Method for evaluating effectiveness of green ecological prevention and control technology

Abstract

The invention provides a method for evaluating the effectiveness of a green ecological prevention and control technology, and belongs to the technical field of biological prevention and control. The method comprises the following steps: performing high-throughput sequencing on arthropod samples treated by a green ecological prevention and control method and a non-green control method; processing metagenome data of the high-throughput sequencing data; performing BOLD system species division; downstream analysis of metagenome data; measuring and analyzing the yield and quality of the planted crops; the determination result of the yield and quality of the planted crops is combined with the alpha or beta diversity of the arthropod samples for effectiveness analysis, and if the determination result of the yield and quality of the planted crops in the destination green ecological prevention and control method is positively correlated with the alpha or beta diversity of the arthropod samples, it is judged that the destination green ecological prevention and control method is effective. And the effectiveness of the green ecological prevention and control method can be accurately evaluated. Based on the evaluation method, the invention further provides a sorghum green ecological prevention and control method, the diversity of arthropods is promoted, and the yield and quality of sorghum are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of biological control, and in particular relates to a method for evaluating the effectiveness of green ecological control technology. Background Art

[0002] The starch in sorghum grains can be used to produce industrial raw materials such as alcohol and glucose, and has strong resistance and resilience. However, sorghum still faces great challenges from pests during cultivation, especially lepidopteran insects such as the Asian corn borer, peach borer and armyworm. These pests feed on leaves, bore into stems and panicles, and threaten crop yields.

[0003] Traditional pest control methods often rely on chemical pesticides, which may harm the environment and non-target pests, including beneficial arthropods. Sorghum is sensitive to pesticides such as pyrethroids, trichlorfon, dichlorvos, organochlorines, fenitrothion, Bordeaux mixture, and lime sulfur. Improper use can easily cause pesticide damage, exacerbating this problem. In addition, most brewing sorghum varieties are tight-ear varieties that help pests hide, and chemical agents are difficult to act on pests, resulting in low utilization rates and increased prevention and control times. The risk of pesticide residues in sorghum grains increases. Therefore, there is an urgent need for a green and ecological control method for sorghum.

[0004] In order to meet these challenges, green ecological control technology has gained attention. Biological control refers to the use of organisms, such as predators, parasites or pathogens, to control the number of pests. This method can reduce dependence on chemical pesticides in some cases, which may have a smaller negative impact on the environment. However, the effectiveness of biological control and its impact on biodiversity depend on many factors, including the selected biological control agents, target pests, characteristics of the ecosystem, and other management practices. In some cases, the introduction of non-native biological control agents may have unexpected negative impacts on local ecosystems, such as competition, predation or hybridization interference with native species, and may even become invasive species, thereby reducing local biodiversity and having a negative impact.

[0005] Therefore, before implementing a biological control strategy, careful scientific research and risk assessment are needed to ensure that the chosen method will not cause long-term negative impacts on the ecosystem and will effectively control the pest. Summary of the invention

[0006] One of the purposes of the present invention is to provide a method for evaluating the effectiveness of green ecological control technology, which can accurately evaluate the effectiveness of green ecological control methods. The method helps to make crops safer and greener, helps to improve crop quality, and plays a vital role in improving ecosystem services and crop safety.

[0007] The second object of the present invention is to provide a green ecological control method for sorghum, which promotes the increase of arthropod diversity, especially the increase of Hymenoptera diversity, and significantly improves the yield and quality of sorghum.

[0008] In order to achieve the above object, the present invention provides the following technical solutions:

[0009] The present invention provides a method for evaluating the effectiveness of green ecological prevention and control technology, comprising:

[0010] (1) Perform high-throughput sequencing on arthropod samples treated with green ecological control methods and non-green control methods;

[0011] (2) performing metagenomic data processing on the raw data obtained by high-throughput sequencing to obtain processed data;

[0012] (3) submitting the processed data to the BOLD system for species classification;

[0013] (4) Community composition after species delineation using downstream analysis of metagenomic data for α and β diversity;

[0014] (5) Determination and analysis of crop yield and quality under green ecological control methods and non-green control methods;

[0015] (6) The effectiveness of the green ecological control method is analyzed by combining the results of the yield and quality of crops grown under the green ecological control method and the non-green control method with the α or β diversity of arthropod samples. If the results of the yield and quality of crops grown under the green ecological control method are positively correlated with the α or β diversity of arthropods, the green ecological control method is judged to be effective.

[0016] Preferably, the arthropod sampling is performed by trapping with a Malay net to collect arthropod samples.

[0017] Preferably, in step (1), the primers used for high-throughput sequencing are LCO1490 and HCO2198; the sequence of LCO1490 is shown as SEQ ID NO.1, and the sequence of HCO2198 is shown as SEQ ID NO.2.

[0018] Preferably, in step (2), the metagenomic data processing includes using Trimmomatic v0.39 software to perform quality control analysis on the original sequence obtained by high-throughput sequencing, using FastQC v0.11.5 to perform data statistics before and after quality control, using FASTX-Toolkit v1.4.1 to remove the connector, using FLASH v2.2.0 to perform double-end sequence splicing, and using default parameters; using vsearchv2.7.1 to remove chimeras to obtain processed data.

[0019] Preferably, in step (3), the species division method adopts MOTUs division, and the MOTUs division includes submitting the processed data to the BOLD system for species division; it is implemented using the bold.py program, the input data is a fas format file, and the output fas format file is the BOLD result.

