Soil structure and fertility synergistic optimization method based on straw return and promotion of decay

Abstract

This invention discloses a method for synergistic optimization of soil structure and fertility based on straw return to the field to promote decomposition, belonging to the field of soil optimization technology. A systematic technical system is constructed from the dimensions of in-situ straw decomposition and compost humification enhancement. Highly efficient decomposition-promoting microorganisms and humification promoters are screened through indoor cultivation experiments. The regulatory mechanism of decomposition promoters on the compost humification process is analyzed using humification kinetic models and structural equation models, forming a compost humification enhancement technology. Key parameters affecting in-situ straw decomposition are screened using the nylon mesh bag method. Multiple physical, chemical, and biological indicators of the soil are measured through years of field experiments. A comprehensive scoring model is constructed using principal component analysis, combined with multi-factor variance analysis and multiple comparisons, to screen the treatment combination with the highest contribution rate to the synergistic improvement of soil structure and fertility. Technical procedures are formulated and demonstrated. This achieves synergistic fertilization of the topsoil and sub-topsoil of degraded soils, with significant economic, ecological, and social benefits.

Description

Technical Field

[0001] This invention relates to the field of soil optimization technology, and in particular to a method for synergistic optimization of soil structure and fertility based on straw return to the field to promote decomposition. Background Technology

[0002] Straw, as an important renewable agricultural resource, is rich in organic matter, nitrogen, phosphorus, potassium, and various trace elements. Returning straw to the field, as a core technology for the resource utilization of agricultural waste, has become one of the key ways to promote green and low-carbon agricultural development and achieve the strategic goal of "reducing fertilizer application."

[0003] The positive effects of straw return to the field on soil improvement have been widely confirmed. Studies have shown that straw return can significantly improve soil physical structure, aeration, and water retention by increasing soil organic matter content and promoting soil aggregate formation. Simultaneously, straw, as a natural slow-release nutrient reservoir, has a nutrient release pattern that better matches crop nutrient requirements, effectively supplementing the supply of nitrogen, phosphorus, and potassium in the soil and enhancing soil chemical fertility. Furthermore, exogenous carbon input can drive the remodeling and functional activation of soil microbial communities, enhance soil enzyme activity, and optimize carbon and nitrogen cycling processes. The rational use of straw return technology can achieve sustainable agricultural development and improve crop yields and soil health.

[0004] However, in practical applications, due to the stable structure of high molecular compounds such as cellulose, hemicellulose, and lignin in straw, the decomposition cycle is long under natural conditions, especially in low-temperature regions. This slow decomposition can easily lead to decreased sowing quality and hindered seedling emergence in subsequent crops. Furthermore, incomplete straw decomposition not only fails to effectively increase soil organic matter content but may also cause nitrogen deficiency in crop seedlings due to microbial nitrogen fixation. Moreover, existing technologies often focus on single-dimensional optimization, such as simply screening decomposition-promoting agents or adjusting tillage methods. They lack a systematic and synergistic technical solution that addresses both "in-situ decomposition" and "composting," making it difficult to achieve simultaneous and synergistic improvement in soil structure and fertility.

[0005] Existing research has explored accelerating straw decomposition through the application of decomposition-promoting microbial agents, improving straw return to the field through optimized tillage methods, and enhancing straw humification through composting processes. The National Key Research and Development Program has developed a direct-return, rapid-decomposition carbon-fixing microbial agent that can accelerate straw decomposition and increase soil organic carbon storage. Research from Hunan Agricultural University shows that the combined application of straw and organic fertilizer can significantly increase soil total carbon, total nitrogen, and total phosphorus levels, enhance the activity of catalase, sucrase, and cellulase, and improve soil aggregate structure. Northeast Agricultural University's precision nutrient management technology under straw return, combining straw return with minimal or no stirring, reduces soil bulk density and improves soil physicochemical properties. Research from the Chinese Journal of Agricultural Engineering also confirms that the combined application of straw, biochar, and biogas slurry can effectively increase the proportion of soil aggregates larger than 0.053 mm and improve soil aggregate structure.

[0006] However, existing technologies still have the following shortcomings: First, there is a lack of systematic regulation of the straw decomposition process. Most technologies only focus on the decomposition rate and ignore the conversion efficiency of decomposition products into stable humus. Second, field parameter optimization relies heavily on empirical adjustments and lacks quantitative screening methods based on multi-index comprehensive evaluation and statistical modeling. Third, the two modes of in-situ return to the field and composting return to the field are often studied in isolation and have failed to form a synergistic and efficient technical system.

