Straw covering deep scarification soil structure optimization method for temperature dominant area of dry farming black land

Abstract

The invention discloses a dry farming black land temperature dominant area straw covering deep scarification soil structure optimization method, and relates to the technical field of straw covering field returning. The method comprises the following steps: by taking conventional ridges as contrast, respectively setting a non-tillage straw non-covering mode and a non-tillage straw full-amount covering mode in a uniform ridge and wide-narrow row planting mode, processing in cooperation with different deep scarification parameters, and collecting soil samples in an experimental area in different processing modes; the method comprises the following steps: measuring soil physical indexes, available nutrients and soil carbon related indexes of a soil sample, calculating to obtain crop yield, and constructing a multi-target optimization model which takes maximization of soil quality and crop yield as an optimization target and meets the soil physical indexes, the available nutrients, the soil carbon related indexes and subsoiling parameters as constraint conditions; according to the obtained experimental data, the optimal values of the straw covering parameters and the deep scarification parameters under different covering modes are obtained, and then the farming strategy for optimizing the soil structure of the dry farming black land temperature dominant area is formed.

Description

Technical Field

[0001] This invention relates to the field of straw mulching and returning to the field, and in particular to a method for optimizing soil structure through deep loosening and straw mulching in dryland black soil temperature-advantage areas. Background Technology

[0002] Black soil is an important agricultural resource, possessing fertile soil and high grain yields. However, due to unreasonable farming practices and overexploitation, the soil structure of black soil has gradually degraded, leading to a series of problems such as declining soil fertility, increased soil erosion, and ecological degradation. This not only affects the sustainable use of black soil but also poses a potential threat to food security and the ecological environment. In black soil farming practices, traditional farming methods such as moldboard plowing, while achieving certain farming effects, lead to increased soil compaction and decreased soil porosity in the long term, thus affecting soil aeration, permeability, and root growth. Furthermore, traditional farming methods also damage soil aggregate structure, weakening soil erosion resistance and making it more susceptible to soil erosion. Therefore, there is an urgent need to find a new farming technology that can effectively improve the soil structure of black soil, enhance soil fertility, and reduce soil erosion.

[0003] Straw mulching and deep tillage, as a conservation tillage technique, has seen some application in black soil areas in recent years. Returning straw to the field increases soil organic matter, loosens the soil, and improves soil water retention by reducing evaporation and increasing infiltration, making it an effective measure for improving soil fertility. Deep tillage breaks up the plow pan, increases soil porosity, improves soil aeration and permeability, and promotes root growth.

[0004] However, the current application of straw mulching and deep tillage technology in black soil remains largely based on experience, lacking scientific data analysis and theoretical support. This results in low adaptability and insufficient standardization, hindering the full realization of the technology's effectiveness. Therefore, optimizing key technical parameters of straw mulching while integrating new conservation tillage technologies to improve soil structure, increase water storage capacity, and enhance fertility to boost crop yields is a pressing issue for the promotion and application of conservation tillage techniques in temperature-advantageous areas of dryland black soil. To address this, a method for optimizing soil structure through straw mulching and deep tillage in temperature-advantageous areas of dryland black soil is proposed. Summary of the Invention

[0005] The main objective of this invention is to provide a method for optimizing soil structure through straw mulching and deep loosening in temperature-advantageous dryland black soil areas, which can effectively solve the problems in the background art.

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

[0007] The straw mulching deep soil structure optimization method for dry farming black land temperature advantage area comprises:

[0008] A straw mulching and returning experiment is designed, wherein the straw mulching and returning experiment adopts a randomized block design, takes a conventional ridge as a control, sets up a straw mulching and returning mode of no-tillage straw mulching and no-tillage straw full amount mulching under a uniform ridge with a ridge distance of 57 cm and a wide-narrow row planting mode with a row distance of 40-80 cm, different mulching modes are matched with different deep loosening parameters for treatment, and a N marked micro area with a size of λm*λm is set up in each treatment area. 15 N marked micro area;

[0009] Soil samples in the experimental area under different treatment modes are collected before and at a mature period of crop sowing, and soil physical indexes, available nutrients and soil carbon related indexes of the soil samples are determined, and at the mature period, a N isotope in-situ tracing technology is used to determine the biomass, total nitrogen content and N abundance of the N marked micro crop samples, and crop yield is calculated and obtained. 15 N isotope in-situ tracing technology 15 N marked micro area; 15 N marked micro area;

[0010] A multi-objective optimization model is constructed, wherein the multi-objective optimization model takes maximizing soil quality and crop yield as optimization targets, takes satisfying the soil physical indexes, the available nutrients, the soil carbon related indexes and the deep loosening parameters as constraint conditions, and takes straw mulching parameters and the deep loosening parameters as optimization objects.

