Method for constructing steady-state microbiome on surfaces of pear fruits based on serratia rubra to inhibit postharvest diseases

Abstract

The invention belongs to the technical crossing field of microbiomics, and relates to a method for constructing a steady-state microbiome on the surface of a pear based on serratia rubra to inhibit postharvest diseases. The method comprises the following steps: firstly, preparing serratia rubra B11 suspension, and spraying the serratia rubra B11 suspension on the surfaces of pear fruits; the method comprises the following steps: standardly collecting epiphytic microorganisms on the surfaces of fruits by adopting a mode of combining physical elution and vacuum filtration, extracting total DNA, respectively carrying out high-throughput amplicon sequencing on a 16S rRNA gene V3-V4 region and a fungus ITS2 region, and carrying out dynamic analysis on alpha diversity, beta diversity, community composition and key class groups, so as to determine the content of the epiphytic microorganisms on the surfaces of the fruits. And finally, associating with the fruit rotting rate and the physiological quality index, establishing a set of full-process standardized system of multi-dimensional bioinformatics analysis, and revealing an ecological mechanism that beneficial bacteria realize disease inhibition by remodeling a fruit surface microbial community structure and regulating and controlling key function class groups. And reliable technical support is provided for mechanism research, efficiency evaluation and application development of the biocontrol microbial inoculum.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of microbiome technology, specifically involving a method for constructing a stable microbiome on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases. Background Technology

[0002] During postharvest storage of pears, rot caused by pathogens such as *Penicillium expansum* is a major factor leading to economic losses. The use of traditional chemical fungicides faces problems such as residues, resistance, and environmental pressure; therefore, the development of green and efficient biological control technologies is imperative. Antagonistic microorganisms, such as certain bacteria and yeasts, which control postharvest diseases through mechanisms such as competition, antagonism, or induced resistance, have become a research hotspot.

[0003] However, current research on biocontrol mechanisms largely focuses on the direct effects of antagonistic bacteria on pathogens or their induction of host physiology, often neglecting the dynamic changes of the fruit surface as a complex micro-ecosystem. The stability of the structure and function of the epiphytic microbial community (i.e., the surface microbiome) on the fruit surface plays a crucial role in the health and disease resistance of the fruit. How the introduction of exogenous beneficial bacteria affects the succession trajectory, key group interactions, and final functional output of this in-situ micro-ecosystem currently lacks systematic and standardized analytical methods. This limits a deeper understanding of the "microbiome-driven effect" of biocontrol agents and hinders the development of precision preservation technologies based on microecological regulation.

[0004] Therefore, it is urgent to establish a complete experimental method that can quantitatively track the temporal changes of the microbiome on the surface of fruit after treatment with beneficial bacteria under simulated actual storage conditions, and reveal the ecological mechanism by which beneficial bacteria construct beneficial microbiome and inhibit diseases from multiple dimensions such as community composition, diversity, structure and key functional groups. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a systematic and reproducible method. Based on Serratia marcescens, a stable microbiome is constructed on the surface of pear fruit. α-diversity, β-diversity, community composition, and dynamic analysis of key taxa are conducted. Finally, this is correlated with fruit decay rate and physiological quality indicators, establishing a standardized system for the entire process of multi-dimensional bioinformatics analysis. This reveals the ecological mechanism by which beneficial bacteria reshape the microbial community structure on the fruit surface and regulate key functional groups to achieve disease suppression, thereby achieving effective control of postharvest diseases in fruits and vegetables.

[0006] To achieve the above objectives, the technical solution provided by the present invention is as follows:

[0007] A method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to suppress postharvest diseases, the specific steps of which are as follows:

[0008] (1) Preparation and processing of bacterial suspension: Serratia marcescens B11 was cultured in LB medium to the logarithmic growth phase, the bacterial cells were collected by centrifugation, and the suspension was obtained by resuspending with sterile phosphate buffer.

[0009] Select pears of uniform maturity and without mechanical damage, and spray the surface of the pears evenly with a suspension of Serratia marcescens B11 bacteria at a rate of 0.5-1.0 mL per 100 square centimeters; after treatment, store the pears.