[0007] In summary, there is an urgent need to develop a method for synergistic optimization of soil structure and fertility based on straw return to the field to promote decomposition. This method should systematically construct a technical framework from two dimensions: "in-situ straw decomposition" and "composting enhancement." Through screening of decomposition-promoting microbial agents, optimization of composting processes, field verification, multi-index comprehensive evaluation, and mathematical model optimization, the treatment combination with the highest contribution rate to soil structure improvement and fertility enhancement can be selected, achieving efficient fertilization and sustainable utilization of degraded soils. Therefore, a method for synergistic optimization of soil structure and fertility based on straw return to the field to promote decomposition is proposed. Summary of the Invention

[0008] The main objective of this invention is to provide a method for synergistic optimization of soil structure and fertility based on straw return to the field to promote decomposition, which can effectively solve the problems in the background art.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for synergistic optimization of soil structure and fertility based on straw return to the field to promote decomposition includes the following steps: S1: Collect degraded soil samples for physicochemical property analysis, collect crop straw and pre-treat it; through indoor constant temperature culture experiments, screen a complex strain of bacteria that can efficiently degrade cellulose and lignin as an in-situ composting agent, and microorganisms or chemical catalysts that promote the polymerization of humus precursors as composting humification promoters. S2: Set up a composting simulation reactor, add the composting humification promoters obtained in step S1, monitor the changes in temperature, pH, EC, carbon-nitrogen ratio and humic composition during the composting process, construct a humification kinetic model, and elucidate the regulatory mechanism of the humification promoters on the humification process. S3: Using the nylon mesh bag method or pot cultivation method, different combination treatments were set up, and the straw weight loss rate, cellulose / lignin degradation rate and soil enzyme activity were measured regularly to preliminarily determine the key parameters affecting the in-situ decomposition of straw. S4: Based on the key parameters that have been preliminarily determined to affect the in-situ decomposition of straw, a long-term fixed experimental field was established in the degraded soil area. Different combined treatments were set up, and soil samples from the top layer and sub-top layer were collected during the critical growth period of crops to determine soil physical structure indicators, chemical fertility indicators and biological characteristics indicators. S5: Based on the field location experiment data from step S4, principal component analysis was used to reduce the dimensionality of multiple indicators and construct a comprehensive scoring model for soil structure improvement and fertility enhancement. Multivariate analysis of variance was used to test the significant impact of different treatment combinations on the comprehensive score. Through multiple comparisons and effect size calculations, the treatment combination with the highest contribution rate to soil structure improvement and fertility enhancement was selected. S6: Establish a core demonstration area in a typical degraded soil area using the optimal treatment combination obtained in step S5 to verify the technical effects and promote its application.

[0010] Furthermore, in step S1, the crop straw includes at least corn straw, wheat straw, or rice straw, and the pretreatment includes crushing the straw to a length of 3-8 cm and measuring its carbon-nitrogen ratio, cellulose, hemicellulose, and lignin content.

[0011] Furthermore, in step S2, the composting humification kinetic model uses the following set of differential equations to describe the transformation process of organic matter: ; in, It is biodegradable organic carbon; P is a precursor to humic substances, and H is humic substances. The rate constant for the decomposition of organic matter is... The humification rate constant under natural conditions. The precursor mineralization rate constant. The catalytic efficiency coefficient of the promoter. The catalytic function of the promoter for the humic polymerization reaction, This is the conversion factor.

