Effects of Exogenous Bacterial Agents on Material Transformation and Microbial Community Composition during Composting of Tomato Stalks

Abstract

Tomato stems can pollute the environment and also cause resource costs. In this study, five combinations of microbial agents were added to tomato stems for aerobic composting to find effective microbial formulations to improve composting performance and product quality through comparative analysis. Six treatments were set up: T1 (Microbial agents A), T2 (0.5% Microbial agents B), T3 (0.5% Microbial agents C), T4 (0.5% Microbial agents D), T5 (0.5% Microbial agents E) and T6 (no addition). The physicochemical parameters of the composting system were measured, and the dynamics of the microbial community during the composting process were studied using high-throughput sequencing technology. The results showed that the T1 treatment had a longer high-temperature period than T6 and the highest cellulose degradation rate (62.0%). The contents of total phosphorus (TP), total potassium (TK) and effective potassium (AK) were 8.11 g·kg⁻¹, 53.98 g·kg⁻¹ and 45.62 g·kg⁻¹, respectively, at the end of composting, representing increases of 270.3%, 56.6% and 25.40% compared to the initial values, significantly higher than the control (p < 0.05). The Chao1 and Shannon indexes of T1 treatment were 73.5% and 41.7% higher in the compost decay stage for bacteria, and 50.2% and 18.1% for fungi, significantly higher than in T6 (p < 0.05) compared to the initial values. During the high-temperature phase, the abundance of Aspergillus increased (4.13% to 44.24%) the abundance of Staphylococcus decreased (58.31% to 8.90%). In terms of numbers and species diversity, bacterial communities were more abundant than fungal communities. Proteobacteria, Firmicutes, Actinomycetes and Bacteroides were the four main bacterial phyla, while Ascomycetes was the absolutely dominant fungal phylum. In conclusion, the addition of microbial agent A can effectively improve the nutrient content of tomato stem compost, promote the maturation of compost, and regulate the microbial community structure and can realize the resource utilization of tomato stems.

1. Introduction

According to statistics, in 2019, China ranked first in the world in tomato production, with 1.1 million hectares under cultivation and a production of about 63 million tons [1]. Due to the high tomato production and extensive planting area, there exists a considerable amount of tomato stalks, estimated to produce about 8.4 million tons per year [2]. Tomato plant stalks tend to accumulate during harvest and are a potential source of plant pathogens and other forms of environmental contamination [3]. Therefore, large amounts of tomato stalks need to be disposed of properly. As an important biological resource, the resourceful and comprehensive utilization of tomato plant stalks is receiving more and more attention from researchers. It has been found that tomato straw is a potential particle board substrate, but the preparation process is difficult [4].

Composting is a method by which aerobic and thermophilic microorganisms consume organic matter as a substrate under controlled conditions, producing stable, mature, deodorized, hygienic material free from pathogenic plants and seeds and rich in humus substances that can be used as a soil conditioner [5]. Anaerobic composts are prone to rapid acidification of tomato straw and other vegetable wastes due to high biodegradability, leading to acid accumulation, which will inhibit the methanogenic process [6]. High-temperature aerobic composting is an effective and economically viable method for treating this type of agricultural waste [7].

Conventional composting processes suffer from practical problems such as low temperature, long fermentation cycles, slow microbial metabolism, and low cellulose and lignin degradation rates [8,9], which not only reduce the agricultural value of compost but also become key factors in limiting the commercial attractiveness of aerobic composting for the treatment of organic waste [10]. Microorganisms with high metabolic intensity and rapid reproduction rates have attracted much attention [11]. Exogenous microbial agents can accelerate the degradation of agricultural wastes while reducing costs and simplifying operations without causing secondary pollution.

It has been shown that the inoculation of microorganisms in compost can improve the quality of compost products. In the process of composting wheat grass and cow and chicken manure, inoculated with 5 mL·kg⁻¹ of the lignocellulolytic bacteria Penicillium expansum, microorganisms were found to increase by 1 to 2 orders of magnitude, humus content by 12.0%, lignocellulose degradation rate by 57.5% and germination index by 150% compared to non-inoculated compost [12]. Nakasaki et al. [13] isolated a strain of Saccharomyces cerevisiae Rb1 from mixed compost of waste and rice bran and observed after inoculation that the inoculum accelerated the degradation of organic acids in the compost material and the proliferation of neutrophilic and thermophilic bacteria. There have also been numerous studies showing that inoculation with a combination of microbial agents is more effective in improving composting compared to single inoculation. Xi et al. [14] inoculated domestic waste compost with ammonia-oxidizing bacteria, nitrifying bacteria, and Thiobacillus and observed that the combination of microorganisms significantly improved the efficiency of the process and the quality of the compost. Vargas-Garcia et al. [15] inoculated horticultural waste compost with Bacillus shackletonni, Streptomyces thermovulgaris and Ureibacillus thermosphaericus and reported the same results.

Since microorganisms undergo complex changes during the composting process after inoculation, it is crucial to identify the microbial community distribution in order to reveal the mechanism of transformation of compost materials and to improve compost quality and performance. High-throughput sequencing technology is widely used in the field of composting, especially for analyzing the composition and dynamics of microbial communities during the composting process [16]. Different temporal succession patterns in bacterial and fungal community structures have been observed in studies of mung bean hull and maize stover composting [17]. The results of composting mushroom residues and wood chips showed that inoculation with microbial agents facilitated the optimization of community structure and the conversion of cellulosic substrates, with Aspergillus, Penicillium, Bacillus and Streptomyces playing active roles in the setup and thermophilic phases of composting [18].

In addition, microorganisms in compost are closely related to physicochemical indicators such as temperature, pH, C/N ratio, and water content [19]. In cattle manure and maize stover composting, NO₃⁻-N, NH₄⁺-N and C/N and temperature were found to have significant effects on the succession of only bacterial communities only, whereas TN and water content had significant impacts on both bacterial and fungal communities [20]. Redundancy analysis (RDA) has been widely used to assess the correlation between microbial community composition and environmental factors, and it can identify composting factors that can influence changes in microbial community dynamics [21]. It is important to elaborate on the relationship between microbial communities and physicochemical indicators in tomato stalk compost.

