%). Despite the impacts from sampling year and plant growth stage, phosphorus fertilization modified the microbial relative abundance in canola roots. For example, fungi Xylariaceae had higher relative abundance but lower relative abundance of Olpidiaceae in canola roots grown in HP soils (Fig. 3 ). And higher relative abundance of Pseudomonadaceae and Mortierellaceae were found in canola roots grown in RP soils, especially when supplied with the narrow opener (OW1). The abundance of specific microbes in canola roots shifted under varying phosphorus rates. In 2019, this response included 17 bacterial ASVs and 11 fungal ASVs in canola roots. Bacteria including 9 ASVs from Gammaproteobacteria (including 4 Burkholderia-Caballeronia-Paraburkholderia , 2 Luteibacter, and 1 from Comamonas, Enterobacteriaceae , and Rhodanobacter , respectively), 6 ASVs from Bacteroidia (including 2 ASVs from Sphingobacterium, Chryseobacterium , and Chitinophaga , respectively) and 2 ASVs from Actinobacteria (including a single ASV from Actinoallomurus and Rhodococcus , respectively) were differentially abundant in canola roots grown under different phosphorus treatments. The differential abundant root fungi included 3 ASVs from Agariomycetes (including 1 ASV from Amaurodon, Thanatephorus , and Calyptella , respectively), 3 ASVs from Sordariomycetes (including 1 ASV from Conlarium, Trichoderma , and Lectera , respectively), 2 ASVs from Lachnum , as well as 1 ASV from Olpidiomycetes ( Olpidium ), Euroriomycetes ( Penicillium ), and Dothideomycetes ( Sigarispor a), respectively (Fig. 4 ). Moreover, in 2019, genera from high-phosphorus (HP) responsive Gammaproteobacteria (e.g., Rhodanobacter, Luteibacter , and Burkholderia-Caballeronia-Paraburkholderia ) in canola roots were positively correlated with soil total phosphorus (STP) and soil available phosphorus (SAP). Positive correlations were also detected between canola biomass and the abundance of Burkholderia-Caballeronia-Paraburkholderia (ASV2088, ASV558, and ASV20) in canola roots, with ASV2088 being positively correlated with canola yield. On the contrary, genera from low-phosphorus (LP) responsive Bacteroidia in canola roots were negatively correlated with SAP (e.g., Chryseobacterium and Chitinophaga ) and shoot total phosphorus concentration (e.g., Sphingobacterium ). The abundance of Chryseobacterium (ASV5933) and Chitinophaga (ASV5762) in canola roots were positively correlated with plant density. Sordariomycetes genera Amaurodon , Conlarium , and Trichoderma were more abundant in canola roots grown in phosphorus-fertilized soils, and the abundance of Trichoderm were positively correlated with canola yield. Further, fungi Olpidium were enriched in canola roots grown in LP soils, while root Penicillium were enriched in HP soils and negatively correlated with plant density (p < 0.05) (Fig. 4 ). In 2020, the abundance responses included 13 bacterial ASVs and 6 fungal ASVs in canola roots grown in varied soil phosphorus fertilizations. More specifically, 8 bacterial ASVs from Gammaproteobacteria (including 3 ASVs from Pseudomonas , and a single ASV from Providencia, Erwinia, Celivibrio, Duganella , and Burkholderiaceae ), and 5 ASVs from Bacteroidia (including 3 ASVs from Flavobacterium , and a single ASV from Mucilaginibacter and Chryseobacterium , respectively) were differentially abundant in canola roots grown in different phosphorus treatments. And the differentially abundant root fungi included 3 ASVs from Sordariomycetes, 2 ASVs from Dothideomycetes (a single ASV from Sigarispora and Mycosphaerella , respectively), and 1 ASV from Mortierellomycetes ( Mortierella ) (Fig. 5 ). Additionally in 2020, bacteria Providencia and Erwinia showed higher abundance in canola roots grown in HP soils, while Pseudomonas (ASV3109), Cellvibrio , Duganella , and Flavobacterium exhibited high abundance in roots grown in LP soils, with negative correlations observed in Pseudomonas and Duganella with SAP and ShTP. Moreover, fungi Nectriaceae (ASV93 and ASV116) had higher abundance in canola roots grown in HP soils, while root Dothidomycetes genera Sigarispora and Mycosphaerella had higher abundance in LP soils, with the former negatively associated with plant phosphorus and nitrogen uptakes (p < 0.05) (Fig. 5 ). Discussion The impact of phosphorus fertilization on plant performance Due to the immobility and fixation properties of phosphorus, seed-placed fertilizers are considered an effective method to provide readily accessible phosphorus to plants. However, canola seedlings are sensitive to seed-placed phosphorus, which limits the rates of application (Qian and Schoenau 2010 ). In accordance with previous studies (Bailey and Grant 1990 ; Lemke et al. 2009 ), we found that high-rate seed-placed phosphorus fertilizers reduced canola population (emergence and plant density), especially when placed closer to the seeds in a narrow opener (HP-OW1). This decrease in canola emergence and plant density did not affect yield in 2020, while it increased yield in 2019 (Table. 1). Phosphorus fertilization increased canola biomass and yield only in 2019 but not 2020, while overall yield was higher in 2020 (Table 1 ). This indicated that local climate and environment, particularly moisture and temperature, may have overridden the impact from P fertilization in 2020. In particular, both the in-season (March-September at 289 mm) and total precipitation (378 mm) in 2020 were higher than those in 2019 (in season at 278 mm and total at 341 mm), with higher GWC in 2020 at the flowering stage. The higher moisture content in 2020 likely increased phosphate solubility and diffusion in the soil solution, increasing phosphate movement to roots and contributing to better root phosphorus uptake, and ultimately transmitted to a better yield. The limited moisture in 2019, on the contrary, contributed to greater treatment level responses to phosphorus fertilization. Bélanger et al. ( 2015 ) found that canola growth response to phosphorus fertilizer was highly dependent on year and site in the Canadian Prairies. They demonstrated that soil moisture can often override nutrient management for plant growth in arid and semi-arid environments. Moreover, the lack of yield response in 2020 may have been due to initially high soil phosphorus levels. In 2019, pre-seeding soil tests indicated relatively high available phosphorus (22 kg P ha − 1 ), despite the site having high phosphorus responsiveness in previous growing seasons. Due to global pandemic restrictions in 2020, spring sampling soil fertility did not occur. However, considering that theses fields were side by side with similar rotations, it is assumed that the field in 2020 had similarly high background soil phosphorus levels, supported by high levels of available phosphorus in plots without phosphorus fertilizer (LP) during early growth stages, averaging 35 mg kg − 1 in 2019 and 44 mg kg − 1 in 2020 (Table S1 ). Saskatchewan's phosphorus fertilizer guidelines suggest a probability of less than 25% for a yield response to phosphorus fertilizer when available phosphorus exceeds 30 mg kg − 1 (Saskatchewan Ministry of Agriculture 2023 ), similar to the phosphorus threshold for canola yield response reported by McKenzie et al. ( 2003 ). Furthermore, observations of increased shoot nitrogen and phosphorus uptake with higher and more concentrated phosphorus fertilization suggested luxury uptake by canola, aligning with previous studies (Bélanger et al. 2015 ; Shao et al. 2023 ). The impact of phosphorus fertilization on the canola root-associated microbial community Compared to the bulk soil, the rhizosphere is a hotspot for plant-soil-microbe interactions, where nutrient cycling is intensified (Reinhold-Hurek et al. 2015 ). A recent review of 123 studies of soil and root-associated microbiomes validated that the rhizosphere region has higher activities of nitrogen fixation, phosphorus mineralization and phosphorus solubilization compared to the bulk soil (Liu et al. 2022 ). In accordance with our findings, the highest microbial diversity has been observed in bulk soil, followed by rhizosphere soil, and was lowest in roots (Fig. S1 ) because of increasingly selective microenvironments at the soil-root interface (Ling et al. 2022 ). Despite the major impact of the environment (year) and/or plant growth stage on the microbiome of all sample types (bulk soil, rhizosphere soil, and the roots), phosphorus fertilization had a minor but significant impact specifically on the root microbiome. This impact was greater in 2019 compared to 2020, indicating its dependence on year-to-year environmental conditions, as observed in our study (Fig. S2, Table S2, Table S3) and extensively discussed in previous studies (Philippot et al. 2013 ; Qu et al. 2020 ; Bell et al. 2022 ; Cordero et al. 2021; Li et al. 2023a ). In 2019, the diversity (observed richness, Pielou’s evenness, and Shannon diversity) of both the root bacteria and fungi was the highest in high phosphorus soil, especially when applied with the narrow opener, and this trend was more apparent at the early vegetative stage compared to the late flowering stage (Fig. 1 ). Similar observations have reported in maze roots, where high phosphorus increased the richness, Shannon diversity and Pielou’s evenness of the fungal community (Gomes et al. 2018 ), as well as the increased bacterial richness in soil under long-term phosphorus addition (Zhang et al. 2024 ). The pronounced canola root microbial diversity responses at the vegetative stage, compared to the flowering stage, indicated that 1) at early vegetative growth stage, plant nutrient demands are higher, leading to more intense competition between plants and microbes for nutrient resources, consistent with findings in wheat (García-Díaz et al. 2024 ); 2) early-season phosphorus fertilizer had absorbed by canola plants and subsequently had less influence on the root microbiome. This observation aligned with findings from Wang et al. ( 2024 ) on soybeans, where root bacterial diversity remained stable in later growth stages despite varying nitrogen and phosphorus fertilization; or 3) soil phosphorus ceased to be a dominant determinant of microbial diversity as mature canola plants exhibit increased selective capability to support specific microbial community in roots (Edwards et al. 2018 ). We found that soil phosphorus can shift the composition of the canola root microbial community (Table. 2, Fig. 2 , Fig. S3). Similar impacts of phosphorus have been documented in the fungal community in the rhizosphere and roots of Arabis alpina (Almario et al. 2017 ) and Arabidopsis thaliana (Fabiańska et al. 2019 ), the bacterial and fungal communities in the rhizosphere and roots of maize (Deng et al. 2021 ; Bourceret et al. 2022 ), the rhizosphere bacterial community in blueberry (Pantigoso et al. 2018), and the rhizosphere bacterial and the root fungal communities in wheat (Pagé et al. 2019 ). These findings emphasize the significant role of phosphorus in modulating the microbial communities associated with plant roots, with potential implications for plant growth and biomass production. Conversely, some other studies did not detect any impact of phosphorus fertilization on the diversity or the structure of the root-associated microbiome (Sawyer et al. 2018 ; Wang et al. 2018 ). The root-associated microbial community diversity and composition exhibited various responses to phosphorus fertilizer managements, underscoring the complexity of the root microbiome. This complexity arises from a multitude of influencing factors including soil properties, plant genetic material, root phenotypes, and the intricate interactions among soil, roots, and microbes. These factors collectively shape the structure and function of the root microbial communities, highlighting the dynamic nature of plant-microbe-soil interactions in response to nutrient availability and environmental conditions. The impact of phosphorus fertilization on the abundance of specific canola root bacteria and fungi Relative abundance analysis revealed that canola roots were dominated by bacteria from Gammaproteobacteria, followed by Actinobacteria and Bacteroidia, as well as fungi from Sordariomycetes and Olpidiomycetes (Fig. S4), agreed with previous reports (Bell et al. 2022 ; Gkarmiri et al. 2017 ; Chun 2022 ). Olpidium brassicae is commonly recognized as a fungal parasite, especially in Brassicacea plants. Previous studies indicated