1. Introduction
Strawberry (Fragaria × ananassa Duch.) is a perennial herbaceous plant of the Rosaceae strawberry genus. Its fruit is red, sweet and sour; it is rich in vitamin C, folic acid and phenolic components; and it is widely planted worldwide [1,2,3]. However, owing to the limited amount of cultivated land, the phenomenon of continuous cropping is very common in the process of strawberry planting. The problems of soil ecosystem imbalance, severe soil-borne diseases, weak plant growth, and declining fruit quality and yield caused by continuous cropping are also increasingly prominent, which severely restricts the sustainable development of the strawberry industry [4,5].
To date, chemical agents to disinfect the soil, organic fertilizers, microbial inoculants, and other methods have been used to control the obstacles to continuous cropping [6]. Dazomet is a broad-spectrum soil fumigant that has been widely used for the prevention and control of soil-borne diseases of crops. It has characteristics of high efficiency, simplicity, and low toxicity [7,8]. Microbial inoculants are made of one or more microorganisms that can improve soil properties, improve crop agronomic traits, and improve crop quality and yield [9,10]. In recent years, studies have shown that after chemical fumigation and disinfection of soil, microbial inoculants applied to the soil can account for the shortcomings of using soil chemical disinfection which together kill beneficial soil microorganisms and can solve the problem of using microbial inoculants alone to overcome continuous cropping obstacles over the long term. For example, Wu et al. [11] reported that soil fumigation combined with microbial inoculants can effectively optimize the soil ecological environment and reduce the occurrence of soil-borne diseases. Cheng et al. [12] reported that the application of microbial inoculants can restore the microbial community after fumigation and inhibit the development of pathogens. Li et al. [13] reported that after dazomet fumigation, the addition of soil amendments such as Bacillus biofertilizers could significantly increase soil biological activity, promote strawberry growth, and inhibit pathogenic bacteria to varying degrees.
Trichoderma can effectively inhibit or degrade harmful substances in the crop rhizosphere and promote plant growth [14,15,16]. T. harzianum is one of the most widely studied Trichoderma strains. As a microbial inoculant, it has been shown to promote plant disease resistance and improve the rhizosphere microecological environment [17]. T. harzianum is more commonly used to enhance disease resistance in strawberries, but the effects of adding T. harzianum on the microbial diversity of strawberry soil after dazomet fumigation have not been reported [18,19]. Therefore, based on previous studies on the effects of dazomet fumigation and microbial inoculants on the growth and development of other crops and soil ecological environment, this study selected strawberry continuous cropping soil treated with dazomet and T. harzianum chlamydospore inoculants, and analyzed the soil microbial community and composition of different treatments. The relationship between the changes of soil microbial community and composition with soil continuous cropping obstacles was discussed in order to clarify the effects of dazomet and T.harzianum treatment on the diversity of strawberry soil microbial community and provide a scientific basis for solving the problem of strawberry continuous cropping obstacles.
2. Materials and Methods
2.1. Experimental Materials
The organic fertilizer used was cow manure compost, which was purchased from Junlebao Ranch (Shijiazhuang, China). The current study used a ‘Gongxin’ 98% dazomet microparticle agent that was produced by Nantong Shizhuang Chemical Co., Ltd. (Nantong, China). ‘Shibeijian’ Trichoderma harzianum chlamydospore inoculant was produced by Hainan Jinyufeng Biological Engineering Co., Ltd. (Haikou, China), and the effective viable count was ≥200 million·g−1. The strawberry variety used herein was the main local variety, ‘Hongyan’.
2.2. Experimental Methods
The experiment was carried out in the greenhouse of Junlebao Ecological Fruit and Vegetable Garden in Luquan District of Shijiazhuang city in China from July 2022 to April 2023. Strawberry had been continuously planted in the greenhouse for 10 years. The soil was sandy loam with medium fertility, with uniform soil fertility and good water conservation conditions. Before strawberry planting, the soil was prepared and fertilized, and 2000 kg of organic fertilizer applied per 667 m−2. The ridge height was 40 cm, the ridge width 50 cm, and the ridge spacing 40 cm. Strawberry seedlings were planted in 2 rows per ridge, the plant spacing was 18 cm, and the planting density was 8,000,667 m−2. The soil organic matter content was determined to be 20.13 g·kg−1, the alkali hydrolysable nitrogen content 102.03 mg·kg−1, the available phosphorus content 162.37 mg·kg−1, the rapidly available potassium content 303.33 mg·kg−1, and soil pH 7.0. A single-factor randomized block design was used in the experiment. Four treatments were set up, which included soil before dazomet fumigation (M0), soil after dazomet fumigation (M1), soil without T. harzianum after dazomet disinfection (H0), and soil with T. harzianum after dazomet fumigation (H1). Each treatment included 200 strawberry plants and three replicates.