In previous studies, there is still limited information on the physicochemical properties and microbial community succession of tomato stalks, a type of vegetable waste, after inoculation with complex microbial agents. We have well addressed the pollution caused by the improper treatment of tomato stalks with the environment and rational resource utilization. In this study, tomato stalks were used as the composting material and five microbial agents were inoculated. The composting experiment was conducted for 55 d. The main purposes of this study were as follows: (1) to compare the effects of inoculation with different microbial agents on the transformation of materials during the composting of tomato straw. (2) to study the microbial populations and functional succession in the main stages of tomato stalk composting and to determine the dominant functional microorganisms in the composting process; and (3) to evaluate the relationship between microbial communities and the physicochemical characteristics of tomato stalk composting. This study provides solutions for the resourceful treatment of tomato stalks as a type of green waste, useful information for the later process optimization of tomato stalk composting, and assistance for the subsequent screening of specific functional strains and the development of complex microbial agents.

2. Materials and Methods

2.1. Activation of Microbial Agents

Five microbial agents were purchased from different biotechnology companies. The specific microbial species contained in each agent are shown in Table S1 (Supplementary Files). According to the manual, 500 gA, 100 gB, 100 gC, 20 gD and 50 gE were activated one week prior to composting, using different amounts of the added agent to ensure the same number of active bacteria per treatment. To activate, added 100 g brown sugar and 10 kg distilled water in 500 g A, 200 g brown sugar and 1 kg distilled water in 100 g B, 200 g brown sugar and 2 kg distilled water in 100 g C, 40 g brown sugar and 400 g distilled water in 20 g D, 50 g E, and left to cool in a plastic container for about a week.

2.2. Composting Process and Sample Collection

The composting experiment was conducted from July 2021 to September 2021 at the Horticultural Garden of Northwestern Agricultural and Forestry University in Yangling, Shaanxi Province (Figure 1). Tomato stalks were collected from nearby farmers’ sheds. The main initial physicochemical parameters of tomato stalks were determined: 52.53% water content, 6.9 pH, 12.1% total organic carbon (TOC), 336.52 g·kg⁻¹, and 23.79 g·kg⁻¹ total nitrogen (TN). After the tomato stalks were harvested and dried, crushed into small segments of 1–3 cm with a grinder. Sprayed the five activated microbial agents on the compost heap. A total of 6 treatments (T1-Tomato Straw + microbial agent A, T2-Tomato Straw + microbial agent B, T3-Tomato Straw + microbial agent C, T4-Tomato Straw + microbial agent D, T5-Tomato Straw + microbial agent E, T6-Pure Tomato Straw) were set up for each treatment. Adjusted compost has a water content of about 55% and a compost pile of about 2.0 m × 1.5 m × 1 m (long × wide × high). The compost is naturally ventilated and manually turned, once every 3 d at the high-temperature period and once every 5 d after the high-temperature period.

Samples were collected at 0, 1, 5, 9, 14, 19, 24, 32, 42, and 55 d, respectively. 500 g subsamples were collected at 3 different locations in the upper (60~90 cm), middle (30~60 cm) and lower (0~30 cm) of the pile, and 9 subsamples were mixed to obtain high representativeness and evenly divided into two parts. Samples stored at 4 °C were used for the determination of physicochemical parameters, and samples at the 1 d, 5 d, 24 d, and 55 d were labeled as T1d1-T6d1, T1d5-T6d5, T1d24d-T6d24, and T1d55-T6d55, indicating the warming, thermophilic, cooling, and decaying phases of the compost, respectively, and frozen at −80 °C for DNA extraction.

2.3. Determination of Physical and Chemical Indicators

Compost and ambient temperature were recorded by MT-8X multi-channel temperature recorder (Shenzhen Shenzhen Sheng Hua Xuan Technology Co., Ltd., Shenzhen, China). Mean values of 9:00 am, 2:00 pm and 7:00 pm were obtained for daily composting and ambient temperature. A range of physiochemical parameters were determined, including the following:

2.3.1. Determination of Moisture Content, pH and EC

After drying to constant weight at 105 °C, the water content was determined on the basis of the difference between the initial and final weight [22], the fresh sample was mixed with distilled water at 1: 10 (w/v), oscillated 1 h at 120 r/min in a thermostat oscillator, and pH and EC values were determined using a pH meter (OHAUS ST10, OHAUS Instruments Co., Ltd., Changzhou, China) and an EC meter (OHAUS ST20, OHAUS Instruments Co., Ltd., Changzhou, China) after filtration.

2.3.2. Determination of Nutrient Content

TOC determination by TOC analyzer (SSM-5000A, Mitutoyo Instruments Co., Ltd., Kanagawa, Japan). TN was determined using the AA3 Continuous Flow Analyzer (SEAL AutoAnalyzer 3, ELEMENTAR Instruments Co., Ltd., Hanover, Germany). Ammonia nitrogen (NH₄⁺-N) was determined by indigo blue colorimetry (UV-2450 UV spectrophotometer, Shimadzu, Japan; ibid.). Nitrate nitrogen (NO₃⁻-N) was determined by the phenol disulfonic acid colorimetric method. Anticolorimetric determination of total phosphorus (TP) and effective phosphorus (AP) by molybdenum and antimony. Determination of total potassium (TK) and effective potassium (AK) by flame spectrophotometry (Shanghai Instruments Co., Ltd., Shanghai, China).

2.3.3. Determination of Cellulose Content

The cellulose content was determined by Van’s detergent.

2.3.4. Determination of Germination Index

Seed germination was tested using water extracts prepared by the same method. 5 mL of supernatant was placed in a glass dish lined with filter paper. Each dish was evenly distributed with 20 cabbage seeds. The seeds were grown in darkness for 48 hours in a 25 °C incubator. Distilled water was used as a control to determine the seed germination index [23]. The germination index (GI) was calculated according to the following formula

$$GI(\%)=\frac{\mathrm{Germination}\mathrm{rate}\mathrm{of}\mathrm{treated}\mathrm{seeds}(\%)\times \mathrm{Seed}\mathrm{root}\mathrm{length}}{\mathrm{Germination}\mathrm{rate}\mathrm{of}\mathrm{control}\mathrm{seeds}(\%)\times \mathrm{Seed}\mathrm{root}\mathrm{length}}$$

(1)