[0020] Preferably, in step (4), the downstream analysis of the metagenomic data includes: using the Phyloseq software package V.1.44.0 to perform downstream analysis of community composition; the downstream analysis of community composition generates an OTU list by clustering the OTUs at 97% similarity to record the relative abundance of each OTU in each sample and the classification of the OTU; after classification and identification, the differentially abundant OTUs are selected as key OTUs for further statistical analysis.

[0021] Preferably, the OTU is further subjected to statistical analysis including species composition, diversity assessment, inter-group comparison, heat map visualization and identification of key OTUs.

[0022] Preferably, the further statistical analysis analyzes alpha diversity by evaluating differences in the Shannon index and richness index; analyzes beta diversity using principal coordinate analysis based on weighted UniFrac distance, and evaluates statistical significance by ANOSIM similarity analysis to explore differences in community composition between treatment groups and years.

[0023] Preferably, the further statistical analysis is performed under the microbiome, amplicon, microeco and vegan packages in R package (v4.3.1), and the graphic visualization is achieved by ggplot2, dplyr, RColorBrewer, ggpubr in R package (v4.3.1).

[0024] The present invention also provides a green ecological prevention and control method for sorghum, the method comprising the following steps:

[0025] (a) One solar insecticidal lamp is installed for every 48 to 52 mu of field; the parameter settings of the solar insecticidal lamp include wavelength between 320 and 680 nm; grid voltage is 3600 V, electric shock net wire diameter is ≥1.8 mm, grid spacing is ≥10 mm; wind speed at the fan inlet is ≥3.0 m / s;

[0026] (b) Use insect pheromones to lure pests. Install 2 to 3 sets of traps per acre to control pests. The traps are selected to lure stem borers. The lure core of the trap is replaced every 3 to 5 weeks to kill male stem borers, reduce the mating rate of females, and reduce the base number of the next generation;

[0027] (c) Precision release of Trichogramma pine caterpillars. From June to August each year, Trichogramma pine caterpillars are released four times in sorghum fields in green control areas, with 14,000 to 16,000 released per mu each time.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The present invention provides a method for evaluating the effectiveness of green ecological prevention and control technology, which can accurately evaluate the effectiveness of green ecological prevention and control methods; the method helps to make crop production safer and greener, helps to improve crop quality, and plays a vital role in improving ecosystem services and crop safety.

[0030] The present invention also provides a green ecological prevention and control method for sorghum, which promotes the increase of arthropod diversity, especially the increase of Hymenoptera insect diversity, and significantly improves the quality of sorghum. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a schematic diagram of the sampling process in Example 1.

[0032] Figure 2 These are the species composition and difference comparison results of different years (2021, 2022) and different sampling points (LP, SZ, YH) in Example 1; wherein, A is the community composition at the "phylum" level in different years and different sampling points; B is the community composition at the "order" level in different years and different sampling points; C is the difference in α diversity (Shannon index) in different years and different sampling points; D is the community composition at the "family" level between the two years, showing the abundance of key arthropods at the "family" level; E is the community composition at the "genus" level in 2021 and 2022, focusing on the dominant genera and their changes between years.

[0033] Figure 3 The comparison results of species diversity between the control group and the green group at different sampling points and months in Example 1; wherein, A is the richness index at different locations; B is the β diversity at different locations; C is the richness index at different months; D is the β diversity at different months; E is the comparison of the richness index of the control group and the green group in different months; F is the comparison of the β diversity of the control group and the green group in different months; G is the community species composition of the control group and the green group in different months.

[0034] Figure 4The results of species comparison between green control and chemical control in Example 1 show that the number of Hymenoptera insects in the green control group is larger than that in the control group with chemical control. A is the richness index; B is the β diversity; C is the species composition of the community at the "order" level; D is a volcano map showing OTU differences; E is the reduced and enriched genera in the green control group compared with the chemical control group.

[0035] Figure 5 The comparison results of sorghum yield and quality between the control chemical control group and the green control group in Example 1; wherein A is the comparison result of sorghum yield, including yield (kg / 667m 2 ), thousand-grain weight (TGW), grain weight (g); B is the comparison results of sorghum quality, including crude protein content (%DW), crude fat content (%DW), crude starch content (%DW), tannin content (%DW), proportion of amylopectin in total starch (%), DW: dry weight. DETAILED DESCRIPTION

[0036] The present invention provides a method for evaluating the effectiveness of green ecological prevention and control technology, comprising:

[0037] (1) Perform high-throughput sequencing on arthropod samples treated with green ecological control methods and non-green control methods;

[0038] (2) performing metagenomic data processing on the raw data obtained by high-throughput sequencing to obtain processed data;

[0039] (3) submitting the processed data to the BOLD system for species classification;

[0040] (4) Community composition after species delineation using downstream analysis of metagenomic data for α and β diversity;

[0041] (5) Determination and analysis of crop yield and quality under green ecological control methods and non-green control methods;

[0042] (6) The effectiveness of the green ecological control method is analyzed by combining the results of the yield and quality of crops grown under the green ecological control method and the non-green control method with the α or β diversity of arthropod samples. If the results of the yield and quality of crops grown under the green ecological control method are positively correlated with the α or β diversity of arthropods, the green ecological control method is judged to be effective.