2.2.1. Dazomet Fumigation Treatment
After soil preparation and fertilization, dazomet was evenly applied to the soil (25 kg 667 m−2). After rotary tillage and mixing, the film was immediately covered and fumigated. A polyethylene native film with a thickness greater than 0.08 mm was selected, and the closed fumigation time was 30 days. After fumigation, the film was removed, the soil was ploughed to a 30 cm depth, and aerated for 10 days. Soil samples (5–30 cm topsoil) were collected before and after fumigation with a soil drill using a three-point sampling method, and each treatment was repeated three times. During soil collection, the top 5 cm of soil was removed, and an appropriate amount of soil sample was taken according to a quartering method and transported to the laboratory in a sealed sterile plastic bag. After the soil was passed through a 2 mm sterilized sieve, it was packed into a liquid nitrogen freezer for 3 h, and stored at −80 °C for later use. The soil samples were numbered soil before dazomet fumigation (M0) and soil after dazomet fumigation (M1).
2.2.2. Microbial Inoculant Treatment
After fumigation, strawberry plants were planted normally. Immediately after planting, the Trichoderma harzianum chlamydospore inoculant was applied with water drip irrigation (at the recommended concentration of 1 kg 667 m−2, and the control was not supplemented with T. harzianum chlamydospore inoculants. Three months after planting, soil was collected at the maturity stage (early fruiting stage) of the first fruits of the strawberry plants, and the sampling method was the same as that used during the dazomet fumigation test. H0 corresponded to soil samples with no T. harzianum, and H1 corresponded to soil with T. harzianum added.
2.3. Soil Microbial Genomic DNA Extraction, PCR Amplification, and High-Throughput Sequencing
The soil microbial DNA was extracted with an ‘Omega Bio-tek’ Soil DNA Kit produced by Omega Company in the United States, and the operation steps and methods were performed according to the manufacturer’s instructions. After the integrity of the extracted soil, microbial DNA was detected via gel electrophoresis, and the DNA quality was tested via a NanoDrop spectrophotometer; the qualified samples were screened out. The bacterial 16S-V3V4 (F: ACTCCTACGGGAGGCAGCA; R: GGACTACHVGGGTWTCTAAT) and fungi ITS-V1 (F: GTGCCAGCMGCCGCGGTAA); R: CCGTCAATTCCTTTGAGTTT) primers were synthesized for PCR amplification. The Illumina MiSeq platform was used for high-throughput sequencing, and the sequencing was completed by the Shanghai Pasenuo Biotechnology Company (Shanghai, China) in China.
2.4. Effects of Different Treatments on Growth and Yield of Strawberry
On 20 February, after the strawberry plants entered the fruiting period, strawberry plants obtained from soil before dazomet fumigation (M0), from soil without T. harzianum after dazomet fumigation (H0), and from soil with T. harzianum after dazomet fumigation (H1) were analyzed. Three points were randomly selected for each treatment, and 100 plants were investigated continuously. The number of dead seedlings was determined, the average value taken, and the seedling mortality calculated. Thirty plants were taken from each point, and the number of fruits per plant counted. The average number of fruits per plant was calculated, and the average single fruit weight measured. The theoretical yield = fruit number per plant × fruit weight × plant number per plant × 0.85. (Note: M1 and H0 were the same soil collected before and after fumigation with dazomet, but the collection time was different, so M1 was not included in the statistical analysis of the test results.)
2.5. Statistical Analysis
The DNA fragments of the community were sequenced via the Illumina platform, and the amplified sequence variants (ASVs) were generated after quality control, primer removal, denoising, splicing, and chimera removal via the DADA2 method. Microsoft Excel 2016 was used to organize the data. Alpha diversity (Chao1, observed species, Shannon and Simpson indices) was analyzed via QIIME2 (2019.4), the ggplot2 package in R software (
3. Results
3.1. Evaluation of the Sequencing Depth of the Soil Samples
A total of 1,859,586 pairs of reads were obtained via bacterial sequencing of the four treated soil samples. After splicing, dechimerization, double-ended read splicing, and filtration, 755,274 high-quality sequences were obtained, and 23,244 amplified sequence variants (ASVs) were obtained by clustering. A total of 1,290,078 pairs of reads were obtained via fungal sequencing. After splicing, dechimerization, double-ended read splicing, and filtration, 928,087 high-quality sequences were obtained, and 2967 ASVs were obtained by clustering. The sequencing sequences were randomly selected. At the 100% similarity level, the number of ASVs of the representative substances in each treatment was counted and annotated. The number of extracted sequences and the number of species were used as the coordinate axes to construct a dilution curve. As shown in Figure 1, the curve for the number of bacterial species gradually became flat after the number of sequences reached 25,000, while the curve for the number of fungal species gradually became flat after the number of sequences reached 20,000, indicating that the sequencing data were reasonable and could reflect the bacterial and fungal communities of each treatment sample.
Note: M0—soil before dazomet fumigation; M1—soil after dazomet fumigation; H0—soil in the early fruit phase after dazomet fumigation without the addition of T. harzianum; H1—soil in the early fruit phase after dazomet fumigation and the addition of T. harzianum. The following figures are the same representation.
