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Article

Effects of Different Substrate Ratios on Bacterial Community Structure and Diversity in the Rhizosphere of the Tomato

by
Hengbin Luo
1,
Xiaojing Ma
1,
Haohao Ma
1,
Hongdan Fu
2,
Han Dong
1,
Zhixin Guo
1,
Xiaoxing Dong
1,
Fengzhi Piao
1,
Shunshan Shen
3,
Xinzheng Li
4,
Yong Wang
1,* and
Tao Zhang
1,*
1
College of Horticulture, Henan Agricultural University, Zhengzhou 450046, China
2
College of Horticulture, Shenyang Agricultural University, Shenyang 110866, China
3
College of Plant Protection, Henan Agricultural University, Zhengzhou 450046, China
4
College of Horticulture and Landscape, Henan Institute of Science and Technology, Xinxiang 453003, China
*
Authors to whom correspondence should be addressed.
Horticulturae 2026, 12(4), 427; https://doi.org/10.3390/horticulturae12040427
Submission received: 30 January 2026 / Revised: 14 March 2026 / Accepted: 24 March 2026 / Published: 1 April 2026
(This article belongs to the Special Issue Vegetable Crops: Cultivation, Nutritional Value and Bioactive Components)
Browse Figures
Versions Notes

Abstract

Although peanut shells represent an abundant agricultural waste, their high-value utilization potential as a horticultural substrate has not been fully recognized. Meanwhile, horticultural crops such as tomatoes are in urgent demand for high-quality and innovative cultivation substrates. This study investigated the effects of different ratios of peanut shell–substrate on tomato yield and rhizosphere bacterial community structure, aiming to provide a theoretical basis for the utilization of agricultural waste and the development of novel growth substrates for tomato cultivation. Results showed that peanut shell–substrate improved tomato yield and quality, and enhanced soil urease, sucrase, and catalase activities. High-throughput 16S rRNA gene sequencing revealed significant differences in rhizosphere bacterial alpha diversity between peanut shell substrates and the control. Proteobacteria, Acidobacteria, and Actinobacteriota were the dominant phyla, while unclassified genera, Devosia A_501803 and Bauldia, were identified as the core genera at the genus level. In conclusion, peanut shell substrates enriched dominant functional bacterial genera and enhanced the ecological functions of the substrate.

1. Introduction

Tomato (Solanum lycopersicum), a major protected–cultivated vegetable in China, belongs to the genus Solanum in the Solanaceae family. It has high edible value and large market demand, and is widely cultivated throughout China [1,2]. To achieve year-round tomato production and seasonal supply, current tomato production primarily relies on solar greenhouses and plastic greenhouses. Due to the large area of tomato-protected cultivation in China and severe continuous cropping, problems such as soil compaction and salinization frequently occur. The soil microbial community is disturbed, and the abundance of dominant microbial taxa gradually decreases, exerting a series of negative effects on tomato yield and quality [3,4]. Cultivation substrates can effectively alleviate soil problems caused by long-term continuous cropping, thereby improving crop yield and quality to a certain extent and optimizing the growing environment. As such, they represent a newly developed model for protected horticulture in recent years [5,6].
Rhizospheric microbes play a crucial role in promoting plant growth, enhancing stress resistance, improving soil structure, and mediating soil nutrient cycling and metabolic processes [7,8,9,10]. Plant Rhizopheric microbes are abundant and diverse, and are often used as key indicators to evaluate the health of rhizosphere soil and the stability of the ecological environment [11]. For instance, many dominant bacterial groups in the rhizosphere possess strong capabilities for nitrogen fixation, phosphorus and potassium solubilization, and the production of plant growth-promoting hormones (e.g., auxins), thereby supplying plants with bioavailable nitrogen, phosphorus, potassium, and other essential nutrients [12]. It has been reported that microbial abundance in the rhizosphere can be several to dozens of times higher than that in bulk soil [13]. However, some studies have also indicated that bacterial abundance may be higher in bulk soil than in the rhizosphere [14]. Rhizosphere soil microbial communities are mainly dominated by copiotrophic bacteria, such as Proteobacteria, Firmicutes, and Actinobacteria, which facilitate the uptake of phosphorus, potassium, and other essential nutrients by plant roots [15]. Notably, most rhizosphere microorganisms are not plant growth-promoting; the community comprises beneficial, neutral, and pathogenic taxa, with functions of the majority remaining uncharacterized [16].
Henan Province, renowned as a major peanut-producing region in China, accounts for 33% of the country’s total peanut output and produces over 1.6 million tons of peanut shells annually [17,18]. Peanut shells are predominantly rich in cellulose, vitamins, flavonoids, and essential minerals [19]. To date, there has been a dearth of research investigating the feasibility of using peanut shell compound substrates as growing media. Studies have demonstrated that incorporating peanut shell compost into cultivation substrates can significantly reduce the usage of coconut coir, thereby boosting crop yields [20]. Peanut shell compost also serves as an excellent substrate for rooftop ornamental horticulture [21]. Numerous studies have confirmed that fruit and vegetable processing residues can be converted into high-quality cultivation substrates via appropriate processing [22,23]. At present, common raw materials for mixed substrate preparation include spent mushroom substrate, coconut coir, sawdust, peanut shells and so on. These materials are inexpensive and optimized formulations for different crops can be obtained by adjusting the types and mixing ratios of these materials [20,22,24].
Previous studies have mainly focused on crop cultivation using peanut shell-based mixed substrates. However, few studies have investigated the effects of different mixing ratios of peanut shell-based materials and commercial substrates on the rhizosphere microbial environment of tomato (Solanum lycopersicum). To fill this research gap, the present study proposes two testable hypotheses: (1) compared with the sole commercial substrate (T1), different mixing proportions of peanut shell-based materials and commercial substrates significantly alter the diversity, composition, and relative abundance of the tomato rhizosphere bacterial community; (2) there exists an optimal mixing ratio that facilitates the enrichment of beneficial bacterial taxa involved in nutrient cycling and plant growth promotion, thereby enhancing the stability of the rhizosphere bacterial community.
Based on these hypotheses, high-throughput sequencing was used to compare the effects of different mixing ratios on the tomato rhizosphere bacterial community. This study provides a theoretical and practical reference for the application of a novel cultivation model using peanut shell–commercial substrate mixtures.

