Microbial Community Structure in Soilless Substrates Used for Nursery Crops

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Silvia Valles-Ramirez Department of Food, Agricultural and Biological Engineering, The Ohio State University, 1680 Madison Avenue, Wooster, OH 44691, USA

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James E. Altland United States Department of Agriculture-Agricultural Research Service Application Technology Research Unit, 1680 Madison Avenue, Wooster, OH 44691, USA

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Anna L. Testen United States Department of Agriculture-Agricultural Research Service Application Technology Research Unit, 1680 Madison Avenue, Wooster, OH 44691, USA

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Jelmer W. Poelstra Molecular and Cellular Imaging Center, The Ohio State University, 1680 Madison Avenue, Wooster, OH 44691, USA

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Frederick C. Michel Jr. Department of Food, Agricultural and Biological Engineering, The Ohio State University, 1680 Madison Avenue, Wooster, OH 44691, USA

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Abstract

Soilless substrates are widely used for plant cultivation. However, little is known about how soilless substrate components, plant growth, or their interactions impact microbial communities in soilless media. The objectives of this study were to analyze microbial communities in typical pine bark substrates used for nursery crop production and determine the impacts of substituting peat with a compost substrate, and planting, on microbial community dynamics over a production cycle. Three soilless substrate mixtures were compared. The substrate mixes consisted of 80:20:0, 80:10:10, and 80:0:20 (volume:volume:volume) ratios of pine bark:peatmoss:leaf compost, respectively. One set of each treatment was planted with a single birch (Betula nigra ‘Cully’) liner and another set was not planted. The treatments (n = 3) were maintained in a nursery production setting, and samples were taken after 0, 1, 2, 3, and 4 months. Bacterial and fungal communities were characterized by sequencing polymerase chain reaction-amplified 16s rRNA genes and internal transcribed spacer regions. Initially, the two substrate mixtures that contained compost had more phyla than the substrate mixture that only contained peat and bark. After 1 month, microbial communities in all treatments contained similar phyla, but at different relative abundances based on the amount of compost they contained. Over time, Nitrosomonadaceae and Acetobacteraceae were the most abundant bacterial families in substrate mixes containing 10% and 20% compost, but they were absent from treatments without compost. The communities were dynamic and changed the most over the first 2 months. Microbial communities and their dynamics were similar between planted and unplanted treatments. Planting had less of an effect on microbial communities than compost amendment. Among the fungal communities, differences were observed based on both compost amendment and plant presence. Ascomycota and Basidiomycota were the most abundant fungal phyla and resembled those originally in the peat and compost, respectively. These findings could be used to understand the importance and dynamics of specific microbial communities present in substrate components and how they develop during greenhouse production.

Soilless substrates consist of mixtures of several components, including peat, wood fiber, pine bark, coir, perlite, vermiculite, compost, sand, and other materials. Although much research has addressed the chemical and physical properties of soilless substrates (Altland et al. 2008, 2018; Kaudal et al. 2015; Lemaire, 1995), much less is known about microbial communities in these substrates. Regarding biological properties, compost is one of the most frequently studied substrate components, and it is thought to contain the most diverse microbial communities (Palaniveloo et al. 2020; Xu et al. 2022). Most research concerning the biological properties of soilless substrates has focused on individual or specific groups of pathogens or beneficial microorganisms at one time. For example, previous studies have addressed certain species of plant growth-promoting bacteria or fungi, such as mycorrhizal fungi (Parniske 2008). Bennett and Meek (2020) studied the influence of arbuscular mycorrhiza during plant reproduction in container media (perlite and coir 1:1) and found that arbuscular mycorrhiza was positively correlated with plant defense responses, plant root development, and nutrient uptake.

To date, very few studies have examined the complete microbiome of soilless substrates used for container-grown plants. In one study, Montagne et al. (2017) examined how bacterial and fungal communities vary with the type of substrate during biocontrol of Fusarium oxysporum and found that bacterial and fungal community richness was greater in coir and peatmoss than in wood fiber. This study indicated that substrate components and types influenced microbial communities in substrates. Other studies have shown that cultural management practices, such as fertilization (Grunert et al. 2019), and the environment of a particular facility (Foster et al. 2020) can also influence microbial communities during different stages of plant growth.

Nursery substrates used in the eastern United States primarily consist of pine bark amended with lesser amounts of sphagnum peat and other components. Pine bark is used because of its low cost, availability, and physical properties such as air space and container capacity (Owen et al. 2008). Sphagnum peat is used as an amendment to pine bark, primarily for its ability to improve the water-holding capacity (Puustjarvi and Robertson 1975). Amending nursery substrates with compost is a common practice (Ozores-Hampton 2021). However, one of the primary benefits of compost is its ability to suppress soil-borne plant pathogens (Hoitink and Kuter 1986), a property shared by most finished composts. When peat alone is used or compost is sterilized, media lack the ability to suppress disease (Pugliese et al. 2011). The suppressiveness is restored when unsterile (active) compost is added (De Corato et al. 2018), thus demonstrating the pivotal role of the microbial communities in compost-based potting mixed soils for plant disease suppression (De Corato 2020).

The use of soilless substrates in plant production continues to expand globally (Fields et al. 2021); however, information regarding the microbial communities active in these substrates, especially pine bark-based substrates, is scarce. Therefore, the objectives of this project were to determine the composition of microbial communities in a typical pine bark soilless substrate during the nursery crop production cycle, assess the impacts of the substitution of peat with compost and plant growth on microbial communities, and determine how substrate microbial communities change over time.