3.2. Analysis of the Soil Bacterial and Fungal Groups
The Venn diagram intuitively shows the overlap of ASVs between treatments and reflects the number of ASVs that are shared and unique to different treatments. Through the species represented by ASVs, the core fungi of different soil environments were identified. Figure 2a shows that the number of ASVs in the bacterial samples from the different soil treatments was 1291. At 100% similarity, M0, M1, H0, and H1 presented 8227, 6580, 9073, and 9533 ASVs, respectively. Among them, there were 2353 fungal communities in M0 and M1 and 5874 and 4237 unique communities, respectively, with obvious quantitative differences. There were 3116 fungal communities in H0 and H1 and 5957 and 6417 unique communities, respectively, with fewer quantitative differences. As shown in Figure 2b, the number of ASVs in the fungal samples was 183. At 100% similarity, M0, M1, H0, and H1 presented 799, 660, 744, and 764 ASVs, respectively. Among them, there were 300 fungal communities in M0 and M1 and 321 and 265 unique communities, respectively, with obvious quantitative differences. There were 325 fungal communities in H0 and H1 and 288 and 319 unique communities, respectively, with fewer quantitative differences.
3.3. Alpha Diversity Analysis of the Soil Bacterial and Fungal Communities
We used SPSS22.0 to analyze the Chao1 index, species number, Shannon index, and Simpson index of different soil treatments. The Chao1 index and species number can reflect community species richness. Table 1 shows that the bacterial community richness index of M1 was significantly lower than that of M0, and its Chao1 index and species number were 34.76% and 25.88% lower than those of M0, respectively. The number of H1 species was significantly greater than that of H0, and the Chao1 index and species number increased by 12.1% and 9.82%, respectively. The Shannon index and Simpson index can comprehensively reflect the diversity of community species. Compared with those of M0, the Shannon and Simpson indices of M1 were slightly lower. The Simpson index of M0 was significantly greater than that of M1. Compared with those of H0, the Shannon index and Simpson index of H1 increased slightly, but the differences were not significant. Analysis of the richness and diversity indices of the fungal community revealed that the number of fungal community species in M1 was significantly lower than that in M0, and the Chao1 index and the number of species were reduced by 15.08% and 17.18%, respectively, compared with those in H0. Compared with those under H0, the Chao1 index and species number under H1 increased by 3.13% and 2.94%, respectively. The Shannon index and Simpson index of M1 were significantly lower than those of M0, which decreased by 32.05% and 13.98%, respectively. Compared with those of H0, the Shannon index and Simpson index of H1 increased by 11.29% and 4.4%, respectively, and the Shannon index of H1 was significantly greater than that of H0.
3.4. Analysis of the Soil Bacterial and Fungal Community Compositions
3.4.1. Analysis of Soil Bacterial and Fungal Phylum-Level Community Composition
The samples were analyzed at the phylum level. As shown in Figure 3a, the soil bacteria were mainly Proteobacteria, Actinobacteria, Chloroflexi, Firmicutes, and Bacteroidetes. The relative abundance of Proteobacteria was the highest in all the treatments, at 39.77% (M0), 39.24% (M1), 37.96% (H0), and 36.27% (H1). Compared with those in M0, the relative abundance of Actinobacteria in M1 decreased by 4.56%, whereas the relative abundances of Chloroflexi, Firmicutes, and Bacteroidetes increased slightly. Compared with those in H0, the abundances of Chloroflexi, Bacteroidetes, Acidobacteria, Patescibacteria, Nitrospirae, and Entotheonellaeota in H1 increased slightly. According to Figure 3b, the soil fungi were mainly from Ascomycota, Basidiomycota, Mortierellomycota, Mucoromycota, and Chytridiomycota. Ascomycota had the highest relative abundance in all the treatments, at 82.31% (M0), 89.28% (M1), 76.47% (H0), and 83.21% (H1). Compared with those in M0, Ascomycota in M1 increased, whereas Basidiomycota and Chytridiomycota decreased slightly. Compared with those in H0, Ascomycota in H1 increased significantly, whereas Basidiomycota and Chytridiomycota decreased slightly. The results showed that dazomet fumigation and the addition of T. harzianum affected the composition of soil bacteria and fungi.
3.4.2. Analysis of the Soil Bacterial and Fungal Community Compositions at the Genus Level
The top 50 genera according to relative abundance at the genus level were analyzed, and the relative abundance of the remaining species was combined with that of the other species. At the genus level, the compositions of soil bacterial and fungal communities in different treatments were quite different. As shown in Table 2, there were 35, 32, 33, and 32 genera of soil bacteria with relative abundances greater than 0.5% in M0, M1, H0, and H1, respectively. Additionally, there were 20, 9, 19, and 18 genera of soil fungi with relative abundances greater than 0.5% in M0, M1, H0, and H1, respectively.