that high doses of the O. brassicae inoculation reduced shoot and root growth in canola (Hilton et al. 2013 ), and its high abundance in roots was associated with low yield in field-grown canola (Hilton et al. 2021 ). We observed a high abundance of O. brassicae in field canola roots, especially at the later full-flowering stage without pathogenic symptoms (Fig. S4). This observation aligns with previous findings (Li et al. 2023a ; Floc’h et al. 2020 ), suggesting that a) O. brassicae may act as an opportunistic colonizer of canola, occupying a microbial niche with little competition, b) interactions among O. brassicae and other microbial species in the soil-root interface can be complex (Lay et al. 2018 ), and c) the relationship between O. brassicae and yield were highly dependent on site and strain (Town et al. 2023 ), with the O. brassicae strain in our Scott field not impacting canola yield. Additionally, in 2019, the abundance of the canola root O. brassicae was the highest in soil without phosphorus supply, while the lowest in high phosphorus soil (Fig. 4 ). This is consistent with a previous study in another Brassicaceae plant, Arabidopsis thaliana , where depletion of the root the O. brassicae were noted under replete phosphorus conditions (Fabiańska et al. 2019 ). The proliferation of O. brassicae appears to be common in Brassicaceae plants, and the underlying ecological functions require further study. We identified specific root bacterial and fungal ASVs which responded actively to phosphorus and were correlated with plant performance, with more phosphorus-responsive organisms identified in 2019 than 2020, suggesting the major impact from the year-to-year environmental difference. ASVs from Gammaproteobacteria genera Burkholderia-Caballeronia-Paraburkholderia , Luteibacter Rhodanobacter , and from fungi Sordariomycetes genera Trichoderma and Nectria were enriched in roots of canola grown in phosphorus-fertilized soils (Fig. 4 , Fig. 5 ). Burkholderia-Caballeronia-Paraburkholderia were enriched in canola roots grown in phosphorus-fertilized soils compared to unfertilized soils, and were positively correlated with both soil available phosphorus and plant biomass in 2019 (Fig. 4 ). Burkholderia-Caballeronia-Paraburkholderia are known as plant-growth-promoting bacteria which inhibit fungal diseases (Jung et al. 2018 ). While a previous study found that Burkholderia were enriched in plant tissue under phosphorus starvation (Finkel et al. 2019 ), we observed enrichment of Burkholderia in canola roots in phosphorus-fertilized soils, consistent with a study on soybean, where reduced Burkholderiales abundance was detected in soils without phosphorus fertilization (Wang et al. 2024 ). This can be explained by the fact that Burkholderia are generally considered fast-growing r-strategists that thrive in nutrient-rich environment and can utilize resources such as carbon substrates, nitrogen, and phosphorus that are abundant in the rhizosphere (Philippot et al. 2013 ). Burkholderia spp. possess putative growth promotion and stress tolerance abilities (Verma et al. 2021 ; Pal et al. 2022 ). Under phosphorus-sufficient conditions, canola plants may favor the growth of fungal disease antagonistic Burkholderia to enhance its pathogen defense system, benefiting plant growth. This hypothesis is supported by studies in another Brassicaceae plant Arabidopsis (Hacquard et al. 2016 ; Motte and Beeckman 2017 ), as well as evidence from the Burkholderia inoculation to Arabidopsis leaves, which promoted plant growth and increased plant defense responses (Colavolpe et al. 2021 ). In addition, root fungi Sordariomycetes genus Trichoderma was the most abundant in recommended phosphorus rates (RP) and positively correlated with canola yield (Fig. 5 ). Consistent with our results, a study in maize detected higher abundance of Sordariomycetes in the rhizosphere under high phosphorus for all three maize genotypes studied (Gomes et al. 2018 ). Specifically, the phosphorus-responding Trichoderma identified in our study is Trichoderma hamatum . This species possesses several beneficial traits for plants, including antimicrobial activity, antioxidant activity, insecticidal activity, herbicidal activity, and plant growth promotion (Lodi et al. 2023 ). Trichoderma hamatum strains have been found to promote plant growth in Arabidopsis thaliana (Studholme et al. 2013 ) and increase productivity in some leafy Brassica crops (Velasco et al. 2021 ), potentially through activation of biocontrol against soil pathogens and induced systemic resistance. Other root fungi such as Amaurodon , Penicillium, Mortierella , and Nectria were also abundant in phosphorus-fertilized soils, with positive correlations found between the first two genera with soil available phosphorus. Among these, the ecological function of Amaurodon has rarely been documented. Mortierella has been considered a phosphate-solubilizing fungi, which also participates in carbon cycling (Ozimek and Hanaka 2020). Some Penicillium species have high potential for phosphorus solubilization (Elias et al. 2016 ; Doilom et al. 2020 ) and can promote plant growth by enhancing soil nitrogen mineralization (Niu et al. 2021 ). Nectria , in particular Nectria ramulariae in our study, is considered a plant pathogen (Lee et al. 2023 ), indicating the potential for pathogen effects under excessive phosphorus fertilization. On the contrary, certain root genera, such as Bacteroidia genera Sphingobacterium, Chryseobacterium, Chitinophaga , and Flavobacterium , as well as fungal genus Olpidium were enriched in roots without phosphorus fertilization (Fig. 4 , Fig. 5 ). Sphingobacterium has been reported to participate in phosphorus solubilization, making phosphorus more available for root absorption, especially under stress conditions (Ahmed et al. 2014 ; Wan et al. 2020 ; Vaishnav et al. 2020 ). Some Chryseobacterium species can solubilize phosphorus or exhibit antimicrobial activity against some Gram-negative bacteria, thus promoting plant growth in horse gram legume (Singh et al. 2013 ) and canola (Farina et al. 2012 ). In our study, root Chryseobacterium , specifically Chryseobacterium halperniae , were positively correlated with canola plant density and negatively correlated with yield. Limited information is available for this specific species, and further studies are required to elucidate their potential ecological functions. Chitinophaga spp. can potentially promote carbon-phosphorus synergistic conversion, and participated P cycling in peanut (Chen et al. 2018 ). In unfertilized soils, Flavobacterium was reported to produce enzymes that target soil organic phosphorus (Lidbury et al. 2021 ) and may participate in plant growth promotion (Soltani et al. 2010 ). It is important to recognize the complexity of phosphorus dynamics within the soil-plant-microbe system, and the differences between applied soil phosphorus and soil available phosphorus. Low soil available phosphorus can signify either efficient plant phosphorus uptake and removal from the soil or indicate fierce competition of soil and root-associated microorganisms with plants for soil resources, while high soil available phosphorus may indicate poor plant uptake or excessive soil phosphorus availability. Similarly, a high concentration of shoot phosphorus may reflect effective phosphorus uptake or result from smaller plants with less biomass, resulting in more concentrated tissue phosphorus. Although the responses of the root microbiome to phosphorus fertilization varied across different sampling years and plant growth stages here and in other studies (Edwards et al. 2018 ; Ofek-Lalzar et al. 2014 ; Bell et al. 2022 ), phosphorus fertilization tends to have a long-lasting effect on the root microbiome. This effect was highly correlated with canola field performance, indicating that the root microbiome can participate in phosphorus cycling, mitigate phosphorus stress, and enhance plant defense responses. Plant phosphorus uptake and growth could be impacted by shifting the overall root microbiome as well as fine-tuning specific microorganisms (Castrillo et al. 2017 ; Zheng et al. 2020 ). While treatment-level effects on the microbiome were inconsistent between years, the correlation of soil available and total phosphorus with community structure (Fig. 2 ) indicates a strong link between the root microbiome and phosphorus availability which may not be linearly related to phosphorus fertilizer application. Conclusions High-rate phosphorus supplied in a narrow opener decreased canola seed emergence and density, but did not impact seed yield responses. Despite significant environmental influences, early phosphorus fertilizer managements had a minor but significant long-lasting effect on the canola root microbiome. High-rate near-seed phosphorus increased root bacterial and fungal diversity, altering the root microbial structure and composition. Specific root microbial genera, such as Burkholderia-Caballeronia-Paraburkholderia, Luteibacter, Rhodanobacter, Amaurodon, Conlarium, Trichoderma , and Nectria were enriched in canola roots grown in phosphorus-fertilized soils, whereas genera like Sphingobacterium, Chryseobacterium, Chitinophaga, Flavobacterium , and Olpidium were enriched in roots without phosphorus fertilization. Canola yield was positively correlated with Burkholderia-Caballeronia-Paraburkholderia and Trichoderma . Future studies can focus on these taxa to more comprehensively understand their ecological roles and functions in nutrient cycling and plant growth responses, aiming to manipulate the root microbiome for improved fertilization practices and optimal canola yield. Declarations Funding This study was supported by Canola Agronomic Research Program (CARP.2019.24), Natural Sciences and Engineering Research Council of Canada (NSERC), Canada Excellence Research Chair (CERC), and China Scholarship Council (CSC). Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author contributions SPM designed, conducted, and supervised the field trial. BLH designed the microbiome experiments and supervised the project. LK and ML prepared sequence samples and first draft of the manuscript. YL and DS conducted data collection and analysis, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data availability The datasets generated during this current study were submitted to the National Center for Biotechnology Information (NCBI) Sequence read archive (SRA) under Bioproject accession PRJNA1062716. Acknowledgments We would like to thank Arlen Kapiniak for his assistance with fieldwork, Kimberley Hamonic and Jesse Reimer for their help with microbiome sampling and processing, and Jieyu Chen for her valuable contribution in reviewing the manuscript. 