Materials and Methods

Container substrate components and mixes

The treatment design for the experiment was a 3 × 2 factorial, with three mix ratios of bark, peat, and compost, with one set planted and the other left unplanted. The three substrate components used to prepare the soilless mixes were pine bark from loblolly pine (Pinus taeda) hammer-milled to a particle size <12.5 mm (75% <4 mm) (Pacific Organics, Henderson, NC, USA), Canadian sphagnum peatmoss (Conrad Fafard, Agawam, Manitoba, Canada), and leaf compost made from leaves collected from The Ohio State University College of Food, Agricultural, and Environmental Sciences campus in Wooster, OH, USA, that was composted for 9 months in a windrow system. These three substrate components had pH values of 4.90, 3.61, and 7.81, respectively. Three soilless substrate mixes that consisted of 80:20:0, 80:10:10, and 80:0:20 volumetric ratios of pine bark:peatmoss:leaf compost, respectively, were prepared. All the substrate mixes were amended with 1.8 kg⋅m−3 pulverized dolomitic lime (National Lime & Stone Co., Carey, OH, USA) and 0.3 kg⋅m−3 of a micronutrient package (Micromax; The Scotts Co., Marysville, OH, USA). One set of the mixes was planted with a single tree seedling and another set was not planted.

Physical and chemical properties of soilless substrate mixes.

Before adding soilless substrate mixes to containers, a 4-L subsample of each was retained for analysis. To physically characterize the mixes, they were packed in 347-cm3 aluminum cores (7.6 cm tall × 7.6 cm internal diameter) according to the methods described by Fonteno and Bilderback (1993). Aluminum cores were attached to porometers (North Carolina State University Porometers™; Horticultural Substrates Laboratory, North Carolina State University, Raleigh, NC, USA) to determine the air space. Cores were weighed, oven-dried for 4 d at 110 °C, and reweighed to determine the water-holding capacity. Total porosity was calculated as the sum of air space and water-holding capacity. Four replicates of each mix were measured.

Extractable nutrients (NO3-N, P, K, Ca, Mg, B, Cu, Fe, Mn, and Zn), pH, and electrical conductivity (EC) of pine bark, peat, and compost were determined immediately before mixing. Each substrate mix was analyzed to determine water-extractable macronutrients and diethylenetriaminepentaacetic acid (DTPA) extractable micronutrients using the methods described by Warncke (1990). Briefly, ∼400 mL of each mix was placed into a glass jar and saturated with either distilled water or 5 mm DTPA for the macronutrient and micronutrient analyses, respectively. The media remained saturated for 24 h; thereafter, it was filtered (Q5 filter paper; Fisherbrand, Waltham, MA, USA) under vacuum conditions. Filtrate concentrations of macronutrients and micronutrients were determined by mixing 1 mL of a solution sample with 9 mL of 3.89% HNO3 in 18 MΩ⋅cm−1 water and analyzed using optical emission spectroscopy (iCAP 6300 Duo; Thermo Scientific, Waltham, MA, USA).

Plant growth and harvest

The three substrate mixes were added to 20-L nursery containers (Nursery Supplies, Chambersburg, PA, USA), and each container was top-dressed with 73 g of controlled-release fertilizer (Osmocote Plus 15N–3.9P–9.9K; The Scotts Miracle-Gro Co.). One set of the containers were planted with a single birch liner (Betula nigra ‘Cully’) with an average height of 43.5 cm, and another set was not planted. Six replicates of each treatment were arranged randomly. The containers were placed in a polyethylene-covered greenhouse with passive ventilation from April until July. Irrigation was applied twice per day, totaling 400 mL, through spray stakes (yellow, 11.4 L per h; Netafim, Fresno, CA, USA). All containers were weighed weekly to determine water loss, and irrigation was programmed to replace this volume of water to minimize leaching.

Plants were harvested after 4 months to measure the shoot dry weight and analyze foliar tissue. Harvesting consisted of removing approximately 0.5 L of substrate from each container, avoiding the substrate surface where fertilizer prills were located. An analysis of water-extractable macronutrients and DTPA-extractable micronutrients was conducted as previously described by Warncke (1990). The shoot dry weight was determined by removing the aboveground portion of the plant, oven drying it at 55 °C for 3 d, and weighing it. Thirty newly matured and fully expanded leaves were harvested from each plant for the foliar nutrient analysis (Mills and Jones, 1996). Leaves were rinsed with deionized water and then oven-dried at 55 °C for 3 d. Leaf samples were milled through a 0.5-mm screen (Tecator Cyclotec AB; Hogenas, Sweden). Foliar N was determined by measuring approximately 2.5 mg of dry tissue into tin capsules (Costech Analytical, Valencia, CA, USA) and then analyzing it (CHNS/O PerkinElmer 2400 Series II Analyzer; PerkinElmer, Waltham, MA, USA). Macronutrients and micronutrients (N, P, K, Ca, Mg, S, B, Cu, Fe, Mn, Mo, and Zn) were determined by inductively coupled plasma optical emission spectroscopy after digestion using nitric acid (15.8 N) in a programmable microwave (MARS 6; CEM Corp., Matthews, NC, USA).

Sampling substrates for DNA extraction

Approximately 100 g of substrate components (pine bark, peatmoss, and leaf compost) and the three initial substrate mixes (month 0) were collected and placed in Ziploc bags (S.C. Johnson & Son, Inc., Racine, WI, USA) and stored at −22 °C until DNA extraction.