[0011] According to the obtained experimental data, the best values of the straw mulching parameters and the deep loosening parameters under different mulching modes are obtained by using the multi-objective optimization model, and then a soil structure optimization tillage strategy for dry farming black land temperature advantage area is formed.

[0012] Further, the soil physical indexes include soil bulk density, soil porosity and soil water content.

[0013] The available nutrients include ammonium nitrogen, nitrate nitrogen, available phosphorus and available potassium.

[0014] The soil carbon related indexes include total organic carbon content, particulate organic carbon content, mineral organic carbon content, dissolved organic carbon content, active organic carbon content, carbon-nitrogen ratio and microbial biomass carbon content.

[0015] The straw mulching parameters include mulching amount.

[0016] The deep loosening parameters include deep loosening depth and deep loosening time.

[0017] Further, the constraint conditions of the soil physical indexes include:

[0018] the soil bulk density is less than or equal to an upper limit of the soil bulk density;

[0019] the soil porosity is greater than or equal to a lower limit of the soil porosity;

[0020] the soil water content is greater than or equal to a lower limit of the soil water content.

[0021] Further, the constraint condition of the available nutrient includes:

[0022] the ammonium nitrogen content is greater than or equal to a lower limit of the ammonium nitrogen content;

[0023] the nitrate nitrogen content is greater than or equal to a lower limit of the nitrate nitrogen content;

[0024] the available phosphorus content is greater than or equal to a lower limit of the available phosphorus content;

[0025] the available potassium content is greater than or equal to a lower limit of the available potassium content.

[0026] Further, the constraint condition of the soil carbon-related index includes:

[0027] the total organic carbon content is greater than or equal to a lower limit of the total organic carbon content

[0028] the particulate organic carbon content is greater than or equal to a lower limit of the particulate organic carbon content;

[0029] the mineral organic carbon content is greater than or equal to a lower limit of the mineral organic carbon content;

[0030] the dissolved organic carbon content is greater than or equal to a lower limit of the dissolved organic carbon content;

[0031] the active organic carbon content is greater than or equal to a lower limit of the active organic carbon content;

[0032] the microbial biomass carbon content is greater than or equal to a lower limit of the microbial biomass carbon content;

[0033] the carbon-nitrogen ratio is less than or equal to an upper limit of the suitable ratio.

[0034] Further, the constraint condition of the deep ploughing parameter includes:

[0035] the minimum deep ploughing depth is less than or equal to the deep ploughing depth which is less than or equal to the maximum deep ploughing depth;

[0036] the minimum covering amount is less than or equal to the covering amount which is less than or equal to the maximum covering amount.

[0037] The maximum soil quality is described by the minimum value of the Euclidean distance between the soil physical index, the available nutrient and the soil carbon-related index and the optimal value of each index, specifically:

[0038]

[0039] In the formula, maxSq represents the maximum soil quality; Si udenotes the u-th soil physical index value; Si u-best denotes the optimal value of the u-th soil physical index; An v denotes the v-th available nutrient content; An v-best denotes the optimal value of the v-th available nutrient content; Ci w denotes the w-th soil carbon-related index value; Ci w-best denotes the optimal value of the w-th soil carbon-related index value.