2. Materials and Methods

2.1. Experiment Design and Sampling

The experimental site was located at the plastic arched greenhouse of the College of Horticulture, Science and Education Park, Huiji District, Zhengzhou City, Henan Province, China (34°53′ N, 113°33′ E). The tomato variety used in this study “was” Chunwang 17. Test substrates included peanut shells and a commercial substrate mainly composed of peat, vermiculite, and perlite. The experiment employed a single-factor randomized block design, with five cultivation modes established as treatments, each with three replications. Each treatment was as follows: (1) CK treatment, field soil cultivation; (2) T1 treatment, commercial substrate; (3) T2 treatment, decomposed peanut shells; (4) T3 treatment, compound substrate (peanut shells: commercial substrate = 1:1); and (5) T4 treatment, compound substrate (peanut shells: commercial substrate = 3:1). Each treatment included 90 tomato plants, with a plant spacing of 17 cm, a row spacing of 1.5 m, and 0.5 m wide operation lanes. Seedlings were raised in mid-February, transplanted in late March, and the tomato harvest period started in late May. Tomatoes were harvested in batches by treatment plot, and conventional weighing methods were employed to determine and record tomato yield. Tomato seedlings at the 3–4 true-leaf stage were transplanted into the prepared mixed substrates. All treatments were grown in a greenhouse under uniform environmental conditions. Drip irrigation was applied to maintain suitable substrate moisture, and regular fertilization was performed using water-soluble fertilizer. Plants were subjected to single-stem pruning, with all lateral shoots removed in a timely manner. Four fruit trusses were retained per plant, and the apex was excised after fruit setting of the fourth truss. Green integrated management was adopted for pest and disease control.

2.2. Analysis of Soil Physical and Chemical Properties

Soil physical properties were determined using Guo Shi Rong’s method [25]. Soil pH and EC were measured using a pH Meter (PHB-4; Shanghai Yike, Shanghai, China) and an EC Meter (DDB-303A; Shanghai Yike, Shanghai, China), respectively, with a soil-to-water ratio of 1:5 (w/v). A container of known volume (V) was weighed first (W1), then filled with the air-dried substrate for analysis and reweighed (W2). The opening of the container was sealed with gauze, whose mass was negligible. Subsequently, the substrate-filled container was fully immersed in water for 24 h, removed, and weighed (W3). After removal, the container was inverted to drain gravitational water, followed by a final weighing (W4). Finally, the bulk density, total porosity, and water-holding capacity of the substrate were calculated based on the above weight data. Bulk density (g·cm−3) = (W2 − W1)/V; total porosity = [(W3 − W2)/V] × 100%; air-filled porosity = [(W3 − W4)/V] × 100%; water-holding porosity = [(W4 − W2)/V] × 100%.
Soil chemical properties were determined following the method described by Bao Shidan [26]. Soil organic matter content was measured via the potassium dichromate oxidation method. Total nitrogen (TN), phosphorus (TP), and potassium (TK) were determined using the Kjeldahl method, molybdenum–antimony colorimetric method, and flame spectrophotometric method, respectively. Alkaline-hydrolyzable nitrogen (AN), available phosphorus (AP), and available potassium (AK) were determined via the alkaline hydrolysis–diffusion method, molybdenum–antimony anti-spectrophotometric method, and flame photometric method, respectively.

2.3. Determination of Tomato Yield and Quality

Tomato fruits were harvested in batches per plot throughout the entire harvest period, and yields were recorded. Yield data recording ceased after harvesting the fourth fruit cluster, following which the yield per plant was calculated. The nutritional quality of tomato fruits is primarily determined by soluble sugars, soluble proteins, soluble solid content, and ascorbic acid (VC). The anthrone colorimetric method, Coomassie Brilliant Blue G-250 staining method, a handheld refractometer (WZB, Shanghai Yidian, Shanghai, China), and the 2,6-dichlorophenolindophenol titration method were employed respectively to determine these indices [27].

2.4. Determination of Key Soil Enzymes Activities

During the peak fruiting period (when tomato plants bear four trusses of fruits), 0.03 g of rhizosphere soil was collected for enzyme activity assays. Enzyme activities were determined using three detection kits: total catalase (S-CAT, item No. BC0095, batch No. YX-W-B937, Suzhou, China), urease (S-UE, item No. YX-W-B933, Suzhou, China), and soil sucrase (S-SC, item No. YX-W-B939, Suzhou, China).

2.5. Sample Collection

In late June 2024, when the tomato plants reached the peak fruiting stage, rhizosphere substrate samples were collected from plants grown under different mixing ratios. For each treatment, 10 plants with uniform growth vigor were selected, and rhizosphere substrate samples were collected using the root-shaking method. Before sampling, scissors, gloves, and spatulas were disinfected with 75% ethanol to prevent sample contamination. The roots of the selected plants were carefully dug out with a sterile spatula, and the loosely adhering substrate was gently shaken off. The substrate tightly attached to the root surface (defined as rhizosphere substrate) was collected, placed into sterile sampling bags, immediately frozen in liquid nitrogen, and transported to the laboratory for long-term storage at −80 °C.

2.6. DNA Extraction and PCR Amplification

Total genome DNA from samples was extracted using CTAB method [28]. DNA concentration and purity was monitored on 1% agarose gels. According to the concentration, DNA was diluted to 1 ng/µL using sterile water. Distinct regions of 16S rNA genes (16S V4 + V5) were amplified using specific primer 16S-515F (5′-GTGCCAGCMGCCGCGGTAA-3) and 16S-907R (5′-CCGTCAATTCCTTTGAGTTT-3′) with the barcode. All PCR reactions were carried out with 15 µL of Phusion® High-Fidelity PCR Master Mix (New England Biolabs, Ipswich, MA, USA); 2 µM of forward and reverse primers; and about 10 ng template DNA. Thermal cycling consisted of initial denaturation at 98 °C for 1 min, followed by 30 cycles of denaturation at 98 °C for 10 s, annealing at 50 °C for 30 s, elongation at 72 °C for 30 s and finally, 72 °C for 5 min. The same volume of 1XTAE buffer was mixed with PCR products and electrophoresis was operated on 2% agarose gel for detection. PCR products were mixed in equidensity ratios. Then, the mixture of PCR products was purified with Universal DNA (TianGen, Beijing, China).
Sequencing libraries were generated using NEB Next® Ultra DNA Library Prep Kit (Illumina, San Diego, CA, USA) following manufacturer’s recommendations and index codes were added. The library quality was assessed on the Agilent 5400 (Agilent Technologies Co Ltd., Santa Clara, CA, USA). At last, the library was sequenced on an Illumina platform (version novaseq 6000) and 250 bp paired-end reads were generated.