[0010] (2) Multi-time point dynamic sampling strategy: In order to capture the dynamic succession process of microbial communities, sampling is carried out in the early, middle and late stages of storage;

[0011] (3) Standardized collection of microorganisms on the surface of fruit: After sampling in step (2), each pear fruit sample is immersed in a sterile homogenizing bag containing pre-cooled phosphate buffer; the loosely attached and tightly adhered microbial cells on the surface of the fruit are effectively washed into the buffer solution by a physical method combining mechanical oscillation and low-frequency ultrasound to obtain washing solution; then, the microorganisms in the washing solution are collected onto the filter membrane by vacuum filtration.

[0012] (4) Microbiome sequencing and bioinformatics analysis: Total genomic DNA of the microbial community was extracted from the filter membrane. High-throughput amplicon sequencing was performed on the V3-V4 hypervariable region of the bacterial 16S rRNA gene and the ITS2 region of the fungus. The raw sequence data obtained from sequencing were then quality controlled, denoised, and assembled to generate an amplicon sequence variant (ASV) table. The following analyses were performed using bioinformatics software, including QIIME2:

[0013] (a) α-diversity analysis: Shannon index and Chao1 index for each sample were calculated to assess community richness and evenness.

[0014] (b) β-diversity analysis and community structure analysis: Based on the Bray-Curtis distance matrix, principal coordinate analysis (PCoA) was performed to visualize community differences, and permutation multivariate analysis of variance (PERMANOVA) was used to statistically test the contributions of factors and time factors to community structure.

[0015] (c) Community composition analysis: Analyze the relative abundance of fungi and bacteria at the genus level to identify dominant groups and key variable groups;

[0016] (5) Analysis of the correlation between the dynamics of key microbial groups and disease phenotypes: Combining the microbiome data obtained in step 4 with the parallel measured disease phenotype data, key fungal and bacterial genera that showed significant changes in relative abundance during storage and were closely related to disease occurrence were screened. Among them, the fungal genera included Penicillium and Vishniacozyma, and the bacterial genera included Serratia and Acinetobacter. Abundance change curves of these key groups of fungal and bacterial genera during storage were plotted to determine the optimal spraying amount of Serratia rubra B11 suspension, construct stable sites, establish a stable epiphytic microbiome dominated by beneficial bacteria, and thus realize the ecological mechanism for postharvest disease control.

[0017] The biocontrol strain of Serratia rubidaea is Serratia rubidaea B11, with accession number CCTCCNO: M 20241377.

[0018] Preferably, the LB culture medium described in step (1) is: 10g tryptone, 5g yeast extract, 10g sodium chloride, distilled water to a final volume of 1000mL, natural pH, sterilized at 115℃ for 20min.

[0019] Preferably, the activation culture conditions in step (1) are: 37℃ for 16-18h; the centrifugation conditions are: 4℃, 8000rpm, for 10-15min.

[0020] Preferably, the concentration of the Serratia marcescens suspension in step (1) is 1×10⁸ cells / mL.

[0021] Preferably, the storage conditions in step (1) are: 0-4℃, relative humidity 85-95%.

[0022] Preferably, in step (2), the initial storage period is 2 hours; the middle storage period is 13-26 days; and the later storage period is 39-52 days. Specifically, the storage time can be 2 hours (defined as day 0), 13 days, 26 days, 39 days, and 52 days after treatment. At each time point, at least 3 independent biological replicates must be collected for each treatment group, and each replicate must consist of at least 5 fruits to ensure sample representativeness.

[0023] Preferably, in step 3, the temperature of the pre-cooled phosphate buffer is 0-4°C and the pH is 7.2; the mechanical oscillation conditions are: horizontal oscillation at 120 rpm for 30 minutes at 4°C; the low-frequency ultrasonic conditions are: treatment at 40 kHz frequency and 150 W power for 5 minutes at 4°C; and the pore size of the filter membrane is 0.22 μm.

[0024] Preferably, in step 4, the primers used for bacterial community analysis are 341F (5'-CCTACGGGNGGCWGCAG-3') and 806R (5'-GGACTACHVGGGTATCTAAT-3'); and the primers used for fungal community analysis are ITS3 (5'-GCATCGATGAAGAACGCAGC-3') and ITS4 (5'-TCCTCCGCTTATTGATATGC-3').

[0025] Preferably, in step 4, when performing PERMANOVA analysis, the number of permutations is set to 999 to test the statistical significance of the difference in microbial community structure between the treatment group and the control group.