[0040] The present application has the following beneficial effects,

[0041] Compared with the prior art, the present application designs a straw mulching and returning test, adopts a random block design, takes a conventional ridge as a control, sets up straw mulching and returning modes of no-tillage straw non-mulching and no-tillage straw full-mulching under uniform ridges and wide-narrow row planting modes, processes different mulching modes in cooperation with different deep loosening parameters, and sets up 15 N labeled microzones in each processing test area, collects soil samples in the test area under different processing modes before and at the mature stage of crops, measures soil samples including soil physical indexes, available nutrients and soil carbon-related indexes, and at the mature stage, measures 15 N isotopic in-situ tracing technology 15 N labeled micro-crop samples in biomass, total nitrogen content and 15 N abundance, calculates crop yield, constructs a multi-objective optimization model taking maximum soil quality and crop yield as optimization objectives, taking soil physical indexes, available nutrients, soil carbon-related indexes and deep loosening parameters as constraint conditions, and taking straw mulching parameters and deep loosening parameters as optimization objects, obtains optimal values of straw mulching parameters and deep loosening parameters under different mulching modes according to obtained experimental data, and forms a cultivation strategy for optimizing soil structure in the dry black land temperature advantage area, provides technical support for straw mulching and deep loosening strategies in the dry black land temperature advantage area according to scientific data analysis, and optimizes soil structure to solve the problems of low adaptability and lack of standardization. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 It is a straw mulching and deep loosening soil structure optimization method flowchart in the dry black land temperature advantage area of the present application;

[0043] Figure 2 It is a processing mode schematic diagram of the straw mulching and returning test in the present application scheme;

[0044] Figure 3 It is a distribution schematic diagram of the 15 N labeled microzone set in the test area. DETAILED DESCRIPTION

[0045] The present invention will be further described below with reference to specific embodiments. The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the present invention. In order to better illustrate the specific embodiments of the present invention, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the actual product size.

[0046] The specific implementation process of the technical solution of this invention includes the following steps:

[0047] Step 1: Design an experiment on straw mulching and returning to the field.

[0048] 1) The straw mulch return experiment adopted a randomized block design, with conventional ridges as the control. Under uniform ridge spacing of 57cm and wide-narrow row planting patterns of 40-80cm row spacing, two mulch treatments were set up: no-till straw mulch and no-till straw full mulch. Different mulch treatments were combined with different deep tillage parameters. Specifically, there were: no-till straw mulch, no-till straw full mulch, no-till straw full mulch combined with 25cm deep tillage, and no-till straw full mulch combined with 35cm deep tillage, for a total of 9 treatments. Each treatment was replicated 3 times. See the detailed distribution diagram below. Figure 2 As shown, the amount of straw returned to the field is approximately 10 t / hm. 2 / yr, the fertilizer application rate was the same for all treatments, and the application rate of blended fertilizer was 825 kg / hm. 2 Where N:P2O5:K2O=26:11:12;

[0049] Among them, the straw mulching parameters include the mulching amount; the deep loosening parameters include the deep loosening depth and the deep loosening time.

[0050] 2) Set up a test area of ​​size λm×λm in each treatment. 15 N-labeled microregions, see [link] Figure 3 As shown;

[0051] in, 15 The N-marked micro-regions are independently enclosed by PVC frames, which are embedded to a depth of 60cm. Each micro-region measures 2m x 2m. To avoid edge effects, [the following text is incomplete and likely refers to further details about edge marking]. 15 Soil samples were collected from the central region of the N-labeled micro-regions. In situ. 15 In the N-labeled micro-region experiment, the fertilization amount of each treatment was the same as that of each experimental area. The only difference was that 10% abundance of labeled urea was applied in the first year of the experiment.

[0052] Step 2: Soil samples were collected from the experimental areas under different treatments before crop sowing and at maturity. The soil samples were then analyzed for soil physical parameters, available nutrients, and soil carbon-related parameters. Specifically:

[0053] Soil physical indicators include:

[0054] Soil bulk density:

[0055] Definition: The mass of soil per unit volume, including pores.

[0056] Significance: Reflects the degree of compaction of the soil. The lower the bulk density, the looser the soil, and the better the aeration and water permeability.

[0057] Measurement method: Ring method.

[0058] Soil porosity:

[0059] Definition: The percentage of pore volume in the total volume of soil.

[0060] Significance: Reflects the aeration and water permeability of the soil. The higher the porosity, the better the aeration and water permeability of the soil.

[0061] Measurement method: Calculated from soil bulk density and soil density.

[0062] Soil water content:

[0063] Definition: The content of water in the soil.

[0064] Significance: Reflects the water retention capacity of the soil. Suitable water content is conducive to plant growth.

[0065] Measurement method: Oven drying method, tensiometer method, time domain reflectometry (TDR), etc.