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Nat Commun 15(1). https://doi.org/10.1038/s41467-024-45925-5 Wang Q, Wang C, Yu W, Turak A, Chen D, Huang Y, Ao J, Jiang Y & Huang Z (2018) Effects of Nitrogen and Phosphorus Inputs on Soil Bacterial Abundance, Diversity, and Community Composition in Chinese Fir Plantations. Front Microbiol 9: 1543. https://doi.org/10.3389/fmicb.2018.01543 Weeks JJ, Hettiarachchi GM (2020) Source and formulation matter: New insights into phosphorus fertilizer fate and transport in mildly calcareous soils. Soil Sci Soc Am J 84(3): 731–746. https://doi.org/10.1002/saj2.20054 Wei T & Simko V (2021). corrplot: Visualization of a Correlation Matrix. In CRAN: Contributed Packages. The R Foundation. https://doi.org/10.32614/cran.package.corrplot Wickham H, 2016. Data analysis. In ggplot2, 189-201. Springer. http://www.springer.com/series/6991 Yu H, Chang KF, Fredua-Agyeman R, Hwang SF & Strelkov SE (2024) Diversity and Pathogenicity of Fusarium Root Rot Fungi from Canola ( Brassica napus ) in Alberta, Canada. Int J Mol Sci 25(11): 6244. https://doi.org/10.3390/ijms25116244 Zhang H, Jiang N, Wang H, Zhang S, Zhao J, Liu H, Zhang H & Yang, D (2024). Importance of plant community composition and aboveground biomass in shaping microbial communities following long-term nitrogen and phosphorus addition in a temperate steppe ecosystem. Plant Soil. https://doi.org/10.1007/s11104-024-06881-7 Zhang Y, Li Y, Guo S (2020) Effects of the mycorrhizal fungus Ceratobasidium sp. AR2 on growth and flavonoid accumulation in Anoectochilus roxburghii . PeerJ 8 : e8346. https://doi.org/10.7717/peerj.8346 Zhao ZB, He JZ, Quan Z, Wu CF, Sheng R., Zhang LM & Geisen S (2020) Fertilization changes soil microbiome functioning, especially phagotrophic protists. Soil Biol Biochem 148: 107863. https://doi.org/10.1016/j.soilbio.2020.107863 Zheng Y, Liang J, Zhao DL, Meng C, Xu ZC, Xie ZH, Zhang CS (2020) The root nodule microbiome of cultivated and wild halophytic legumes showed similar diversity but distinct community structure in yellow river delta saline soils. Microorganisms, 8(2): 207. https://doi.org/10.3390/microorganisms8020207 Zhou J, Jiang X, Zhou B, Zhao B, Ma M, Guan D, Li J, Chen S, Cao F, Shen D & Qin J (2016) Thirty-four years of nitrogen fertilization decreases fungal diversity and alters fungal community composition in black soil in northeast China. Soil Biol Biochem 95: 135–143. https://doi.org/10.1016/j.soilbio.2015.12.012 Zuur AF, Ieno EN, Elphick CS (2010) A protocol for data exploration to avoid common statistical problems. Methods Ecol and Evol 1(1): 3–14. https://doi.org/10.1111/j.2041-210x.2009.00001.x Supplementary Files LiuetalSupplementaryInfoPlantandSoil.docx Cite Share Download PDF Status: Published Journal Publication published 17 Feb, 2025 Read the published version in Plant and Soil → Version 1 posted Editorial decision: Major revisions 17 Oct, 2024 Reviewers agreed at journal 27 Aug, 2024 Reviewers invited by journal 16 Aug, 2024 Editor invited by journal 13 Aug, 2024 Editor assigned by journal 13 Aug, 2024 First submitted to journal 12 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4902932","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":341018266,"identity":"e14b30be-5d91-4ff4-a195-9cecbf207280","order_by":0,"name":"Mengying Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYFAC5sbHfwxswCxitTA2G/BUpJGmpU2C58xhErTotjc2SEi2nU+c3378sQFDjR1hLWZnDjYYGLbdTtxwJsc4geFYMhFabiQ2JCSCtDDkMB9gbCDCcWb3HzYcONh2LnF+//PHQC31xNjC2NjYcOZAYsONBOMExobDxPglsZmZoSLZeMONN8YGCceOE6Hl+OHjvxkM7GTn96c/lvhQU01YCypIIFXDKBgFo2AUjALsAABdOz/2NdKKqwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-5363-8548","institution":"University of Saskatchewan","correspondingAuthor":true,"prefix":"","firstName":"Mengying","middleName":"","lastName":"Liu","suffix":""},{"id":341018267,"identity":"8d6e143f-185f-432a-94d2-21ca3bf76a62","order_by":1,"name":"Patrick Mooleki","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"","lastName":"Mooleki","suffix":""},{"id":341018268,"identity":"63f5c4de-76cf-41a6-89c6-403d0b668e7b","order_by":2,"name":"Dave Schneider","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Dave","middleName":"","lastName":"Schneider","suffix":""},{"id":341018269,"identity":"53787f22-9431-417a-a7d9-8ec1bb3b4514","order_by":3,"name":"Leon V. Kochian","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Leon","middleName":"V.","lastName":"Kochian","suffix":""},{"id":341018270,"identity":"b38a7cf4-7666-4258-9c40-c6a6664ff327","order_by":4,"name":"Bobbi L. Helgason","email":"","orcid":"https://orcid.org/0000-0003-1664-8250","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Bobbi","middleName":"L.","lastName":"Helgason","suffix":""}],"badges":[],"createdAt":"2024-08-12 22:07:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4902932/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4902932/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11104-025-07286-w","type":"published","date":"2025-02-17T15:57:14+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":64369059,"identity":"a362f0dc-be8e-4243-9c71-d330b467b2bb","added_by":"auto","created_at":"2024-09-12 08:50:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":232153,"visible":true,"origin":"","legend":"\u003cp\u003eRoot bacterial and fungal alpha diversity indices (observed richness, Pielou’s evenness and Shannon diversity) under six treatments of three P rates (PR) at 0 (LP), 17 (RP), and 32 kg ha\u003csup\u003e-1\u003c/sup\u003e (HP) in combination with narrower (1) or wider (2) opener widths (OW) in 2019 at the vegetative and the full-flowering stages (different letters indicated statistical significance, determined using ANOVA followed by Tukey’s test, p\u0026lt;0.05, n=4)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4902932/v1/d2f9d7ef62c6cacc70233896.png"},{"id":64369063,"identity":"023af16b-3774-4be3-96cb-f746ad717c36","added_by":"auto","created_at":"2024-09-12 08:50:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":191307,"visible":true,"origin":"","legend":"\u003cp\u003eRedundant analysis on the impact of soil properties, including soil total P (STP), soil available P (SAP), soil total N (STN), soil available N (SAN), gravimetric water content (GWC), on the root bacterial community in 2019 and 2020 at vegetative and full-flowering stages, under phosphorus fertilizations of phosphorus rates (PR) at 0 (LP), 17 (RP), and 32 kg ha\u003csup\u003e-1\u003c/sup\u003e (HP) in combinations of opener widths (OW) at the narrow 2.5 cm (1) and the wide 10 cm (2). Only the soil properties significantly impacted the microbial community were shown as arrows (p\u0026lt;0.05, n=4)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4902932/v1/5b29d0f03d9e4994cc41be0d.png"},{"id":64369061,"identity":"cfc3442b-0f1a-477b-8111-9ab56f500b5a","added_by":"auto","created_at":"2024-09-12 08:50:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":286459,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of the dominant bacterial and fungal families in canola roots in different sampling years (2019 and 2020) and growth stages (vegetative “V” and flowering “F”), or under three P rates at 0 kg ha\u003csup\u003e-1\u003c/sup\u003e (LP), 17 kg ha\u003csup\u003e-1\u003c/sup\u003e (RP), and 32 kg ha\u003csup\u003e-1\u003c/sup\u003e (HP)\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4902932/v1/6e1ab7c961940e8134487b87.png"},{"id":64369064,"identity":"208a255c-48a2-427d-9219-99ed4d9f6b40","added_by":"auto","created_at":"2024-09-12 08:50:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":610380,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of the differentially abundant canola root bacterial ASVs under phosphorus rates (PR) at 0 (LP), 17 (RP), and 32 kg ha\u003csup\u003e-1\u003c/sup\u003e (HP), determined with ANCOM-BC (colors indicated log\u003csub\u003e10\u003c/sub\u003e abundance, and gray color indicated absence), and the Spearman’s correlations of theses genera to soil and plant properties in 2019 and 2020, including soil total P (STP), soil available P (SAP), soil total N (STN), soil available N (SAN), gravimetric water content (GWC), shoot total P (ShTP), shoot total N (ShTN), shoot P uptake (Puptake), shoot N uptake (Nuptake), plant yield, biomass, and density. Only the significant correlations were presented (p \u0026lt; 0.001) with coefficients shown as numbers on the circles. Red and blue circles indicated positive and negative correlations, respectively. The legend color showed the\u0026nbsp;correlation coefficients\u0026nbsp;and the corresponding colors. “\u003cem\u003eBurkholderia\u003c/em\u003e” in 2019 referred to “\u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e”\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4902932/v1/add3930d83c468e36a67728b.png"},{"id":64369060,"identity":"fa7da880-145f-4827-b897-e4ed1a180c44","added_by":"auto","created_at":"2024-09-12 08:50:42","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":416936,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of the differentially abundant canola root fungal ASVs under phosphorus rates (PR) at 0 (LP), 17 (RP), and 32 kg ha\u003csup\u003e-1\u003c/sup\u003e (HP), determined with ANCOM-BC (colors indicated log\u003csub\u003e10\u003c/sub\u003e abundance, and gray color indicated absence), and the Spearman’s correlations of theses genera to soil and plant properties in 2019 and 2020, including soil total P (STP), soil available P (SAP), soil total N (STN), soil available N (SAN), gravimetric water content (GWC), shoot total P (ShTP), shoot total N (ShTN), shoot P uptake (Puptake), shoot N uptake (Nuptake), plant yield, biomass, and density. Only the significant correlations were presented (p \u0026lt; 0.001) with coefficients shown as numbers on the circles. Red and blue circles indicated positive and negative correlations, respectively. The legend color showed the\u0026nbsp;correlation coefficients\u0026nbsp;and the corresponding color\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4902932/v1/7e14b37e40c45df489202833.png"},{"id":77052526,"identity":"fe7d7580-5a18-4f49-841d-b235d6603423","added_by":"auto","created_at":"2025-02-24 16:13:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3021291,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4902932/v1/1e1327d7-4881-499d-973a-ef609a6c52d7.pdf"},{"id":64369065,"identity":"afae62d2-f25b-43eb-a241-825c99f84319","added_by":"auto","created_at":"2024-09-12 08:50:42","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1264329,"visible":true,"origin":"","legend":"","description":"","filename":"LiuetalSupplementaryInfoPlantandSoil.docx","url":"https://assets-eu.researchsquare.com/files/rs-4902932/v1/b2220b78cbb1f4b65d88ae6c.docx"}],"financialInterests":"","formattedTitle":"Phosphorus fertilizer responsive bacteria and fungi in canola (Brassica napus L.) roots are correlated with plant performance","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCanola (\u003cem\u003eBrassica napus\u003c/em\u003e. L) plants have high phosphorus demand, and early season phosphorus deficiency can restrict crop growth, potentially reducing grain yield (Grant et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Granular monoammonium phosphate (MAP) (11-52-0) has been widely applied as seed-placed phosphorus fertilizer to satisfy this demand, and its efficiency depends on both phosphorus rate and placement (Malhi et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The recommended rate of seed-placed phosphorus fertilizer in western Canada is7-12 kg P ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and 12 kg P ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in Saskatchewan (Saskatchewan Ministry of Agriculture \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These rates, however, cannot compensate the phosphorus removal by canola, as optimal yields require 30\u0026ndash;35 kg P ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Canola Council of Canada 2023), whereas excessive rate can result in phosphorus toxicity to seedlings (Grant and Flaten \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Qian and Schoenau \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The placement of phosphorus fertilizer, particularly the width of the furrow opener in which seeds and fertilizers placed together into the soil, can impact fertilizer efficiency. For instance, a narrow opener can elevate phosphorus concentration in the seed-row, making phosphorus more accessible for the plant, but can escalates the risk of seedling damage (Lemke et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Shao et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, optimizing phosphorus fertilization is crucial for canola, and studies on the combinations of varied phosphorus rates and placements can fill this gap.