[0043] In step (1) of the above method of the present invention, the green ecological prevention and control method comprises: (a) installing one solar insecticidal lamp for every 48 to 52 mu in the field, the parameter settings of the solar insecticidal lamp include a wavelength between 320 and 680 nm; a grid voltage of 3600 V, a wire diameter of the electric shock net of ≥1.8 mm, and a grid spacing of ≥10 mm; a wind speed at the fan inlet of ≥3.0 m / s; (b) using insect pheromones to lure pests, installing 2 to 3 sets of traps per mu to prevent and control pests, the traps selectively lure stem borers, replacing the lure core of the trap every 3 to 5 weeks, killing male stem borers, reducing the mating rate of females, and reducing the base number of the next generation; (c) accurately releasing pine caterpillar trichogrammatids, releasing pine caterpillar trichogrammatids 4 times in the sorghum fields in the green prevention and control area from June to August each year, and releasing 14,000 to 16,000 per mu each time. Preferably, in step (c), pine caterpillar trichogrammatids are released 4 times in the sorghum field in the green control area, with 15,000 released per mu each time. The crops applicable to the green ecological control method include sorghum. The green ecological control method in the present invention does not use any chemical control measures. The abiotic control method includes chemical control; the chemical control adopts stem and leaf spray chemical control; the stem and leaf spray chemical control uses a total of 5 times during the whole growth period: seedling stage, jointing stage, large trumpet stage, initial ear stage, ear stage; the pesticides used include emamectin benzoate, chlorantraniliprole, imidacloprid, and thiamethoxam. The arthropod sampling uses Malay nets to trap and collect arthropod samples. Further, the method of trapping and collecting arthropod samples using Malay nets includes: 3 Malay nets are randomly set up in each base, and the base area is about 200 mu. Each Malay net is 10 meters away from the edge of the farmland. The Malay net is 10 meters away from the edge of the farmland to avoid the influence of marginal effects on the experimental results. Samples collected from the Malay web are collected once every half a month. The collection time is from early July to the end of October each year. The applicable area of ​​the green ecological prevention and control method can optionally include the warm temperate monsoon climate zone, further preferably the Huaibei Plain, and more preferably Suqian City, Jiangsu Province. The high-throughput sequencing includes PCR amplification using primers LCO1490 and HCO2198; the sequence of LCO1490 is shown in SEQ ID NO.1, and the sequence of HCO2198 is shown in SEQ ID NO.2. The reaction system for the PCR amplification is 50 μL: containing 2 μL DNA template, 25 μL 2×EXTaqPCRMasterMix, 1 μL of the above primers (10 μmol / L) plus double distilled water to make up the remaining amount. In the present invention, the PCR amplification conditions of the PCR amplification are: 95°C pre-denaturation for 5min; 95°C for 30s, 50°C for 30s, and 72°C for 1min. 40 cycles; 72°C extension for 10min. The PCR amplification products were sequenced using the IIllumina MiSeq PE300 platform.

[0044] In step (2) of the above method of the present invention, the metagenomic data processing includes using Trimmomatic v0.39 software to perform quality control analysis on the original sequence obtained by high-throughput sequencing, using FastQC v0.11.5 to perform data statistics before and after quality control, using FASTX-Toolkit v1.4.1 to remove connectors, and using FLASH v2.2.0 to perform double-end sequence splicing with default parameters; using vsearch v2.7.1 to remove chimeras to obtain processed data.

[0045] In step (3) of the above method of the present invention, the species division method adopts MOTUs division, and the MOTUs division includes submitting the processed data to the BOLD system for species division; using bold.py program to implement, the input data is a fas format file, and the output fas format file is a BOLD result. For example, XX.fas is an input file, and the file name in the file is ">22YH030930.249"), and 4 files are output: ①XXouts.fa; ②XX BOLD.sum.fas; ③XXouts.fa.error.fas; ④XXBOLD.fas, where "XXBOLD.fas" is the final BOLD result, and the file name in the specific file contains the six-level annotation result ">22YH010715.1_Arthropoda_Insecta_Hyme noptera_Formicidae_Rhytidoponera_XX(55.56)".

[0046] In step (4) of the above method of the present invention, the downstream analysis of the metagenomic data includes: using the Phyloseq software package V.1.44.0 to perform downstream analysis of community composition; the downstream analysis of community composition generates an OTU list by clustering OTUs at 97% similarity to record the relative abundance of each OTU in each sample and the classification of OTUs; after classification and identification, the differentially abundant OTUs are selected as key OTUs for further statistical analysis. The further statistical analysis of the OTUs includes species composition, diversity assessment, inter-group comparison, heat map visualization and identification of key OTUs. The statistical analysis analyzes alpha diversity by evaluating the difference in Shannon index and richness index; analyzes beta diversity using principal coordinate analysis based on weighted UniFrac distance, and evaluates statistical significance by similarity analysis (ANOSIM). The statistical analysis was performed under the microbiome, amplicon, microeco and vegan packages in R package (r4.3.1), while the graphical visualization was mainly created using ggplot2, dplyr, RColorBrewer, ggpubr in R package (r4.3.1). The Chinese name of the OTU is molecular operational taxonomic unit.

[0047] In step (5) of the above method of the present invention, the Wilcoxon rank sum test is used to measure and analyze the yield and quality of crops planted under the green ecological prevention and control method and the non-green control method. The Wilcoxon rank sum test is based on the rank sum of sample data. The two samples are first regarded as a single sample (mixed sample) and then the observations are arranged from small to large and ranked uniformly. If the original hypothesis that the two independent samples come from the same population is true, then the ranks will be approximately evenly distributed in the two samples, that is, small, medium, and large rank values ​​should be approximately evenly divided in the two samples. If the alternative hypothesis that the two independent samples come from different populations is true, then one of the samples will have more small rank values, so a smaller rank sum will be obtained; the other sample will have more large rank values, so a larger rank sum will be obtained.