[0066] Available nutrients include:

[0067] Ammonium nitrogen, nitrate nitrogen:

[0068] Significance: Forms of nitrogen that can be directly absorbed and utilized by plants.

[0069] Measurement method: Alkaline hydrolysis diffusion method.

[0070] Available phosphorus:

[0071] Significance: Forms of phosphorus that can be directly absorbed and utilized by plants.

[0072] Measurement method: Bray-Kurtz method, Olsen method.

[0073] Available potassium:

[0074] Significance: Forms of potassium that can be directly absorbed and utilized by plants.

[0075] Measurement method: Ammonium acetate extraction method.

[0076] Soil carbon-related indicators include:

[0077] Total organic carbon content

[0078] Definition: The total amount of all organic carbon in the soil, including particulate organic carbon, mineral-bound organic carbon, and dissolved organic carbon.

[0079] Significance: It is one of the important indicators to measure soil fertility and soil quality. The higher the TOC content, the stronger the soil fertility and water and fertilizer retention capacity.

[0080] Measurement method:

[0081] Elemental analyzer method: Organic carbon is converted into carbon dioxide by high-temperature combustion method, and the content of carbon dioxide is determined by infrared detector.

[0082] Potassium dichromate oxidation method: Using potassium dichromate to oxidize organic carbon in soil under acidic conditions, the remaining potassium dichromate is determined by titration method, and the content of organic carbon is calculated.

[0083] Particulate organic carbon content

[0084] Definition: Organic carbon in soil in the form of particles, usually with particle size greater than 0.053mm.

[0085] Significance: Particulate organic carbon is an important component of soil organic carbon, with high biological activity and easy to be decomposed and utilized by microorganisms.

[0086] Measurement method:

[0087] Particle size classification method: Particulate organic carbon is separated by screening or sedimentation method, and its carbon content is determined by elemental analyzer.

[0088] Density separation method: Particulate organic carbon is separated by using different density liquids (such as bromo-chromocyanol solution), and then determined.

[0089] Mineral organic carbon content

[0090] Definition: Organic carbon closely combined with soil mineral particles, usually difficult to be decomposed by microorganisms.

[0091] Significance: Mineral-bound organic carbon is a stable part of soil organic carbon, and plays an important role in the long-term stability of soil carbon pool.

[0092] Measurement method:

[0093] Chemical extraction method: Mineral-bound organic carbon is extracted by chemical reagents (such as sodium hydroxide, hydrochloric acid, etc.), and then determined by elemental analyzer.

[0094] Physical separation method: Mineral-bound organic carbon is separated by ultrasonic wave, centrifugation, etc., and then determined.

[0095] Dissolved organic carbon content

[0096] Definition: Dissolved organic carbon in soil solution, usually obtained by water extraction.

[0097] Significance: Dissolved organic carbon is the most bioavailable fraction of soil organic carbon, directly absorbed and utilized by plants and microorganisms.

[0098] Measurement Method:

[0099] Water extraction method: Soil samples are soaked in water, filtered, and then the dissolved organic carbon content is measured using an elemental analyzer.

[0100] High-performance liquid chromatography (HPLC): Used to analyze the composition and content of dissolved organic carbon.

[0101] Active organic carbon content

[0102] Definition: The fraction of organic carbon in soil that is easily decomposed and utilized by microorganisms, including particulate organic carbon and part of dissolved organic carbon.

[0103] Significance: Active organic carbon is an important indicator of soil biological activity, reflecting the biological availability of soil.

[0104] Measurement Method:

[0105] Chemical oxidation method: Oxidize active organic carbon with chemical reagents (such as potassium permanganate), and determine its content by titration.

[0106] Microbial respiration method: By measuring the respiration of soil microorganisms, indirectly reflecting the content of active organic carbon.

[0107] Carbon-nitrogen ratio

[0108] Definition: The ratio of total organic carbon content to total nitrogen content in soil.

[0109] Significance: The carbon-nitrogen ratio reflects the balance of carbon and nitrogen in soil, and has an important influence on the activity of soil microorganisms and the decomposition rate of organic matter. Generally speaking, the higher the carbon-nitrogen ratio, the slower the decomposition rate of organic matter.

[0110] Measurement Method:

[0111] Elemental analyzer method: Simultaneously measure the total organic carbon and total nitrogen content in soil, and calculate the carbon-nitrogen ratio.