2.4. DNA Extraction, PCR Amplification and High-Throughput Sequencing

According to the manufacturer, use E.Z. N.A. Stool DNA Kit (D4015, Omega, Inc. USA) extracts genomic DNA from compost samples (1, 5, 24, 55 d). DNA was then extracted using 1% agarose gel electrophoresis and quantified by NanoDrop ™ 2000 spectrophotometer. All extracted DNA was stored at −80 °C for further analysis. Gene expression of TS1 FI2 (5′-CCTACGGGGGGWGCAG-3′) and TS1 FI2 (5′-CCTACGGGGGGGWGCAG-3′) and TS1 FI2 (5′-CCTACWGCWGCAG-3′) and TS2 (5′-CCTACWGCWGCAG-3′-3′) were amplified, respectively [24]. All PCR responses were amplified by PCR in a total volume of 25 μL reactive mixtures (including 25 ng template DNA, 12.5 μL PCR premixes, 2.5 μL primers, and PCR-grade water). The PCR reaction process was as follows: initial denaturation of 30 s at 98 °C; 32 denatures at 98 °C for 10 s, annealing for 30 s at 54 °C and extending for 45 s at 72 °C; Then, it finally stretches for 10 min at 72 °C.

PCR products were reconfirmed by 2% agarose gel electrophoresis. Ultra-pure water was used in place of sample solution throughout DNA extraction to rule out false-positive PCR results as negative controls. PCR products were purified using AMPure XT (Beckman Coulter Genomics, Danvers, MA, USA) and quantified by Qubit (Invitrogen, Waltham, MA, USA). Purified PCR products were evaluated for size and number of amplified libraries on Agilent 2100 Bioanalyzer (USA) and Illumina (Kapa Biosciences, Woburn, MA, USA) library quantitative kits. Qualified and sequenced on NovaSeq PE250 platform (LC-Bio Technology CO., Ltd., Hangzhou, China).

2.5. Processing of Sequencing Data and Bioinformatics Analysis

After obtaining the raw sequencing data by NovaSeq PE250, the samples first needed to be split according to the barcode information and the splice and barcode sequences removed. Primers were removed using cutadapt (v1.9), and the raw sequences were filtered under specific filtering conditions using FLASH (v1.2.8) and PEAR (v0.9.6) for each pair of paired-end reads of bacteria and fungi, respectively, based on the overlap to splice the double-end data, according to fqtrim (v0.94) to obtain high-quality sequences. Chimeric sequences were filtered using Vsearch software (v2.3.4). After de-duplication using DADA2, feature tables and feature sequences were obtained. Species classification was performed using SILVA (Release 132, https://www.arb-silva.de/documentation/release-132/, accessed on 20 August 2022) as well as the NT-16S database for bacteria and RDP and unite databases for fungi.

The alpha diversity (Includes Chao1, Shannon, Simpson and Coverage indices) of bacteria and fungi was calculated using QIIME2 based on the obtained feature tables and feature sequences. Beta diversity analysis was used to assess differences in species complexity between samples and was completed using the distance matrix in QIIME2. The data were then subjected to heat map clustering and principal coordinates analysis (PCoA) using the weighted UniFrac distances in R software. Correlations between the selected physicochemical factors (T, pH, EC, GI, TOC, TN, NH₄⁺-N, NO₃⁻-N, TP, AP, TK, AK) and the sample and microbial community composition triad (top 15 microorganisms) were analyzed by redundancy analysis (RDA) and Spearman.

2.6. Statistical Analysis

All tests were performed using 3 replicates, and the data obtained were statistically analyzed using SPSS 22.0 software. The means of physicochemical indicators and microbial alpha diversity of the different treatments were compared using one-way ANOVA, and multiple comparisons (Duncan) tested the significance level of the means at a 95% confidence level (p < 0.05). Using Origin 2018 for Plotting. RDA was performed using Canoco 5 software to assess the correlation between microbial communities and environmental factors.

3. Results

3.1. Changes in Physicochemical Parameters during the Composting Process

3.1.1. Temperature and Water Content

Temperature is an important environmental factor affecting the composting process. Pile temperature increased rapidly in the initial stage in all treatments, and on 1 d, the temperature exceeded 60 °C in all six treatments. Upon turning the pile after 3 d, the pile temperatures of all treatments decreased slightly, and thereafter the pile temperatures increased rapidly. As the composting progressed, the temperature gradually decreased, and from 32 d onwards, the temperature was always lower in T6 than in T1–T5 (Figure 2a). The water content composted in treatments T1, T4 and T6 decreased significantly on 1 d due to strong microbial activity coupled with external temperature; the compost was rehydrated after 5 d and covered with plastic film to prevent excessive evaporation (Figure 2b).

3.1.2. Changes in pH and EC

The most suitable pH for composting is generally considered to be neutral or weakly alkaline. On 1 d of composting, the pH increased rapidly. The pH of treatment T6 showed a slight fluctuation at 14 d, while the pH of T1–T5 showed a large decrease. From 19d onwards, pH stabilized, while the pH of T1–T6 ranged from 7.9 to 8.6 after composting. At the end of composting, treatment T2 had the lowest pH compared to the control, T6, suggesting that inoculation with agent B created a better pH environment for composting by reducing NH₃ volatilization and controlling N loss (Figure 2c).

The change in EC content is shown in Figure 2d; EC values were obviously reduced in each treatment on 1 d. Wang et al. [25] reported the same results in a study of Chinese herbal residue composting. The decreased EC in compost on 1 d may be related to nitrogen loss caused by ammonia volatilization after rapid temperature increase, which reduces the content of soluble salt. After 14 d of composting, the EC values for all treatments showed less variation, indicating that most of the organic matter in the compost was decomposed by the microorganisms (Figure 2d).

3.1.3. Changes in NH₄⁺-N, NO₃⁻-N, TOC and TN Content

The changes in NH₄⁺-N in treatments T1–T6 showed an overall trend of increasing and then decreasing, and the content of NH₄⁺-N varied remarkably in the first 14 d of composting in each treatment. The NH₄⁺-N content reached a maximum of 6.37 g·kg⁻¹ on 9 d of composting in treatment T2 and subsequently decreased sharply in all treatments, and stabilized at the end of composting at about 0.04 g·kg⁻¹ (Figure 3a). The NO₃⁻-N content in treatments T1–T6 remained at a reduced level until 14 d of composting, probably due to the low activity of nitrifying bacteria in a high-temperature environment. The NO₃⁻-N content in treatment T1 reached a maximum of 3.15 g·kg⁻¹ at the end of composting (Figure 3b).