2.7. Bioinformatics Analysis

The analysis was conducted by following the “Atacama soil microbiome tutorial” of QIIME 2 documentation along with customized program scripts (https://amplicon-docs.qiime2.org/en/stable/tutorials/moving-pictures.html (accessed on 18 October 2024). Briefly, raw FASTQ data files were imported into the QIIME 2 artifact format using the qiime tools import command. Demultiplexed sequences from each sample were quality filtered and trimmed, denoised, merged, and then chimeric sequences were identified and removed using the QIIME 2 DADA2 plugin to obtain the feature table of amplicon sequence variants (ASVs) [29]. The QIIME 2 feature-classifier plugin was then used to align ASVs to a pre-trained SILVA 138.2 (99%) database (trimmed to the V4–V5 region bound by the 515F/907R primer pair) to generate the taxonomy table [30]. Any contaminating mitochondrial and chloroplast sequences were filtered using the QIIME 2 feature-table plugin. Appropriate methods such as ANCOM, ANOVA, Kruskal–Wallis, LEfSe and DEseq2 were employed to identify the bacteria with different abundance among samples and groups [31,32,33]. Diversity metrics were calculated using the core-diversity plugin within QIIME2. Feature-level alpha diversity indices, such as observed OTUs, Chao1 richness estimator, Shannon diversity index, and Faith’s phylogenetics diversity index, were calculated to estimate the microbial diversity within an individual sample. Beta diversity distance measurements, including Bray–Curtis, unweighted UniFrac, and weighted UniFrac were performed to investigate the structural variation in microbial communities across samples and then visualized via principal coordinate analysis (PCoA) and nonmetric multidimensional scaling (NMDS) [34]. Partial least squares discriminant analysis (PLS-DA) was also introduced as a supervised model to reveal microbiota variation among groups, using the “plsda” function in R package “mixOmics” (version 1.18.8) [35]. Redundancy analysis (RDA) was performed to reveal the association of microbial communities in relation to environmental factors based on relative abundances of microbial species at different taxa levels using the R package “vegan” [36]. Co-occurrence analysis was performed by calculating Spearman’s rank correlations between predominant taxa and the network plot was used to display the associations among taxa. In addition, the potential KEGG Ortholog (KO) functional profile of microbial communities was predicted with PICRUSt [37]. Unless specified above, parameters used in the analysis were set as default.

2.8. Microbial Functional Prediction

Microbial functional prediction was performed using PICRUSt2 v2.3.0 software based on 16S rRNA gene ASV sequences. The predicted results were annotated to the MetaCyc database and KEGG database, respectively, to obtain functional composition profiles at the pathway level [38].

2.9. Statistical Analyses

Statistical analyses were performed using Statistics Package for Social Science (SPSS) version 19.0 [39]. Differences between treatments were evaluated using either Tukey’s test, with significance determined at p < 0.05, as indicated in the figure legends [40].

3. Results

3.1. Physical Properties of Substrates with Different Mixing Ratios

As presented in Table 1, significant differences in pH values were observed among the different treatments. The suitable pH range for tomato cultivation is 5.5–7.0 [41], and the pH values of all treatments fell within the range of 5.81–7.14. The conductivity values across all treatments ranged from 0.8 to 1.83 mS·cm−1. Significant differences in bulk density were observed among all treatments. Specifically, the CK treatment exhibited the highest bulk density at 1.12 g·cm−3, whereas the T4 treatment showed the lowest value at 0.15 g·cm−3. Substrate bulk density was significantly affected by the peanut shell ratio, as evident from the comparison between T3 and T4. As the proportion of peanut shells in the substrate increased, the bulk density progressively decreased. The total porosity of all treatments exceeded 50%, with T2 treatment exhibiting the highest value at 73.29% and CK treatment showing the lowest at 51.51%. The ventilation porosity of each treatment exhibits distinct differences. Notably, the T4 treatment exhibits the largest ventilation porosity, accounting for 32.11%, whereas the T1 treatment shows the smallest value of 2.64%. The water-holding porosity of all treatments ranges from 39.33% to 66.55%. Specifically, for the T3 and T4 treatments, with the increase in peanut shell dosage and the decrease in substrate dosage, the water-holding porosity gradually decreases.

3.2. Chemical Properties of Substrates Under Different Mixing Ratios

As shown in Table 2, the incorporation of peanut shells into the substrate exerts varying degrees of influence on the substrate’s nutrient contents. Regarding the content of AK, the CK exhibited the lowest value at a mere 0.47 g·kg−1, whereas the T1 treatment showed the highest content, reaching 1.95 g·kg−1. Available phosphorus (AP) contents in all T1–T4 treatments were higher than those in the CK treatment, with the lowest value (0.22 g·kg−1) observed in the T2 treatment. Among these treatments, the T2 treatment exhibited the lowest AP content, at 0.22 g·kg−1. Regarding available phosphorus (AP) content, all substrate treatments (T1–T4) were significantly higher than the CK treatment. The T2 treatment showed the lowest AP content (0.22 g·kg−1), while significant differences were observed among treatments, with the highest value recorded in the T4 treatment (3.85 g kg−1). Analysis of total nitrogen (TN) content showed that TN content in T1–T4 treatments was significantly higher than that in the CK treatment. Among these, the T2 treatment exhibited the highest TN content (10.53 g·kg−1), followed by T3 (6.26 g·kg−1) and T4 (6.01 g·kg−1). TP content exhibited significant differences among various treatments, with the T1 treatment showing the highest content (1.73 g·kg−1) and the T4 treatment the lowest (0.79 g·kg−1). Regarding TK content, the content in T1–T4 treatments was higher than that in the CK treatment. Among these, the T3 treatment (66.89 g·kg−1) and T4 treatment (66.28 g·kg−1) exhibited the highest content. Regarding SOM content, the content in T1–T4 treatments was significantly higher than that in the CK treatment. Among these, the T1 treatment exhibited the highest content (455.74 g·kg−1), followed by the T4 treatment (430.74 g·kg−1) and the T2 treatment (408.19 g·kg−1).