[0012] Furthermore, in step S2, elucidating the regulatory mechanism of the humification process by the humifying agent further includes: Structural equation modeling was used to analyze the pathway by which putrefactive agents affect humus formation by altering the structure and function of the microbial community. Calculate the normalized pathway coefficients for putrefactive agent → enzyme activity → precursor polymerization → humic aromatization. The bootstrapping method was used to examine whether the microbial community or enzyme activity played a significant mediating role. The structural equation model includes a measurement model for reflecting the relationship between observed variables and latent variables, and a structural model for describing the causal path relationship between latent variables. The measurement model is represented as follows: Where X is the vector of external observed variables, including the concentration of humification promoter and the redox potential of the promoter; Y is the vector of endogenous observed variables, including microbial biomass carbon, fungal / bacterial ratio, laccase activity, manganese peroxidase activity, humic acid content, and humification index. As an external latent variable, it represents the humic growth promoter effect; These are endogenous latent variables, including latent variables of microbial community structure, key enzyme activity, and humification degree. This is the loading matrix, representing the degree to which the observed variables explain the latent variables; This is the measurement error vector; The structural model is represented as follows: Its expanded path equation system takes the form: ,in, As a latent variable in microbial community structure; This is a potential variable for key enzyme activity; As a latent variable for the degree of humification; The direct effect path coefficients of humification promoters on each endogenous latent variable; The path coefficients between endogenous latent variables; This refers to the residual terms of the structural model.

[0013] Furthermore, in step S3, the different tillage methods include rotary tillage, deep loosening, or plowing; the amount of straw returned to the field includes half-amount return, full-amount return, or double-amount return; and the amount of the decomposition promoter applied is 0.5-2.0 kg / mu.

[0014] Furthermore, the soil physical structure indicators mentioned in step S4 include at least soil bulk density, porosity, content of aggregates >0.25mm, and average weight diameter of aggregates; the chemical fertility indicators include at least soil organic carbon, particulate organic carbon, mineral-bound organic carbon, total nitrogen, available phosphorus, and available potassium; and the biological characteristic indicators include at least microbial biomass carbon, microbial community diversity index, and soil enzyme activity.

[0015] Furthermore, in steps S3 and S4, the combined treatment method includes at least the tillage method, the amount of straw returned to the field, and the amount of decomposition agent applied.

[0016] Furthermore, the comprehensive scoring model constructed by the principal component analysis method described in step S5 is as follows: ; in, The top k principal components with eigenvalues ​​greater than 1 and cumulative variance contribution rates greater than 80% are selected. Let F be the eigenvalue of the i-th principal component, and F be the comprehensive score of each treatment combination.

[0017] Furthermore, in step S5, the step of using multifactor ANOVA to test the significance of different treatment combinations on the comprehensive score specifically involves: ,in, The overall average; Effects of farming methods; For the effect of straw returning to the field; For the effect of a preservative; This is a second-order interaction; It is a third-order interaction; This is random error.

[0018] Furthermore, in step S5, the step of selecting the treatment combination that contributes the most to soil structure improvement and fertility enhancement further includes: Multiple comparisons were performed on the mean comprehensive scores of each treatment combination using the least significant difference method or the Tukey HSD method. Using effect size model Quantify the extent to which each factor and its interaction explains the overall variation; The treatment combination with the highest overall score and the most significant difference from other treatments was determined as the optimal treatment combination.

[0019] The present invention has the following beneficial effects: Compared with existing technologies, this solution, through the selection of highly efficient decomposition-promoting microorganisms and humification accelerators, combined with optimized composting process parameters, can increase the cellulose degradation rate of straw by 25%-35% and the lignin degradation rate by 15%-25%. The composting maturity cycle is shortened by 7-10 days, the humification index (HI) is increased from 0.8-1.2 in conventional composting to 1.5-2.0, the humic acid content increases by more than 30%, the fulvic acid content is relatively reduced, and the quality of humic matter is significantly improved.

[0020] Compared with existing technologies, this method, through the selection of optimal tillage techniques combined with composting agents (such as deep tillage + full return to the field + compound composting agents), reduces the topsoil bulk density by 8%-15% after 2-3 years of continuous implementation, from the typical 1.45-1.55 g / cm³ of degraded soil.3 Reduced to 1.30-1.40 g / cm³ 3 Total porosity increased by 10%-18%; the content of water-stable aggregates >0.25mm increased by 20%-30%; the average weight diameter (MWD) of aggregates increased by 25%-35%; and the soil permeability and erosion resistance were significantly enhanced.

[0021] Compared with existing technologies, this scheme, through multi-index measurement and a comprehensive scoring model, can increase the organic matter content of the topsoil by 0.2-0.4 g / kg annually, with a cumulative increase of 0.8-1.2 g / kg over three consecutive years; increase total nitrogen content by 12%-18%; and increase available phosphorus and available potassium by 10%-15% and 8%-12%, respectively. The organic matter content in the sub-topsoil (20-40cm) will simultaneously increase by 0.3-0.5 g / kg, achieving a full-profile fertilization effect.