\u003c/p\u003e \u003cp\u003eSoil fertilization can not only directly impact plant growth through nutrient supply, but also through the indirectly impact on the belowground bulk soil microbiome, and thus the root-associated microbiome (Zhao et al. \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e; Gomes et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Previous studies have revealed that both soil nitrogen and phosphorus fertilization can determine the relative abundance and composition of the bacterial communities in the rhizosphere of maize and wheat (Liu et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). The decrease in microbial richness and diversity in the bulk soil upon fertilization has also been reported (Zhou et al. \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Despite major observations of decreased microbial diversity, the increased of microbial diversity were also reported. The addition of a balanced fertilization of nitrogen-phosphorus-potassium, increased the soil microbial diversity, potentially related to the acceleration of nutrient turnover and genes involved in carbon, nitrogen, phosphorus, and sulfur cycling, which promoted rice growth (Su et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Moreover, the long-term inorganic fertilization on a paddy soil increased the bacterial richness and diversity in the bulk soil (Huang et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Except for the impact of the overall microbial community, specific microbes responded to fertilization. For example, nitrogen fertilization has been shown to impact the root-associated microbiome in field-grown canola, where \u003cem\u003eGammaproteobacteria, Bacteroidia, Actinobacteria, Sordariomycetes, Dothideomycetes\u003c/em\u003e, and \u003cem\u003eAgaricomycetes\u003c/em\u003e from the rhizosphere soil were suggested to be the nitrogen-responding bacterial classes (Li et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurrently, the root-associated microbiome of canola has been profiled and the impact of nitrogen fertilization on the microbiome has been reported (Lay et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e), however, there is limited information on the effects of phosphorus fertilization. This gap in knowledge is particularly significant because, despite the large total pool of phosphorus in soil, only a small fraction is directly available to plants, primarily bound in organic forms requiring conversion to inorganic forms for uptake (Richardson and Simpson, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Moreover, soil phosphorus availability is further constrained by its binding to minerals such as iron, aluminum, and calcium, which limits its bioavailability (Raghothama \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Weeks and Hettiarachchi \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe root-associated microbiome plays an important role in plant phosphorus uptake. Plants can recruit these microorganisms from the bulk soil, which then influence soil phosphorus cycling and plant phosphorus acquisition. These microorganisms solubilize inorganic phosphorus by producing organic acids and phosphatases, which release phosphate from phosphorus-bound minerals (Hunter et al. 2014). Additionally, certain microorganisms mineralize organic phosphorus by producing enzymes that decompose organic matter, converting it into plant-available forms (Heuck et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These processes significantly enhance plant access to soil phosphorus, thereby improving overall plant health and productivity (Heuer et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eArbuscular mycorrhizal fungi (AMF) are key microbes that that enhance soil phosphorus efficiency and promote plant growth (Wahab et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hou et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, canola, being a \u003cem\u003eBrassica\u003c/em\u003e plant, is non-mycorrhizal, necessitating the recruitment of alternative microbes to improve its phosphorus uptake. Except for AMF, various bacterial strains such as \u003cem\u003eBurkholderia, Erwinia, Enterobacter, Pseudomonas, Bacillus\u003c/em\u003e, and \u003cem\u003eSerratia\u003c/em\u003e, as well as fungal stains like \u003cem\u003eAspergillus\u003c/em\u003e, \u003cem\u003eFusarium, Mortierella, Penicillium\u003c/em\u003e, and Trichoderma, have been identified as potential phosphorus-solubilizing and phosphorus-mineralizing microorganisms (Alori et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Elhaissoufi et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Notably, some of these species have been reported in the root-associated microbiome of \u003cem\u003eBrassica\u003c/em\u003e plants (Haney et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yu et al. \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), however, their specific roles in response to phosphorus fertilization in canola remain underexplored.\u003c/p\u003e \u003cp\u003eThis study investigates the effects of phosphorus fertilizer rate and placement on canola performance and its root-associated bacterial and fungal microbiomes. We hypothesize that i) high-rate seed-placed phosphorus fertilizer negatively affects canola seedling emergence and yield, especially when placed closer to seeds in a narrow opener, ii) phosphorus fertilizer managements impacts the diversity, composition, and structure of the canola root and rhizosphere bacterial and fungal microbiomes, iii) specific root-associated bacterial and fungal taxa are enriched in phosphorus-abundant conditions, while others thrive in phosphorus-limited conditions, iv) the abundance of specific phosphorus-responsive microorganisms in the rhizosphere and roots correlates with canola field performance. Understanding the influence of phosphorus fertilization on the overall root-associated microbial community and specific phosphorus-responsive microbes, is crucial for improving phosphorus use efficiency in canola, ultimately reducing dependency on phosphorus fertilizers while maintaining optimal crop yields.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSite description and sampling\u003c/h2\u003e \u003cp\u003eA 2-year field experiment was conducted using a commercial canola InVigor L233P at the Agriculture and Agri-Food Canada Research Farm in Scott, Saskatchewan, Canada (52\u0026deg;21'38.6\"nitrogen, 108\u0026deg;50'00.8\"W) in 2019 and 2020. The Scott field site was chosen because it previously showed good phosphorus fertilizer response in canola. This canola line was chosen for its good herbicide tolerance and its wide geographic suitability. The field soil was classified as a dark brown silt loam soil at pH of 5.5-6.0, with concentrations of organic matter at 3.7%, total nitrogen at 2000 mg.kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, available nitrogen at 88 mg.kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, total phosphorus at 555 mg.kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, available Olsen phosphorus at 25 mg.kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, total potassium at 2225 mg.kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and total sulfur at 262 mg.kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The total growing season precipitation (May-September) was 278 mm in 2019 and 289 mm in 2020.\u003c/p\u003e \u003cp\u003eIn 2019 and 2020, the blend of urea and ammonium sulphate was banded to a depth of 7.5 cm at a rate of 156.8 kg nitrogen ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 22.4 kg sulfur ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and mid-row-banded during the seeding operation. Six different seed-placed phosphorus fertilizer managements were supplied in combinations of three phosphorus rates: low P (LP, 0 kg P ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), recommended P (RP, 17 kg P ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and high P (HP, 32 kg P ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and in placements of two opener widths (OW): narrower (OW1 at 2.5 cm) and wider (OW2 at 10 cm) in a replicated randomized complete block design (n\u0026thinsp;=\u0026thinsp;4). In each sampling year, we randomly selected 4\u0026ndash;6 plants per plot for microbiome studies, and obtained samples from three compartments (bulk soil, rhizosphere soil, and roots) at two growth stages, including the 4\u0026ndash;5 leaf vegetative stage (V) and the full-flowering stage (F). In total, 288 microbiome samples were collected (2 years x 2 growth stages x 3 phosphorus rates x 2 phosphorus placements x 4 reps x 3 sample compartments\u0026thinsp;=\u0026thinsp;288 samples). Detailed methods for field sampling and sample processing are provided in Method S1, and the procedures for the measurements soil traits (total and available phosphorus, total and available nitrogen, and gravimetric water content) and plant properties (biomass, seed yield, plant density, shoot total phosphorus and nitrogen concentrations, shoot phosphorus and nitrogen uptakes) can be found in Method S2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDNA Extraction and Amplicon Sequencing\u003c/h2\u003e \u003cp\u003eTotal DNA from the bulk and rhizosphere soil was extracted with the DNeasy PowerSoil Pro Kit (QIAGEnitrogen, Germany), and DNA from the roots was extracted with the DNeasy Plant Mini Kit (QIAGEnitrogen, Germany). Genomic DNA in the extracts were quantified using a Qubit 4 fluorometer (Invitrogen\u0026trade;, CA) and standardized to 5 ng.ul\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e prior to polymerase chain reaction (PCR). Primer pairs with Illumina adapters of 342F (5\u0026prime;-CTACGGGGGGCAGCAG-3\u0026prime;; 16 nt) and 806R (5\u0026prime;-GGACTACCGGGGTATCT-3\u0026prime;; 17 nt) (Mori et al. 2014) were used to target the 16s rRNA region of bacteria; ITS1-F_KYO1 (TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CTH GGT CAT TTA GAG GAA STA A) and ITS2-R_KYO2 (GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA GTT YRC TRC GTT CTT CAT C) were used to target the ITS region of fungi (Toju et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) for PCR. Detailed methods for library preparation of amplicon-based DNA Illumina sequencing are illustrated in Method S3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSequence Data Processing and Statistical Analysis\u003c/h2\u003e \u003cp\u003eQuality-controlled sequence data of both bacteria and fungi generated from the Illumina MiSeq platform were processed using QIIME2 v2022.8 software (Bolyen et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), where sequence data were demultiplexed, denoised, and representative sequences were generated as Amplicon Sequence Variants (ASVs) (Callahan et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Then the SILVA database (Silva_138) was trained as the classifier for 16S rRNA (Quast et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and UNITE database (version 9.0) for ITS (Abarenkov et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), to determine the taxonomic classification of the above generated ASVs. Detailed methods for raw sequence data processing can be found in Method S4. After removing singletons and doubletons, the abundance and taxonomy tables containing the sample information were generated and imported into R software (v. 4.3.3) for downstream analyses.\u003c/p\u003e \u003cp\u003eFor analyses in R, we firstly evaluated whether plant and soil properties differed under different phosphorus fertilizer managements, using analysis of variance (ANOVA), followed by post-hoc pairwise comparisons of Tukey\u0026rsquo;s test. Plant traits included plant emergence, density, shoot biomass, grain yield, shoot phosphorus concentration (ShTP), shoot phosphorus uptake (Puptake), shoot nitrogen concentration (ShTN), shoot nitrogen uptake (Puptake). Soil properties included soil total phosphorus (STP), soil available phosphorus (SAP), soil total nitrogen (STN), soil available nitrogen (SAN), gravimetric water content (GWC).\u003c/p\u003e \u003cp\u003eFor microbial data analyses in R, Vegan (Oksanen et al. 2020) and Phyloseq (McMurdie and Holmes \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) packages were used to calculate the bacterial and fungal alpha diversity (indices including Pielou\u0026rsquo;s evenness, richness of observed ASVs, and Shannon diversity) in each sample type (bulk soil, rhizosphere soil, and roots). The influence of sample type, sampling year, plant growth stage and phosphorus fertilization on the alpha diversity indices were assessed using analysis of variance (ANOVA) followed by a pairwise comparison on the results of ANOVA using false-discovery-rate-corrected (FDR) post-hoc test. Similar analyses were conducted for the root microbiome from a specific sampling event. Next, microbial relative abundance under different phosphorus fertilizer managements were calculated at the family or class level. The 20 most abundant bacterial and fungal families or classes were then visualized using \u0026ldquo;ggplot2\u0026rdquo; function (Wickham \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), with less abundant ones grouped together and labelled as \u0026ldquo;Others\u0026rdquo;. To profile the bacterial and fungal community compositions (beta diversity), we used the centered log-ratio (CLR) transformation to handle compositional effects and compute the Aitchison distance. Principal component analysis (PCA) was then performed on the CLR transformed data for bacteria and fungi, respectively. The effects of sampling year, plant growth stage, and phosphorus fertilization on the microbial community structure were assessed using permutational analysis of variance (PERMANOVA) for each sample type (bulk soil, rhizosphere soil, and roots) using the \"adonis2\" function (McArdle BH and Anderson 2001).