[0026] Preferably, the disease phenotypic data includes rot rate and physiological quality of fruit during storage; wherein physiological quality includes firmness, browning degree, soluble solids, titratable acid, and ascorbic acid content. This is to facilitate correlation analysis between disease phenotypic data and microbiome changes.

[0027] The beneficial effects obtained by this invention are as follows:

[0028] This invention, through the design of a comprehensive experimental system encompassing processing, dynamic sampling, standardized microbial collection, high-throughput sequencing, and multi-dimensional bioinformatics analysis, achieves a systematic analysis of the temporal succession patterns of fruit surface microbial communities, effectively overcoming the limitations of traditional single-point studies. This method expands the research perspective from traditional binary antagonism to the micro-ecosystem level of "beneficial bacteria-in-situ microbiome-pathogen-host," revealing the ecological mechanism by which beneficial bacteria indirectly control diseases by reshaping microbial community structure, regulating the abundance of key functional groups, and constructing stable sites. Standardized operating procedures and a multi-timepoint intensive sampling strategy ensure high resolution and reproducibility of experimental data. By integrating community diversity, structural changes, and disease phenotypic data, the regulated core microbial groups and their dynamic pathways can be accurately identified, providing a solid basis for elucidating the mechanism of action and evaluating the efficacy of biocontrol agents. Furthermore, the research results can directly guide the optimization of agent application parameters, the development of compound formulations, and the formulation of postharvest preservation processes based on microbiome management, possessing clear practical translational value. Attached Figure Description

[0029] Figure 1 (AB) represents the composition of fungal and bacterial communities on the surface of pear fruit at the genus level; the numbers indicate the storage time (days); CK is the sterile water control group, and B is the Serratia marcescens B11 treatment group; different colors represent different fungal groups, and the area of ​​the rectangles represents the relative proportion of each community.

[0030] Figure 2(AE) is a box plot of the Shannon index of fungal communities on the surface of pear fruit; the numbers represent the storage time (days); CK is the sterile water control group (blue), and B is the Serratia marcescens B11 treatment group (yellow); Welch's t test was used to compare the Shannon index and the Chao1 index (P<0.05).

[0031] Figure 3 (AE) is a box plot of the Shannon index of fungal communities on the surface of pear fruit; the numbers represent the storage time (days); CK is the sterile water control group (blue), and B is the Serratia marcescens B11 treatment group (yellow); Welch's t test was used to compare the Shannon index and the Chao1 index (P<0.05).

[0032] Figure 4 (AB) is the PCoA diagram of fungal and bacterial communities on the surface of pear fruit; the numbers represent the storage time (days); CK is the sterile water control group, and B is the Serratia marcescens B11 treatment group; different colors represent different microbial communities; data analysis was performed based on the Bray-Curtis distance using the PERMANOVA test and principal coordinate analysis (PCoA).

[0033] Figure 5 (AE) represents the effect of changes in the relative abundance of important fungal and bacterial genera on the surface of pear fruit during storage; CK is the sterile water control group, and B is the Serratia marcescens B11 treatment group; * indicates a significant difference between the two groups (P<0.05, two-tailed Student's test).

[0034] Figure 6 The effect of (AF) on the relative abundance of important fungal genera on the surface of pear fruit during storage; CK is the sterile water control group, and B is the Serratia marcescens B11 treatment group; * indicates significant difference between the two groups (P<0.05, two-tailed Student's t test). Detailed implementation method:

[0035] Example 1: Investigating the regulatory effect of Serratia marcescens B11 on the surface microbiome of refrigerated pears

[0036] The *Serratia marcescens* strain provided in this invention is from the China Center for Type Culture Collection (CCTCC), with the strain accession number CCTCC M 20241377, and is a previously disclosed strain.

[0037] Strain culture and bacterial culture preparation: Serratia marcescens B11 was inoculated into LB liquid medium and cultured at 28°C with shaking at 180 rpm until OD. 600 The concentration was 0.8. The bacterial cells were collected by centrifugation, washed twice with sterile PBS (pH 7.2), and resuspended to a final concentration of 1×10⁸. 8 CFU / mL, for later use.