Samples of the substrate container mixes were collected monthly for DNA extraction and chemical analysis. A soil sample probe with a 2-cm diameter was used to collect three subsamples at multiple depths (10–25 cm) from each container, combined, and stored in a Ziploc bag at −22 °C until analysis. The sample probe was rinsed using water and sterilized with 0.1% bleach solution; then, it was rinsed again between each sampling. DNA was extracted from 0.25 to 0.30 g of each sample using the Power Soil DNA Extraction Kit (MO BIO Laboratories, Carlsbad, CA, USA) in triplicate. The concentration and quality of DNA were determined by absorbance at 260 and 280 nm using a spectrophotometer (Nanodrop ND 1000; Thermo Scientific, Wilmington, DE, USA). Concentrations were adjusted to 5 ng⋅μL−1, and 25 μL of DNA was used for polymerase chain reaction (PCR) amplification.

High-throughput sequencing and bioinformatics analyses.

Two sequencing libraries were generated for each of 90 samples after PCR amplification with primers 515F and 806R, which target the V4-V5 region of the 16S rRNA gene, and primers internal transcribed spacer (ITS) 1 and ITS2, which target the ITS region (Gibson et al. 1996). The resulting libraries were sequenced to obtain 300-bp paired-end reads using a MiSeq sequencer (Illumina, San Diego, CA, USA) at the Molecular and Cellular Imaging Center at the Ohio State University.

Raw sequences were examined to determine the appropriate quality with FastQC (Andrews 2010), and primers and adapters were trimmed using cutadapt version 3.1 (Martin 2011). Trimmed reads were processed using R/Bioconductor package dada2 (Callahan et al. 2016) in R version 4.0.2 (R Core Team 2021). Briefly, this involved quality filtering and trimming, sequence error modeling, amplicon sequence variant inference (denoising), read pair merging, detection and removal of chimeric sequences, taxonomic assignment with the SILVA database (Quast et al. 2013) for 16S amplicons and with the UNITE database (Nilsson et al. 2018) for ITS amplicons, removal of nonbacterial sequences for the 16S data, and removal of samples with fewer than 1000 amplicon sequence variants. A total of 90 samples were analyzed. Those with less than 1000 reads were removed from the analysis because of poor amplification (five samples for bacteria and four for fungi). The R package phangorn (Schliep 2011) was used to infer a phylogenetic tree of all amplicon sequence variants.

Statistical analysis.

A principal coordinate analysis was conducted using amplicon sequence variant data and weighted UniFrac distances with the R/Bioconductor package phyloseq version 4.0.2 (McMurdie and Holmes 2013). Phyloseq was also used to compute the Shannon diversity index (SDI) (n = 3). To examine overall differences in microbiome composition between replicates, treatments, and over time, the adonis2 function from the R package vegan version 4.0.1 (Oksanen et al. 2013) was used to perform a permutation multivariate analysis of variance (PERMANOVA) with the weighted UniFrac distance between samples as the responding variable. A differential abundance analysis was performed using R/Bioconductor package DESeq version 4.0.1 (Love et al. 2014), with multiple testing correction using the Benjamini-Hochberg method and an adjusted P value threshold of 0.05.

Substrate physical and chemical properties and plant growth data were subjected to an analysis of variance, and the least significant difference was determined with Fisher’s protected least significant difference with a P value of 0.05. The statistical analyses for physical and chemical properties were performed with SAS (version 9.3; SAS Institute Inc., Cary, NC, USA).

Results

Physicochemical properties of the soilless substrate mixes

The physical properties of the three initial substrate mixes were moderately affected by the compost amendment (Table 1). The air space of the 10% and 20% compost amended blends were greater than the 0% compost treatment and similar to one another. However, with the 10% compost amendment treatment, the difference was significantly greater than that with the 0% compost (P = 0.054). The water-holding capacity of all three different substrate mixes were similar but decreased with the compost amendment (P = 0.148). Total porosity was highest in the 10% compost (P = 0.046). Bulk density increased (P < 0.001) from 0.16 to 0.18 g⋅cm−3 and was positively corelated with the amount of compost in the substrate mixes.

Table 1.

Physical properties of soilless substrate mixes composed of 80% pine bark plus 0%, 10%, or 20% compost and/or sphagnum peatmoss before fertilization and potting (n = 3).

Table 1.

The chemical properties of the three substrate mixes before planting also varied to a certain degree with the amount of compost (Table 2). The pH values increased slightly with increasing amounts of compost and ranged from 5.4 to 5.6 (Table 2). These pH differences were minor (P = 0.061), and all three substrate mixes were within an optimal pH range for growing media (5.2–6.3) (Bunt 1988). The EC values increased from 398 to 513 μS⋅cm−1, with increasing amounts of compost reflecting increases in the concentrations of water-extractable macronutrients in the compost amended substrates. The 0% and 10% compost mixes had an EC value less than 500 μS⋅cm−1, as recommended by Abad et al. (2001) before fertilization, whereas the 20% compost treatment had an EC of 513.3 μS⋅cm−1.

Table 2.

Chemical properties of soilless substrate mixes composed of 80% pine bark and 0%, 10%, or 20% compost and/or sphagnum peatmoss before fertilization and potting (n = 3).

Table 2.

The compost amendment had a strong effect on the concentrations of extractable macronutrients, especially P, K, and Ca (Table 2). Regarding DTPA-extractable micronutrients, concentrations of B decreased, Cu and Fe were unaffected, and Mn and Zn increased with increasing amounts of compost amendment. However, all extractable nutrient concentrations in the three initial unfertilized substrate mixes were classified as low relative to the recommended range for fertilized containerized plant substrates (Warncke 1990).

After 4 months, chemical properties of the three substrate mixes continued to be affected by the amount of compost in the substrate (Table 3). The final substrate pH remained greater with increasing amounts of compost amendment (P = 0.063) in both planted and unplanted treatments and were greater than that in the initial substrate mixes (Table 2). Substrate pH was greater (P < 0.001) in planted than unplanted treatments, in which pH decreased to low levels (<4.5). Substrate EC was also affected by the planting regime (P < 0.001), with EC values 1.5- to 2-times greater in unplanted treatments because of the lack of plant nutrient uptake in the unplanted treatments. The EC was only marginally affected by the compost amendment (P = 0.072).