[0022] Compared with existing technologies, this scheme, through structural equation model analysis, shows that the optimal treatment combination can increase soil microbial biomass carbon by 25%-35%, increase the fungal / bacterial ratio by 0.3-0.5, and increase the activities of laccase, urease, and sucrase by 30%-45%, 20%-30%, and 25%-35%, respectively, thus significantly enhancing the soil carbon and nitrogen cycle function.

[0023] Compared with existing technologies, this solution effectively solves the problems of slow decomposition and seedling burn caused by direct straw return to the field through tillage optimization and the application of decomposition promoters. It enables straw to be rapidly converted into soil organic matter in the field, increasing the annual straw decomposition rate from the conventional 45%-55% to 70%-80%. Through decomposition promoters and process optimization, the compost products achieve a higher degree of humification, have a stronger promoting effect on aggregate formation after being applied to the soil, and increase the retention rate of compost organic carbon in the soil by 20%-30%. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating the method for synergistic optimization of soil structure and fertility based on straw return to the field to promote decomposition, as described in this invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0026] Example 1: See Figure 1 The diagram shown is a flowchart of a method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition, according to the present invention. The implementation process may specifically include the following stages and steps: Phase 1: Preliminary Preparation and Screening of Key Materials (Indoor Culture Phase) Step 1: Soil baseline survey and straw pretreatment 1.1 Soil samples were collected from the 0-20cm and 20-40cm soil layers in typical degraded soil areas, and basic physicochemical properties were determined, including: bulk density, porosity, pH, organic matter, total nitrogen, available phosphorus, available potassium, and cation exchange capacity.

[0027] 1.2 Collect local main crop straw (corn straw or wheat straw), air dry it naturally, then crush it to a length of 3-5 cm, mix it evenly, and take samples to determine the moisture content, carbon-nitrogen ratio, cellulose content, hemicellulose content, and lignin content.

[0028] 1.3 Soil and straw samples were classified and preserved for subsequent culture experiments.

[0029] Step 2: Screening of highly effective putrefactive bacteria and humification promoters 2.1 Prepare basic culture medium and isolate microbial strains with cellulose degradation and lignin degradation capabilities from local farmland soil and well-rotted straw compost.

[0030] 2.2 The plate transparency zone method and enzyme activity assay were used to initially screen strains with high cellulase activity and high laccase activity.

[0031] 2.3 The initially screened strains were combined and matched to construct a composite bacterial system; Set different temperatures (15℃, 25℃, 35℃); Different pH conditions (6.0, 7.0, 8.0); The growth adaptability and degradation capacity of the composite bacterial strain were determined.

[0032] 2.4 Select 1-2 groups of compound bacterial strains that maintain high activity under low temperature conditions for use as in-situ preservatives.

[0033] 2.5 Screen or formulate chemical / biological materials with redox mediator function or phenol polymerization catalysis function as composting promoters for future use.

[0034] Phase Two: Research and Development of Composting and Humic Enhancement Technology (Composting Simulation Phase) Step 3: Experimental Design for Composting and Humicification 3.1 Set up a composting simulation reactor with a volume of 50-100L and equipped with ventilation and temperature monitoring functions.

[0035] 3.2 Test treatment settings: Treatment 1: Straw + conventional compost (control) Treatment 2: Straw + humification promoter (low dose, such as 0.1%) Treatment 3: Straw + humification promoter (medium dose, such as 0.3%) Treatment 4: Straw + humification promoter (high dose, such as 0.5%) 3.3 Adjust the initial carbon-nitrogen ratio of each treatment material to 25:1-30:1, and control the moisture content at 60%-65%.

[0036] Step 4: Composting process monitoring and sample collection 4.1 After composting begins, monitor the temperature of the compost pile and the ambient temperature daily, and record the duration of the high-temperature period.

[0037] 4.2 The compost was turned over and representative samples were collected on days 0, 3, 7, 14, 21, 35 and 60.

[0038] 4.3 Fresh samples were immediately measured for pH, EC, and moisture content; some samples were air-dried and then measured for organic carbon, total nitrogen, and carbon-nitrogen ratio; some samples were frozen for enzyme activity assays.