\u003c/p\u003e \u003cp\u003eTo investigate how phosphorus rates and placements impacted the root microbiomes, relative abundance and PCA analyses were conducted using methods similar to those described above. In addition, redundancy analysis (RDA) was performed using the \u0026ldquo;rda\u0026rdquo; function (Legendre and De C\u0026aacute;ceres 2012) to explore the impact of soil properties (including STP, SAP, STN, SAN, GWC) on the root microbial community structure. Only the soil properties that significantly explained variability in microbial community structure were fitted to the ordination and visualized with the \u0026ldquo;plot\u0026rdquo; function (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Differential abundance analyses were conducted using the Analysis of Compositions of Microbiomes with Bias Correction function (ANCOM-BC2) to identify ASVs that were differentially abundant under varied phosphorus rates (Lin and Peddada \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The identified ASVs were then plotted on a heatmap, using log-transformed data to illustrate their abundance. Focusing on these differentially abundant root bacterial and fungal ASVs, Spearman\u0026rsquo;s correlations between these ASVs and all soil and plant parameters (including STP, SAP, ShTP, Puptake, STN, SAN, ShTN, Nuptake, GWC, yield, biomass, and density) were calculated using the \u0026ldquo;rcorr\u0026rdquo; function from the Hmisc package (Press et al. 1998), and then visualized with the \u0026ldquo;corrplot\u0026rdquo; function (Wei and Simko, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). All detailed analysis methods in R were illustrated in Method S4.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eHigh-rate and more concentrated seed-placed phosphorus fertilization decreased plant density but did not affect grain yield or biomass\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePlant field performance was impacted by growing season conditions in 2019 and 2020. More specifically, plant emergence (on 14, 21 and 28 days after seedling (DAS)) and plant density at harvest were higher, while grain yield and plant shoot biomass were lower in 2019 compared to 2020 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHigh-rate seed-placed phosphorus consistently decreased plant emergence and density in both 2019 and 2020. Compared to unfertilized soil (LP), plant emergence (on 14, 21 and 28 days after seedling (DAS)) and plant density at harvest decreased in phosphorus fertilized soils (recommended RP and high-rate HP), especially when applied using the narrower opener (OW1). (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Specifically in 2019, higher shoot biomass, grain yield, and shoot total phosphorus concentration were observed in HP-OW1 compared to LP-OW2 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while no significant impact of soil phosphorus was found in either shoot phosphorus uptake, or shoot nitrogen concentration and uptake (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In 2020, however, no significant differences were detected in any of these traits.\u003c/p\u003e \u003cp\u003eIn addition, nutrient analyses revealed that soil total phosphorus and nitrogen, available nitrogen, nitrogen to phosphorus ratio, GWC, as well as shoot phosphorus and nitrogen uptakes were higher in 2019 compared to 2020 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Apart from the impact of sampling year, plant growth stage also impacted soil and plant nutrient concentration. In both 2019 and 2020, soil available phosphorus and nitrogen, as well as shoot total phosphorus and nitrogen concentrations were higher at the early vegetative than the later flowering stage, while shoot phosphorus and nitrogen uptake were greater at flowering stage as biomass increased (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCanola performance under six soil phosphorus treatments of phosphorus rates (PR) at 0 (LP), 17 (RP), and 32 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (HP) in combinations of narrower (1) and wider (2) opener widths (OW) in sampling year 2019 and 2020 (pairwise comparisons were conducted within a specific sampling year, where different letters indicated statistical significance, determined using ANOVA followed by Tukey\u0026rsquo;s test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP treatment\u003c/p\u003e \u003cp\u003e[PR (OW)]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlant Emergence-14DAS (plants m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePlant Emergence-21DAS (plants m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePlant Emergence-28DAS (plants m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePlant Density (plants m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBiomass\u003c/p\u003e \u003cp\u003e(g m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYield\u003c/p\u003e \u003cp\u003e(kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eShoot N concentration\u003c/p\u003e \u003cp\u003e(mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eShoot N uptake\u003c/p\u003e \u003cp\u003e(mg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eShoot P concentration\u003c/p\u003e \u003cp\u003e(mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eShoot P uptake\u003c/p\u003e \u003cp\u003e(mg)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLP(1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e738 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3668 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.6 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e886 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.6 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e65.3 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRP(1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e775 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3938 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.0 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e811 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.1 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e78.8 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHP(1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e934 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3990 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.7 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e990 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.6 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e91.7 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLP(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e706 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3413 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.3 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e553 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.5 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e43.0 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRP(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e851 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3654 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e45.5 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e789 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.1 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e71.5 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHP(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e941 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3871 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e45.4 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e647 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.0 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e61.2 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLP(1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e983 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4861 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e43.4 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e533 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.6 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e63.6 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRP(1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1019 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4689 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40.9 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e665 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.6 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e81.0 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHP(1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1044 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4723 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40.1 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1102 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.9 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e160.2 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLP(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1098 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4563 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e42.8 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e814 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.4 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e105.0 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRP(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e998 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4598 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e41.5 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1043 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.6 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e136.4 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHP(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44 b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e956 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4536 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e41.3 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1001 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.7 a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e137.4 a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePhosphorus fertilization impacted only the root bacterial and fungal diversity and community structure\u003c/h2\u003e \u003cp\u003eA total of 10,176 unique bacterial ASVs and 3,599 unique fungal ASVs were identified in 288 samples (ninety-six samples each of bulk soil, rhizosphere soil, and root). The alpha diversity (observed richness, Pielou\u0026rsquo;s evenness, and Shannon diversity) of both bacteria and fungi was the highest in the bulk soil, followed by the rhizosphere soil, and was the lowest in the root (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Table S2).\u003c/p\u003e \u003cp\u003eNotably, only the root bacterial and fungal diversity in 2019 were impacted by phosphorus treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table S3). At the early vegetative stage, lower root bacterial alpha diversity was found in RP compared to both LP and HP, for OW1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Comparable patterns were observed in the root fungal community but were not statistically significant. Instead, phosphorus placement rather than rate, impacted root fungal diversity, with higher diversity observed in OW1 compared to OW2 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). At the flowering stage, the root bacterial and fungal diversities showed no significant differences between phosphorus treatments.\u003c/p\u003e \u003cp\u003eIn terms of microbial community structure, the greatest separation occurred in the three sample types under investigation, and this separation was greater in the bacterial compared to the fungal community (Fig. S2, Table S3). In the bulk soil, sampling year had a major impact on both bacterial and fungal community structure, with a minor impact of plant growth stage on the fungal community. In the rhizosphere soil and roots, both sampling year and plant growth stage contributed to separations in bacterial and fungal communities.