The initial TOC content was 336.52 g·kg⁻¹, and at the end of composting in T1–T6 the content was reduced by 45.5, 51.8, 49.7, 46.5, 45.1 and 57.0%, respectively (Figure 3c). During the high-temperature composting, TOC levels decreased dramatically due to the rapid decomposition of biodegradable carbon and the metabolism of bacteria and fungi to produce CO₂ [26]. Zhao et al. [27], in a composting study using mushroom substrates and microbial agents, also found a decrease in TN levels throughout the composting cycle and a significant decrease during under high temperatures. It is possible that the loss of TN is due to the significant volatilization of ammonia during high temperatures. After 9 d of composting, the TN content in each treatment stabilized (Figure 3d). This shows that the addition of microbial agents can increase the nutrient content of the tomato stalk composting process, which can promote the growth of nitrifying bacteria, convert ammonia into nitrate and effectively increase the nitrate nitrogen content. The nitrification index (NH₄⁺/NO₃⁻ ratio) reflects the maturity of the compost, and a value less than 3 indicates maturity [28]. The nitrification index of all treatments in this study was less than 3, indicating that the compost reached the putrefaction requirement.

3.1.4. Changes in TP, AP, TK and AK Content

Phosphorus is an essential element for plant growth and is often used as an inorganic fertilizer in agricultural production. The TP content increased rapidly in the initial composting stages, fluctuated slightly after 9 d and finally stabilized (Figure 4a). Various forms of phosphorus are converted during composting by microbial action, such as the insoluble phosphorus into AP, which is more easily taken up by crops. These transformations are dynamically balanced during decaying phases when the TP content gradually stabilizes. At the end of composting, T1 had a 270.3% increase in TP content, significantly higher than control T6 (p < 0.05). AP levels increased rapidly on the 1 d of composting and fluctuated until stabilizing thereafter (Figure 4b), and AP release was associated with organic acid compounds reacting with organophosphates and biodegradable organic decomposition [29]. At the end of composting, T1 had a 16.0% increase in AP content, significantly higher than T2 (p < 0.05).

In addition to N and P, the potassium content of the final product plays an important role in improving soil fertility and crop growth [30]. The increase in TK, similar to the increase in TP, is due to the so-called concentration effect that occurs when gas emissions and organic matter decompose [31]. TK levels peaked at 56.21 g·kg⁻¹ on 24 d in treatment T1 and gradually stabilized from 32 d (Figure 4c). TK levels in T1 increased by 56.6%, significantly higher than in T6 (p < 0.05). AK levels were increased overall, with the levels in all treatments except T4 prior to 9 d being 9.3% lower at the end of compost compared to the initial treatment (Figure 4d), and AK levels in T1, T3, T4, T5, and T6 increased by 25.40, 25.75, 17.00, 6.2, and 6.2%, respectively (p < 0.05).

3.1.5. Changes in Germination Index and Cellulose Content

The GI of all treatments before composting remained low (<50%) and there was a high phytotoxicity of the compost (Figure 5a). After turning the pile on 3 d of composting, the microorganisms were exposed to sufficient oxygen for enhanced metabolism, a sharp increase in temperature, and the release of ammonia and short-chain volatile fatty acid acetic acid [32], leading to a decrease in GI. Subsequently, the GI index gradually increased and decomposition was completed first in T3 and T4 at 19 d of composting, with GI greater than 80% continuing until the end of composting. Eventually, T1–T6 had a GI greater than 80% at the end of composting, and all treatments met the criteria for compost decay. GI of T2 and T4 was as high as 105.6 and 103.5%, indicating that inoculation can effectively accelerate compost decay to reduce toxicity.

Thermophilic microorganisms in the composting process can decompose cellulose in cellulosic waste to different degrees, and the degradation rate of cellulose gradually increased as the composting progresses (Figure 5b). The cellulose degradation rate in inoculated at the beginning of composting was lower in treatments T1–T5 than in T6, which may be due to the competition between the added and indigenous microorganisms in the initial composting material. The degradation rate of cellulose in T3 and T1 was obviously higher from 9 d of the high-temperature stage of composting. Usually, cellulose can be broken down into polysaccharides, simple fermentable sugars and amino compounds, which are the basic substrates for humic substance formation [33]. The cellulose degradation rate leveled off at the later stages of composting and was significantly higher in T1 than in T6 at the end of composting (p < 0.05).

4. Microbial Community Succession in Composting Process

4.1. Alpha Diversity Analysis of Microbial Communities

High-quality bacterial and fungal sequences of 37091–77117 and 65489–109782, corresponding to 309–1499 and 106–345 operational taxonomic units (OTUs), respectively, were obtained from samples at different stages of composting and clustered based on a 97% similarity. Alpha diversity of bacterial and fungal communities during the composting process is shown in Table S2 (Supplementary Files). In terms of bacterial communities, the Chao1 index gradually increased in T1, T2, and T5, reaching a maximum of 55 d. The Chao1 index in the T1 treatment increased 276.8% from the initial time and was 3.6 times higher than that in T6; the Chao1 index in the T3, T4, and T6 treatments showed a trend of increasing and then decreasing, reaching a peak at 24 d. Shannon and Simpson’s indices reflected the diversity of species communities, and the diversity of bacterial communities in T1, T3, T4, and T6 was highest during the cooling period, and the Shannon index in the T1 treatment increased by 76.0% from the initial and was 3.2 times higher than that in T6. T2 and T5 were highest during the decaying period.

In terms of fungal communities, the Chao1 index was greatest at 55 d in T1, T2 and T5 treatments, and at d 24 in T3, T4 and T6, again with the highest number of fungal species in the decay and cooling phases. Shannon and Simpson’s indices continued to increase in T5 treatment, peaking at 55 d. The T5 treatment significantly increased the cooling and decay phases of the bacterial Chao1 index. The coverage index is commonly used to describe the depth of sequencing and presents results that accurately reflect the depth of sequenced samples. The Coverage index was greater than 0.99 in all compost samples, indicating the reasonableness of the sequencing data.

Overall, the alpha diversity index of bacterial communities was significantly higher than that of fungal communities, indicating that bacterial communities are more abundant in compost than fungal communities. This is consistent with the results previously reported in the literature [34]. Inoculation was able to significantly increase the number of species and community diversity of bacterial and fungal communities in compost.