[0048] Based on the above evaluation method, the present invention also provides a green ecological prevention and control method for sorghum, the method steps comprising:

[0049] (a) One solar insecticidal lamp is installed for every 48-52 mu of field; the parameter settings of the solar insecticidal lamp include: wavelength between 320-680nm; grid voltage is 3600V, electric shock net wire diameter is ≥1.8mm, grid spacing is ≥10mm; wind speed at fan inlet: ≥3.0m / s;

[0050] (b) Use insect pheromones to lure pests. Install 2 to 3 sets of traps per acre to control pests. The traps are selected to lure stem borers. The lure core of the trap is replaced every 3 to 5 weeks to kill male stem borers, reduce the mating rate of females, and reduce the base number of the next generation;

[0051] (c) Precision release of Trichogramma pine caterpillars. From June to August each year, Trichogramma pine caterpillars are released four times in sorghum fields in green control areas, with 14,000 to 16,000 released per mu each time.

[0052] The green ecological control method for sorghum of the present invention, in step (a), the solar insecticidal lamp installed in step (a) utilizes the tropism of lepidopteran pests to light, lures and kills adult pests, reduces the amount of eggs laid in the field, and reduces the insect population base. In step (c), the specific release dates of releasing pine caterpillar trichogrammatids 4 times in the sorghum field in the green control area are June 25, July 1, July 8 and August 16. In step (c), preferably about 15,000 pine caterpillar trichogrammatids are released per mu each time. In the present invention, the sorghum is planted in the Huaibei Plain.

[0053] The green ecological control method of the present invention increases the richness of arthropods, increases the dominance of Hymenoptera, promotes a more balanced and diverse arthropod community, reduces dependence on chemical pesticides, and meets the goal of sustainable agriculture. At the sampling point, the precise release technology of pine caterpillar trichogrammatid was also implemented to achieve synergistic effects of biological control measures and greatly improve the green control effect of sorghum target pests. The green ecological control technology increases the abundance of Hymenoptera in the community, once again demonstrating the effectiveness of incorporating natural enemies into pest control strategies.

[0054] The green ecological control method of the present invention not only promotes the increase of arthropod diversity, especially the increase of Hymenoptera diversity, but also improves the quality of sorghum to a certain extent. Although there is no significant difference in sorghum yield between the green group and the control group, the green group always shows higher average values ​​in key quality indicators, including the proportion of crude protein, crude starch and amylopectin, while the crude fat content is reduced.

[0055] In the present invention, LX, PW, YH, LP, and SZ represent Liulipengxi, Peixu, Yanghe, Liulipeng, and Sanzhuang, respectively.

[0056] In the following examples, the Trichogramma dendrolimus was purchased from Jilin Taihe Agricultural Science and Technology Co., Ltd.

[0057] In the following embodiments, the "wind power integrated" new solar insecticidal lamp was purchased from Nanjing Liye Pest Control Co., Ltd.; the "wind power integrated" new solar insecticidal lamp specifications: 1. The solar insecticidal lamp battery panel is used: the product complies with IEC 60904-1:2006 standard, power ≥40W; 2. Lithium battery for solar insect killer lamp: voltage is 12V, capacity is ≥40AH; 3. Wavelength is between 320-680nm, including at least 5 wavelengths: 367±20nm, 403±20nm, 435±20nm, 545±20nm, 578±20nm; 4. Grid voltage is 3600V, electric shock net wire diameter is ≥1.8mm, grid spacing is ≥10mm; 5. Wind speed at fan inlet: ≥3.0m / s; whole lamp power: 15W±0.5W; 6. The whole lamp height is more than 3 meters, the lamp pole is made of galvanized steel pipe, sprayed with plastic, the pipe diameter is ≥60mm, the wall thickness is ≥1.4mm, and the overall color is white. 7. The whole lamp of the product complies with GB / T24689.2-2017 standard.

[0058] In the following examples, the traps and pheromone lures were purchased from Nanjing Liye Pest Control Co., Ltd.

[0059] Unless otherwise specified, the test methods used in the following examples are all conventional test methods; the materials and reagents used are reagents and materials that can be obtained from commercial channels unless otherwise specified.

[0060] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention.

[0061] Example 1

[0062] 1. Materials and Methods

[0063] 1.1 Basic information of sampling points

[0064] Sorghum samples were taken from the wine-making grain base in Yanghe Agricultural High-tech Zone, Suqian City, Jiangsu Province (18m above sea level, 118.432°E, 33.783°N) and the Chengnan base in Siyang County, Suqian City (17m above sea level, 118.32°E, 33.97°N). The base is located in the Huaibei Plain and belongs to the warm temperate monsoon climate zone, with an average annual temperature of 14.2℃, an average annual precipitation of 910 mm, an average annual sunshine of 2291 hours, and a crop growth period of 310.5 days throughout the year. Sorghum is a local specialty small grain crop, and is mostly used for liquor brewing. Green control areas (LX, PW) and non-green control areas, namely chemical control areas (YH, LP, SZ), were set up in the two sorghum planting bases. Among them, LX, PW, YH, LP, and SZ represent Liulipengxi, Peixu, Yanghe, Liulipeng, and Sanzhuang, respectively.