\u003c/p\u003e \u003cp\u003eSpecifically for the root microbiome, in 2019, the root bacterial community structures were significantly influenced by phosphorus treatments. The root fungal community structure was affected by phosphorus rate (PR), particularly when supplied with a specific OW, across all sampling events except at the flowering stage in 2020 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Despite these inconsistent impacts from PR and OW, soil available phosphorus (SAP) was consistently correlated with the bacterial community of the canola roots across all sampling events (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The impact of additional soil factors on root fungal community was only observed at the early vegetative stage (e.g., SAP, total nitrogen, and GWC) (Fig. S3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePERMANOVA of the effect of phosphorus rate (PR) and opener width (OW) on root bacterial and fungal communities in 2019 and 2020 at the 4\u0026ndash;5 leaf vegetative stage (V) and the full-flowering (F) stages\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBacteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eFungi\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePr(\u0026gt;\u0026thinsp;F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePr(\u0026gt;\u0026thinsp;F)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2019V\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR x OW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2019F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR x OW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2020V\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR x OW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.030\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2020F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR x OW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Bold values denote statistical significance at the p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePhosphorus fertilization affected the abundance of root bacteria and fungi\u003c/h2\u003e \u003cp\u003eSampling year and plant growth stage influenced the bacterial and fungal compositions in canola roots. For instance, the abundance of \u003cem\u003eStreptomycetaceae\u003c/em\u003e was higher in the vegetative stage (12%-15%), compared to the flowering stage (2%-3%), while the abundance of \u003cem\u003eOlpidiaceae\u003c/em\u003e was higher in the flowering stage (60%-70%), compared to the vegetative stage (2%-20%).\u003c/p\u003e \u003cp\u003eDespite the impacts from sampling year and plant growth stage, phosphorus fertilization modified the microbial relative abundance in canola roots. For example, fungi \u003cem\u003eXylariaceae\u003c/em\u003e had higher relative abundance but lower relative abundance of \u003cem\u003eOlpidiaceae\u003c/em\u003e in canola roots grown in HP soils (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). And higher relative abundance of \u003cem\u003ePseudomonadaceae\u003c/em\u003e and \u003cem\u003eMortierellaceae\u003c/em\u003e were found in canola roots grown in RP soils, especially when supplied with the narrow opener (OW1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe abundance of specific microbes in canola roots shifted under varying phosphorus rates. In 2019, this response included 17 bacterial ASVs and 11 fungal ASVs in canola roots. Bacteria including 9 ASVs from Gammaproteobacteria (including 4 \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e, 2 Luteibacter, and 1 from \u003cem\u003eComamonas, Enterobacteriaceae\u003c/em\u003e, and \u003cem\u003eRhodanobacter\u003c/em\u003e, respectively), 6 ASVs from Bacteroidia (including 2 ASVs from \u003cem\u003eSphingobacterium, Chryseobacterium\u003c/em\u003e, and \u003cem\u003eChitinophaga\u003c/em\u003e, respectively) and 2 ASVs from Actinobacteria (including a single ASV from \u003cem\u003eActinoallomurus\u003c/em\u003e and \u003cem\u003eRhodococcus\u003c/em\u003e, respectively) were differentially abundant in canola roots grown under different phosphorus treatments. The differential abundant root fungi included 3 ASVs from Agariomycetes (including 1 ASV from \u003cem\u003eAmaurodon, Thanatephorus\u003c/em\u003e, and \u003cem\u003eCalyptella\u003c/em\u003e, respectively), 3 ASVs from Sordariomycetes (including 1 ASV from \u003cem\u003eConlarium, Trichoderma\u003c/em\u003e, and \u003cem\u003eLectera\u003c/em\u003e, respectively), 2 ASVs from \u003cem\u003eLachnum\u003c/em\u003e, as well as 1 ASV from Olpidiomycetes (\u003cem\u003eOlpidium\u003c/em\u003e), Euroriomycetes (\u003cem\u003ePenicillium\u003c/em\u003e), and Dothideomycetes (\u003cem\u003eSigarispor\u003c/em\u003ea), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, in 2019, genera from high-phosphorus (HP) responsive Gammaproteobacteria (e.g., \u003cem\u003eRhodanobacter, Luteibacter\u003c/em\u003e, and \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e) in canola roots were positively correlated with soil total phosphorus (STP) and soil available phosphorus (SAP). Positive correlations were also detected between canola biomass and the abundance of \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e (ASV2088, ASV558, and ASV20) in canola roots, with ASV2088 being positively correlated with canola yield. On the contrary, genera from low-phosphorus (LP) responsive Bacteroidia in canola roots were negatively correlated with SAP (e.g., \u003cem\u003eChryseobacterium\u003c/em\u003e and \u003cem\u003eChitinophaga\u003c/em\u003e) and shoot total phosphorus concentration (e.g., \u003cem\u003eSphingobacterium\u003c/em\u003e). The abundance of \u003cem\u003eChryseobacterium\u003c/em\u003e (ASV5933) and \u003cem\u003eChitinophaga\u003c/em\u003e (ASV5762) in canola roots were positively correlated with plant density. Sordariomycetes genera \u003cem\u003eAmaurodon\u003c/em\u003e, \u003cem\u003eConlarium\u003c/em\u003e, and \u003cem\u003eTrichoderma\u003c/em\u003e were more abundant in canola roots grown in phosphorus-fertilized soils, and the abundance of \u003cem\u003eTrichoderm\u003c/em\u003e were positively correlated with canola yield. Further, fungi \u003cem\u003eOlpidium\u003c/em\u003e were enriched in canola roots grown in LP soils, while root \u003cem\u003ePenicillium\u003c/em\u003e were enriched in HP soils and negatively correlated with plant density (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 2020, the abundance responses included 13 bacterial ASVs and 6 fungal ASVs in canola roots grown in varied soil phosphorus fertilizations. More specifically, 8 bacterial ASVs from Gammaproteobacteria (including 3 ASVs from \u003cem\u003ePseudomonas\u003c/em\u003e, and a single ASV from \u003cem\u003eProvidencia, Erwinia, Celivibrio, Duganella\u003c/em\u003e, and \u003cem\u003eBurkholderiaceae\u003c/em\u003e), and 5 ASVs from Bacteroidia (including 3 ASVs from \u003cem\u003eFlavobacterium\u003c/em\u003e, and a single ASV from \u003cem\u003eMucilaginibacter\u003c/em\u003e and \u003cem\u003eChryseobacterium\u003c/em\u003e, respectively) were differentially abundant in canola roots grown in different phosphorus treatments. And the differentially abundant root fungi included 3 ASVs from Sordariomycetes, 2 ASVs from Dothideomycetes (a single ASV from \u003cem\u003eSigarispora\u003c/em\u003e and \u003cem\u003eMycosphaerella\u003c/em\u003e, respectively), and 1 ASV from Mortierellomycetes (\u003cem\u003eMortierella\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdditionally in 2020, bacteria \u003cem\u003eProvidencia\u003c/em\u003e and \u003cem\u003eErwinia\u003c/em\u003e showed higher abundance in canola roots grown in HP soils, while \u003cem\u003ePseudomonas\u003c/em\u003e (ASV3109), \u003cem\u003eCellvibrio\u003c/em\u003e, \u003cem\u003eDuganella\u003c/em\u003e, and \u003cem\u003eFlavobacterium\u003c/em\u003e exhibited high abundance in roots grown in LP soils, with negative correlations observed in \u003cem\u003ePseudomonas\u003c/em\u003e and \u003cem\u003eDuganella\u003c/em\u003e with SAP and ShTP. Moreover, fungi \u003cem\u003eNectriaceae\u003c/em\u003e (ASV93 and ASV116) had higher abundance in canola roots grown in HP soils, while root Dothidomycetes genera \u003cem\u003eSigarispora\u003c/em\u003e and \u003cem\u003eMycosphaerella\u003c/em\u003e had higher abundance in LP soils, with the former negatively associated with plant phosphorus and nitrogen uptakes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eThe impact of phosphorus fertilization on plant performance\u003c/h2\u003e \u003cp\u003eDue to the immobility and fixation properties of phosphorus, seed-placed fertilizers are considered an effective method to provide readily accessible phosphorus to plants. However, canola seedlings are sensitive to seed-placed phosphorus, which limits the rates of application (Qian and Schoenau \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In accordance with previous studies (Bailey and Grant \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Lemke et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), we found that high-rate seed-placed phosphorus fertilizers reduced canola population (emergence and plant density), especially when placed closer to the seeds in a narrow opener (HP-OW1). This decrease in canola emergence and plant density did not affect yield in 2020, while it increased yield in 2019 (Table. 1).\u003c/p\u003e \u003cp\u003ePhosphorus fertilization increased canola biomass and yield only in 2019 but not 2020, while overall yield was higher in 2020 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This indicated that local climate and environment, particularly moisture and temperature, may have overridden the impact from P fertilization in 2020. In particular, both the in-season (March-September at 289 mm) and total precipitation (378 mm) in 2020 were higher than those in 2019 (in season at 278 mm and total at 341 mm), with higher GWC in 2020 at the flowering stage. The higher moisture content in 2020 likely increased phosphate solubility and diffusion in the soil solution, increasing phosphate movement to roots and contributing to better root phosphorus uptake, and ultimately transmitted to a better yield. The limited moisture in 2019, on the contrary, contributed to greater treatment level responses to phosphorus fertilization. B\u0026eacute;langer et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) found that canola growth response to phosphorus fertilizer was highly dependent on year and site in the Canadian Prairies. They demonstrated that soil moisture can often override nutrient management for plant growth in arid and semi-arid environments.\u003c/p\u003e \u003cp\u003eMoreover, the lack of yield response in 2020 may have been due to initially high soil phosphorus levels. In 2019, pre-seeding soil tests indicated relatively high available phosphorus (22 kg P ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), despite the site having high phosphorus responsiveness in previous growing seasons. Due to global pandemic restrictions in 2020, spring sampling soil fertility did not occur. However, considering that theses fields were side by side with similar rotations, it is assumed that the field in 2020 had similarly high background soil phosphorus levels, supported by high levels of available phosphorus in plots without phosphorus fertilizer (LP) during early growth stages, averaging 35 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in 2019 and 44 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in 2020 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Saskatchewan's phosphorus fertilizer guidelines suggest a probability of less than 25% for a yield response to phosphorus fertilizer when available phosphorus exceeds 30 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Saskatchewan Ministry of Agriculture \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), similar to the phosphorus threshold for canola yield response reported by McKenzie et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Furthermore, observations of increased shoot nitrogen and phosphorus uptake with higher and more concentrated phosphorus fertilization suggested luxury uptake by canola, aligning with previous studies (B\u0026eacute;langer et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Shao et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eThe impact of phosphorus fertilization on the canola root-associated microbial community\u003c/h2\u003e \u003cp\u003eCompared to the bulk soil, the rhizosphere is a hotspot for plant-soil-microbe interactions, where