[0039] Step 5: Humus component analysis and kinetic fitting 5.1 The humic substances were separated by sodium pyrophosphate-sodium hydroxide extraction method, and the contents of humic acid and fulvic acid were determined. The humification index (HI) was calculated as humic acid / total humic acid.

[0040] 5.2 Determination of the activities of lignin degradation-related enzymes: laccase, manganese peroxidase, and lignin peroxidase.

[0041] 5.3 Application of the humification kinetic model: Parameter fitting was performed using Python or MATLAB software to estimate the humification rate constant for each treatment group. and catalytic efficiency coefficient of promoter .

[0042] 5.4 Using structural equation modeling, the regulatory pathway of humification promoter → microbial community → enzyme activity → humus formation was analyzed, and the standardized path coefficients were calculated. The bootstrapping method was used to test whether the microbial community or enzyme activity played a significant mediating role.

[0043] Specifically, structural equation modeling includes: A measurement model used to reflect the relationship between observed variables and latent variables is expressed as: Where X is the vector of external observed variables, including the concentration of humification promoter and the redox potential of the promoter; Y is the vector of endogenous observed variables, including microbial biomass carbon, fungal / bacterial ratio, laccase activity, manganese peroxidase activity, humic acid content, and humification index. As an external latent variable, it represents the humic growth promoter effect; These are endogenous latent variables, including latent variables of microbial community structure, key enzyme activity, and humification degree. This is the loading matrix, representing the degree to which the observed variables explain the latent variables; This is the measurement error vector; A structural model used to describe causal path relationships between latent variables is represented as follows: Its expanded path equation system takes the form: ,in, As a latent variable in microbial community structure; This is a potential variable for key enzyme activity; As a latent variable for the degree of humification; The direct effect path coefficients of humification promoters on each endogenous latent variable; The path coefficients between endogenous latent variables; This refers to the residual terms of the structural model.

[0044] Mediation effect test: The Bootstrapping method was used to test the significance of indirect effects, and the effect sizes and 95% confidence intervals for the following mediation pathways were calculated: Pathway 1: Humus promoter → Microbial community → Degree of humification, with an effect value of ; Pathway 2: Humus promoter → Key enzyme activity → Degree of humification, with an effect value of ; Pathway 3: Humus promoter → Microbial community → Key enzyme activity → Degree of humification, with an effect value of ; Effect decomposition: Calculate the total effect, direct effect, and indirect effect for each pathway: Total effect = Direct effect + Indirect effect; The direct effect is The indirect effect is ; Judgment criteria: If the Bootstrapping confidence interval of an indirect path does not contain 0, the mediation effect of the path is considered significant; by comparing the magnitude and significance of the coefficients of each path, the dominant path of humification promoters in regulating the humification process is determined, thereby elucidating their mechanism of action.

[0045] Step 6: Develop technical specifications for composting and humus enhancement. 6.1 By comprehensively comparing the humification index, total humus content, and kinetic parameters of each treatment, the optimal type and dosage of humification promoter were selected.

[0046] 6.2 Determine the key process parameters for composting: initial carbon-nitrogen ratio, moisture content, turning frequency, and composting cycle.

[0047] 6.3 Compile the "Technical Specification for Enhanced Combustion of Straw", clarifying key operational points and quality control standards.

[0048] Phase 3: Research and Development of In-situ Return-to-Field Decomposition Technology (Micro-area Simulation Phase) Step 7: Micro-area simulation experiment design 7.1 Experiments were conducted in a controlled environment or field micro-plot using the nylon mesh bag method or pot cultivation method.

[0049] 7.2 Experimental factors and level settings: Factor A (Tillage Simulation): No disturbance (simulating no-tillage), shallow mixing (simulating rotary tillage), deep loosening (simulating deep loosening); Factor B (Application of preservatives): No application, application of primary screening agent (low amount), application of primary screening agent (high amount); Factor C (amount of straw returned to the field): half amount returned to the field (3000 kg / mu), full amount returned to the field (6000 kg / mu); 7.3 Each treatment was repeated 3 times, for a total of 27 treatment combinations.

[0050] Step 8: Sample Collection and Index Measurement 8.1 The nylon mesh bag or rhizosphere soil was removed on days 15, 30, 60 and 90 after the start of the experiment.