[0065] 1.2 Green control and chemical control

[0066] 1.2.1 Green prevention and control treatment

[0067] In the green control area, no chemical control measures are used. Instead, the following green ecological control technologies are used:

[0068] (a) Solar insecticidal lamps. Taking advantage of the tropism of lepidopteran pests to light, one new type of "wind power integrated" solar insecticidal lamp is installed for every 50 mu of field to lure and kill adult pests, reduce the amount of eggs laid in the field, and lower the insect population base.

[0069] (b) Insect pheromone luring technology. Install 2 to 3 sets of traps per mu to control pests. The traps are selected to lure corn borers and peach borers. The lure core is replaced every 3 to 5 weeks to kill male borers, reduce the mating rate of female borers, and reduce the base number of the next generation.

[0070] (c) Precision release technology of pine caterpillar trichogrammatids. From June 2021 to August 2022, pine caterpillar trichogrammatids will be released four times a year in sorghum fields in the green control zone. The release dates are June 25, July 1, July 8, and August 16. About 15,000 pine caterpillar trichogrammatids will be released per mu each time, with 5 release points set up per mu, and 4 to 5 pine caterpillar trichogrammatid release balls evenly thrown.

[0071] 1.2.2 Chemical control treatment

[0072] Use stem and leaf spray chemical control.

[0073] The pesticides were applied five times in total during the whole growth period: seedling stage, jointing stage, trumpet stage, initial heading stage, and heading stage. The pesticides used included avermectin benzoate, chlorfenapyr, imidacloprid, and thiamethoxam. The details of the pesticides used are shown in the table below (Table 1).

[0074] Table 1 Frequency, time, agent and dosage of chemical control

[0075]

[0076] 1.3 Arthropod collection

[0077] 1.3.1 Arthropod sampling

[0078] Use Malay nets to trap and collect arthropod samples. The sampling process diagram is as follows Figure 1As shown. Three Malay nets were randomly set up in each base (about 200 mu). In order to avoid the influence of marginal effects on the experimental results, each Malay net was 10 meters away from the edge of the farmland. Samples collected from the Malay net were collected once every half a month, and a total of 104 Malay net bottles were obtained (Table 2 is the arthropod sample collection information). From July 1 to October 28, 2021, 83 bottles were collected from the four sampling locations of Liulipeng, Sanzhuang, Liulipeng West, and Peixu. From July 15 to October 25, 2022, 21 bottles were collected from the sampling point Yanghe.

[0079] Table 2 Arthropod sample collection information

[0080]

[0081] 1.3.2 DNA extraction, PCR amplification, and high-throughput sequencing

[0082] After removing the ethanol from each arthropod sample collected by the Malay net, add 500 mL of sterile water and soak at 4°C for 24 h. Repeat the soaking three times to remove the residual ethanol.

[0083] The total DNA of the insects was then extracted using a non-destructive testing method, specifically, using 10 mL of lysis solution GA to lyse the whole insect, and using a membrane adsorption method to extract the total DNA in the lysis solution. The total DNA obtained was the DNA template.

[0084] The forward primer LCO1490: GGTCAACAAA TCATAAAGATATTGG (SEQ ID NO. 1) and the reverse primer HCO2198: TAAAC TTCAG GGTGA CCAAAAAATCA (SEQ ID NO. 2) were used.

[0085] The PCR reaction system was 50 μL: 2 μL DNA template, 25 μL 2×EX Taq PCR MasterMix, 1 μL forward and reverse primers (10 μmol / L), and double distilled water was added to make up the remaining amount.

[0086] The PCR amplification conditions were as follows: pre-denaturation at 95°C for 5 min; 40 cycles of 95°C for 30 s, 50°C for 30 s, and 72°C for 1 min; and extension at 72°C for 10 min.

[0087] The amplified products were sequenced using the IIllumina MiSeq PE300 platform to obtain the original sequence.

[0088] 1.3.3 Metagenomic Data Processing

[0089] The original sequence was analyzed for quality control using Trimmomatic v0.39 software (Bolger, AM, Lohse, M., and Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114-2120.), and FastQC v0.11.5 (de Sena, BG, and Smith, AD (2019). Falco: high-speed FastQC emulation for quality control of sequencing data. F1000 Research 8, 1-22.) was used for data statistics before and after quality control. FASTX-Toolkit v1.4.1 was used to remove the adapter, and FLAS H v2.2.0 was used for double-end sequence splicing. The parameters were set to default, and the splicing efficiency was above 95% ( T., and Salzberg, SL (2011). FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957-2963.).

[0090] Chimeras were removed using vsearch v2.7.1 (Rognes, T., Flouri, T., Nichols, B., Quince, C., and Mahé, F. (2016). VSEARCH: a versatile open source tool for metagenomics. PeerJ 4, e2584.). Finally, 8488 sequences were obtained: 4723 in 2021 and 3765 in 2022. All raw sequences were submitted to the NCBI database (https: / / www.ncbi.nlm.nih.gov / ), with sequence numbers ranging from SRR30663504 to SRR30663512.

[0091] 1.3.4 BOLD system MOTUs division

[0092] All 8488 sequences were submitted to the BOLD system for species classification. The website is http: / / www.boldsystems.org / index.php / IDS_IdentificationRequest. The bold.py program was used to implement the system. The input data was a fas format file (for example, XX.fas was the input file, and the file name in the file was ">22YH030930.249"), and 4 files were output: ①XXouts.fa; ②XXBOLD.sum.fas; ③XXouts.fa.error.fas; ④XXBOLD.fas, where "XXBOLD.fas" was the final BOLD result, and the specific file name contained the six-level annotation result ">22YH010715.1_Arthropoda_Insecta_Hymenoptera_Formicidae_Rhytidoponera_XX(55.56)".