nutrient cycling is intensified (Reinhold-Hurek et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). A recent review of 123 studies of soil and root-associated microbiomes validated that the rhizosphere region has higher activities of nitrogen fixation, phosphorus mineralization and phosphorus solubilization compared to the bulk soil (Liu et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In accordance with our findings, the highest microbial diversity has been observed in bulk soil, followed by rhizosphere soil, and was lowest in roots (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) because of increasingly selective microenvironments at the soil-root interface (Ling et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the major impact of the environment (year) and/or plant growth stage on the microbiome of all sample types (bulk soil, rhizosphere soil, and the roots), phosphorus fertilization had a minor but significant impact specifically on the root microbiome. This impact was greater in 2019 compared to 2020, indicating its dependence on year-to-year environmental conditions, as observed in our study (Fig. S2, Table S2, Table S3) and extensively discussed in previous studies (Philippot et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Qu et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bell et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Cordero et al. 2021; Li et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). In 2019, the diversity (observed richness, Pielou\u0026rsquo;s evenness, and Shannon diversity) of both the root bacteria and fungi was the highest in high phosphorus soil, especially when applied with the narrow opener, and this trend was more apparent at the early vegetative stage compared to the late flowering stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Similar observations have reported in maze roots, where high phosphorus increased the richness, Shannon diversity and Pielou\u0026rsquo;s evenness of the fungal community (Gomes et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), as well as the increased bacterial richness in soil under long-term phosphorus addition (Zhang et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The pronounced canola root microbial diversity responses at the vegetative stage, compared to the flowering stage, indicated that 1) at early vegetative growth stage, plant nutrient demands are higher, leading to more intense competition between plants and microbes for nutrient resources, consistent with findings in wheat (Garc\u0026iacute;a-D\u0026iacute;az et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); 2) early-season phosphorus fertilizer had absorbed by canola plants and subsequently had less influence on the root microbiome. This observation aligned with findings from Wang et al. (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) on soybeans, where root bacterial diversity remained stable in later growth stages despite varying nitrogen and phosphorus fertilization; or 3) soil phosphorus ceased to be a dominant determinant of microbial diversity as mature canola plants exhibit increased selective capability to support specific microbial community in roots (Edwards et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe found that soil phosphorus can shift the composition of the canola root microbial community (Table. 2, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig. S3). Similar impacts of phosphorus have been documented in the fungal community in the rhizosphere and roots of \u003cem\u003eArabis alpina\u003c/em\u003e (Almario et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and \u003cem\u003eArabidopsis thaliana\u003c/em\u003e (Fabiańska et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), the bacterial and fungal communities in the rhizosphere and roots of maize (Deng et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bourceret et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the rhizosphere bacterial community in blueberry (Pantigoso et al. 2018), and the rhizosphere bacterial and the root fungal communities in wheat (Pag\u0026eacute; et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These findings emphasize the significant role of phosphorus in modulating the microbial communities associated with plant roots, with potential implications for plant growth and biomass production. Conversely, some other studies did not detect any impact of phosphorus fertilization on the diversity or the structure of the root-associated microbiome (Sawyer et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe root-associated microbial community diversity and composition exhibited various responses to phosphorus fertilizer managements, underscoring the complexity of the root microbiome. This complexity arises from a multitude of influencing factors including soil properties, plant genetic material, root phenotypes, and the intricate interactions among soil, roots, and microbes. These factors collectively shape the structure and function of the root microbial communities, highlighting the dynamic nature of plant-microbe-soil interactions in response to nutrient availability and environmental conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe impact of phosphorus fertilization on the abundance of specific canola root bacteria and fungi\u003c/h2\u003e \u003cp\u003eRelative abundance analysis revealed that canola roots were dominated by bacteria from Gammaproteobacteria, followed by Actinobacteria and Bacteroidia, as well as fungi from Sordariomycetes and Olpidiomycetes (Fig. S4), agreed with previous reports (Bell et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gkarmiri et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Chun \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). \u003cem\u003eOlpidium brassicae\u003c/em\u003e is commonly recognized as a fungal parasite, especially in \u003cem\u003eBrassicacea\u003c/em\u003e plants. Previous studies indicated that high doses of the \u003cem\u003eO. brassicae\u003c/em\u003e inoculation reduced shoot and root growth in canola (Hilton et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and its high abundance in roots was associated with low yield in field-grown canola (Hilton et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We observed a high abundance of \u003cem\u003eO. brassicae\u003c/em\u003e in field canola roots, especially at the later full-flowering stage without pathogenic symptoms (Fig. S4). This observation aligns with previous findings (Li et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e; Floc\u0026rsquo;h et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), suggesting that a) \u003cem\u003eO. brassicae\u003c/em\u003e may act as an opportunistic colonizer of canola, occupying a microbial niche with little competition, b) interactions among \u003cem\u003eO. brassicae\u003c/em\u003e and other microbial species in the soil-root interface can be complex (Lay et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and c) the relationship between \u003cem\u003eO. brassicae\u003c/em\u003e and yield were highly dependent on site and strain (Town et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), with the \u003cem\u003eO. brassicae\u003c/em\u003e strain in our Scott field not impacting canola yield. Additionally, in 2019, the abundance of the canola root \u003cem\u003eO. brassicae\u003c/em\u003e was the highest in soil without phosphorus supply, while the lowest in high phosphorus soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This is consistent with a previous study in another \u003cem\u003eBrassicaceae\u003c/em\u003e plant, \u003cem\u003eArabidopsis thaliana\u003c/em\u003e, where depletion of the root the \u003cem\u003eO. brassicae\u003c/em\u003e were noted under replete phosphorus conditions (Fabiańska et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The proliferation of \u003cem\u003eO. brassicae\u003c/em\u003e appears to be common in \u003cem\u003eBrassicaceae\u003c/em\u003e plants, and the underlying ecological functions require further study.\u003c/p\u003e \u003cp\u003eWe identified specific root bacterial and fungal ASVs which responded actively to phosphorus and were correlated with plant performance, with more phosphorus-responsive organisms identified in 2019 than 2020, suggesting the major impact from the year-to-year environmental difference. ASVs from Gammaproteobacteria genera \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e, \u003cem\u003eLuteibacter Rhodanobacter\u003c/em\u003e, and from fungi Sordariomycetes genera \u003cem\u003eTrichoderma\u003c/em\u003e and \u003cem\u003eNectria\u003c/em\u003e were enriched in roots of canola grown in phosphorus-fertilized soils (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e were enriched in canola roots grown in phosphorus-fertilized soils compared to unfertilized soils, and were positively correlated with both soil available phosphorus and plant biomass in 2019 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e are known as plant-growth-promoting bacteria which inhibit fungal diseases (Jung et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). While a previous study found that \u003cem\u003eBurkholderia\u003c/em\u003e were enriched in plant tissue under phosphorus starvation (Finkel et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), we observed enrichment of \u003cem\u003eBurkholderia\u003c/em\u003e in canola roots in phosphorus-fertilized soils, consistent with a study on soybean, where reduced \u003cem\u003eBurkholderiales\u003c/em\u003e abundance was detected in soils without phosphorus fertilization (Wang et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This can be explained by the fact that \u003cem\u003eBurkholderia\u003c/em\u003e are generally considered fast-growing r-strategists that thrive in nutrient-rich environment and can utilize resources such as carbon substrates, nitrogen, and phosphorus that are abundant in the rhizosphere (Philippot et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). \u003cem\u003eBurkholderia spp.\u003c/em\u003e possess putative growth promotion and stress tolerance abilities (Verma et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pal et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Under phosphorus-sufficient conditions, canola plants may favor the growth of fungal disease antagonistic \u003cem\u003eBurkholderia\u003c/em\u003e to enhance its pathogen defense system, benefiting plant growth. This hypothesis is supported by studies in another \u003cem\u003eBrassicaceae\u003c/em\u003e plant \u003cem\u003eArabidopsis\u003c/em\u003e (Hacquard et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Motte and Beeckman \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), as well as evidence from the \u003cem\u003eBurkholderia\u003c/em\u003e inoculation to \u003cem\u003eArabidopsis\u003c/em\u003e leaves, which promoted plant growth and increased plant defense responses (Colavolpe et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, root fungi Sordariomycetes genus \u003cem\u003eTrichoderma\u003c/em\u003e was the most abundant in recommended phosphorus rates (RP) and positively correlated with canola yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Consistent with our results, a study in maize detected higher abundance of Sordariomycetes in the rhizosphere under high phosphorus for all three maize genotypes studied (Gomes et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Specifically, the phosphorus-responding \u003cem\u003eTrichoderma\u003c/em\u003e identified in our study is \u003cem\u003eTrichoderma hamatum\u003c/em\u003e. This species possesses several beneficial traits for plants, including antimicrobial activity, antioxidant activity, insecticidal activity, herbicidal activity, and plant growth promotion (Lodi et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003cem\u003eTrichoderma hamatum\u003c/em\u003e strains have been found to promote plant growth in \u003cem\u003eArabidopsis thaliana\u003c/em\u003e (Studholme et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and increase productivity in some leafy \u003cem\u003eBrassica\u003c/em\u003e crops (Velasco et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), potentially through activation of biocontrol against soil pathogens and induced systemic resistance.