[0038] Sample processing and storage: 300 Crown pear fruits were randomly divided into two groups: a control group (CK) and a treatment group (B11). In the B11 group, a prepared *Serratia marcescens* B11 bacterial suspension was evenly sprayed onto the surface of each fruit until completely wet (1.0 mL per 100 cm²). The CK group was sprayed with an equal volume of sterile saline. After treatment, the fruits were air-dried indoors, then placed in plastic preservation baskets and placed in an artificial climate chamber, simulating commercial cold storage at 0.5±0.5℃ and 90±5% relative humidity.

[0039] Microbiome sampling and DNA extraction: Samples were collected at 2 hours post-treatment (day 0) and on days 13, 26, 39, and 52. Three biological replicates were taken from each treatment group at each time point, with 13 fruits per replicate. The sampled fruits were placed in a sterile homogenizing bag containing 1.8 L of ice-cold PBS, and 1.8 L of ice-cold PBS buffer (0.1 M, pH 7.2) was added. The bag was sealed and placed on a horizontal shaker at 4°C and 120 rpm for 30 minutes. Subsequently, the entire bag was placed in an ultrasonic cleaner bath (water bath temperature maintained at 4°C) and ultrasonicated at 40 kHz and 150 W for 5 minutes. The washing solution was filtered through a vacuum pump onto a 0.22 μm mixed cellulose ester membrane. The membrane was folded with sterile forceps, immediately flash-frozen in liquid nitrogen, and then transferred to a -80°C freezer for long-term storage.

[0040] DNA extraction, sequencing, and bioinformatics analysis: Total microbial community DNA was extracted from each filter membrane using the DNeasy PowerSoil Pro kit, following the instructions. PCR amplification was performed by a professional sequencing company using specified primer pairs (bacteria: 341F / 806R; fungi: ITS3 / ITS4), followed by 2×250bp paired-end sequencing on the Illumina MiSeq platform.

[0041] 341F: 5'-CCTACGGGNGGCWGCAG-3'; 806R: 5'-GGACTACHVGGGTATCTAAT-3';

[0042] ITS3: 5'-GCATCGATGAAGAACGCAGC-3'; ITS4: 5'-TCCTCCGCTTATTGATATGC-3'.

[0043] The data from the experiment were quality controlled and ASVs were generated using the DADA2 workflow; subsequent analyses were performed in the QIIME2 environment: the α diversity index (Shannon, Chao1) was calculated; PCoA analysis and PERMANOVA test (parameter: 999 permutations) were performed based on the Bray-Curtis distance; and a histogram of species composition at the genus level was generated.

[0044] Figure 1 (AB) represents the genus-level composition of fungal and bacterial communities on the surface of pears; the numbers indicate storage time (days). CK is the sterile water control group, and B is the Serratia marcescens B11 treatment group. Different colors represent different fungal groups, and the area of ​​the rectangles represents the relative proportion of each community. Figure 1 Analysis revealed the initial composition and core groups of epiphytic microorganisms on the surface of pears. In the fungal category, dominant groups were identified, including *Cladosporium*, *Alternaria*, *Vessilospora*, and *Penicillium*. In the bacterial category, *Serratia*, *Acinetobacter*, *Pseudomonas*, and the *Methylobacterium-Methylococcus* complex were identified as core members.

[0045] Fungal community regulation: Figure 2 Analysis of the temporal changes in the Shannon index of fungi in the AE (Acute Antifungal) study showed that the Serratia marcescens B11 treatment significantly inhibited the relative abundance of putrefaction-related fungi such as Penicillium, Vitis vinifera, Paphiopedilum, and Golbevia, while promoting the enrichment of the biocontrol potential genus Arthrophyll. The Shannon diversity index of the fungal community was significantly higher in the Serratia marcescens B11 treatment group than in the control group at days 26, 39, and 52 of storage (P<0.05).

[0046] Bacterial community regulation: Figure 3 Analysis of the Shannon index of AE bacteria over time showed that treatment with Serratia marcescens B11 stabilized the relative abundance of Serratia spp. from 70-80% at the beginning of treatment to 45-55% on day 52, significantly higher than the control group (which was less than 25% at the same time). Simultaneously, it significantly inhibited the proliferation of opportunistic bacteria such as Acinetobacter spp., Methylobacterium-Methylococcus complex, and Abnormal cocci spp.