[0093] 1.3.5 Downstream analysis of metagenomic data

[0094] Downstream analysis of community composition was performed using the Phyloseq software package V.1.44.0 (McMurdie, PJ, and Holmes, S. (2013). Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PloS one 8, e61217.).

[0095] By clustering OTUs (Operational Taxonomic Units) at 97% similarity, an OTU list was generated to record the relative abundance of each OTU in each sample, as well as the classification of the OTUs. After taxonomic identification, differentially abundant OTUs were selected as key OTUs for further statistical analysis. Further statistical analysis included species composition, diversity assessment, intergroup comparison, heat map visualization, and identification of key OTUs. Alpha diversity was analyzed by evaluating the differences in the Shannon index and richness index, beta diversity was analyzed using principal coordinates analysis (PCoA) based on weighted UniFrac distance, and statistical significance was assessed by analysis of similarities (ANOSIM) (Liu, Y.-X., Chen, L., Ma, T., Li, X., Zheng, M., Zhou, X., Chen, L., Qian, X., Xi, J., Lu, H., et al. (2023). EasyAmplicon: An easy-to-use, open-source, reproducible, and community-based pipeline for amplicon data analysis in microbiome research. iMeta 2, e83.). The above statistical analyses were performed under R packages (r4.3.1) such as microbiome, amplicon, microeco and vegan, while the graphical visualizations were mainly created using ggplot2, dplyr, RColorBrewer, ggpubr in R packages (r4.3.1) (Neuwirth, E., and Neuwirth, ME (2014). Package 'RColorBrewer'. ColorBrewer palettes 991. Wickham, H. (2011). ggplot2. Wiley interdisciplinary reviews: computational statistics 3, 180-185.).

[0096] 1.4 Determination of sorghum yield and quality

[0097] 1.4.1 Sample Collection

[0098] The sorghum grains of the green control group and the non-green control group were harvested when they reached full maturity. After harvesting, they were promptly dried, threshed, air-dried, and weighed. The yield was calculated based on 14% moisture content in kg, with one decimal place. When harvesting, the side rows (one row on each side) were removed and the middle rows were collected for yield.

[0099] 1.4.2 Data Analysis

[0100] The test collects yield, thousand kernel weight (TGW), kernel weight and quality data.

[0101] In terms of yield, each harvest covers an area of ​​no less than 1,200 square meters. At each sampling point, three plots were randomly selected, and the actual yields of these plots were measured and converted into yields per hectare (1 hectare = 10,000 square meters). When the moisture content of the grain reaches 14%, the TGW of fully mature grains is measured and expressed in grams (g). The weight of a single ear of grain is expressed in grams (g). A 1 kg grain sample was collected from each plot and sent to the Grain and Product Quality Supervision, Inspection and Testing Center of the Ministry of Agriculture and Rural Affairs (Harbin) for analysis. Detection indicators: crude protein (dry basis), crude fat (dry basis), crude starch (dry basis), amylopectin (percentage of starch) and tannin (dry basis).

[0102] Then, the Wilcoxon rank sum test was used to analyze the differences in sorghum yield and quality between the green control group and the non-green control group.

[0103] 2. Results

[0104] 2.1 Arthropod dominance in different years

[0105] To investigate the diversity of arthropods in sorghum fields in different years, a Malaynet survey was conducted in two fields (LP and SZ) in 2021 and in one field (YH) in 2022.

[0106] The results showed that the Malay net survey method was highly effective in capturing arthropod species, with arthropods accounting for more than 90% of the collected samples ( Figure 2 A). This has proved the dominant position of arthropods in the sorghum field ecosystem. Among the samples collected, the most dominant ones were Diptera, Hymenoptera and Lepidoptera, so the subsequent analysis focused on these key arthropod groups ( Figure 2 B).

[0107] When comparing diversity across areas and years, no significant differences in species diversity indices were found between the different sampling sites surveyed in 2021 ( Figure 2 C). This suggests that arthropod communities at different sites were relatively consistent in terms of species diversity within the same year. However, a clear difference emerged when comparing the two years: the Shannon Diversity Index in 2021 was significantly higher than that in 2022, indicating that arthropod diversity was significantly richer in 2021. However, it is worth noting that the actual differences in the Shannon Index were relatively small, suggesting that the effect size, while statistically significant, was low.

[0108] Further analysis revealed that the families with the largest numbers of arthropods in both years were Muscidae, Braconidae, and Chironomidae. These families persisted in large numbers and made a significant contribution to the overall community structure ( Figure 2 D). At the genus level, several genera were identified that were dominant in both years, including Atherigona, Rivellia, Sarcophaga, Chironomus, Lispe, Psychoda, and Adelius ( Figure 2 E), although their relative abundances changed between 2021 and 2022. For example, Psychoda and Chironomus were significantly more common in the LP sampling site starting in 2021, indicating a local surge of these genera in that year. In contrast, Atherigona showed a clear dominance in 2022, occurring in 20 of the 21 samples that year, indicating that the arthropod community structure changed significantly between 2021 and 2022, with Atherigona becoming the dominant genus in 2022 compared to 2021.