The abundance data of the top 20 genera were used to construct heatmaps and perform cluster analysis. As shown in Figure 4a, M0 was significantly greater than that of the other treatments with six genera: Flavobacterium, Subgroup_6, Streptomyces, TRA3-20, Skermanella, and Steroidobacter; the relative abundances were 1.16, 3.31, 1.86, 2.14, 2.01, and 1.82, respectively. M1 was significantly greater than that of the other treatments with three genera: MND1, Nitrospira, and CCD24; the relative abundances were 2.16, 1.03, and 1.39, respectively. H0 was significantly greater than that of the other treatments with three genera: Subgroup_10, Micromonospora, Dongia; the relative abundances were 2.16, 1.03, and 1.39. The bacterial community of H1 was significantly greater than that of the other treatments with 1 genus: KD4-96; the relative abundance was 1.12. The bacterial community compositions of the different treatment groups can be divided into three categories: H0 and H1 are clustered into the first category, M1 is the second category, and M0 is the third category. The results revealed that the community compositions of H0 and H1 were the most similar, indicating that at the early stage of strawberry fruit (3 months after dazomet fumigation), the soil bacterial community structures without T. harzianum and with T. harzianum after dazomet fumigation were the most similar.
Figure 4b shows that M0 is significantly higher than the other treatments of the fungal community with four genera: Tetracladium, Cladosporium, Talaromyces, and Ascobolus; the relative abundances were 9.19, 1.73, 2.28, and 1.25, respectively. M1 was significantly higher than the other treatments of the fungal community with three genera: Monilinia, Mycothermus, and Myceliophthora; the relative abundances were 32.69, 34.36, 4.27. H0 was significantly higher than the other treatments of the fungal community with two genera: Iodophanus and Acremonium; the relative abundances were 2.92 and 1.76. There were two genera, Remersonia and Cladosporium, in the fungal community whose abundance in H1 was significantly greater than that in the other treatments, at 2.44 and 1.77, respectively. The composition of the fungal community in the different treatment samples can be divided into three categories: M0 and H0 are clustered into the first category, H1 is the second category, and M1 is the third category.
3.4.3. Analysis of Soil Dominant Bacteria and Fungi Community at Genus Level
With the relative abundance of >1% as the dominant groups standard, M0, M1, H0, and H1 had 16, 15, 15, and 11 dominant bacterial, respectively. By analyzing the dominant groups (Figure 5a), four soil treatments contained nine common bacterial communities, namely SBR1031, BIrii41, Subgroup_6, Bacillus, TRA3-20, Haliangium, MND1, A4b, and Micromonospora. Among them, 11 bacterial communities were shared by M0 and M1, and 7 bacterial communities were shared by H0 and H1. In addition, M0 had three unique dominant bacterial groups, Flavobacterium, bacteriap25, MB-A2-108, M1 had one unique dominant bacterial group, Nitrospira, and H0 had one unique dominant bacterial group, Dongia.
According to Figure 5b, M0, M1, H0, and H1 had 15,8,13, and 11 dominant fungal groups, respectively. The proportion of dominant genera in the whole fungal community of each treatment was 62.32% (M0), 79.07% (M1), 55.87% (H0), and 67.68% (H1), respectively. Analysis of the dominant flora showed that there were three common fungal communities in the four soil treatments, namely Mycothermus, Plectosphaerella, and Ilyonectria. Among them, M0 and M1 shared five fungal communities. H0 and H1 shared seven fungal communities. In addition, there were two unique dominant fungal groups in M0, which were Cladosporium and Ascobolus, and one unique dominant fungal group in H1, which was Cladorrhinum.
3.4.4. Analysis of Beneficial and Harmful Dominant Bacteria and Fungi in Soil at the Genus Level
Figure 6a,b shows that, compared with the M0 treatment before dazomet fumigation, the composition of the bacterial and fungal communities in the soil of M1 after fumigation changed significantly. SBR1031, Bacillus, Haliangium, MND1, A4 b, Micromonospora, Pseudomonas, CCD24, IS-44, Dongia, Subgroup_10, and Nitrospira increased in the bacterial community, while BIrii41, Subgroup_6, TRA3-20, Streptomyces, Skermanella, Steroidobacter, KD4-96, Flavobacterium, bacteriap25, and MB-A2-108 decreased in the bacterial community. In the fungal community, Mycothermus, Monilinia, Myceliophthora, and Acremonium increased, whereas Plectosphaerella, Ilyonectria, and Tetracladium, Fusarium, Iodophanus, Dokmaia, Talaromyces, Remersonia, Stachybotrys, Humicola, Solicoccozyma, Cladosporium, Ascobolus decreased in the fungal community.