[0112] Kjeldahl nitrogen determination method: Measure the total nitrogen content in soil, and calculate the carbon-nitrogen ratio in combination with the total organic carbon content.

[0113] Microbial biomass carbon content

[0114] Definition: Carbon content in microbial biomass in soil.

[0115] Significance: Microbial biomass carbon is an important indicator of soil biological activity, reflecting the total amount and activity of microorganisms in the soil.

[0116] Measurement method:

[0117] Chloroform fumigation method: Microorganisms in the soil are killed by chloroform fumigation, releasing microbial biomass carbon, and then its content is determined by chemical oxidation method.

[0118] Fluorescence method: The content of microbial biomass carbon is detected by fluorescence probe.

[0119] The above indicators have important significance in soil quality evaluation, which is specifically manifested in:

[0120] Total organic carbon content: reflects the fertility and total amount of organic matter in the soil.

[0121] Particulate organic carbon content: reflects the content of easily decomposable organic carbon in the soil, which is closely related to soil biological activity.

[0122] Mineral-bound organic carbon content: reflects the content of stable organic carbon in the soil, which plays an important role in the long-term stability of soil carbon pool.

[0123] Dissolved organic carbon content: reflects the content of the most biologically available organic carbon in the soil, which has an important impact on soil ecological function.

[0124] Active organic carbon content: reflects the content of organic carbon that is easily decomposed and utilized by microorganisms, which is an important indicator of soil biological activity.

[0125] Carbon-nitrogen ratio: reflects the balance of carbon and nitrogen in the soil, which has an important impact on soil microbial activity and organic matter decomposition rate.

[0126] Microbial biomass carbon content: directly reflects the total amount and activity of microorganisms in the soil, which is an important indicator of soil biological activity.

[0127] By measuring these indicators, the physical, chemical and biological properties of the soil can be comprehensively evaluated, providing scientific basis for the evaluation and management of soil quality.

[0128] Step 3: During the maturation period, the 15 N isotope in-situ tracing technology is used to measure 15 N-labeled micro-internal crop sample biomass, total nitrogen content and 15 N abundance, and the crop yield is calculated. The specific calculation process can be carried out according to the following steps:

[0129] 1) Sample collection

[0130] Crop sample collection:

[0131] At the maturity stage of the crop, plant samples, including aboveground stalks, grains, and underground roots, are collected from the marked microzones.

[0132] The samples are processed separately by part, such as stalks and grains.

[0133] After the samples are collected, the plant samples are killed at 105°C for 30 minutes and then dried at 75°C to a constant weight.

[0134] Soil sample collection:

[0135] Before the crop is sown and after it is harvested, soil samples of different layers (such as the 0-20 cm soil layer) are collected.

[0136] When the soil samples are collected, they are sampled with a soil drill and mixed before being sampled according to the one-fourth rule.

[0137] 2) Sample processing

[0138] Plant sample processing:

[0139] The dried plant samples are crushed into powder for subsequent determination.

[0140] The crushed samples are used to determine total nitrogen content and 15 N abundance.

[0141] Soil sample processing:

[0142] After the soil samples are air-dried, the total nitrogen content and 15 N abundance are determined.

[0143] 3) Determination method

[0144] Biomass determination:

[0145] The dried plant samples are weighed, and the dry matter weight is recorded.

[0146] Biomass includes aboveground biomass (stalks and grains) and underground biomass (roots).

[0147] Total nitrogen content determination:

[0148] The total nitrogen content of plant and soil samples is determined using the Kjeldahl method or an elemental analyzer.

[0149] Kjeldahl method: The nitrogen content is obtained by high-temperature digestion with concentrated sulfuric acid, distillation with sodium hydroxide, and titration with a standard hydrochloric acid titration solution.

[0150] 15N abundance determination:

[0151] The 15N abundance of the samples is determined using an elemental analysis-isotope mass spectrometer (EA-IRMS).

[0152] 15N abundance calculation formula:

[0153] 15N atom percentage (%) = 15N abundance of sample or 15N labeled fertilizer - 15N natural abundance

[0154] wherein the 15N natural abundance is about 0.3663%.