Table 3.

Final (4 months) chemical properties of planted and unplanted soilless substrate mixes composed of 80% pine bark and 0%, 10%, or 20% compost and/or sphagnum peatmoss. Planted treatments were planted with a single birch (Betula nigra ‘Cully’) tree liner (n = 3).

Table 3.

Major nutrient concentrations increased in the unplanted treatments after 4 months. However, both macronutrient and micronutrient concentrations increased in both unplanted and planted treatments (except for Mg; P = 0.241) (Table 3) compared with the initial mixes (Table 2) because of nutrient release from controlled-release fertilizers. The compost amendment had no significant effect on nutrient concentrations after 4 months, except for Zn (P < 0.001).

Birch tree growth was vigorous in all planted treatments, and there were no significant differences in shoot dry biomass after 4 months (P = 0.163) (Table 4). However, trees grown in the 0% compost mix had significantly greater foliar nutrient concentrations (P < 0.001) than those grown in the compost-amended treatments, except for K, Cu, and Mn (Table 4). There were no significant differences in the water-holding capacity between the three substrates (Table 1); however, the water-holding capacity tended to increase with increasing levels of peat relative to compost. Greater water-holding capacity in 0% compost treatments might have resulted in a greater volume of nutrient solution retained in the substrate and available for plant uptake.

Table 4.

Final (4 months) shoot dry weight and foliar nutrient concentrations of birch (Betula nigra ‘Cully’) trees grown in 80% pine bark substrate amended with different proportions of compost and/or peatmoss grown in 20-L plastic nursery containers (n = 6).

Table 4.

Bacterial communities in the substrate components

Bacterial communities in the three substrate components had differing diversity and composition. The bacterial SDI were significantly different (P = 0.002) and greatest in the leaf compost and lowest in the peatmoss. The SDI values of the leaf compost, pine bark, and peatmoss were 6.8, 4.3, and 3.1, respectively.

The predominant bacterial phyla present in the leaf compost were Pseudomonadota (33.7%), Chloroflexi (15.5%), Actinomycetota (11.8%), Bacteroidota (8.6%), Acidobacteriota (7.2%), and Planctomycetes (6.6%) (Fig. 1A). Predominant families within the Pseudomonadota included Nitrosomonadaceae and Xanthobacteraceae (Table 5). The family A4b was most abundant within the phylum Chloroflexi (Table 5).

Fig. 1.
Fig. 1.

Average relative abundance of bacterial (A) and fungal (B) phyla detected in the three individual substrate components; leaf compost, peatmoss, and pine bark. Each bar represents an average across the samples (n = 3) for each substrate component.

Citation: HortScience 58, 11; 10.21273/HORTSCI17275-23

Table 5.

Predominant bacterial families found in planted pine bark media containing 0%, 10%, or 20% compost from planting to harvest (4 months). Values represent average percentages of all amplicon sequence variant (ASV) counts that were assigned to the focal family. Only families from the 10 most abundant phyla are shown. Others ASVs were grouped as “other” (bottom).

Table 5.

The predominant phyla in pine bark were Pseudomonadota (49.66%), Acidobacteriota (30.73%), Bacteroidota (7.63%), and Actinomycetota (5.08%) (Fig. 1A). Within Pseudomonadota, the Acetobacteraceae and Burkholderiaceae families were most abundant (Table 5). Within the Acidobacteriota, the family Acetobacteraceae was the most abundant, whereas the family Sphingobacteriaceae was the most abundant among Bacteroidota (Table 5).

The predominant phyla in peatmoss were Actinomycetota (82.46%), Acidobacteriota (8.49%), Pseudomonadota (4.20%), and Chloroflexi (4.21%) (Fig. 1A). Within the Actinomycetota phylum, Acidothermaceae was most abundant (55.60%) (Table 5).

Bacterial communities in soilless substrate mixes.

The microbial communities in the soilless substrate mixes had phyla similar to those found in the pine bark, peatmoss and leaf compost components, but at different relative abundances (month 0) (Fig. 2). The DESeq analysis revealed that the mix with no compost was significantly different from those amended with 10% or 20% compost (P < 0.001). In substrates with 0% compost, the three most abundant phyla were Pseudomonadota (44.30%), Acidobacteriota (24.40%), and Actinomycetota (24.10%) (Fig. 2). Within Pseudomonadota, the families Acetobacteraceae and Burkholderiaceae were the most abundant and similar to those families present in pine bark (Table 5). Among the Acidobacteriota, Acidobacteriaceae (24.4%) was the most abundant family. The predominant family among the phylum Actinomycetota was Acidothermaceae (22.90%) (Table 5).

Fig. 2.
Fig. 2.

Average relative abundance of bacterial phyla detected in pine bark substrates (80% volume:volume) amended with different proportions of peatmoss and/or compost (0%, 10%, or 20%, as indicated below the x-axis) at different time points (0, 1, 2, 3, and 4 months after potting, as indicated below the x-axis), and either left (A) unplanted or (B) planted with a single birch (Betula nigra ‘Cully’) liner. Each bar represents an average (n = 3) across the three samples in each treatment combination.