4.2. Beta Diversity of Microbial Communities

To assess the differences in the composition of microbial communities in the composting process samples, PCoA analysis was performed using the weighted UniFrac metric and the results showed significant temporal succession patterns for bacteria (ANOSIM, R = 0.7338 p = 0.001 ***) and fungi (ANOSIM, R = 0.5946 p = 0.001 ***). For bacterial communities, PCoA1 and PCoA2 explained 46.99% and 15.38% of the total variance, respectively, with samples from T1d1, T2d1, T4d1 and T6d1 clustered in one group during the warming period, while samples from T3d1 and T5d1 clustered in one group. It indicates that the samples of T1, T2, T4 and T6 composting 1 d are similar in composition, and the samples of T3 and T5 are similar in structure. The samples from T1d5-T6d5 clustered together more intensively during the high-temperature period, and the samples from T1d24-T6d24 and T1d55-T6d55 clustered closely together, indicating that the composition was similar between the samples of the compost cooling and decomposition periods, and the bacterial community structure gradually stabilized in the later stages of composting (Figure 6a). For the fungal communities, PCoA1 and PCoA2 explained 36.23% and 20.04% of the total variance, respectively. Compared to the bacterial community structure, the fungal communities differed significantly in composition structure between composting stages. Samples from the 1 d and 5 d of composting were clustered in a more concentrated manner, while samples from the 24 d and 55 d were distant and dispersed from each other, indicating that a significant community succession occurred in the later stages of fungal community composting (Figure 6b).

4.3. Changes in Bacterial Community Structure during the Composting Process

Information on the number and structure of microbial communities from composting environments was obtained by 16SrRNA sequencing to analyze changes in their composition. The relative abundance of bacterial communities at the phylum level, with 30 bacterial phyla detected, is shown in Figure 7a. Among them, six phyla had relative abundance greater than 2%: Proteobacteria (32.67%), Firmicutes (28.01%), Actinobacteria (16.83%), Bacteroidetes (12.59%), Gemmatimonadetes (2.68%), and Deinococcus–Thermus (2.03%). The relative abundance of Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes was 32.67, 28.01, 16.83, and 12.59%, respectively, accounting for 90.1% of the bacteria. These four major bacteria were also found during composting of other plant wastes [35].

An abundance heat map of bacterial communities at the genus level is shown in Figure 7b. Columns represent individual samples, colonies are indicated crosswise, and the color blocks represent species abundance. The redder the color, the higher the relative abundance, and vice versa. Staphylococcus (9.26–58.31%), Corynebacterium (5.91–9.66%), Brachybacterium (4.22–13.51%), Gracilibacillus (1.62–6.00%), and Oceanobacillus (1.11–1.99%) were the dominant genera (>1%) in all treatments during the warming period. The relative abundance of Bacillus in T4 and T6 during the heating phase was 18.82 and 25.61%, and due to its prevalent heat resistance in lignocellulose composting [36], the genus is also common in manure composting systems [37,38], suggesting that Bacillus is highly resilient and adaptable to different composting habitats. Treatment T5 significantly increased the relative abundance of Galbibacter and Halomonas at the beginning of composting (1 d) (p < 0.05). The study found that Cellvibrio, a thermophilic bacterium with the ability to degrade polysaccharides attached to plant cellulose, was highly adaptable to the environment [39]. As the temperature decreased, the relative abundance of Corynebacterium, Brachybacterium, Galbibacter, Lysobacter, and Gracilibacillus declined.

4.4. Changes in the Structure of Fungal Communities during Composting

A taxonomic map of the fungal communities at the phylum level is shown in Figure 8a, indicating six fungal phyla detected in all samples. Throughout the composting process, Ascomycota was the main group (average relative abundance 93.99%), followed by Basidiomycota (3.51%), and fungi_unclassified (2.48%), and Zygomycota (0.02%) and Chytidiomycota (0.003%) were found in small quantities. The results showing the dominant position of Ascomycetes in the whole composting process are consistent with previous research reports [40]. Both Ascomycota and Basidiomycota belong to saprophytic macrofungi [41]; the average relative abundance of Ascomycota during compost warming and high-temperature periods was as high as 98.35%, and it has been reported to be the main species in lignocellulose degradation during composting [42]. The relative abundance of Basidiomycota and fungi_unclassified increased during the compost cooling stage, most significantly in T5, and then gradually decreased during the decaying stage.

The changes in fungal genera at each stage of composting are shown in Figure 8b. Microascus, Cladosporium, and Davidiella in Zygomycetes had fairly high abundance throughout the composting process and were the absolute dominant fungal genera. Microascus has been reported to be one of the few fungal communities capable of causing human diseases [43]. The relative abundance of Microascus in T2, T3, and T6 was 57.37, 27.55, and 36.43%, respectively, during the warm-up period of composting, and decreased to 7.79, 3.65, and 7.54% at the end of composting. The removal rate of Microcystis aeruginosa was 86.42, 86.75, and 79.30% in the three treatments. This shows that the addition of fungicides in T2 and T3 had a better killing effect on pathogenic fungi. The relative abundance of Acremonium in all treatments was generally low at the high-temperature stage of composting and increased significantly at the cooling stage, and they became the dominant fungi at the cooling stage.

5. Correlation between Physical and Chemical Indicators and Microorganisms

Correlation of Compost Physicochemical Indicators with Bacteria and Fungi

To investigate the relationship between the physicochemical indicators (T, pH, EC, GI, TOC, TN, NH₄⁺-N, NO₃⁻-N, TP, AP, TK, AK) and the microbial community during composting, redundancy analysis (RDA) was performed based on the relative abundance of bacteria and fungi (Top15) with the physicochemical indicators.

Table 1. Eigenvalues, F-values and p-values of environmental factors on changes in bacterial community structure in RDA.