[0109] 2.2 Increased arthropod diversity and Hymenoptera dominance in the green control treatment group

[0110] The alpha and beta diversity of different sampling sites (LP, SZ, LX, PW) in 2021 were compared, and the data of the chemical control control group (LP, SZ) and the green control group (LX, PW) were compared. In the control group (LP, SZ) and the green group (LX, PW), the richness index ( Figure 3 A) and β diversity ( Figure 3 No significant differences were observed in either group (B), indicating that the sampling was representative and both groups were reproducible. Then, the differences between the green group (LX, PW) and the control group (LP, SZ) were analyzed. The richness index was significantly higher in the green group compared to the control group ( Figure 4 A), the β diversity was significantly different from that of the control group (P<0.05, Figure 4 B). Diptera, Hymenoptera, Lepidoptera, and Hemiptera were the dominant orders in the control group and the green group ( Figure 4 C).

[0111] To highlight specific differences between the control and green groups, 28 OTUs that were decreased in the green group and 27 OTUs that were enriched in the green group compared to the control group were identified ( Figure 4 C). To further study these OTUs, species classified only at the genus level were removed and species within the same genus were merged together. The results showed that the green group had 22 enriched genera and 17 reduced genera ( Figure 4D). Perilampus (Hymenoptera, Macrobrachiidae) was the most abundant genus in the green group, while Dasyhelea (Diptera, Trichodidae) was the most abundant genus in the chemical control group. The green group was dominated by Hymenoptera genera, while the control group was dominated by Diptera and Lepidoptera genera, with a change greater than log2-fold.

[0112] In addition, there were no significant differences in the richness index between July, August, September, and October ( Figure 3 C). However, β diversity was mainly affected by the month, with July showing significant differences compared to other months ( Figure 3 D). We further compared the differences in taxa between the groups at different times (July, August to October). Although there was no difference in the richness index between the groups at different times, the green group had higher values ​​from August to October compared with the control group ( Figure 3 E). There were significant differences in β diversity between groups and at different times, and β diversity values ​​at different times were more similar along the PCo1 axis ( Figure 3 F), which indicates that the community composition at these times is more similar based on the first principal coordinate. It is noteworthy that from August to October, the proportion of Hymenoptera species in the green group is higher than in other periods.

[0113] 2.3 The sorghum yield of the green control treatment group was higher, and the grain quality showed an improvement trend

[0114] Using four locations (control group: LP, SZ; green group: LX, PW), the sorghum yield and quality of the green group and the control group were compared in 2021-2022.

[0115] To evaluate the yield of sorghum ( Figure 5 A), analyzed the yield (kg / 667m 2 ), thousand-grain weight (g) and grain weight (g). Although there was no significant difference between the groups, the yield of the green group (557.30kg / 667m 2 ), thousand-grain weight (22.45g) and grain weight (55.73g), the yield of the green group (541.45kg / 667m 2 ), thousand-grain weight (22.30 g) and grain weight (54.15 g) were higher in average.

[0116] The sorghum quality of the green and control groups was also compared using the following indicators: crude protein content (%DW), crude fat content (%DW), crude starch content (%DW), tannin content (%DW), and the proportion of amylopectin to total starch (%DW). DW stands for dry weight ( Figure 5B). The analysis showed that the crude fat content of the green group was significantly lower than that of the control group (P = 0.041). Although no other indicators showed significant differences, the mean values ​​of crude protein content (%DW), crude starch content (%DW), and the ratio of total starch to amylopectin (%DW) in the green group were higher than those in the chemical control group, while the mean value of tannin content (%DW) was lower than that in the control group ( Figure 5 B).

[0117] 3. Conclusion and discussion

[0118] 3.1 Impact on arthropod diversity

[0119] The analysis showed that arthropod diversity varied more significantly between years than between fields within the same year. Although arthropod diversity was similar across sampling sites in the same year, significant changes in arthropod diversity from 2021 to 2022 highlighted the impact of temporal factors on arthropod communities. This temporal variability suggests that external factors such as climatic conditions, seasonal changes, and agronomic practices may play a key role in the formation of arthropod populations. In 2021, the abundance of certain genera, such as Psychoda and Chironomus, increased significantly, especially at the LP sampling site. However, in 2022, Atherigona became the dominant genus, present in large numbers in most samples. This change highlights the importance of year-to-year fluctuations in species composition and community structure, which may be affected by environmental changes or differences in agricultural management practices.

[0120] 3.2 Impact of green ecological control technology on arthropod communities

[0121] Comparison between the green and control groups showed that the green ecological control method increased the richness of arthropods and the dominance of Hymenoptera. This result shows that the green ecological control technology promotes a more balanced and diverse arthropod community. Hymenoptera, which includes beneficial species such as parasitoids and predators, plays a vital role in natural pest control and makes an important contribution to ecosystem health. These insects help regulate the number of pests and can reduce dependence on chemical pesticides, which is in line with sustainable agricultural goals. The increase in Hymenoptera in the green control group shows that the green ecological control method strengthens ecosystem service functions, especially through natural pest control mechanisms. At the sampling point, the precise release technology of pine caterpillar trichogrammatid was also implemented to achieve synergistic effects of biological control measures and greatly improve the green control effect of sorghum target pests. The green ecological control technology increased the abundance of Hymenoptera in the community, once again demonstrating the effectiveness of incorporating natural enemies into pest control strategies.