Compared with those in H0, Subgroup_6, Bacillus, MND1, A4 b, Skermanella, Steroidobacter, KD4-96, Flavobacterium, bacteriap25, and MB-A2-108 in H1 increased in the soil bacteria, while SBR1031, BIrii41, TRA3-20, Haliangium, Micromonospora, Streptomyces, Pseudomonas, CCD24, IS-44, Dongia, Subgroup_10, and Nitrospira decreased. Mycothermus, Plectosphaerella, Tetracladium, Myceliophthora, Remersonia, Cladorrhinum, and Dorrhinum increased in the soil fungi while Monilinia, Ascobolus, Mortierella, Fusarium, Iodophanus, Dokmaia, Talaromyces, Stachybotrys, Humicola, Solicoccozyma, and Cladosporium decreased in the soil fungi.
3.4.5. Effects of Different Treatments on the Growth and Yield of Strawberry
We used SPSS22.0 to analyze the seedling mortality, number of surviving plants, average fruit per plant, average single fruit weight, and yield of different soil treatments. From Table 3, it can be seen that there were significant differences in seedling mortality, plant survival number, average fruit per plant, average single fruit weight, and yield of strawberry under different treatments. Seedling mortality in soil without dazomet fumigation (M0) was significantly higher than that in H0 and H1 after dazomet fumigation, and the average fruit per plant and yield in M0 were significantly lower than those in H0 and H1. The average single fruit weight and yield were significantly higher in soil with T. harzianum after dazomet fumigation (H1) than those in soil without T. harzianum (H0). The results showed that the addition of T. harzianum after dazomet fumigation could improve the single fruit weight and yield of strawberry and reduce seedling mortality.
4. Discussion
Soil microorganisms are useful indicators of soil health. Previous studies have shown that in a healthy soil ecosystem, beneficial microorganisms and pathogenic microorganisms maintain a dynamic balance in terms of communities and abundance [20]. Soil-borne diseases caused by long-term continuous cropping of strawberry are important causes of reductions in strawberry yield and seedling death [21,22,23].
Dazomet fumigation can kill most pathogenic bacteria in continuously cropped soil. This study revealed that the abundance and diversity of soil bacterial and fungal communities decreased after dazomet fumigation, thereby influencing the composition ratio of soil bacteria and fungi. These findings were consistent with the results of Li et al. [24]. The dominant groups of soil bacteria and fungi, such as Ilyonectria, Fusarium, and other harmful fungi, also changed. Ilyonectria can cause plant root rot and black rot [25]; Fusarium is the main pathogenic fungus of strawberry stem base rot and root rot and is also recognized as an important plant pathogenic fungal group [26]. However, dazomet fumigation also reduced beneficial bacteria and fungi such as Streptomyces, Flavobacterium, Mortierella, and Talaromyces in the soil. Streptomyces is famous for its ability to produce a variety of antifungal and antiviral compounds, which can reduce the incidence and severity of plant diseases caused by fungi [27]. Flavobacterium can promote plant growth and purify contaminated soil [28,29]. Mortierella can promote plant growth and improve the utilization efficiency of phosphorus in soil [30]. Talaromyces is an important biocontrol fungus that can inhibit a variety of pathogenic fungi [31,32]. This may be due to the broad spectrum of biological fumigation, which leads to the killing of beneficial bacteria and fungi while killing harmful bacteria and fungi in the soil.
The application of microbial inoculants is an effective way to improve the structure of soil microbial community and inhibit the growth of pathogenic bacteria and fungi [9]. In this study, after 3 months of dazomet fumigation to the maturity of the first ear fruit, the bacterial community abundance and fungal community diversity increased in the soil treated with T. harzianum (H1) compared with those in the soil without T. harzianum (H0). At the phylum level, Ascomycota increased, whereas Basidiomycota and Chytridiomycota decreased slightly. Ascomycota maintain soil ecosystem stability and nutrient cycling and are important decomposers in soil [33,34]. At the genus level, the abundance of some populations in the soil (H0) without T. harzianum was greater than that in the soil with fumigation (M1); for example, the abundance of the pathogenic fungus Ascobolus increased from 1.57% to 5.75%, and the abundance of Fusarium increased from 0.44% to 2.49%. In addition, cluster analysis revealed that the fungal community compositions of M0 and H0 were the closest at the genus level, indicating that after 3 months, the soil fungal community without T. harzianum gradually approached the initial level before fumigation. Therefore, although the use of dazomet fumigation alone can greatly reduce the number of pathogenic fungi in the soil, its maintenance time is short, and dazomet fumigation alone cannot effectively solve strawberry continuous cropping obstacles. However, in the soil treated with T. harzianum after fumigation (H1), the abundances of pathogenic fungi such as Ascobolus and Fusarium decreased by 3.29% and 1.36%, respectively, compared with those in H0. The beneficial bacteria and fungi Bacillus, Flavobacterium, and Cladorrhinum in H1 increased by 7.9%, 1.1%, and 1.42%, respectively compared with H0. Among them, Cladorrhinum is a unique dominant fungal group of H1 that has broad application prospects in the biological control of plant pathogens, promotion of plant growth, and production of enzyme preparations [35].