Physical and Chemical Factors	Explains%	Contribution%	Pseudo-F	p
Cellulose	51.8	59.4	23.7	0.002
TP	11.1	12.7	6.3	0.002
AP	6.8	7.8	4.5	0.002
T	3.8	4.4	2.7	0.014
NH4+-N	3	3.4	2.3	0.024
NO3−-N	2.6	2.9	2.1	0.046
TN	1.8	2	1.6	0.168
AK	1.5	1.8	1.3	0.254
pH	1.4	1.6	1.2	0.34
EC	1.3	1.5	1.1	0.372
GI	1	1.2	0.9	0.522
TOC	0.8	0.9	0.7	0.674
TK	0.3	0.4	0.2	0.97

Note: The bolded parts of the table indicate the physicochemical factors that have a significant effect on the bacterial community. Same as below.

shows the results of the RDA analysis between environmental factors and bacterial communities, where all physicochemical indicators measured explained 87.2% of the variation in bacterial communities (70.6% adjusting for explanatory variables). The effects of each parameter on the bacterial community were as follows, Cellulose (51.8%), AP (11.1%), T (6.8%), TP (3.8%), NH₄⁺-N (3.0%) and NO₃⁻-N (2.6%) were the six physicochemical parameters that significantly affected the bacterial community structure (p < 0.05). While TN (1.8%), AK (1.5%), pH (1.4%), EC (1.3%), GI (1.0%), TOC (0.8%), and TK (0.3%) did not significantly affect the changes in bacterial communities. TP, TK, NO₃⁻-N, AK, EC, and GI were positively correlated with the samples at the cooling and decaying stages of each treatment compost (Figure 9a). As for fungi, all physicochemical indicators measured explained 75.4% of the variation in fungal communities (adjusted for explanatory variables 43.4%), with T (44.4%) and GI (7.3%) being the two physicochemical factors that significantly affected the variation in fungal communities (p < 0.05), while AK (5.7%), cellulose (3.8%), TOC (3.1%), pH (2.9%), AP (2.2%), NH₄⁺-N (2.0%), TP (1.7%), NO₃⁻-N (0.8%), TN (0.8%), EC (0.5%) and TK (0.3%) had insignificant effects on the fungal community (

Table 2. Eigenvalues, F-values and p-values of environmental factors on changes in fungal community structure in RDA.

Physical and Chemical Factors	Explains%	Contribution%	Pseudo-F	p
T	44.4	58.9	17.6	0.002
GI	7.3	9.7	3.2	0.018
AK	5.7	7.6	2.7	0.074
Cellulose	3.8	5	1.9	0.118
TOC	3.1	4.1	1.5	0.196
pH	2.9	3.8	1.4	0.242
AP	2.2	3	1.2	0.31
NH4+-N	2	2.6	1	0.33
TP	1.7	2.2	0.9	0.472
NO3−-N	0.8	1	0.4	0.8
TN	0.8	1.1	0.4	0.792
EC	0.5	0.6	0.2	0.924
TK	0.3	0.4	0.1	0.962

), which were distant and more dispersed across time periods for each treatment relative to bacteria. Cellulose, T, AP TOC, TN, and NH₄⁺- N were positively correlated between samples in the warming and high-temperature periods of each treatment, and TP, NO₃⁻-N, and TK were positively correlated with samples in the cooling and decaying periods.

Spearman correlation between bacterial and fungal communities and physical and chemical factors during composting is shown in Figure 9a,b, in which AP, Cellulose, T, TN, NH₄⁺-N and TOC are associated with Halomonas and Lysobacter in Proteobacteria, Staphylococcus, Jeotgalicoccus, Gracilibacillus and Oceanobacillus in Firmicutes, Brachybacterium and Corynebacterium in Actinobacteria, Sphingobacterium in Bacteroidetes and Cyanobacteria in Oxyphotobacteria_unclassified showed a significant positive correlation. It shows that these microorganisms play an important role in the decomposition of organic matter and the formation of nutrients. Firmicutes can secrete a variety of proteases and pectinases, which can degrade cellulose and other hard-to-decompose carbohydrates. TP, TK and NO₃⁻-N are negatively correlated with the above microorganisms, while they are negatively correlated with Chelativorans and Methylloccaceae_unclassified, BIrii41_unclassified, Membranicola, Truepera, Actinomadura, Longispora, Limnochordaceae_unclassified, Luteimonas, S0134_terrestrial_group_ unclassified, unclassified, Fodinicurvataceae_unclassified and Gammaproteobacteria_unclassified shows a significant positive correlation. In terms of fungal communities, TN, TOC, AP, Cellulose, NH₄⁺-N, and T, all correlated with Ascomycota_unclassified, Microascus, Wallemia, Gibberella, Verticillium, Cladosporium Sarocladium, Davidiella, and Trichothecium were positively correlated, while TP, TK, and NO₃⁻-N were negatively correlated with the above microorganisms, and with Coprinopsis, Fungi_unclassified, Acremonium, Chaetomiaceae_unclassified, Chaetomium, Basidiomycota_unclassified and Microascaceae_unclassified were positively correlated.

6. Discussion

6.1. Influence of Inoculants on Physicochemical Parameters of Compost

Successful composting is inextricably linked to many environmental factors that directly or indirectly affect microbial activity. Temperature one of the most important factors that directly affect the composting process usually reflects the activity of soil microorganisms and their utilization of organic matter in the environment [44]. Inoculation with microbial agents can rapidly increase the temperature of compost, and Liu et al. [45] found that the addition of combined microbial agents can promote the decomposition of organic matter in the pile, generating more heat and thus increasing the temperature of the pile. Various pathogens can be killed when the compost temperature exceeds 60 °C and lasts for at lasts 5 d, and all six treatments in this study met the sanitary waste treatment requirements.

The pH value reflects the acid–base environment of microorganisms during composting, with an initial pH value of 6.9, which is favorable for microbial metabolic activity [46]. In the early stages of composting, pH rises rapidly, which may be due to the strong ammonification of microorganisms, in which ammonia is released by the decomposing of nitrogenous organic matter [47]. Zhang et al. [48] reported that H⁺ released through nitrification caused a decrease in pH at the beginning of composting, and the same result was found in this study. The pH of treatment T6 showed a small fluctuation at 14 d of composting, while the pH of T1-T5 decreased significantly, probably due to the decomposition of organic matter by bacteria, producing organic acids [49]. From 19 d onwards, the pH stabilized, and the pH of T1–T6 ranged from 7.9 to 8.6 after composting. The ideal pH for microbial decomposition of organic matter has been reported to be between 6.7 and 9.0 [50], and the pH variation of all treatments in this study was within this reasonable range.

EC values reflect the content of soluble salts during the composting process. The EC values of raw compost materials in this study were generally high, and with increased pile temperature, a large amount of ammonia volatilization reduced the content of water-soluble salts, resulting in a rapid decrease in EC values at 1 d. Zhang et al. [2] reported similar results in a study of major lignocellulosic degrades in tomato straw compost. This is not unrelated to the high nutrient content of the compost feedstock itself. Usually, the EC values after the decaying process is completed are higher than the initial values due to the reduction in compost mass, which makes it more concentrated.