[0051] 8.2 Measurement Indicators: Straw weight loss rate (%) = (initial dry weight - residual dry weight) / initial dry weight × 100%; Changes in the content of cellulose, hemicellulose, and lignin; Soil enzyme activity: urease, sucrase, cellulase, catalase; Soil microbial biomass carbon and nitrogen.

[0052] Step 9: Preliminary identification of key parameters 9.1 Multivariate analysis of variance was used to test the significant effects of each factor and its interaction on the straw decomposition rate.

[0053] 9.2 Based on the analysis results, the key parameter combination affecting the in-situ decomposition of straw was preliminarily determined, providing a basis for subsequent field trials.

[0054] Phase 4: Field Validation and Collaborative Optimization (Field Trial Phase) Step 10: Field Positioning Experiment Design 10.1 Select flat and uniformly fertile plots in typical degraded soil areas to establish long-term fixed-location experimental fields.

[0055] 10.2 The experiment adopted a split-plot design or a randomized block design, and the following treatment combinations were set (optimized based on the results of step 9): Treatment 1: Conventional tillage + no straw return to the field (control CK); Treatment 2: Conventional tillage + full straw return to the field; Treatment 3: Deep tillage + full straw return to the field; Treatment 4: Deep tillage + full straw return to the field + decomposition promoter (low amount); Treatment 5: Deep tillage + full straw return to the field + high amount of decomposition promoter; Treatment 6: Rotation (deep tillage / rotary tillage rotation) + full straw return to the field + decomposition promoter (optimal amount).

[0056] 10.3 Each process is repeated 3 times, the cell area is not less than 30㎡, and a protection row is set.

[0057] 10.4 The continuous location experiment shall be conducted for no less than 3 years, with the same crop (such as corn) planted each year.

[0058] Step 11: Sample Collection and Index Measurement 11.1 Soil samples were collected annually during the seedling, jointing, and maturity stages of crops, with soil samples collected from the 0-20cm (topsoil layer) and 20-40cm (sub-topsoil layer) layers, respectively.

[0059] 11.2 Measurement Indicators: Physical properties: soil bulk density (ring cutter method), total porosity, capillary porosity, content of aggregates >0.25mm (wet sieving method), average weight diameter of aggregates (MWD); Chemical indicators: soil organic carbon, particulate organic carbon, mineral-bound organic carbon, soluble organic carbon, total nitrogen, alkaline-available nitrogen, available phosphorus, available potassium, pH; Biological indicators: microbial biomass carbon, microbial biomass nitrogen, bacterial / fungal community structure (high-throughput sequencing), soil enzyme activity (urease, sucrase, catalase, cellulase).

[0060] 11.3 At the crop maturity stage, assess the yield and record the grain yield and biomass yield.

[0061] Step 12: Data Cleaning and Preprocessing 12.1 Enter all measured index data into the database and check for outliers and missing values.

[0062] 12.2 Standardize the data (Z-score standardization) to eliminate the influence of dimensions.

[0063] Phase 5: Parameter Optimization and Pattern Integration (Data Analysis Phase) Step 13: Principal Component Analysis for Dimensionality Reduction and Comprehensive Scoring 13.1 Use SPSS, R, or Python software to perform principal component analysis on all soil indicators.

[0064] 13.2 Extract the top k principal components with eigenvalues ​​> 1 and cumulative variance contribution rate > 80%.

[0065] 13.3 Calculate the scores of each principal component.

[0066] 13.4 According to the formula: Calculate the overall score for each treatment combination.

[0067] 13.5 The comprehensive score F is used as the comprehensive evaluation index for soil structure improvement and fertility enhancement.

[0068] Step 14: Multivariate ANOVA to test significance 14.1 Using the comprehensive score F as the dependent variable and the main effects of tillage method, straw return amount and decomposition agent application, statistical analysis was performed according to the three-factor ANOVA model described in claim 8.

[0069] 14.2 Calculate the F-value and p-value of each factor and its interaction, and test the significance (p<0.05 is considered significant).

[0070] 14.3 If the interaction is significant, a simple effects analysis should be performed.

[0071] Step 15: Multiple comparisons and optimal combination screening 15.1 For significant main effects or interactions, multiple comparisons were performed using the LSD or Tukey HSD method.

[0072] 15.2 According to the effect size model Calculate the contribution rate of each factor and its interaction, where, To handle the sum of squares of factors (between-group differences); This is the total sum of squares.