3.3. Analysis of Tomato Yield and Quality as Affected by Different Substrate Compositions

Tomato yield varied among different substrate ratios (Table 3). The T1 treatment achieved the highest yield per plant (3.46 kg), followed by the T4 (3.42 kg) and T3 (2.92 kg) treatments. The CK treatment had the lowest single-plant yield (1.85 kg). The total yields of T1–T4 treatments were significantly higher than that of the CK treatment. Among these, the T1 and T4 treatments showed the highest yields per mu, at 9227.82 and 9130.03 kg·667 m−2, respectively, followed by the T3 treatment (7787.64 kg·667 m−2). The yields per mu of all treatments were ranked in descending order as follows: T1 > T4 > T3 > T2 > CK.
Different substrate ratios exerted varying effects on tomato fruit quality (Table 4). Vitamin C content in fruits from the T3 and T4 treatments was significantly higher than that in the CK group. Among these, the T4 treatment exhibited the highest vitamin C content (10.52 mg·100 g−1). No significant difference in vitamin C content was observed between the T1 and T2 treatments, with the T2 treatment having the lowest content (3.97 mg·100 g−1). No significant difference in soluble protein content was observed between the T1 and T4 treatments, with the T1 treatment exhibiting the highest content (1.56 mg·g−1). Similarly, no significant difference was detected in soluble protein content between the T3 treatment and the CK. The T2 treatment had the lowest soluble protein content (0.38 mg·g−1). The T3 and T4 treatments exhibited the highest soluble sugar contents, at 1.31% and 0.91% respectively. No significant difference in soluble sugar content was observed between the T1 and T2 treatments, with the T2 treatment having the lowest content (0.59%). Soluble solid content exhibited differences among various treatments. Among these, the T4 treatment had the highest soluble solid content (3.93%), with no significant difference observed between the T4 treatment and the CK. No significant difference was detected in soluble solid content between the T2 and T3 treatments, and the T2 treatment showed the lowest content (3.40%).

3.4. Effects of Different Substrate Ratios on Enzyme Activities in Tomato Rhizosphere Soil

As presented in Figure 1, soil sucrase activity in T1–T4 treatments was significantly higher than that in the CK. Among these, the T4 treatment exhibited the highest sucrase activity, while no significant difference was observed between the T2 and T3 treatments. With respect to soil urease activity, the T1 treatment was significantly lower than the CK treatment, whereas no significant difference was observed between the T3 treatment and the CK. In contrast, urease activity was significantly higher in the T2 and T4 treatments than in the CK, with the T2 treatment showing the highest activity. For soil catalase activity, all treatments showed significantly higher activity than the CK. The highest activity was recorded in the T1 treatment and the lowest in the T3 treatment, with no significant difference observed between the T2 and T4 treatments.

3.5. Bacterial Alpha Diversity and Rarefaction Curves of Tomato Rhizosphere Soil Under Different Substrate Treatments

The rarefaction curves for bacterial alpha diversity in tomato rhizosphere soil under different treatments gradually plateaued with increasing sequencing depth (Figure 2). When the number of sequences exceeded 2000, the curve growth slowed, indicating that the sequencing data were sufficient to reliably represent the bacterial community structure in tomato rhizosphere soil.
The Observed ASVs index refers to the actual number of ASVs detected in a sample (Figure 3). The Observed ASVs index represents the number of detected ASVs per sample, and is used to evaluate the observed richness (an estimate of community richness) at the ASV level. The microbial community diversity and richness under the commercial substrate treatment (T1) were lower than those under the peanut shell–substrate compound treatments (T3, T4). The microbial community diversity and richness under the peanut shell–substrate composite treatment (T4) were higher than those under the CK. Compared with T1 and T2, the peanut shell–substrate composite treatment increased microbial community alpha diversity in tomato rhizosphere soil, whereas the commercial substrate treatment (T1) decreased the microbial diversity and richness indices.

3.6. Taxonomic Classification Levels of Bacterial Phyla and Genera in Tomato Rhizosphere Soil Under Different Substrate Ratios

At the phylum level taxonomic classification (Figure 4a), Proteobacteria was the ubiquitous dominant phylum across all treatments, with its relative abundance ranging from 25.52% (CK, the lowest) to 52.79% (T2 treatment, the highest). The relative abundance in T1, T3, and T4 treatments was 51.58%, 47.79%, and 46.26%, respectively. Acidobacteriota, Chloroflexota, Actinobacteriota, Gemmatimonadota, Myxocoota_A_473307, Bacteroidota, and Planctomycetota were the other major dominant bacterial phyla in all treatments. Notably, Gemmatimonadota had a significantly higher relative abundance in CK (19.17%) than in T1–T4 treatments (1.72–4.48%), while Myxococcota_A_473307 showed the opposite trend, with the highest abundance in T4 (8.53%) and the lowest in CK (2.51%).
The total relative abundance of the remaining bacterial phyla varied among treatments, being the highest in CK (1.59%) and the lowest in T1 (0.18%), followed by T4 (0.83%), T3 (0.86%), and T2 (1.17%). Other phyla (e.g., Firmicutes_D, Desulfobacterota_B, Patescibacteria, Verrucomicrobiota) had relatively low relative abundances (≤3.62%) across all treatments with minor fluctuations (Table S1).
At the genus-level taxonomic classification (Figure 4b), the relative abundances of dominant bacterial genera in tomato root systems varied among CK and T1–T4 treatments. Unclassified genera accounted for 35.32% (CK), 39.57% (T1), 37.16% (T2), 36.64% (T3), and 42.36% (T4), while the total relative abundance of the remaining genera was highest in CK (64.68%) and lowest in T4 (57.64%), with T1–T3 ranging from 60.43% to 63.36%. Bauldia and Devosia_A_501803 were common dominant genera across most treatments, with their abundances showing slight fluctuations.
Notably, SCGC_AG_212_J23 and RSA9 were identified as characteristic dominant genera in CK, with the latter exhibiting the highest relative abundance (8.45%) in the control. Devosia_A_501803, Bauldia, and Usitatibacter were dominant genera specifically enriched in T1–T4 (peanut shell mixed substrate) treatments, being nearly absent in CK (Table S2).
In conclusion, different substrate ratios significantly altered the community composition and relative abundances of bacteria at the genus level in tomato rhizosphere soil. Compared with the CK, both commercial substrate and peanut shell–substrate composite cultivation were more conducive to establishing a diverse and balanced bacterial community structure.