The NH₄⁺-N content increased rapidly on 1 d. Higher temperatures and pH are favorable for microorganisms to convert more organic nitrogen to NH₄⁺ and increase the NH₄⁺-N content significantly [51]. A significant decrease occurred from 9 d, which may be due to NH₃ volatilization from bacterial ammonification. In addition, it has been claimed that increased microbial nitrification and immobilization may lead to a decreased NH₄⁺-N concentration during the composting process [52]. The average NH₄⁺-N content in each treatment at the end of final composting was about 41 mg·kg⁻¹. Some studies have shown that the number and species diversity of microorganisms in compost are directly related to the NH₄⁺-N level [53]. In this study, NH₄⁺-N levels were found to peak successively at the high-temperature stage of composting (Figure 3a), while the alpha diversity of both bacterial and fungal communities reached a maximum at the late stage (Table S2), and no link was found between the two.

The relative content of NO₃⁻-N decreased at the beginning of composting. Tiquia and Tam [54] reported that nitrification rarely occurred at temperatures above 40 °C, suggesting that nitrifying bacteria are intolerant to high temperatures and the lower NO₃⁻-N content at the beginning may be due to high temperatures inhibiting the activity of nitrifying microorganisms, resulting in slow formation and accumulation of NO₃⁻-N. In addition, the high concentration of NH₄⁺-N strongly inhibits the growth of autotrophic nitrifying bacteria and weakens their nitrification ability. The growth rate of NO₃⁻-N content in treatments T1–T6 showed maximum levels at this stage from 19 d to 24 d of composting, indicating that nitrification mainly occurred during this period.

A decrease in TOC content was observed during all treatment processes. The loss of TOC has been reported to be due to microbial activity and mineralization of organic matter during the composting process [55]. The TN content was reduced at the end of composting in all treatments; Zhang et al. [56] explained inoculation with microorganisms during the warming phase accelerates warming and leads to volatilization of TN in the form of ammonia. This also shows that the addition of microbial agents is not effective in increasing the content of the whole mono in the compost.

Phosphorus and potassium play indispensable roles in plants, for example, by increasing their ability to adapt to external environmental conditions. In this study, the total phosphorus and potassium contents were elevated due to the rapid decomposition of easily degradable organic matter, the volatilization of some gaseous substances, and the decrease in dry matter mass, resulting in the so-called concentration effect of increased TP content [57]. At the end of composting, the TP and TK contents of treatment T1 increased by 270.3 and 56.6%, respectively, which were significantly higher compared to T6. This finding indicates that inoculation with microbial agents can effectively increase the nutrient content of compost.

The germination index (GI) can reflect compost characteristics and is used to evaluate phytotoxicity and compost decay. A GI greater than 80% indicates that the compost is not toxic to plant growth, which is one of the basic requirements for compost decay to be non-toxic [58], and all treatments met this requirement at the end of composting. Initially, the GI was found to be low and the seeds could not grow normally, then high temperatures killed some of the harmful substances, and the content of toxic substances in the compost gradually decreased and the GI gradually increased. Li et al. [59] used a bacterial composite consisting of a combination of Bacillus altitudinis and Bacillus subtilis sub sp. Stercoris for inoculation during the composting of corn stover, and the GI reached more than 80% at 24 d. This indicates that inoculation with the bacterial agent was able to reduce the toxicity of the compost to promote seed germination.

6.2. Effect of Inoculants on Microbial Community Composition in Composting Process

The essence of straw composting is the metabolic biochemical process of microbial decomposition and organic matter conversion. The metabolic capacity and structure of microbial communities are the key factors affecting aerobic composting.

Alpha diversity is mainly used to reflect species richness and evenness and sequencing depth. The alpha diversity in different compost types shows great variation, and the diversity index of bacterial communities was found to have a decreasing trend at the end of composting of citrus peel after inoculation with microorganisms, which did not increase the bacterial diversity [60]. Zhong et al. [61] found that the Chao1 index of bacterial communities in a cattle manure composting system decreased significantly during the high-temperature phase of composting and the Shannon index was lowest during the cooling phase. However, in a cattle manure and rice straw co-composting system, Ren et al. [62] found that both the Chao1 and Shannon indexes of bacterial communities had maximum values during the warming stage of composting because sufficient nutrients were available during this stage to facilitate microbial growth and metabolism. In this study, the alpha diversity index of both bacterial and fungal communities was found to reach a peak at the late stage of composting, which may be related to the fact that the excessively high pile temperature inhibited the activity of a large number of thermophilic microorganisms. The growth and reproduction of large numbers of diverse thermophilic microorganisms also increased significantly during the cooling stage. This suggests that inoculation with mycorrhizal agents can significantly increase the species abundance and community diversity of microorganisms in the late composting stage.

The relative diversity of bacterial communities in composting systems at the phylum level was essentially the same in different treatments and sampling periods; however, the relative abundance of phyla differed between treatments and sampling stages, as did the relative abundance of dominant phyla. Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes are the most abundant phyla commonly found in many solid waste composting systems [63]. These four phyla were also dominant in this study. Zhang et al. [64], in a study of green waste composting, reported that Actinobacteria was the most abundant bacterial phylum identified, followed by Proteobacteria. This suggests that the type of compost material affects the microbial community and relative abundance. It has been shown that Bacteroidetes, Firmicutes, and Proteobacteria play crucial roles in the decomposition of lignocellulose, the mineralization of organic matter, and carbon and nitrogen cycling in compost [65]. Actinobacteria are capable of producing heat-tolerant spores, which help them to resist unfavorable environments and promote lignocellulose degradation by inducing microorganisms that produce lignocellulose hydrolases [66].

At the genus level, a total of 30 bacterial genera with abundance greater than 1% were detected, with Staphylococcus in the Firmicutes phylum being the only dominant genus (relative fraction > 1%) present in all treatments in all periods; most Staphylococcus are able to catabolize glucose, maltose, and sucrose, producing acid but not gas, and mannitol [67]. The abundance of Staphylococcus in each treatment decreased significantly with increasing temperature during the high-temperature period because these bacteria are thermophilic and cannot survive at high temperatures. Bacillus belongs to Firmicutes, with heat- and fungus-resistant properties, and can produce a variety of degrading enzymes during organic solid waste composting [68].