[0047] Community structure evolution: Figure 4 PCoA analysis based on Bray-Curtis distance showed that the fungal and bacterial communities in the B11 treatment group and the control group were significantly separated in the later stages of storage (e.g., days 26 and 39), and the samples in the B11 group were more tightly clustered. PERMANOVA confirmed that treatment, time and their interaction all had a highly significant impact on community structure (P≤0.002).

[0048] Key taxa dynamics and data analysis: From the genus-level composition results, fungal genera (such as *Penicillium*, *Vishniacozyma*) and bacterial genera (such as *Serratia*, *Acinetobacter*) with relatively high abundance and significant changes during storage were selected. Statistical software (such as R) was used to plot the relative abundance changes at each time point, and significance tests for inter-group differences (such as t-tests) were performed. Simultaneously, the correlation between the abundance changes of key pathogens (such as *Penicillium*) and disease occurrence was analyzed by combining this data with parallel measurements of fruit rot rate.

[0049] Figure 5 (AE) represents the effect of changes in the relative abundance of important fungal and bacterial genera on the surface of pear fruit during storage; CK is the sterile water control group, and B is the Serratia marcescens B11 treatment group. * indicates a significant difference between the two groups (P<0.05, two-tailed Student's test); Figure 5 AE showed that Serratia marcescens B11 continuously suppressed Penicillium and Vegamycosis species to below 60% of the control and enriched the anthraquinone species that produce anti-metabolites, thus achieving "suppression of harmful organisms and promotion of beneficial organisms".

[0050] Figure 6 The effect of (AF) on the relative abundance of important fungal genera on the surface of pear fruit during storage; CK was the sterile water control group, and B was the Serratia marcescens B11 treatment group; * indicates significant difference between the two groups (P<0.05, two-tailed Student's t-test). Figure 6 AF confirmed that Serratia rubidaea B11 locks its abundance at 45%-55%, while selectively inhibiting later competing bacterial groups (Acinetobacter, Methylobacterium, Abnormal Cocci) and stabilizing harmless groups such as Rhodococcus. Thus, by spraying the specific Serratia rubidaea B11 bacterial suspension of this invention, a stable epiphytic microbiome dominated by beneficial bacteria was established.

[0051] This invention, through the design of a comprehensive experimental system encompassing processing, dynamic sampling, standardized microbial collection, high-throughput sequencing, and multi-dimensional bioinformatics analysis, achieves a systematic analysis of the temporal succession patterns of microbial communities on fruit surfaces, effectively overcoming the limitations of traditional single-point studies. This method expands the research perspective from traditional binary antagonism to the micro-ecosystem level of "beneficial bacteria-in-situ microbiome-pathogen-host," achieving an ecological mechanism for indirect disease control by reshaping microbial community structure, regulating the abundance of key functional groups, and constructing stable sites. This facilitates effective control of postharvest diseases in fruits and vegetables and improves their quality.

[0052] The embodiments listed herein are merely illustrative of the technical points of the present invention to facilitate understanding of its innovative essence, and are not intended to limit the scope of protection of the present invention in any way. Those skilled in the art, based on their understanding of the core concept of the present invention, may add, delete, modify, or replace equivalent technical means with specific embodiments according to the disclosure in this specification; all modifications and substitutions that do not depart from the spirit and scope of the technical solutions defined in the claims shall fall within the protection boundary of the patent rights of this invention, and shall be subject to the claims.