Citation: HortScience 58, 11; 10.21273/HORTSCI17275-23

The substrate mixes amended with 10% (SDI = 6.4) and 20% (SDI = 6.0) compost had similar bacterial community compositions and were significantly more diverse (P = 0.002) than mixes with no compost (SDI = 4.2) (month 0) (Fig. 2). Both composts amended substrate mix contained more than 12 different phyla similar to those found in compost alone. The two most abundant phyla, Pseudomonadota and Acidobacteriota, present in the mix were also the same as compost alone (Figs. 1A and 2). The phylum Chloroflexi and family A4b were only present in the compost and compost-amended mixes (Table 5). Similarly, among the Pseudomonadota, the family Nitrosomonadaceae was found in the compost and the two compost-amended mixes, but not in the peat, bark, or 0% compost treatment mix (Table 5).

Fungal communities in the substrate components

The SDIs of the fungal communities in leaf compost, pine bark, and peatmoss were 4.6, 2.2, and 0.7, respectively, and significantly different (P < 0.001). These values were all less than the SDI of the bacterial communities. Leaf compost contained the following four predominant phyla: Ascomycota (22.90%), Mortierellomycota (29.06%), Aphelidiomycota (6.81%), and Rozellomycota (1.76%) (Fig. 1B). Among the Ascomycota, the classes Dothideomycetes, Pezizomycetes, and Sordariomycetes were the most abundant (data not shown).

In the pine bark, the most abundant phyla were Basidiomycota (89.00%) and Ascomycota (3.00%) (Fig. 1B). Among Basidiomycota, the most abundant family was Cantharellales (Table 6).

Table 6.

Predominant fungal families found from planting to harvest at 4 months in planted pine bark media containing 0%, 10%, or 20% compost. Values represent average percentages of all amplicon sequence variant (ASV) counts that were assigned to the focal family. Only families from the 10 most abundant phyla are shown. Other ASVs were grouped as “other” (bottom).

Table 6.

In peatmoss, the phyla Ascomycota (98.01%) (Fig. 1B) predominated and included the classes Sordariomycetes (21.67%), Leotiomycetes (16.07%), Saccharomycetes (11.59%), and Eurotiomycetes (2.09%) (data not shown).

Fungal communities in soilless substrate mixes.

Fungal communities in the initial soilless substrate mixes with 0% (SDI = 2.9) and 20% (SDI=2.5) compost amendment were similar based on PERMANOVA analysis (P = 0.519) (Fig. 3). DNA from the peatmoss and pine bark mix (10% compost) amplified poorly and did not meet quality filtering during bioinformatic processing; therefore, it was not included in this analysis.

Fig. 3.
Fig. 3.

Average relative abundance of fungal phyla detected in pine bark substrates (80% volume:volume) amended with different proportions of peatmoss and/or compost (0%, 10%, or 20%, as indicated below the x-axis) at different time points (0, 1, 2, 3, and 4 months) after potting, as indicated below the x-axis, and either left (A) unplanted or (B) planted with a single birch (Betula nigra ‘Cully’) liner. Each bar represents an average (n = 3) across the three samples in each treatment combination.

Citation: HortScience 58, 11; 10.21273/HORTSCI17275-23

The initial 0% compost mix was composed primarily of two phyla, Basidiomycota and Ascomycota (Fig. 3). Within Basidiomycota, Cantharellales (26.96%) was the most abundant order (Table 6). Within Ascomycota, Helotiaceae (10.52%), Trichocomaceae (4.87%), and Hyloscyphaceae (2.85%) were the most predominant families (Table 6).

The initial 20% compost mix had a fungal community composition similar to the initial 0% compost mix, with the phyla Basidiomycota and Ascomycota being the most abundant. However, the 20% mix also contained Aphelidiomycota (10.37%). Again, order Cantharellales (31.10%) was the most abundant within the phylum Basidiomycota (Table 6).

Dynamics of microbial communities in soilless substrate mixes

Dynamics in bacterial communities.

The principal coordinate analysis showed that bacterial communities in the initial mix (month 0) and 0% compost treatment clustered separately from the 10% and 20% compost treatment (Fig. 4A). During month 1, the 0%, 10%, and 20% compost treatments clustered apart from each another, but the unplanted and planted treatments of the same compost amendment concentration clustered together. The initial and month 1 communities were distinct from those in the same treatments after 2, 3, and 4 months (Fig. 4A). The PERMANOVA analysis confirmed that the compost amendment and time (P < 0.001) both had significant effects on the composition of the bacterial communities, whereas planting had a less significant effect (P = 0.021). Both planted and unplanted treatments continued to cluster together after 4 months (Fig. 4A).

Fig. 4.
Fig. 4.

Principal coordinate analysis (PCoA) of bacterial (A) and fungal (B) communities in substrates based on the matrix of weighted UniFrac distances among samples. Colors correspond to 0, 1, 2, 3, and 4 months after being potted. Shapes correspond to the proportion of compost amendment rate (0%, 10%, or 20%). Transparency corresponds to whether the mix was left unplanted (transparent) or planted (opaque) with a single birch (Betula nigra ‘Cully’) liner (n = 3).

Citation: HortScience 58, 11; 10.21273/HORTSCI17275-23

After 1 month, the most abundant bacterial phyla in all treatments were Pseudomonadota, Bacteroidota, Actinomycetota, and Verrucomicrobiota (Fig. 2). In the 10% and 20% compost treatments, Chloroflexi were also found, with the family A4b predominating. This family was the same as that found in the compost component, suggesting that it originated from the leaf compost (Table 5). In the planted treatments with compost, ∼29 amplicon sequence variants of A4b family were found, and these were the same amplicon sequence variants present in the leaf compost component. Among unplanted treatments with compost, ∼35 amplicon sequence variants of A4b family were the same as those present in the leaf compost component (data not shown).