5. Conclusions
In this study, the application of dazomet alone reduced the richness and diversity of the soil bacterial and fungal communities, but it also inhibited beneficial bacteria and fungi while killing pathogenic fungi. At the genus level, the abundance of some pathogenic fungi in the soil without T. harzianum (H0) was restored, compared with that after fumigation (M1). In addition, this study found that the fungal community composition of M0 and H0 was the closest by cluster analysis at the genus level, indicating that after 3 months, the soil fungal community without T. harzianum after the initial dazomet fumigation was gradually approaching the level before fumigation. The inhibitory effect of dazomet fumigation on pathogenic microorganisms was maintained for a short period of time, which could not effectively solve the strawberry continuous cropping obstacle. After dazomet fumigation and the addition of T. harzianum, the richness of the soil bacterial community and the diversity of fungal community improved. Additionally, the relative abundance of pathogenic fungi decreased, the relative abundance of beneficial bacteria and fungi increased, seedling mortality decreased, and yield increased. The results showed that the application of 25 kg·667 m−2 dazomet after soil preparation and fertilization and 1 kg·667 m−2 T. harzianum after fumigation could establish a balance in the fungal community of strawberry continuous cropping soil and increase beneficial bacteria species, providing a scientific and effective method to resolve continuous cropping obstacles. In future work, the regulation of soil-borne diseases in strawberry plants by dazomet fumigation combined with microbial inoculants should be further studied to provide a theoretical basis for the prevention and control of soil-borne diseases in strawberry plants and the rational use of microbial inoculants.
J.H. and J.M. conceived and designed the research, and completed the writing of the article; R.W. conducted the experiments; and Y.L. contributed to the research data analysis. All authors have read and agreed to the published version of the manuscript.
The manuscript contains all data that were created or examined during the research.
We thank all the colleagues that helped with the development of the different parts of this manuscript.
The authors declare no conflict of interest.
Footnotes
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Enlarge this image.Figure 1. Bacteria (a) and fungi (b) sequencing dilution curves of soil samples under different treatments in Shijiazhuang, Hebei, China.
Enlarge this image.Figure 2. Venn diagram of soil bacteria (a), and fungi (b), under different treatments in Shijiazhuang, Hebei, China.
Enlarge this image.Figure 3. Analysis of the species composition of the soil bacterial (a), and fungal (b) communities at the phylum level under different soil treatments in Shijiazhuang, Hebei, China.
Enlarge this image.Figure 4. Cluster analysis of bacteria (a), and fungi (b), in different soil treatments at the genus level in Shijiazhuang, Hebei, China.
Enlarge this image.Figure 5. Venn diagram of dominant bacteria (a), and fungi (b), under different soil treatments in Shijiazhuang, Hebei, China.
Enlarge this image.Figure 6. Analysis of the community compositions of the dominant bacteria (a), and fungi (b), under different soil treatments in Shijiazhuang, Hebei, China.
Abundance and diversity indices of the soil bacterial and fungal communities under different soil treatments in Shijiazhuang, Hebei, China.
| Kingdom | Treatment | ASVs | Community Abundance Index | Community Diversity Index | ||
|---|---|---|---|---|---|---|
| Chao1 Index | Observed Species | Shannon | Simpson | |||
| Bacteria | M0 | 8227 | 4564.11 ± 133.25 b | 3775.20 ± 90.35 c | 10.77 ± 0.15 c | 0.9988 ± 0.0001 a |
| M1 | 6580 | 3386.84 ± 413.67 c | 2998.97 ± 259.75 b | 10.43 ± 0.14 bc | 0.9984 ± 0.0001 b | |
| H0 | 9073 | 4968.16 ± 165.88 ab | 3978.27 ± 171.42 b | 10.58 ± 0.27 ab | 0.9978 ± 0.0005 b | |
| H1 | 9533 | 5569.12 ± 392.3 a | 4368.80 ± 224.63 a | 10.91 ± 0.08 a | 0.9985 ± 0.0002 b | |
| Fungi | M0 | 799 | 434.77 ± 21.6 a | 428.93 ± 17.73 a | 5.71 ± 0.4 a | 0.9338 ± 0.023 a |
| M1 | 660 | 369.19 ± 17.68 b | 355.23 ± 11.25 b | 3.88 ± 0.21 c | 0.8022 ± 0.0354 b | |
| H0 | 744 | 404.28 ± 8.82 a | 397.80 ± 22.84 a | 5.05 ± 0.2 b | 0.9061 ± 0.0149 a | |
| H1 | 764 | 416.94 ± 23.69 a | 409.50 ± 19.74 a | 5.62 ± 0.13 a | 0.946 ± 0.0123 a | |
Note: Significant (p < 0.05) differences are expressed with different letters.