Claims

1. A method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases, characterized in that, The specific steps are as follows: (1) Preparation and processing of bacterial suspension: Serratia marcescens B11 was cultured in LB medium to the logarithmic growth phase, the bacterial cells were collected by centrifugation, and the suspension was obtained by resuspending with sterile phosphate buffer. Select pears of uniform maturity and without mechanical damage, and spray the surface of the pears evenly with a suspension of Serratia marcescens B11 bacteria at a rate of 0.5-1.0 mL per 100 square centimeters; after treatment, store the pears. (2) Multi-time point dynamic sampling strategy: In order to capture the dynamic succession process of microbial communities, sampling is carried out in the early, middle and late stages of storage; (3) Standardized collection of microorganisms on the surface of fruit: After sampling in step (2), each pear fruit sample is immersed in a sterile homogenizing bag containing pre-cooled phosphate buffer; the loosely attached and tightly adhered microbial cells on the surface of the fruit are effectively washed into the buffer solution by a physical method combining mechanical oscillation and low-frequency ultrasound to obtain washing solution; then, the microorganisms in the washing solution are collected onto the filter membrane by vacuum filtration. (4) Microbiome sequencing and bioinformatics analysis: Total genomic DNA of the microbial community was extracted from the filter membrane. High-throughput amplicon sequencing was performed on the V3-V4 hypervariable region of the bacterial 16S rRNA gene and the ITS2 region of the fungus. The raw sequence data obtained from sequencing were then quality controlled, denoised, and assembled to generate an amplicon sequence variation table. The following analyses were performed using bioinformatics software, including QIIME2: (a) α-diversity analysis: Shannon index and Chao1 index for each sample were calculated to assess community richness and evenness; (b) β-diversity analysis and community structure analysis: Based on the Bray-Curtis distance matrix, principal coordinate analysis (PCoA) was performed to visualize community differences, and permutation multivariate analysis of variance (PERMANOVA) was used to statistically test the contributions of factors and time factors to community structure. (c) Community composition analysis: Analyze the relative abundance of fungi and bacteria at the genus level to identify dominant groups and key variable groups; (5) Analysis of the correlation between the dynamics of key microbial groups and disease phenotypes: Combining the microbiome data obtained in step 4 with the parallel measured disease phenotype data, key fungal and bacterial genera that showed significant changes in relative abundance during storage and were closely related to disease occurrence were screened. Among them, the fungal genera included Penicillium and Vishniacozyma, and the bacterial genera included Serratia and Acinetobacter. Abundance change curves of these key groups of fungal and bacterial genera during storage were plotted to determine the optimal spraying amount of Serratia rubra B11 suspension, construct stable sites, establish a stable epiphytic microbiome dominated by beneficial bacteria, and thus realize the ecological mechanism for postharvest disease control. The biocontrol strain of Serratia rubidaea is Serratia rubidaea B11, with accession number CCTCC NO: M 20241377.

2. The method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases according to claim 1, characterized in that, The LB culture medium mentioned in step (1) is as follows (1L): 10g tryptone, 5g yeast extract, 10g sodium chloride, distilled water to a final volume of 1000mL, natural pH, sterilized at 115℃ for 20min.

3. The method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases according to claim 1, characterized in that, The activation culture conditions in step (1) are: 37℃ for 16-18h; the centrifugation conditions are: 4℃, 8000rpm, for 10-15min.

4. The method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases according to claim 1, characterized in that, The concentration of the Serratia marcescens suspension in step (1) is 1×10⁻⁶. 8 cells / mL.

5. The method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases according to claim 1, characterized in that, Storage conditions in step (1): 0-4℃, relative humidity 85-95%.

6. The method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases according to claim 1, characterized in that, In step (2), the initial storage period is 2 hours; the middle storage period is 13-26 days; and the later storage period is 39-52 days. Each treatment group needs to collect at least 3 independent biological replicates, and each replicate consists of at least 5 fruits to ensure sample representativeness.

7. The method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases according to claim 1, characterized in that, In step 3, the temperature of the pre-cooled phosphate buffer is 0-4℃ and the pH is 7.2; the mechanical oscillation conditions are: horizontal oscillation at 120 rpm for 30 minutes at 4℃; the low-frequency ultrasonic conditions are: treatment at 40 kHz frequency and 150 W power for 5 minutes at 4℃; and the pore size of the filter membrane is 0.22 μm.

8. The method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases according to claim 1, characterized in that, In step 4, the primers used for bacterial community analysis are 341F and 806R; the primers used for fungal community analysis are ITS3 and ITS4. 341F: 5'-CCTACGGGNGGCWGCAG-3'; 806R: 5'-GGACTACHVGGGTATCTAAT-3'; ITS3: 5'-GCATCGATGAAGAACGCAGC-3'; ITS4: 5'-TCCTCCGCTTATTGATATGC-3'.

9. The method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases according to claim 1, characterized in that, In step 4, when performing PERMANOVA analysis, the number of permutations was set to 999 to test the statistical significance of the differences in microbial community structure between the treatment group and the control group.

10. The method for constructing a stable microbial community on the surface of pear fruit based on Serratia marcescens to inhibit postharvest diseases according to claim 1, characterized in that, The disease phenotypic data include rot rate and physiological quality of fruit during storage; Physiological qualities include hardness, browning degree, soluble solids, titratable acid, and ascorbic acid content.

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