After 2 months, the relative abundance of Pseudomonadota was still greatest, with a relative abundance value similar to that after month 1 (P = 0.121). However, there was a noticeable decrease in the relative abundance of Bacteroidota from approximately 21% during month 1 to 12% during months 2, 3, and 4 (Fig. 2). This decrease was significant in samples containing 10% and 20% of compost (P < 0.001), but not in 0% compost (P = 0.097). Members of the phyla Acidobacteriota, Myxococcota, Chloroflexi, and Gemmatimonadota increased during the second month in all treatments (especially in 10% and 20% compost; P < 0.001) and remained at these levels through month 4 (Fig. 2). The principal coordinate analysis showed that bacterial communities continued to cluster based on the amount of compost they contained in both planted and unplanted treatments (Fig. 4A). However, bacterial communities became more similar to communities present after 3 and 4 months (Fig. 4A and B) in both unplanted and planted treatments.

Acidobacteriota, which had a high relative abundance in all the three initial mixes (Fig. 1A), declined after the first month (P < 0.001) but increased thereafter (Fig. 2). Myxococcota, represented primarily by the family Sandaracinaceae, increased after the second month and had greater abundance after 3 and 4 months in all treatments (Fig. 2). Myxococcota also originated in compost, which shared 15 of the same amplicon sequence variants with mix that contained 10% and 20% compost. The phylum Gemmatimonadota also increased after 2 months in substrate mixes containing 10% and 20% compost in both the planted and unplanted treatments (P < 0.001) (Fig. 2).

Over time, Pseudomonadota, Bacteroidota, Myxococcota, and Actinomycetota became the most abundant phyla in all three mixes. Verrucomicrobiota were more common in the 0% compost treatments than in the compost-amended mixes. Acidobacteriota was correlated with the amount of compost in both the planted and unplanted treatments (Fig. 2).

Dynamics of fungal communities.

The PERMANOVA results indicated that time (P < 0.001), compost amendment (P < 0.001), and time×compost (P < 0.001) were significant factors in the differences in fungal communities in the different treatments.

The principal coordinate analysis of fungal communities in unplanted treatments (Fig. 4B) showed clustering together in initial substrate mixes (month 0). The communities in the 10% and 20% compost mixes at 1 month clustered separately from communities at 2, 3, and 4 months, suggesting that compost affected fungal community composition over time. After 2 months, communities in the 10% and 20% compost treatments clustered closely together. There were no significant differences in the fungal communities in planted and unplanted treatments (P = 0.102). The 0% compost treatment separated from the compost-amended treatments, and this separation became greater with time. In both planted and unplanted treatments, fungal communities in samples with 0% compost after 4 months clustered away from those present after 1, 2, and 3 months, and they clustered closer to communities in compost-amended treatments (Fig. 4B). Communities in samples containing 10% and 20% compost clustered together.

After 1 month, the three most abundant fungal phyla remained Basidiomycota, Ascomycota, and Mortierellomycota in all treatments (Fig. 3). In the 0% compost unplanted treatments (Fig. 3A), the community consisted of Basidiomycota (41.88%), Ascomycota (50.99%), and Mortierellomycota (3.01%), whereas in the planted treatments (Fig. 3B), the community consisted of Basidiomycota (71.67%), Ascomycota (15.01%), and Mortierellomycota (3.51%). The phyla Chytridiomycota was also found in both the planted and unplanted 10% and 20% compost mixes (Fig. 3).

After 2 months, the phyla Aphelidiomycota became significantly more abundant in the 10% and 20% compost communities compared with the 0% compost mix (P < 0.001) (Fig. 3). At 10% compost, the Aphelidiomycota abundance was 48.95% in the unplanted and 42.64% in the planted treatments. The abundance of Aphelidiomycota decreased significantly in months 3 and 4 to 2.70% in the unplanted treatment (P < 0.001) and 5.95% in the planted treatment (P < 0.001) (Fig. 3).

Discussion

Microbial communities in soilless substrates are important mediators of disease and nutrient availability. During this study, the results indicated that the greatest impacts on microbial communities in container substrates were the initial components and substrate age. Most of the changes in the microbial communities occurred during the first or second month. The communities present after this period resembled those initially present in compost and were very different from those present originally in peat or bark. The planting had very little impact on the structure of the microbial communities that developed in the three substrate container mixes.

The addition of compost (10% or 20%) to substrate container mixes affected physical properties, including air space, total porosity, and BD (Table 1). Gabriel et al. (2009) found that adding peatmoss to Douglas fir [Pseudotsuga menziesii Mirb. (Franco)] bark-based mixes resulted in lower air space and greater water-holding capacity compared with bark alone. These physical properties differences have been shown (Xu et al. 2018) to affect microbial community composition. In this study, the physical properties of the mixes were very similar and unlikely to have had a strong impact on the microbial community composition.

Some chemical properties of the three mixes, such as EC, and nutrients, such as P, K, and Ca, were significantly affected by the compost amendment (Table 2). These properties, in turn, are likely to affect nutrient availability as well as the nutritional and metabolic activities of microbial communities (Ferrarezi et al. 2022). The EC (salinity) can also affect the microbial composition (Mukhtar et al. 2018). In this study, different microbial communities were found in substrate mixes with different chemical properties. Substrate mixes were strongly affected by the compost addition, with an increase in the nutrient concentrations of P, K, Ca, Mn, and Zn. Conversely, the B concentration decreased with the addition of compost (Table 2). The compost amendment also affected the pH of the substrate mixes. Substrates with 20% compost had a greater pH value throughout the experiment than those with 10% or no compost (Table 3). This difference is not surprising because of the greater pH of the compost compared with that of sphagnum peatmoss. Composts typically have a pH of 7 to 8 (Michel et al. 1996), whereas sphagnum peatmoss typically has a pH of <5.0 (Evans et al. 2011). Microbial communities that were tolerant of these pH and nutrient differences included bacteria in the phyla Pseudomonadota, Bacteroidota, Actinobacteriota, and Planctomycetota (Fig. 2), and fungi in the phyla Ascomycota and Basidiomycota (Fig. 3). These phyla were the most abundant in all the mixes over months 1 to 4.