[0155] 4) Calculation method

[0156] Plant 15N accumulation amount:

[0157] 15N accumulation amount of a plant organ = total nitrogen content of the organ x 15N abundance of the organ x dry weight of the organ; N

[0158]

[0159] 15N utilization rate:

[0160] Plant 15N utilization rate = plant 15N accumulation amount / amount of 15N in input fertilizer x 100%;

[0161] Crop yield calculation:

[0162] According to the plant dry matter mass (biomass), the yield per unit area is calculated.

[0163] Through the above steps, the biomass, total nitrogen content and 15N abundance of the crop sample can be accurately determined, and the crop yield is calculated, so as to evaluate the influence of the straw mulching and deep loosening technology on crop growth and nitrogen utilization efficiency.

[0164] Step 4: Constructing a multi-objective optimization model.

[0165] The multi-objective optimization model maximizes soil quality and crop yield as the optimization target, meets soil physical indicators, available nutrients, soil carbon related indicators and deep loosening parameters as the constraint condition, and takes straw mulching parameters and deep loosening parameters as the optimization object;

[0166] Specifically, the maximization of soil quality is described by the minimum value of the Euclidean distance between the soil physical indicators, available nutrients and soil carbon related indicators and their respective optimal values, specifically:

[0167]

[0168] In the formula, maxSq represents the maximization of soil quality; Si u represents the u-th soil physical indicator value; Si u-best represents the optimal value of the u-th soil physical indicator; An v represents the v-th available nutrient content; An v-best represents the optimal value of the v-th available nutrient content; Ci w ​​Ci represents the value of the wth soil carbon related index; Ci w-best Ci represents the optimal value of the wth soil carbon related index.

[0169] The multi-objective optimization model above can be written as: F = a maxCy + b maxSq; where F is the optimization objective of the multi-objective optimization model; maxCy is the maximum crop yield; a and b are constant coefficients between 0 and 1, and a + b = 1; during the calculation, the setting can be made according to the calculation requirements.

[0170] The constraint conditions of the multi-objective optimization model meet the soil physical index, the available nutrient, the soil carbon related index and the deep loosening parameter, specifically:

[0171] The constraint condition of the soil physical index:

[0172] The soil bulk density is less than or equal to the upper limit of the soil bulk density;

[0173] The soil porosity is greater than or equal to the lower limit of the soil porosity;

[0174] The soil water content is greater than or equal to the lower limit of the soil water content;

[0175] The constraint condition of the available nutrient:

[0176] The ammonium nitrogen content is greater than or equal to the lower limit of the ammonium nitrogen content;

[0177] The nitrate nitrogen content is greater than or equal to the lower limit of the nitrate nitrogen content;

[0178] The available phosphorus content is greater than or equal to the lower limit of the available phosphorus content;

[0179] The available potassium content is greater than or equal to the lower limit of the available potassium content;

[0180] The constraint condition of the soil carbon related index includes:

[0181] The total organic carbon content is greater than or equal to the lower limit of the total organic carbon content

[0182] The particulate organic carbon content is greater than or equal to the lower limit of the particulate organic carbon content;

[0183] The mineral organic carbon content is greater than or equal to the lower limit of the mineral organic carbon content;

[0184] The dissolved organic carbon content is greater than or equal to the lower limit of the dissolved organic carbon content;

[0185] The active organic carbon content is greater than or equal to the lower limit of the active organic carbon content;

[0186] The microbial carbon content is greater than or equal to the lower limit of the microbial carbon content;

[0187] The carbon-nitrogen ratio is less than or equal to the upper limit of the appropriate ratio;

[0188] The constraint condition of the deep loosening parameter:

[0189] Minimum subsoiling depth ≤ subsoiling depth ≤ maximum subsoiling depth;

[0190] Minimum coverage amount ≤ coverage amount ≤ maximum coverage amount.

[0191] Step 5: According to the obtained experimental data, the optimal values of the straw coverage parameters and the subsoiling parameters under different coverage modes are obtained by using a multi-objective optimization model, and then the optimized tillage strategy of the soil structure of the dry-cultivated black land temperature advantage zone is formed.