[0073] 15.3 The treatment combination with the highest overall score and the most significant difference from other treatments (marked as group “a” in multiple comparisons) is determined as the optimal treatment combination with the highest contribution rate.

[0074] 15.4 Verify the improvement effect of the optimal treatment combination in the sub-tillage layer (20-40cm) to ensure that it has a profile enrichment effect.

[0075] Step 16: Technology Model Integration 16.1 Integrating the composting and humus enhancement technology formed in step 6 and the optimal in-situ return technology model selected in step 15.

[0076] 16.2 Two technical models were formed: Mode A (direct straw return to the field): suitable tillage method + optimal amount of straw returned to the field + method of applying composting agent; Model B (Composting and Returning to the Field): Composting and Humic Enhancement Process + Quota for Applying High-Quality Well-Decomposed Organic Fertilizer.

[0077] 16.3 Compile the "Technical Specification for Soil Structure Improvement and Fertility Synergistic Optimization Based on Straw Returning to Field for Decomposition", clarifying the key technical points, operating procedures and quality control standards.

[0078] Phase 6: Demonstration, Promotion, and Application of Technology (Technology Transfer Phase) Step 17: Construction of the Core Demonstration Zone 17.1 Select contiguous plots of land in typical degraded soil areas to establish core demonstration areas of 50-100 mu.

[0079] 17.2 Demonstrate the application of the integrated technology model in step 16 and set up a control field (farmers' conventional planting model).

[0080] 17.3 Install soil temperature and humidity sensors in demonstration and control fields to monitor changes in soil moisture and temperature in real time.

[0081] Step 18: Verification and Demonstration of Technical Effects 18.1 Organize on-site observation meetings during the critical growth period of crops, and invite farmers, agricultural technicians and researchers to participate.

[0082] 18.2 Field measurements and comparisons: soil compaction (handheld compaction meter), field water holding capacity, crop root development, crop growth and yield.

[0083] 18.3 Distribute technical information materials and answer farmers' questions.

[0084] Step 19: Technical Training and Outreach 19.1 Hold technical training courses to systematically explain the technical principles and key points of straw decomposition and return to the field.

[0085] 19.2 Cultivate local technical backbones and technology demonstration households, and establish a promotion network of "research institutes + agricultural technology extension departments + new business entities".

[0086] 19.3 Collect feedback from farmers to further improve technical details and ease of operation.

[0087] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition, characterized in that, Includes the following steps: S1: Collect degraded soil samples for physicochemical property analysis, collect crop straw and pre-treat it; through indoor constant temperature culture experiments, screen a complex strain of bacteria that can efficiently degrade cellulose and lignin as an in-situ composting agent, and microorganisms or chemical catalysts that promote the polymerization of humus precursors as composting humification promoters. S2: Set up a composting simulation reactor, add the composting humification promoters obtained in step S1, monitor the changes in temperature, pH, EC, carbon-nitrogen ratio and humic composition during the composting process, construct a humification kinetic model, and elucidate the regulatory mechanism of the humification promoters on the humification process. S3: Using the nylon mesh bag method or pot cultivation method, different combination treatments were set up, and the straw weight loss rate, cellulose / lignin degradation rate and soil enzyme activity were measured regularly to preliminarily determine the key parameters affecting the in-situ decomposition of straw. S4: Based on the key parameters that have been preliminarily determined to affect the in-situ decomposition of straw, a long-term fixed experimental field was established in the degraded soil area. Different combined treatments were set up, and soil samples from the top layer and sub-top layer were collected during the critical growth period of crops to determine soil physical structure indicators, chemical fertility indicators and biological characteristics indicators. S5: Based on the field location experiment data from step S4, principal component analysis was used to reduce the dimensionality of multiple indicators and construct a comprehensive scoring model for soil structure improvement and fertility enhancement. Multivariate analysis of variance was used to test the significant impact of different treatment combinations on the comprehensive score. Through multiple comparisons and effect size calculations, the treatment combination with the highest contribution rate to soil structure improvement and fertility enhancement was selected. S6: Establish a core demonstration area in a typical degraded soil area using the optimal treatment combination obtained in step S5 to verify the technical effects and promote its application.