Microbial taxa in the planted containers may have been affected by pH and the lower NO3-N, P, and K levels in these treatments. Root exudates from plants, including sugars, amino acids, and organic acids, may influence the microbiome in the rhizosheath (Canarini et al. 2019). However, a full understanding of the root exudate effects requires several factors that have to be considered, such as plant species, collection method (Williams et al. 2021), growth state (young or mature), and environmental conditions (Grunert et al. 2019; Li et al. 2022). A more complete understanding of root exudates and their effects on the rhizosheath was not within the scope of this work. Microorganisms that increased in abundance because of planting were Myxococcota, Gemmatimonadota, Chloroflexi, and Verrucomicrobiota (Fig. 2). Myxococcota are aerobic bacteria that inhabit soil (Murphy et al. 2021). Fungi were relatively unaffected by planting and its effect on nutrient concentrations, especially Aphelidiomycota and Chytridiomycota (Fig. 3).

Each of the initial substrate components provided different sets of families of microorganisms with presumably different functional roles in the substrate ecosystem. The leaf compost and compost-amended mixes had greater concentrations of Xanthobacteraceae, which has been associated with disease suppression (Grunert et al. 2016; Mendes et al. 2011). Nitrosomonadaceae was only found in leaf compost and the compost-amended mixes. This group is characterized by its influence on nitrification and the ability to oxidize ammonia to nitrite (Prosser et al. 2014). Prosser et al. (2014) indicated that this family includes ammonia oxidizers and is an important group active in the nitrogen cycle that has significant environmental and economic impacts. Another phylum that was identified primarily in the compost and compost mixes was Chloroflexi, represented by the Class Anaerolineae. This group is largely unculturable, but it has been observed in many different types of composts as well as in anaerobic digestate (Liu et al. 2023); however, its role is not well-understood.

The family Acidobacteriaceae of the phylum Acidobacteriota was most abundant in pine bark (Table 5). In another study (Montagne et al. 2017), Acidobacteriaceae was also found in peat substrates. Acidobacteriaceae are mesophilic microorganisms that grow optimally at low and near-neutral pH values and can degrade structural carbohydrates, including cellulose and chitin Huber et al. (2017). In the 20% compost mix that had no peat, these organisms were less abundant. The reduction of Acidobacteriaceae may be caused by competition from other dominant microorganisms in compost, reducing its abundance. In pine bark, Sphingobacteriaceae was among the most abundant families. In a previous study, Khan et al. (2014) showed that members of this family are beneficial to plant growth and improve shoot weight. Sphingobacteriaceae was found in mixes of 0% or 10% compost over the course of the first 3 months (Table 5).

Pseudomonadota was the most abundant phylum in the initial mixes (month 0) and remained abundant over time, independent of the compost amendment or planting. The families Burkholderiaceae and Acetobacteraceae were found in all three mixes as well as pine bark (Table 5). Other research has shown that the phyla Pseudomonadota, as well as Actinomycetota, are the most abundant families in pine wood fiber (Montagne et al. 2017). Actinomycetota was the fourth most abundant phylum in this study. Actinomycetota have been identified as having beneficial plant disease-suppressive properties. Among the Pseudomonadota, Mendes et al. (2011) identified members of the Pseudomonadaceae, Burkholderiaceae, and Xanthomonadales as taxa associated with disease suppression against Rhizoctonia solani. Pseudomonadota has also been associated with the suppression of Fusarium oxysporum and Gaeumannomyces. Both Burkholderiaceae (20.5%) and Pseudomonadaceae (6.7%) (Table 5) from this phylum were found in all three treatments in this study and likely originated in the pine bark (Tunlid et al. 1989).

Ascomycota and Basidiomycota were the most abundant fungal phyla and were found in all treatments (Fig. 3). Both have many members able to decompose cellulose and lignin (De Boer et al. 2005). Montagne et al. (2017) found that the class Sordariomycetes was abundant in coir, whereas Eurotiomycetes was most abundant in wood fiber. Both classes were also found in this study.

Initially, in the two substrate mixes with compost, the bacterial communities were distinct from those in the mix without compost (Fig. 4A). The more active and diverse communities in the compost had the strongest influence on the microbial communities in the initial mixes and month 1 samples.

The fungal communities in initial substrate mixes (month 0) were similar to the communities found in the pine bark and peatmoss mix without compost (Fig. 4B). After 1 month, both compost-amended mixes clustered separately from other treatments. The bark and peat mix without compost clustered separately from the compost-containing mixes for the entire 4 months of the experiment (Fig. 4B). After 4 months, differences in chemical properties caused by planting were pronounced (Table 3). The substrate mixes in planted treatments had a greater pH and much lower NO3-N, P, and K compared with unplanted treatments. This difference was likely caused by the uptake of nutrients by the plants. The EC was also lower in the planted treatments, likely for a similar reason.

This may explain why microbial communities clustered more closely after 4 months. It is possible that after 3 or 4 months of placement in a nursery setting, microbial communities converge to a similar composition because of similarities in environmental conditions such as temperature, irrigation water quality, and other factors, which exert a greater influence on the microbial populations than the initial substrate components. Similar to our findings, Grunert et al. (2019) indicated that in climate chambers under controlled conditions, microbial communities evolve to a stable composition after 34 d, with decreased variation in relative abundances over time.