Ascomycota dominated the fungal community throughout the process (Figure 8a). Ascomycota can secrete a variety of cellulose and hemicellulose-degrading enzymes and efficiently utilize nutrients from compost [69]. At the fungal genus level, the dominant fungal genera were Microascus, Cladosporium and Davidiella and Ascomycota_unclassified during the warming and high-temperature periods, and the relative abundance of Ascomycota_unclassified decreased during the compost cooling and high-temperature periods; and Acremonium became an additional dominant genus at this stage. Cladosporium and Gibberella have been reported as tomato pathogens [70]. The abundance of Cladosporium was generally high at the beginning of composting in all treatments, and its degradation in T3 and T4 at the decomposition stage was more than 90%. The relative abundance of Gibberella was found to decrease in this study, while its degradation rate in T2 and T3 at the end of composting reached more than 90%. This indicates that inoculation reduces the abundance of pathogenic fungi in compost. In addition, according to Homans and Fischer, composting produces strong-smelling sulfur compounds due to incomplete or inadequate aeration [71]. At the end of composting, the irritating odor was lower in T1-T5 compared to the control group T6. This is because the microbial agents we use are environmentally friendly and do not contain any chemicals, hormones, growth regulators or other substances that pollute or harm the environment.

6.3. Correlation between Physical and Chemical Indicators of Compost and Microorganisms

In general, the temperature is the most important environmental factor in the composting process [72]. In this study, the temperature was found to significantly affect bacterial and fungal communities; the bacteria, and the Proteobacteria, Actinobacteria, and Bacteroidetes of bacteria and the fungi Ascomycetes and Basidiomycetes of fungi were significantly correlated with temperature. Many genera in these phyla, such as Bacillus, Galbicella, Pusillimonas, Lysobacter, Halomonas, Cladosporium, and Acremonium, released heat from the decomposition of organic matter during periods of high temperature, and such thermophilic microorganisms rapidly increase the pile temperature rises rapidly.

Phosphorus is an essential macronutrient essential for plant growth, and also plays an essential role in the formation of macronucleic acids, adenosine triphosphate (ATP), and some intermediates of sugar metabolism in microorganisms. Many bacteria and Actinomycetes release phytases and phosphatases that can break down organic matter containing phosphorus, which can be taken up by plants. AP content was found to significantly influence the changes in bacterial communities, with the fastest growth rate of AP content in each treatment observed at the initial stage, while Staphylococcus, Corynebacterium_1, and Brachybacterium. were the dominant species in the ascending stage. The dominant species at that stage may be involved in the synthesis of AP. NH₄⁺-N and NO₃⁻-N significantly affected the bacterial communities, while the effect on the fungal communities was not significant, suggesting that bacterial growth is more sensitive to changes in NH₄⁺-N and NO₃⁻-N than fungi, probably because NH₄⁺-N is the preferred nitrogen source for most microorganisms [73]. During the composting of agricultural wastes, NO₃⁻-N and NH₄⁺-N can affect or be affected by bacterial species but not fungal species [21].

GI has been used to evaluate the decay of compost, and in the present study, GI was found to significantly affect the succession of fungal communities; it has also been reported that GI is closely related to the content of organic acids, such as phenols, in compost [74]. The genera Davidiella, Chrysosporium, and Sarocladium were observed to have a significant association with GI, suggesting that these fungi may be beneficial for improving GI. Other indicators did not have a significant effect on the succession of microbial communities, but also did not indicate that there was no effect on bacterial and fungal communities. Previous studies found that pH is an important determinant of bacterial community diversity, while TOC, which provides nutrients essential for microbial growth, has been reported as an important factor affecting microbial community structure and metabolic type.

7. Conclusions

• In this study, it was found that the pile temperature increased rapidly in the 1st d after inoculation with the fungicide, and compared with T6, T1, T2 and T5 could effectively extend the high-temperature period, effectively killing harmful substances and weed seeds in the compost and realizing the resource utilization of tomato stalks.
• The degradation rate of TOC in T6 reached 57.0%, which was significantly different from other treatments. The TN content of each treatment showed different degrees of reduction. the NH₄⁺-N content in T1 was reduced by 92.3% compared with the initial one, and the difference was not significant compared with T6. After inoculation, TP content in T1 treatment was significantly higher (p < 0.05) especially in T1, AP content in T1 increased by 16.0%, significantly higher than T2 (p < 0.05), but not significantly different from T6. TK content in T1 increased by 56.6%, significantly higher than the T6 treatment (p < 0.05). The differences were not significant but were significantly higher than the other inoculated groups. The GI at the end of composting was more than 80%, so it can be said that the compost reached the standard of decomposition.
• The results of α and β diversity analysis showed that the bacterial α diversity index was significantly higher than that of fungi in the tomato stalk composting system, and the Chao1 and Shannon indices gradually increased in T1, T2 and T5 in the bacterial community, and the Chao1 and Shannon indices in T3, T4 and T6 were the largest in the cooling stage. The Chao1 index in the fungal community was greatest at 55 d in T1, T2 and T5 treatments, and at 24 d in T3, T4 and T6, while the Shannon index was highest at the cooling stage in each treatment. T1 treatment significantly increased the abundance and diversity of the bacterial and fungal communities and improved the composition of the microbial community. Both bacteria and fungi had significant temporal succession patterns, and bacterial communities were more closely aggregated among samples at different periods of each treatment, while fungal communities were relatively dispersed among them, indicating that inoculation had a greater effect on fungal communities.
• Proteobacteria, Firmicutes, Actinomycetes and Bacteroides are the four most abundant bacterial phyla. T1 significantly increases the abundance of Proteobacteria at the high-temperature stage and decreases the abundance of Staphylococcus. T5 significantly increased the relative abundance of Lysobacter in a high-temperature period. Ascomycetes is the absolute dominant phylum during composting. The abundance of Basidiomycetes in the T2 and T5 cooling stages increased significantly, and T2 and T3 treatments significantly reduced the relative abundance of pathogenic fungi.
• The results of RDA and Spearman correlation analysis showed that Cellulose, AP, T, TP, NH₄⁺-N and NO₃⁻-N were the six physicochemical parameters that significantly affected the structure of bacterial communities, and T and GI significantly affected the two physicochemical parameters of fungal communities.