[0122] 3.3 Effects of green ecological control technology on sorghum quality

[0123] The results showed that the green ecological control technology not only promoted the increase of arthropod diversity, especially the increase of Hymenoptera diversity, but also had a certain improvement in the quality of sorghum. Although there was no significant difference in sorghum yield between the green group and the control group, the green group consistently showed higher average values ​​in key quality indicators (including crude protein, crude starch and amylopectin ratios), while crude fat content decreased.

[0124] Behind these changes may be an increase in the number of beneficial Hymenoptera insects (such as parasitic wasps and pollinators), which enhances the ecological control of pests and contributes to crop safety and ecosystem stability. By reducing pest pressure, these insects may improve nutrient allocation in plants and affect crop quality, such as protein and starch content. In addition, studies on plant-insect interactions have shown that insect herbivory can change plant biochemical pathways, thereby affecting the composition of nutrients. Green ecological control technology can alleviate the negative effects of herbivory by regulating a balanced arthropod community.

[0125] The green ecological control method in the present invention promotes the abundance of beneficial arthropods, which may help crops become safer and greener, and help improve crop quality. Through the present invention, it is found that the green ecological control method is used for production management, which drives the increase in arthropod diversity and plays a vital role in improving ecosystem services and crop safety.

[0126] Although the above embodiment describes the present invention in detail, it is only a part of the embodiments of the present invention, not all of the embodiments. People can also obtain other embodiments based on this embodiment without creativity, and these embodiments all fall within the protection scope of the present invention.

Claims

1. A method for evaluating the effectiveness of green ecological prevention and control technology, characterized in that: include: (1) Perform high-throughput sequencing on arthropod samples treated with green ecological control methods and non-green control methods; (2) performing metagenomic data processing on the raw data obtained by high-throughput sequencing to obtain processed data; (3) submitting the processed data to the BOLD system for species classification; (4) Community composition after species delineation using downstream analysis of metagenomic data for α and β diversity; (5) Determination and analysis of crop yield and quality under green ecological control methods and non-green control methods; (6) The effectiveness of the green ecological control method is analyzed by combining the results of the yield and quality of crops grown under the green ecological control method and the non-green control method with the α or β diversity of the arthropod samples. If the results of the yield and quality of crops grown under the green ecological control method are positively correlated with the α or β diversity of the arthropod samples, the green ecological control method is judged to be effective.

2. The method according to claim 1, characterized in that: The arthropod sampling is carried out by using Malay net trapping to collect arthropod samples.

3. The method according to claim 1, characterized in that: In step (1), the primers used for the high-throughput sequencing are LCO1490 and HCO2198; the sequence of LCO1490 is shown in SEQ ID NO.1, and the sequence of HCO2198 is shown in SEQ ID NO.

2.

4. The method according to claim 1, characterized in that: In step (2), the metagenomic data processing includes using Trimmomatic v0.39 software to perform quality control analysis on the original sequence obtained by high-throughput sequencing, using FastQCv0.11.5 to perform data statistics before and after quality control, using FASTX-Toolkit v1.4.1 to remove the connector, and using FLASH v2.2.0 to perform double-end sequence splicing with default parameters; using vsearchv2.7.1 to remove chimeras to obtain processed data.

5. The method according to claim 1, characterized in that: In step (3), the species division method adopts MOTUs division, and the MOTUs division includes submitting the processed data to the BOLD system for species division; it is implemented using the bold.py program, the input data is a fas format file, and the output fas format file is the BOLD result.

6. The method according to claim 1, characterized in that: In step (4), the downstream analysis of the metagenomic data includes: using the Phyloseq software package V.1.44.0 to perform downstream analysis of community composition; the downstream analysis of community composition generates an OTU list by clustering the OTUs at 97% similarity to record the relative abundance of each OTU in each sample and the classification of the OTU; after classification and identification, the differentially abundant OTUs are selected as key OTUs for further statistical analysis.

7. The method according to claim 6, characterized in that: The OTUs were further subjected to statistical analyses including species composition, diversity assessment, inter-group comparison, heat map visualization, and identification of key OTUs.

8. The method according to claim 7, characterized in that: Further statistical analyses were performed to analyze alpha diversity by assessing differences in the Shannon index and richness index; beta diversity was analyzed using principal coordinates analysis based on weighted UniFrac distances, and statistical significance was assessed by ANOSIM similarity analysis to explore differences in community composition between treatment groups and years.

9. The method according to claim 7, characterized in that: The further statistical analysis was performed under the microbiome, amplicon, microeco and vegan packages in R package v4.3.1, while the graphical visualization was achieved by ggplot2, dplyr, RColorBrewer, ggpubr in R package v4.3.

1.

10. A green ecological prevention and control method for sorghum, characterized in that: The method steps include: (a) One solar insecticidal lamp is installed for every 48 to 52 mu of field; the parameter settings of the solar insecticidal lamp include wavelength between 320 and 680 nm; grid voltage is 3600 V, electric shock net wire diameter is ≥1.8 mm, grid spacing is ≥10 mm; wind speed at the fan inlet is ≥3.0 m / s; (b) Use insect pheromones to lure pests. Install 2 to 3 sets of traps per acre to control pests. The traps are selected to lure stem borers. The lure core of the trap is replaced every 3 to 5 weeks to kill male stem borers, reduce the mating rate of females, and reduce the base number of the next generation; (c) Precision release of Trichogramma pine caterpillars. From June to August each year, Trichogramma pine caterpillars are released four times in sorghum fields in green control areas, with 14,000 to 16,000 released per mu each time.

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