3.7. Tomato Rhizosphere Bacterial Phyla and Soil Physicochemical Properties: RDA

The top 10 bacterial phyla with relatively high abundance in the tomato rhizosphere were selected (Figure 5), and redundancy analysis (RDA) was employed to investigate the correlations between these bacterial phyla and soil physicochemical properties. The two axes in the RDA plot accounted for 38.37% and 19.50% of the total variation in the bacterial community structure, respectively. Specifically, soil bulk density was positively correlated with Desulfobacterota_B, Gemmatimonadota, Actinobacteriota, Chloroflexota, and unclassified bacterial groups; soil pH and total phosphorus were positively correlated with the Desulfobacterota_B group; air-filled porosity, electrical conductivity (EC), total potassium, and available potassium were positively correlated with Bacteroidota, Acidobacteriota, Planctomycetota, and Patescibacteria; Proteobacteria exhibited a positive correlation with water-holding porosity, alkali-hydrolyzable nitrogen, available phosphorus, total nitrogen, organic matter, total porosity, and available potassium; additionally, Bacteroidota was positively correlated with available potassium, air-filled porosity, total potassium, and EC.
At the bacterial genus level, soil bulk density and total phosphorus were positively correlated with SCGC_AG_212_J23 and RSA9; soil pH and total nitrogen were positively correlated with Chryseolinea, Usitatibacter and UBA5216; air-filled porosity, alkaline-hydrolyzable nitrogen, organic matter, total porosity, available potassium, available phosphorus, electrical conductivity, water-holding porosity and total potassium were positively correlated with Bauldia, ELB16_189, unclassified, Devosia_A_501803 and QUBU01.

3.8. Functional Annotation of Microbial Communities Based on MetaCyc and KEGG Pathways

To further investigate the functional profiles of tomato rhizosphere bacteria under different substrate ratios, this study combined high-throughput sequencing with functional annotation based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The results indicated that the bacterial communities associated with tomato roots encompass six primary-level functional categories: metabolism, genetic information processing, cellular processes, environmental information processing, organismal systems, and human diseases (Table 5). Among these, metabolism, genetic information processing, and cellular processes were the dominant functional categories, accounting for 73.27–73.86%, 9.42–10.42%, and 6.43–7.24% of the total functional abundance, respectively. Among these, metabolism, genetic information processing, and cellular processes were the primary level 1 functions, accounting for 73.27–73.86%, 9.42–10.42%, and 6.43–7.24% of the total functional abundance, respectively. Furthermore, no significant variation was observed in the types of predicted genes assigned to the primary-level functional categories across different substrate ratios used in tomato cultivation.
Figure 6 shows the relative abundance of predicted microbial metabolic pathways annotated against the MetaCyc database. The plot displays the top 20 functional categories in the bacterial community of the tomato rhizosphere. These pathways were mainly associated with valine, leucine and isoleucine biosynthesis, biosynthesis of terpenoids and steroids, fatty acid biosynthesis, synthesis and degradation of ketone bodies, biotin metabolism, lipoic acid metabolism, D-alanine metabolism, and cell cycle, as well as Caulobacter, bacterial chemotaxis, streptomycin biosynthesis, D-glutamine and D-glutamate metabolism, flagellar assembly, biosynthesis of amino acids, pantothenate and CoA biosynthesis, aminoacyl-tRNA biosynthesis, fatty acid metabolism, protein export, ribosome, mismatch repair, and citrate cycle (TCA cycle). The relative abundance of these top pathways ranged from approximately 1.07% to 2.23%. All other metabolic pathways with lower abundances were combined into the category “Other” (Table S3).

4. Discussion

4.1. Effects of Different Substrate Ratios on Tomato Yield and Quality

The substrate is a fundamental and pivotal component in facility-based vegetable cultivation, directly affecting crop yield and quality [42]. Studies have shown that an optimized substrate formulation can effectively improve tomato yield and fruit quality [43]. Specifically, coconut coir-based composite substrates have been demonstrated to significantly improve these key parameters [44]. The findings of this study indicate that incorporating peanut shell materials into the substrate markedly enhances tomato yield. Notably, the T4 treatment (peanut shells:commercial substrate = 3:1) produced significantly higher yield than the CK, and showed no significant difference compared with the T1 treatment. In contrast, the CK had the lowest yield. Key quality indicators of tomato fruits, including vitamin C content, soluble sugar content, soluble protein content, and total soluble solid content, are widely acknowledged as core indices for assessing tomato fruit quality [45]. Organic substrates have been demonstrated to enhance the quality of tomatoes grown in controlled-environment facilities, with a notable enhancement in the sugar-to-acid ratio [46]. This study further demonstrates that integrating peanut shell materials into the substrate significantly enhances tomato fruit quality, among which the T3 and T4 treatments achieved the best results. The highest vitamin C content was detected in the T4 treatment, which may be attributed to the increased nutrient availability in the substrate following the incorporation of peanut shell materials. This, in turn, promotes the activity of beneficial Rhizopheric microbes, thereby optimizing the rhizosphere growth environment for tomato plants.

4.2. Effects of Different Substrate Ratios on Soil Enzyme Activities in Tomato-Growing Soil

Soil enzyme activity plays a crucial role in the transformation of soil organic matter. Specifically, soil enzymes can catalyze the decomposition of plant and animal residues and other organic substances in the soil into simple inorganic compounds, which are then available for plant absorption to sustain normal growth and development [47]. Notably, the combination of peanut shell biochar and fermented cow manure has been demonstrated to significantly enhance the activities of ATPase and acid phosphatase [48]. In this study, the proportion of peanut shell materials in the substrate significantly increased the activities of urease, sucrase, and peroxidase, showing a consistent trend of enhancement with the increase in its proportion. The optimal effect was achieved in the T4 treatment, with a peanut shell material-to-commercial substrate volume ratio of 3:1. Urease activity across treatments followed the order: T2 > T4 > T3 > CK > T1; sucrase activity followed the order: T4 > T3 > T2 > T1 > CK; and peroxidase activity followed the order: T1 > T2 > T4 > T3 > CK. The rational application of peanut shell materials can optimize the crop growth environment, thereby promoting crop growth. Furthermore, peanut shell raw materials and other similar materials are rich in phosphorus, calcium, carbohydrates, and other nutrients, which can adequately meet the nutritional requirements of plants and provide sufficient reaction substrates for enzymatic reactions [48,49].
In conclusion, an optimal proportion of peanut shell materials in the substrate can increase substrate nutrient content and enzyme activity, optimize the rhizosphere growth environment of tomatoes, and ultimately promote tomato plant growth.