2. The method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition as described in claim 1, characterized in that, In step S1, the crop straw includes at least corn straw, wheat straw or rice straw, and the pretreatment includes crushing the straw to a length of 3-8 cm and measuring its carbon-nitrogen ratio, cellulose, hemicellulose and lignin content.

3. The method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition as described in claim 1, characterized in that, In step S2, the composting humification kinetic model uses the following set of differential equations to describe the transformation process of organic matter: ; in, It is biodegradable organic carbon; P is a precursor to humic substances, and H is humic substances. The rate constant for the decomposition of organic matter is... The humification rate constant under natural conditions. The precursor mineralization rate constant. The catalytic efficiency coefficient of the promoter. The catalytic function of the promoter for the humic polymerization reaction, This is the conversion factor.

4. The method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition as described in claim 1, characterized in that, In step S2, clarifying the regulatory mechanism of the humification process by the humification agent further includes: Structural equation modeling was used to analyze the pathway by which putrefactive agents affect humus formation by altering the structure and function of the microbial community. Calculate the normalized pathway coefficients for putrefactive agent → enzyme activity → precursor polymerization → humic aromatization. The bootstrapping method was used to examine whether the microbial community or enzyme activity played a significant mediating role. The structural equation model includes a measurement model for reflecting the relationship between observed variables and latent variables, and a structural model for describing the causal path relationship between latent variables. The measurement model is represented as follows: Where X is the vector of external observed variables, including the concentration of humification promoter and the redox potential of the promoter; Y is the vector of endogenous observed variables, including microbial biomass carbon, fungal / bacterial ratio, laccase activity, manganese peroxidase activity, humic acid content, and humification index. As an external latent variable, it represents the humic growth promoter effect; These are endogenous latent variables, including latent variables of microbial community structure, key enzyme activity, and humification degree. This is the loading matrix, representing the degree to which the observed variables explain the latent variables; This is the measurement error vector; The structural model is represented as follows: Its expanded path equation system takes the form: ,in, As a latent variable in microbial community structure; This is a potential variable for key enzyme activity; As a latent variable for the degree of humification; The direct effect path coefficients of humification promoters on each endogenous latent variable; The path coefficients between endogenous latent variables; This refers to the residual terms of the structural model.

5. The method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition as described in claim 1, characterized in that, In step S3, the different tillage methods include rotary tillage, deep loosening or plowing, the amount of straw returned to the field includes half amount returned to the field, full amount returned to the field or double amount returned to the field, and the amount of decomposition promoter applied is 0.5-2.0 kg / mu.

6. The method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition as described in claim 1, characterized in that, The soil physical structure indicators mentioned in step S4 include at least soil bulk density, porosity, content of aggregates >0.25mm and average weight diameter of aggregates; the chemical fertility indicators include at least soil organic carbon, particulate organic carbon, mineral-bound organic carbon, total nitrogen, available phosphorus and available potassium; the biological characteristic indicators include at least microbial biomass carbon, microbial community diversity index and soil enzyme activity.

7. The method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition as described in claim 1, characterized in that, In steps S3 and S4, the combined treatment method includes at least the tillage method, the amount of straw returned to the field, and the amount of decomposition agent applied.

8. The method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition as described in claim 1, characterized in that, The comprehensive scoring model constructed by the principal component analysis method described in step S5 is as follows: ; in, The top k principal components with eigenvalues ​​greater than 1 and cumulative variance contribution rates greater than 80% are selected. Let F be the eigenvalue of the i-th principal component, and F be the comprehensive score of each treatment combination.

9. The method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition as described in claim 1, characterized in that, In step S5, the step of using multifactor ANOVA to test the significance of different treatment combinations on the comprehensive score specifically involves: ,in, The overall average; Effects of farming methods; For the effect of straw returning to the field; For the effect of a preservative; This is a second-order interaction; It is a third-order interaction; This is random error.

10. The method for synergistic optimization of soil structure and fertility based on straw return to the field for decomposition as described in claim 1, characterized in that, In step S5, the step of selecting the treatment combination that contributes the most to soil structure improvement and fertility enhancement further includes: Multiple comparisons were performed on the mean comprehensive scores of each treatment combination using the least significant difference method or the Tukey HSD method. Using effect size model Quantify the extent to which each factor and its interaction explains the overall variation; The treatment combination with the highest overall score and the most significant difference from other treatments was determined as the optimal treatment combination.

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