Conclusion

The objectives of this study were to determine the composition of microbial communities in a typical pine bark soilless substrate and the impacts of planting and compost and/or peat amendments on these communities over a typical 4-month production cycle. The microbial communities in the soilless substrates changed over time and differed based on the amount of compost they contained. The main substrate components of the substrate mixes, leaf compost, peatmoss, and pine bark, each had unique microbial communities and levels of diversity. The communities inherent in the initial components affected the overall diversity and community makeup early during the production cycle (0–2 months). Bacteria including Pseudomonadota (Nitrosomonadaceae family) and Bacteroidota were stable over time and could be traced directly to amplicon sequence variants found initially in compost. Over time, the community composition in the different substrate mixes became more similar and resembled that originally present in the compost.

To highlight the impacts of a living root system, media in both planted and unplanted containers were examined. Planting caused significant differences in pH, EC, and nutrients such as NO3-N, P, and K. However, it surprisingly had less impact on microbial communities than compost amendment or time. These findings could be used as a reference for the community present in substrates that are commonly used in greenhouse production. Including 10% compost hastened the development of a microbiome resembling those that eventually developed in all three treatments.

Future opportunities for this type of research include using omics technology to identify microbiome taxonomy in soilless substrates and understand the dynamics of microbial communities that may harm or benefit crops. Plant growth-promoting organisms and communities could also be identified and cataloged. Further studies of the function and availability of these microbial communities are necessary to understand the roles they have and how they can be manipulated to improve plant health.

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  • Fig. 1.

    Average relative abundance of bacterial (A) and fungal (B) phyla detected in the three individual substrate components; leaf compost, peatmoss, and pine bark. Each bar represents an average across the samples (n = 3) for each substrate component.

  • Fig. 2.

    Average relative abundance of bacterial phyla detected in pine bark substrates (80% volume:volume) amended with different proportions of peatmoss and/or compost (0%, 10%, or 20%, as indicated below the x-axis) at different time points (0, 1, 2, 3, and 4 months after potting, as indicated below the x-axis), and either left (A) unplanted or (B) planted with a single birch (Betula nigra ‘Cully’) liner. Each bar represents an average (n = 3) across the three samples in each treatment combination.

  • Fig. 3.

    Average relative abundance of fungal phyla detected in pine bark substrates (80% volume:volume) amended with different proportions of peatmoss and/or compost (0%, 10%, or 20%, as indicated below the x-axis) at different time points (0, 1, 2, 3, and 4 months) after potting, as indicated below the x-axis, and either left (A) unplanted or (B) planted with a single birch (Betula nigra ‘Cully’) liner. Each bar represents an average (n = 3) across the three samples in each treatment combination.

  • Fig. 4.

    Principal coordinate analysis (PCoA) of bacterial (A) and fungal (B) communities in substrates based on the matrix of weighted UniFrac distances among samples. Colors correspond to 0, 1, 2, 3, and 4 months after being potted. Shapes correspond to the proportion of compost amendment rate (0%, 10%, or 20%). Transparency corresponds to whether the mix was left unplanted (transparent) or planted (opaque) with a single birch (Betula nigra ‘Cully’) liner (n = 3).

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Silvia Valles-Ramirez Department of Food, Agricultural and Biological Engineering, The Ohio State University, 1680 Madison Avenue, Wooster, OH 44691, USA

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James E. Altland United States Department of Agriculture-Agricultural Research Service Application Technology Research Unit, 1680 Madison Avenue, Wooster, OH 44691, USA

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Anna L. Testen United States Department of Agriculture-Agricultural Research Service Application Technology Research Unit, 1680 Madison Avenue, Wooster, OH 44691, USA

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Jelmer W. Poelstra Molecular and Cellular Imaging Center, The Ohio State University, 1680 Madison Avenue, Wooster, OH 44691, USA

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Frederick C. Michel Jr. Department of Food, Agricultural and Biological Engineering, The Ohio State University, 1680 Madison Avenue, Wooster, OH 44691, USA

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Contributor Notes

F.C.M. is the corresponding author. E-mail: Michel.36@osu.edu.

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  • Fig. 1.

    Average relative abundance of bacterial (A) and fungal (B) phyla detected in the three individual substrate components; leaf compost, peatmoss, and pine bark. Each bar represents an average across the samples (n = 3) for each substrate component.

  • Fig. 2.

    Average relative abundance of bacterial phyla detected in pine bark substrates (80% volume:volume) amended with different proportions of peatmoss and/or compost (0%, 10%, or 20%, as indicated below the x-axis) at different time points (0, 1, 2, 3, and 4 months after potting, as indicated below the x-axis), and either left (A) unplanted or (B) planted with a single birch (Betula nigra ‘Cully’) liner. Each bar represents an average (n = 3) across the three samples in each treatment combination.

  • Fig. 3.

    Average relative abundance of fungal phyla detected in pine bark substrates (80% volume:volume) amended with different proportions of peatmoss and/or compost (0%, 10%, or 20%, as indicated below the x-axis) at different time points (0, 1, 2, 3, and 4 months) after potting, as indicated below the x-axis, and either left (A) unplanted or (B) planted with a single birch (Betula nigra ‘Cully’) liner. Each bar represents an average (n = 3) across the three samples in each treatment combination.

  • Fig. 4.

    Principal coordinate analysis (PCoA) of bacterial (A) and fungal (B) communities in substrates based on the matrix of weighted UniFrac distances among samples. Colors correspond to 0, 1, 2, 3, and 4 months after being potted. Shapes correspond to the proportion of compost amendment rate (0%, 10%, or 20%). Transparency corresponds to whether the mix was left unplanted (transparent) or planted (opaque) with a single birch (Betula nigra ‘Cully’) liner (n = 3).

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