4.3. Effects of Different Substrate Ratios on Microbial Community Structure in Tomato Rhizosphere

The species diversity of soil microbial communities is a key indicator for assessing soil quality and health [50]. Microorganisms play vital roles in the degradation of organic matter and nutrient transformation within the substrate, and bacteria act as the primary drivers of biogeochemical cycling in ecosystems [51,52]. In protected tomato cultivation, variations in the physicochemical properties of different substrate types exert a significant influence on the structure and abundance of rhizosphere microorganisms [53]. Additionally, peanut shell materials possess excellent physicochemical properties and can effectively promote rhizosphere microbial proliferation [54]. When combined with other substrates, they can complement one another’s strengths, improve the inherent physicochemical properties of the substrate, and ultimately provide a favorable growth environment for plants [55]. The present study demonstrated that compared with the CK group, the two treatment groups (T3 and T4) formulated by mixing peanut shell materials with other substrates exhibited significant differences in rhizosphere microbial abundance. In the present study, we observed that compared with the CK, the two treatments (T3 and T4) prepared by mixing peanut shell materials with commercial substrates exhibited elevated relative abundances of the dominant bacterial phyla (Proteobacteria and Acidobacteriota). Meanwhile, the number of bacterial genera with relative abundance greater than 1% at the genus level increased significantly. These results demonstrate that the compounding of peanut shell materials with commercial substrates can enhance the diversity and richness of the rhizosphere bacterial community in tomato plants. The biodegradation of peanut shells and corn stover can promote the degradation of lignin in the former, accelerate the transformation of substrate organic matter, and enhance rhizosphere microbial community activity [56], which is consistent with the findings of the present study. Compared with the CK group, the T1–T4 treatment groups not only exhibited a significant increase in species diversity but also had a significant advantage in community richness.
Multiple studies have demonstrated that the phyla Proteobacteria, Actinobacteria, and Chloroflexi are dominant bacterial taxa in soil ecosystems, and they play crucial roles in maintaining soil health and regulating soil functionality [57,58]. In this study, at the bacterial phylum level, the most abundant taxa included the phyla Proteobacteria, Acidobacteria, and Actinobacteria. Phylum Proteobacteria harbors diverse groups of nitrogen-fixing and pathogenic bacteria and is recognized as a dominant bacterial group in plant rhizosphere soil [59]. Compared with the CK, the relative abundance of Proteobacteria increased by 26.06%, 27.29%, 22.29%, and 20.76%, respectively. Acidobacteriota are acidophilic bacteria widely distributed in soil and play key ecological roles in ecosystem functioning [60]. Compared with the CK, the combination of peanut shell materials and other substrates resulted in a 3.08% and 2.81% increase in the abundance of Acidobacteria. Within the phylum Chloroflexota, certain bacterial taxa—for instance, those affiliated with the class Anaerolineae—exhibit the dual capacity to decompose labile soil substrates (e.g., sugars and amino acids) and to break down relatively stable organic carbon compounds such as phenol and p-methylbenzoate [61,62,63]. Members of the Actinobacteria phylum are predominantly aerobic saprophytes and exhibit functional traits such as nitrogen fixation and phosphorus solubilization [64]. Overall, after the application of peanut shells combined with substrate, the relative abundances of Proteobacteria and Acidobacteria were significantly higher than those in the CK while the abundances of Chloroflexota and Actinobacteria were significantly reduced. When peanut shells are mixed with commercial substrates, specific beneficial functional bacterial genera become enriched in the tomato rhizosphere. Notably, the genus Dokdonella_A—recognized as a dominant genus—has been demonstrated to be involved in the soil nitrogen cycle and may enhance plant stress resistance by providing essential nutrients under adverse conditions, thanks to its denitrifying ability [65]. Additionally, other specific dominant genera, such as Bauldia and Hyphomicrobium_A, have been found under the treatment of peanut shells combined with commercial substrates. The genus Bauldia is generally found in specific soil environments characterized by low available phosphorus and alkaline pH, and functions in denitrification as well as organic carbon degradation [66]. The genus Hyphomicrobium_A contributes to key soil biochemical processes including nitrogen fixation, nitrogen mineralization, and humus formation via its denitrifying and phosphorus-removing activities, thus effectively enhancing soil fertility [67]. Overall, the enrichment of these specific functional bacterial genera optimizes the tomato rhizosphere microbial ecosystem, facilitating nutrient uptake and bolstering the tomato plant’s adaptation to environmental stresses.

4.4. Effects of Different Substrate Ratios on Microbial Community Diversity in Tomato Rhizosphere

Substrate cultivation, compared with traditional soil-based methods, boasts several advantages, including enhanced water conservation and moisture retention, reduced production costs, and reduced environmental impact. It can help to partially reduce the demands for inputs in agricultural production [68]. This approach effectively promotes crop growth and optimizes the rhizosphere environment, thereby increasing crop yield and quality while enhancing the enrichment of the microbial community in the rhizosphere soil [69]. In practice, strategies such as the application of biofertilizers and the adoption of substrate cultivation are widely adopted to optimize the composition and structure of rhizosphere microbial communities. By modulating these microbial communities, the tomato rhizosphere environment can be optimized to further boost crop productivity [70]. The abundance and diversity of rhizosphere microbial communities play a pivotal role in promoting plant growth and facilitating disease prevention and management. This study demonstrates that substrates formulated by mixing peanut shells with commercial substrates (T3, T4) significantly increased the alpha diversity index of rhizosphere microbial communities. Although no significant difference in overall microbial diversity was detected when compared with the CK, a significant increase in the ASVs CK count was noted. Changes in microbial community diversity induced by different peanut shell–substrate ratios indicate that various substrate combinations can disrupt the original microbial stability and trigger adaptive shifts in the microbial community. For instance, in soil remediation, amending soil with peanut shells can increase the abundance of beneficial microorganisms, thereby improving soil fertility and regulating the soil ecological environment [71]. Several studies have shown that the incorporation of peanut shells into substrate mixtures can significantly enhance microbial biomass in the substrate [72]. Furthermore, as the cultivation period advances, peanut shells in the substrate undergo a process analogous to aerobic composting. This process not only increases the richness of microbial species in the substrate but also facilitates the release of additional nutrients [73]. The present study demonstrated that mixing different ratios of peanut shells with commercial substrates regulated the proportions of dominant bacteria (at both the phylum and genus levels) in the tomato rhizosphere, and modified, to varying degrees, the diversity and richness of the rhizobacterial community. These findings are consistent with previous research.