Changes in the abundance of different soil treatments at the genus level in Shijiazhuang, Hebei, China.
| Kingdom | Genus | Relative Abundance (%) | |||
|---|---|---|---|---|---|
| M0 | M1 | H0 | H1 | ||
| Bacteria | SBR1031 | 2.11 | 2.81 | 4.78 | 4.39 |
| BIrii41 | 3.12 | 2.83 | 3.17 | 2.71 | |
| Subgroup_6 | 3.31 | 2.65 | 2.40 | 2.82 | |
| Bacillus | 1.87 | 2.23 | 2.90 | 3.13 | |
| TRA3-20 | 2.14 | 1.97 | 1.92 | 1.77 | |
| Haliangium | 1.73 | 2.08 | 2.03 | 1.58 | |
| MND1 | 1.77 | 2.16 | 1.31 | 1.39 | |
| A4b | 1.12 | 1.87 | 1.62 | 1.75 | |
| Micromonospora | 1.03 | 1.28 | 1.71 | 1.27 | |
| Streptomyces | 1.86 | 0.98 | 1.11 | 0.96 | |
| Skermanella | 2.01 | 1.41 | 0.70 | 0.76 | |
| Pseudomonas | 0.73 | 1.54 | 1.34 | 1.16 | |
| Steroidobacter | 1.82 | 1.15 | 0.83 | 0.86 | |
| CCD24 | 0.79 | 1.39 | 1.00 | 0.96 | |
| KD4-96 | 1.03 | 0.99 | 0.94 | 1.12 | |
| IS-44 | 0.71 | 1.29 | 1.12 | 0.87 | |
| Dongia | 0.66 | 0.94 | 1.37 | 0.98 | |
| Flavobacterium | 1.16 | 0.58 | 0.90 | 0.91 | |
| Subgroup_10 | 0.53 | 1.02 | 1.27 | 0.73 | |
| Nitrospira | 0.77 | 1.03 | 0.73 | 0.77 | |
| S0134_terrestrial_group | 0.70 | 0.85 | 0.79 | 0.65 | |
| JG30-KF-CM45 | 0.62 | 0.82 | 0.78 | 0.69 | |
| Acidibacter | 0.98 | 0.73 | 0.71 | 0.46 | |
| 67-14 | 0.82 | 0.72 | 0.61 | 0.71 | |
| S085 | 0.70 | 0.70 | 0.59 | 0.83 | |
| Saccharimonadales | 1.08 | 0.71 | 0.40 | 0.51 | |
| bacteriap25 | 0.64 | 0.46 | 0.70 | 0.75 | |
| Microvirga | 0.67 | 0.60 | 0.47 | 0.59 | |
| TK10 | 0.48 | 0.99 | 0.42 | 0.42 | |
| Chryseolinea | 0.30 | 0.87 | 0.57 | 0.53 | |
| Actinomadura | 1.18 | 0.49 | 0.22 | 0.34 | |
| MB-A2-108 | 0.73 | 0.57 | 0.43 | 0.45 | |
| Aeromicrobium | 0.56 | 0.52 | 0.51 | 0.50 | |
| Mycobacterium | 0.42 | 0.44 | 0.57 | 0.50 | |
| Hyphomicrobium | 0.45 | 0.30 | 0.45 | 0.65 | |
| Sphingomonas | 0.33 | 0.45 | 0.51 | 0.50 | |
| AKYG1722 | 0.21 | 0.41 | 0.66 | 0.49 | |
| Saccharomonospora | 0.51 | 0.36 | 0.44 | 0.44 | |
| Nocardioides | 0.78 | 0.49 | 0.32 | 0.15 | |
| Actinoplanes | 0.35 | 0.45 | 0.47 | 0.44 | |
| Gemmatimonas | 0.39 | 0.47 | 0.42 | 0.41 | |
| Devosia | 0.76 | 0.31 | 0.27 | 0.36 | |
| JG30-KF-CM66 | 0.29 | 0.33 | 0.53 | 0.50 | |
| Actinotalea | 0.44 | 0.32 | 0.33 | 0.51 | |
| Saccharimonadaceae | 0.53 | 0.38 | 0.31 | 0.29 | |
| Blastococcus | 0.30 | 0.35 | 0.43 | 0.43 | |
| OLB14 | 0.48 | 0.28 | 0.28 | 0.44 | |
| Gitt-GS-136 | 0.38 | 0.29 | 0.47 | 0.32 | |
| Ramlibacter | 0.47 | 0.28 | 0.33 | 0.36 | |
| Agromyces | 0.70 | 0.85 | 0.79 | 0.65 | |
| Others | 69.73 | 67.82 | 66.82 | 69.11 | |
| Fungi | Mycothermus | 18.98 | 34.36 | 8.20 | 25.25 |
| Monilinia | 0.31 | 32.69 | 14.97 | 12.07 | |
| Plectosphaerella | 11.70 | 2.91 | 9.26 | 12.55 | |
| Ilyonectria | 3.91 | 1.57 | 5.75 | 4.71 | |
| Tetracladium | 9.19 | 0.22 | 0.69 | 1.07 | |
| Mortierella | 2.41 | 0.57 | 3.24 | 2.58 | |
| Myceliophthora | 0.80 | 4.27 | 0.51 | 2.28 | |
| Fusarium | 2.88 | 0.44 | 2.49 | 1.13 | |