[0192] The basic principles and main features of the present application and the advantages of the present application are shown and described above. Those skilled in the art should understand that the present application is not limited by the above examples, and the above examples and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing soil structure of straw mulching deep loosening in the temperature advantage area of dryland black soil, characterized in that, The method comprises the following steps: The straw mulching and returning experiment is designed by using random block design, taking conventional ridge as control, setting up non-cultivation straw mulching and full amount of straw mulching in the uniform ridge with ridge distance of 57 cm and wide-narrow row planting mode with row distance of 40-80 cm, and processing different mulching modes with different deep loosening parameters, and setting up λm×λm size in each treatment test area 15 N-marked micro area; Collect soil samples in the experimental area under different treatment methods before and at the mature stage of crop seeding, determine the soil samples including soil physical indicators, available nutrients and soil carbon related indicators, and at the mature stage, adopt 15 N isotope in-situ tracing technology to determine the 15 N labeled micro-internal crop sample biomass, total nitrogen content and 15 N abundance, and calculate the crop yield; constructing a multi-objective optimization model, wherein the multi-objective optimization model takes maximizing soil quality and crop yield as optimization objectives, takes the soil physical indicators, the available nutrients, the soil carbon-related indicators, and the deep ploughing parameters as constraint conditions, and takes the straw covering parameters and the deep ploughing parameters as optimization objects; according to the obtained experimental data, the multi-objective optimization model is used to obtain the optimal values of the straw covering parameters and the deep ploughing parameters under different covering modes, and then an optimized cultivation strategy of soil structure in the dry farming black land temperature advantage zone is formed.

2. The method according to claim 1, wherein the soil physical indicators include soil bulk density, soil porosity, and soil water content; the available nutrients include ammonium nitrogen, nitrate nitrogen, available phosphorus, and available potassium; the soil carbon-related indicators include total organic carbon content, particulate organic carbon content, mineral organic carbon content, dissolved organic carbon content, active organic carbon content, carbon-nitrogen ratio, and microbial biomass carbon content; the straw covering parameters include covering amount; and the deep ploughing parameters include deep ploughing depth and deep ploughing time.

3. The method according to claim 2, wherein the constraint conditions of the soil physical indicators include: the soil bulk density is less than or equal to the upper limit of the soil bulk density; the soil porosity is greater than or equal to the lower limit of the soil porosity; and the soil water content is greater than or equal to the lower limit of the soil water content.

4. The method according to claim 2, wherein the constraint conditions of the available nutrients include: the ammonium nitrogen content is greater than or equal to the lower limit of the ammonium nitrogen content; the nitrate nitrogen content is greater than or equal to the lower limit of the nitrate nitrogen content; the available phosphorus content is greater than or equal to the lower limit of the available phosphorus content; and the available potassium content is greater than or equal to the lower limit of the available potassium content.

5. The method according to claim 2, wherein the constraint conditions of the soil carbon-related indicators include: the total organic carbon content is greater than or equal to the lower limit of the total organic carbon content; the particulate organic carbon content is greater than or equal to the lower limit of the particulate organic carbon content; the mineral organic carbon content is greater than or equal to the lower limit of the mineral organic carbon content; the dissolved organic carbon content is greater than or equal to the lower limit of the dissolved organic carbon content; the active organic carbon content is greater than or equal to the lower limit of the active organic carbon content; the microbial biomass carbon content is greater than or equal to the lower limit of the microbial biomass carbon content; and the carbon-nitrogen ratio is less than or equal to the upper limit of the suitable ratio.

6. The method according to claim 2, wherein the constraint conditions of the deep ploughing parameters include: the minimum deep ploughing depth is less than or equal to the deep ploughing depth, and the deep ploughing depth is less than or equal to the maximum deep ploughing depth; and the minimum covering amount is less than or equal to the covering amount, and the covering amount is less than or equal to the maximum covering amount. The maximized soil quality is described by the minimum value of the Euclidean distance between the soil physical indicators, the available nutrients, and the soil carbon-related indicators and their respective optimal values, and is specifically: ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ 7. The dryland black soil temperature advantage zone straw mulching subsoiling soil structure optimization method according to claim 1, characterized in that, ​ where maxSq represents maximizing soil quality; Si u represents the u-th soil physical indicator value; Si u-best represents the optimal value of the u-th soil physical indicator; An v represents the v-th available nutrient content; An v-best represents the optimal value of the v-th available nutrient content; Ci w represents the w-th soil carbon-related indicator value; Ci w-best represents the optimal value of the w-th soil carbon-related indicator.

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