4.5. Peanut Shells Improve Tomato Growth, Yield and Quality by Modulating Substrate Properties, Soil Enzyme Activities and Root-Associated Microbial Communities

A comprehensive analysis of the experimental results demonstrates that incorporating peanut shells into the substrate significantly enhances tomato growth, yield, and fruit quality. These improvements arise from the integrated modulation of three interrelated factors: substrate physicochemical properties, soil enzyme activities, and the composition and function of the root-associated microbial community. Furthermore, peanut shells altered substrate bulk density, total porosity, and nutrient availability, thereby fostering a more favorable rhizosphere microenvironment. This, in turn, promoted the activities of key soil enzymes, including urease, sucrase and peroxidase. Enhanced enzyme activity accelerated the mineralization and bioavailability of nitrogen, carbon, and phosphorus, thereby directly supporting tomato physiological demands while simultaneously supplying essential substrates for microbial metabolism and proliferation. Concurrently, the improved substrate microenvironment markedly increased both the alpha diversity and taxonomic richness of root-associated bacterial communities, with notable increases in the relative abundances of dominant taxa. Among all treatments, T4 (peanut shells:substrate = 3:1) resulted in the most significant improvements in enzyme activities, microbial community structure, and agronomic performance, including marketable yield and enhanced fruit quality. Thus, T4 is considered optimal for soilless culture of greenhouse tomatoes in this study.

5. Conclusions

In recent years, high-throughput sequencing has been widely used to investigate the diversity and abundance of plant-associated bacteria. In this study, we systematically examined the effects of different mixing ratios of peanut shells and commercial substrate on tomato yield, fruit quality, rhizosphere enzyme activities, and rhizosphere microbial community structure and function. Based on MiSeq sequencing combined with KEGG and MetaCyc functional annotation, our results demonstrated that different peanut shell–substrate ratios altered the composition, diversity, and abundance of tomato rhizosphere microorganisms. Correspondingly, the functional profiles related to metabolism, genetic information processing, and cellular processes were also modified to varying degrees. Among all treatments, T4 (peanut shells:commercial substrate = 3:1) performed the best in enhancing available nutrient contents, rhizosphere enzyme activities, and the structure and function of the rhizosphere microbial community, indicating that it can establish a favorable rhizosphere microecosystem to synergistically promote tomato yield and quality.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae12040427/s1, Table S1: Relative abundance of dominant bacterial phyla under different treatments (%); Table S2: Relative abundance of dominant bacterial genera under different treatments (%); Table S3: Relative abundance and percentage composition of MetaCyc pathways predicted by PICRUSt2.

Author Contributions

H.D.: Investigation, Data curation. H.F.: Writing—review and editing. H.M.: Investigation, Formal analysis. X.L.: Supervision, Conceptualization. T.Z.: Writing—review and editing, Resources. X.M.: Investigation, Data curation. H.L.: Writing—original draft, Investigation. X.D.: Resources, Project administration. Z.G.: Investigation, Formal analysis. Y.W.: Writing—review and editing. F.P.: Formal analysis, Data curation. S.S.: Investigation, Formal analysis. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Major Science and Technology Special Project of Henan Province [grant number 241100110200], the National Key Research and Development Program of China [grant number 2024YFD2300703].