| Iodophanus | 1.47 | 1.08 | 2.92 | 0.76 | |
| Dokmaia | 1.27 | 0.25 | 2.64 | 1.83 | |
| Talaromyces | 2.28 | 1.00 | 1.26 | 0.77 | |
| Acremonium | 0.86 | 1.19 | 1.76 | 0.69 | |
| Remersonia | 1.36 | 0.26 | 0.10 | 2.44 | |
| Stachybotrys | 1.43 | 0.18 | 1.29 | 0.87 | |
| Humicola | 1.20 | 0.26 | 1.08 | 0.71 | |
| Solicoccozyma | 1.27 | 0.20 | 1.00 | 0.56 | |
| Cladosporium | 1.73 | 0.33 | 0.27 | 0.25 | |
| Staphylotrichum | 0.97 | 0.09 | 0.89 | 0.61 | |
| Ascobolus | 1.25 | 0.33 | 0.71 | 0.06 | |
| Cladorrhinum | 0.00 | 0.00 | 0.35 | 1.77 | |
| Penicillium | 0.53 | 0.17 | 0.69 | 0.24 | |
| Dichotomopilus | 0.41 | 0.12 | 0.77 | 0.12 | |
| Nigrospora | 0.39 | 0.23 | 0.25 | 0.15 | |
| Apodus | 0.08 | 0.38 | 0.16 | 0.31 | |
| Lophotrichus | 0.35 | 0.08 | 0.34 | 0.06 | |
| Gibberella | 0.31 | 0.07 | 0.27 | 0.10 | |
| Mycosphaerella | 0.28 | 0.20 | 0.11 | 0.13 | |
| Waitea | 0.68 | 0.00 | 0.00 | 0.00 | |
| Sodiomyces | 0.06 | 0.20 | 0.09 | 0.26 | |
| Fusicolla | 0.30 | 0.05 | 0.17 | 0.07 | |
| Schizothecium | 0.12 | 0.00 | 0.33 | 0.13 | |
| Pseudogymnoascus | 0.16 | 0.05 | 0.16 | 0.20 | |
| Botryotrichum | 0.13 | 0.06 | 0.26 | 0.06 | |
| Acaulium | 0.15 | 0.07 | 0.09 | 0.16 | |
| Aspergillus | 0.18 | 0.06 | 0.16 | 0.08 | |
| Preussia | 0.22 | 0.02 | 0.17 | 0.07 | |
| Metarhizium | 0.22 | 0.03 | 0.06 | 0.04 | |
| Clonostachys | 0.18 | 0.01 | 0.07 | 0.05 | |
| Podospora | 0.11 | 0.09 | 0.08 | 0.02 | |
| Fusariella | 0.06 | 0.07 | 0.02 | 0.09 | |
| Epicoccum | 0.04 | 0.00 | 0.19 | 0.00 | |
| Tausonia | 0.03 | 0.00 | 0.04 | 0.14 | |
| Kernia | 0.03 | 0.05 | 0.08 | 0.05 | |
| Udeniozyma | 0.08 | 0.00 | 0.07 | 0.03 | |
| Metacordyceps | 0.11 | 0.01 | 0.06 | 0.02 | |
| Byssochlamys | 0.04 | 0.07 | 0.03 | 0.04 | |
| Achroiostachys | 0.02 | 0.01 | 0.12 | 0.03 | |
| Myrmecridium | 0.05 | 0.03 | 0.06 | 0.03 | |
| Microdochium | 0.04 | 0.00 | 0.02 | 0.10 | |
| Ustilago | 0.08 | 0.00 | 0.03 | 0.04 | |
| Others | 29.28 | 15.66 | 35.66 | 24.23 | |
Effects of different treatments on the growth and yield of strawberry in Shijiazhuang, Hebei, China.
| Treatment | Seedling Mortality (%) | Number of Surviving | Average Fruit per Plant (Units) | Average Single Fruit Weight (g−1) | Yield 667 kg m−2 |
|---|---|---|---|---|---|
| M0 | 11.33 ± 1.52 a | 7093.33 ± 122.20 b | 7.20 ± 0.10 b | 24.23 ± 0.31 b | 1052.08 ± 22.82 c |
| H0 | 4.00 ± 1.00 b | 7680.00 ± 80.00 a | 7.50 ± 0.10 a | 24.70 ± 0.60 b | 1209.44 ± 39.73 b |
| H1 | 3.67 ± 1.52 b | 7706.67 ± 122.20 a | 7.70 ± 0.36 a | 25.70 ± 0.36 a | 1296.57 ± 47.12 a |
Note: Significant (p < 0.05) differences are expressed with different letters.
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Details
; Meng, Jian 2 ; Han, Jiangwei 3 1 Shijiazhuang Academy of Agricultural and Forestry Sciences, Shijiazhuang 050041, China;
2 Hebei Province Agricultural Technology Extension Station, Shijiazhuang 050021, China
3 Shijiazhuang Seed Management Station, Shijiazhuang 050021, China