\u003c/p\u003e \u003cp\u003eOther root fungi such as \u003cem\u003eAmaurodon\u003c/em\u003e, \u003cem\u003ePenicillium, Mortierella\u003c/em\u003e, and \u003cem\u003eNectria\u003c/em\u003e were also abundant in phosphorus-fertilized soils, with positive correlations found between the first two genera with soil available phosphorus. Among these, the ecological function of \u003cem\u003eAmaurodon\u003c/em\u003e has rarely been documented. \u003cem\u003eMortierella\u003c/em\u003e has been considered a phosphate-solubilizing fungi, which also participates in carbon cycling (Ozimek and Hanaka 2020). Some \u003cem\u003ePenicillium\u003c/em\u003e species have high potential for phosphorus solubilization (Elias et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Doilom et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and can promote plant growth by enhancing soil nitrogen mineralization (Niu et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). \u003cem\u003eNectria\u003c/em\u003e, in particular \u003cem\u003eNectria ramulariae\u003c/em\u003e in our study, is considered a plant pathogen (Lee et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), indicating the potential for pathogen effects under excessive phosphorus fertilization.\u003c/p\u003e \u003cp\u003eOn the contrary, certain root genera, such as Bacteroidia genera \u003cem\u003eSphingobacterium, Chryseobacterium, Chitinophaga\u003c/em\u003e, and \u003cem\u003eFlavobacterium\u003c/em\u003e, as well as fungal genus \u003cem\u003eOlpidium\u003c/em\u003e were enriched in roots without phosphorus fertilization (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). \u003cem\u003eSphingobacterium\u003c/em\u003e has been reported to participate in phosphorus solubilization, making phosphorus more available for root absorption, especially under stress conditions (Ahmed et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Wan et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Vaishnav et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Some \u003cem\u003eChryseobacterium\u003c/em\u003e species can solubilize phosphorus or exhibit antimicrobial activity against some Gram-negative bacteria, thus promoting plant growth in horse gram legume (Singh et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and canola (Farina et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In our study, root \u003cem\u003eChryseobacterium\u003c/em\u003e, specifically \u003cem\u003eChryseobacterium halperniae\u003c/em\u003e, were positively correlated with canola plant density and negatively correlated with yield. Limited information is available for this specific species, and further studies are required to elucidate their potential ecological functions. \u003cem\u003eChitinophaga spp.\u003c/em\u003e can potentially promote carbon-phosphorus synergistic conversion, and participated P cycling in peanut (Chen et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In unfertilized soils, \u003cem\u003eFlavobacterium\u003c/em\u003e was reported to produce enzymes that target soil organic phosphorus (Lidbury et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and may participate in plant growth promotion (Soltani et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is important to recognize the complexity of phosphorus dynamics within the soil-plant-microbe system, and the differences between applied soil phosphorus and soil available phosphorus. Low soil available phosphorus can signify either efficient plant phosphorus uptake and removal from the soil or indicate fierce competition of soil and root-associated microorganisms with plants for soil resources, while high soil available phosphorus may indicate poor plant uptake or excessive soil phosphorus availability. Similarly, a high concentration of shoot phosphorus may reflect effective phosphorus uptake or result from smaller plants with less biomass, resulting in more concentrated tissue phosphorus. Although the responses of the root microbiome to phosphorus fertilization varied across different sampling years and plant growth stages here and in other studies (Edwards et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ofek-Lalzar et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Bell et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), phosphorus fertilization tends to have a long-lasting effect on the root microbiome. This effect was highly correlated with canola field performance, indicating that the root microbiome can participate in phosphorus cycling, mitigate phosphorus stress, and enhance plant defense responses. Plant phosphorus uptake and growth could be impacted by shifting the overall root microbiome as well as fine-tuning specific microorganisms (Castrillo et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zheng et al. \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). While treatment-level effects on the microbiome were inconsistent between years, the correlation of soil available and total phosphorus with community structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) indicates a strong link between the root microbiome and phosphorus availability which may not be linearly related to phosphorus fertilizer application.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eHigh-rate phosphorus supplied in a narrow opener decreased canola seed emergence and density, but did not impact seed yield responses. Despite significant environmental influences, early phosphorus fertilizer managements had a minor but significant long-lasting effect on the canola root microbiome. High-rate near-seed phosphorus increased root bacterial and fungal diversity, altering the root microbial structure and composition. Specific root microbial genera, such as \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia, Luteibacter, Rhodanobacter, Amaurodon, Conlarium, Trichoderma\u003c/em\u003e, and \u003cem\u003eNectria\u003c/em\u003e were enriched in canola roots grown in phosphorus-fertilized soils, whereas genera like \u003cem\u003eSphingobacterium, Chryseobacterium, Chitinophaga, Flavobacterium\u003c/em\u003e, and \u003cem\u003eOlpidium\u003c/em\u003e were enriched in roots without phosphorus fertilization. Canola yield was positively correlated with \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e and \u003cem\u003eTrichoderma\u003c/em\u003e. Future studies can focus on these taxa to more comprehensively understand their ecological roles and functions in nutrient cycling and plant growth responses, aiming to manipulate the root microbiome for improved fertilization practices and optimal canola yield.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Canola Agronomic Research Program (CARP.2019.24), Natural Sciences and Engineering Research Council of Canada (NSERC), Canada Excellence Research Chair (CERC), and China Scholarship Council (CSC).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSPM designed, conducted, and supervised the field trial. BLH designed the microbiome experiments and supervised the project. LK and ML prepared sequence samples and first draft of the manuscript. YL and DS conducted data collection and analysis, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during this current study were submitted to the National Center for Biotechnology Information (NCBI) Sequence read archive (SRA) under Bioproject accession PRJNA1062716.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Arlen Kapiniak for his assistance with fieldwork, Kimberley Hamonic and Jesse Reimer for their help with microbiome sampling and processing, and Jieyu Chen for her valuable contribution in reviewing the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbarenkov K, Henrik Nilsson R, Larsson K, Alexander IJ, Eberhardt U, Erland S, H\u0026oslash;iland K, Kj\u0026oslash;ller R, Larsson E, Pennanen T, Sen R, Taylor AFS, Tedersoo L, Ursing BM, Vr\u0026aring;lstad T, Liimatainen K, Peintner U, K\u0026otilde;ljalg U (2010) The UNITE database for molecular identification of fungi \u0026ndash; recent updates and future perspectives. 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Methods Ecol and Evol 1(1): 3\u0026ndash;14. https://doi.org/10.1111/j.2041-210x.2009.00001.x\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Phosphorus fertilizer management, canola growth response, rhizosphere and root microbiomes, phosphorus responsive bacteria and fungi","lastPublishedDoi":"10.21203/rs.3.rs-4902932/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4902932/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCanola (\u003cem\u003eBrassica napus\u003c/em\u003e L.) has high phosphorus demand, but its seedlings are sensitive to seed-placed phosphorus fertilizers. Optimizing phosphorus fertilizer managements (rates and placements) for canola is critical and can be aided by a better understanding of the root-associated microbiome, as it plays key roles in improving phosphorus availability through mineralization and solubilization.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a two-year field experiment applying monoammonium phosphate fertilizers at three rates (no addition, recommended, and high rates at 0, 17, and 32 kg P ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) using two opener placements (narrow at 2.5 cm vs. wide at 10 cm) which affect seedbed concentration of phosphorus. Canola performance was evaluated, and rhizosphere and root bacterial and fungal microbiomes were profiled by DNA amplicon sequencing.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eHigh-rate and near-seed placement of phosphorus (32 kg P ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in the 2.5 cm opener) consistently reduced canola seedling emergence but not biomass and yield, which were higher in 2020 than in 2019. Yearly variations and plant growth stages impacted both the rhizosphere and root microbiomes, while phosphorus fertilization only affected the root microbiome. Specifically, phosphorus fertilization enriched root genera \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e, \u003cem\u003eLuteibacter\u003c/em\u003e, \u003cem\u003eAmaurodon\u003c/em\u003e, \u003cem\u003eTrichoderma\u003c/em\u003e, and \u003cem\u003ePenicillium\u003c/em\u003e. Conversely, \u003cem\u003eChryseobacterium\u003c/em\u003e, \u003cem\u003eChitinophaga\u003c/em\u003e, \u003cem\u003eFlavobacterium\u003c/em\u003e and \u003cem\u003eOlpidium\u003c/em\u003e were more prevalent in roots without phosphorus addition. Canola yield was positively correlated with the abundance of \u003cem\u003eBurkholderia-Caballeronia-Paraburkholderia\u003c/em\u003e and \u003cem\u003eTrichoderma\u003c/em\u003e in roots.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003ePhosphorus fertilizer rates and placements affect canola germination but not seed yield. Profiling of phosphorus-responsive bacteria and fungi in the roots suggests that phosphorus fertilization can have a lasting impact on the canola root microbiome, modulating plant growth responses to soil phosphorus availability.\u003c/p\u003e","manuscriptTitle":"Phosphorus fertilizer responsive bacteria and fungi in canola (Brassica napus L.) roots are correlated with plant performance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-12 08:50:37","doi":"10.21203/rs.3.rs-4902932/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2024-10-18T02:47:05+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-08-27T10:02:23+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-16T08:42:17+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Plant and Soil","date":"2024-08-13T08:23:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-13T07:39:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant and Soil","date":"2024-08-12T18:06:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8041b3a4-ca7d-4dc0-9e8e-13ecd7868ab3","owner":[],"postedDate":"September 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-24T16:00:32+00:00","versionOfRecord":{"articleIdentity":"rs-4902932","link":"https://doi.org/10.1007/s11104-025-07286-w","journal":{"identity":"plant-and-soil","isVorOnly":false,"title":"Plant and Soil"},"publishedOn":"2025-02-17 15:57:14","publishedOnDateReadable":"February 17th, 2025"},"versionCreatedAt":"2024-09-12 08:50:37","video":"","vorDoi":"10.1007/s11104-025-07286-w","vorDoiUrl":"https://doi.org/10.1007/s11104-025-07286-w","workflowStages":[]},"version":"v1","identity":"rs-4902932","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4902932","identity":"rs-4902932","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}