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Effects of different peanut shell–commercial substrate combinations on tomato rhizosphere soil enzyme activity. Soil enzyme activities in the tomato rhizosphere were determined at the fruiting stage, including sucrase activity (a), urease activity (b), and catalase activity (c). Values are the mean ± standard deviation (n = 3). Different letters indicate significant differences (p < 0.05) according to Tukey’s test.
Figure 1. Effects of different peanut shell–commercial substrate combinations on tomato rhizosphere soil enzyme activity. Soil enzyme activities in the tomato rhizosphere were determined at the fruiting stage, including sucrase activity (a), urease activity (b), and catalase activity (c). Values are the mean ± standard deviation (n = 3). Different letters indicate significant differences (p < 0.05) according to Tukey’s test.
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Figure 2. Sample rarefaction curve.
Figure 2. Sample rarefaction curve.
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Figure 3. Microbial colony diversity index with different substrate ratios. Simpson Index (a), Shannon Index (b), Observed features (c), Chao1 Index (d). Note: Individual data points are overlaid on the boxplot to show the full distribution.
Figure 3. Microbial colony diversity index with different substrate ratios. Simpson Index (a), Shannon Index (b), Observed features (c), Chao1 Index (d). Note: Individual data points are overlaid on the boxplot to show the full distribution.
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Figure 4. Relative abundance of dominant bacterial phyla (a) and bacterial genera (b) in tomato rhizosphere under different substrate ratios.
Figure 4. Relative abundance of dominant bacterial phyla (a) and bacterial genera (b) in tomato rhizosphere under different substrate ratios.
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Figure 5. Redundancy analysis (RDA) of microbial community composition in relation to substrate physicochemical properties. (a) Bacteria (phylum), (b) bacteria (genus). Note: Each point represents a single species, where the size of the point is positively correlated with the species abundance (i.e., larger points correspond to higher species abundance). Gray points indicate species with low abundance, which are not labeled with their taxonomic names in the figure. When species are projected onto each environmental factor, the corresponding value reflects the environmental conditions that the species tends to inhabit. RZ: Bulk density, ZK: Total porosity, TQ: Air-filled porosity, CS: Water-holding porosity, pH: pH value, EC: Electrical conductivity, JZ: soil organic matter, SK: Available potassium, JN: Alkaline-hydrolyzable nitrogen, YL: Available phosphorus, QD: Total nitrogen, QL: Total phosphorus, QJ: Total potassium.
Figure 5. Redundancy analysis (RDA) of microbial community composition in relation to substrate physicochemical properties. (a) Bacteria (phylum), (b) bacteria (genus). Note: Each point represents a single species, where the size of the point is positively correlated with the species abundance (i.e., larger points correspond to higher species abundance). Gray points indicate species with low abundance, which are not labeled with their taxonomic names in the figure. When species are projected onto each environmental factor, the corresponding value reflects the environmental conditions that the species tends to inhabit. RZ: Bulk density, ZK: Total porosity, TQ: Air-filled porosity, CS: Water-holding porosity, pH: pH value, EC: Electrical conductivity, JZ: soil organic matter, SK: Available potassium, JN: Alkaline-hydrolyzable nitrogen, YL: Available phosphorus, QD: Total nitrogen, QL: Total phosphorus, QJ: Total potassium.
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Figure 6. Percentage composition of the relative abundance of MetaCyc pathways predicted by PICRUSt2.
Figure 6. Percentage composition of the relative abundance of MetaCyc pathways predicted by PICRUSt2.
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Table 1. Matrix physical properties.
Table 1. Matrix physical properties.
TreatmentpHEC
(mS·cm−1)		Bulk Density (g·cm−3)Total Porosity
%		Air-Filled Porosity
%		Water-Holding Porosity
%
CK6.31 ± 0.04 b1.46 ± 0.01 d1.12 ± 0.03 a51.61 ± 1.21 b3.40 ± 1.58 c48.97 ± 1.21 c
T16.10 ± 0.06 c1.83 ± 0.30 a0.17 ± 0.01 c69.94 ± 2.09 a2.64 ± 0.52 c66.55 ± 2.75 a
T27.14 ± 0.14 a0.80 ± 0.03 e0.33 ± 0.03 b73.29 ± 1.10 a14.99 ± 4.29 b58.30 ± 3.64 b
T35.81 ± 0.05 d1.72 ± 0.48 b0.17 ± 0.01 c71.35 ± 2.25 a20.59 ± 4.52 b50.76 ± 3.38 bc
T45.84 ± 0.02 d1.64 ± 0.31 c0.15 ± 0.02 c71.44 ± 1.63 a32.11 ± 3.40 a39.33 ± 2.86 d
Note: Different letters indicate statistical significance at the p < 0.05 level.
Table 2. Chemical properties of the matrix (g·kg−1).
Table 2. Chemical properties of the matrix (g·kg−1).
TreatmentANAPAKTNTPTKSOM
CK0.47 ± 0.02 e0.18 ± 0.01 c0.54 ± 0.10 c3.03 ± 0.82 d1.45 ± 0.41 c7.60 ± 0.38 d22.56 ± 0.42 e
T11.95. ± 0.10 a0.48 ± 0.03 a2.75 ± 0.27 b4.83 ± 0.27 c1.73 ± 0.34 a13.75 ± 0.45 b455.74 ± 2.87 a
T21.65 ± 0.04 b0.22 ± 0.01 c2.79 ± 0.18 b10.53 ± 0.46 a1.57 ± 0.24 b11.63 ± 0.05 c408.19 ± 1.53 c
T30.75 ± 0.04 e0.32 ± 0.02 b3. 57 ± 0.18 a6.26 ± 0.49 b1.41 ± 0.20 c66.89 ± 0.25 a308.98 ± 7.93 d
T41.40 ± 0.07 c0.23 ± 0.02 c3.85 ± 0.37 a6.01 ± 0.31 b0.79 ± 0.15 d66.28 ± 0.02 a430.74 ± 7.08 b
Note: AN, Alkaline-hydrolyzable nitrogen; AP, available phosphorus; AK, available potassium; TN, total nitrogen; TP, total phosphorus; TK, total potassium; SOM, soil organic matter. Note: Different letters indicate statistical significance at the p < 0.05 level.
Table 3. Effects of different peanut shell–commercial substrate ratios on tomato yield.
Table 3. Effects of different peanut shell–commercial substrate ratios on tomato yield.
TreatmentYield per Plant (kg)Yield per Mu (kg·667 m−2)
CK1.85 ± 0.12 d4925.06 ± 40.74 d
T13.46 ± 0.26 a9227.82 ± 70.56 a
T22.47 ± 0.21 c6578.60 ± 67.12 c
T32.92 ± 0.21 b7787.64 ± 46.19 b
T43.42 ± 0.57 a9130.03 ± 107.79 a
Note: Different letters indicate statistical significance at the p < 0.05 level.
Table 4. Effects of different peanut shell–commercial substrate ratios on tomato fruit quality.
Table 4. Effects of different peanut shell–commercial substrate ratios on tomato fruit quality.
TreatmentVitamin C Content
(mg·100 g−1)		Soluble Protein Content
(mg·g−1)		Soluble Sugar Content
(%)		Soluble Solids Content
(%)
CK7.44 ± 0.45 b0.89 ± 0.03 b0.79 ± 0.01 bc3.73 ± 0.21 ab
T14.88 ± 0.45 c1.56 ± 0.11 a0.69 ± 0.07 cd3.67 ± 0.06 b
T23.97 ± 0.59 c0.38 ± 0.12 c0.59 ± 0.01 d3.37 ± 0.06 c
T39.75 ± 0.89 a0.79 ± 0.14 b1.31 ± 0.18 a3.40 ± 0.10 c
T410.52 ± 1.18 a1.05 ± 0.18 a0.91 ± 0.02 b3.93 ± 0.06 a
Note: Different letters indicate statistical significance at the p < 0.05 level.
Table 5. Level 1 functional pathways based on the KEGG database.
Table 5. Level 1 functional pathways based on the KEGG database.
Treatment
(Pathway Level 1)		MetabolismGenetic Information ProcessingCellular
Processes		Human
Diseases		Environmental
Information Processing		Organismal Systems
CK73.86%10.42%6.43%4.67%2.30%2.32%
T173.86%9.42%6.77%5.30%2.33%2.33%
T273.27%9.92%7.24%5.40%2.31%2.33%
T373.45%9.73%6.80%5.28%2.39%2.35%
T473.40%9.63%6.88%5.28%2.37%2.44%
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Luo, H.; Ma, X.; Ma, H.; Fu, H.; Dong, H.; Guo, Z.; Dong, X.; Piao, F.; Shen, S.; Li, X.; et al. Effects of Different Substrate Ratios on Bacterial Community Structure and Diversity in the Rhizosphere of the Tomato. Horticulturae 2026, 12, 427. https://doi.org/10.3390/horticulturae12040427

AMA Style

Luo H, Ma X, Ma H, Fu H, Dong H, Guo Z, Dong X, Piao F, Shen S, Li X, et al. Effects of Different Substrate Ratios on Bacterial Community Structure and Diversity in the Rhizosphere of the Tomato. Horticulturae. 2026; 12(4):427. https://doi.org/10.3390/horticulturae12040427

Chicago/Turabian Style

Luo, Hengbin, Xiaojing Ma, Haohao Ma, Hongdan Fu, Han Dong, Zhixin Guo, Xiaoxing Dong, Fengzhi Piao, Shunshan Shen, Xinzheng Li, and et al. 2026. "Effects of Different Substrate Ratios on Bacterial Community Structure and Diversity in the Rhizosphere of the Tomato" Horticulturae 12, no. 4: 427. https://doi.org/10.3390/horticulturae12040427

APA Style

Luo, H., Ma, X., Ma, H., Fu, H., Dong, H., Guo, Z., Dong, X., Piao, F., Shen, S., Li, X., Wang, Y., & Zhang, T. (2026). Effects of Different Substrate Ratios on Bacterial Community Structure and Diversity in the Rhizosphere of the Tomato. Horticulturae, 12(4), 427. https://doi.org/10.3390/horticulturae12040427

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