Organic fertilizer gradient instead of chemical fertilizer planting method and system in northeast brown soil region

Abstract

The application discloses a northeast brown soil area organic fertilizer gradient replacement chemical fertilizer planting method and system, relates to the organic planting technical field.The application comprises collecting plot basic information, establishing a fertilizer basic information dataset, a soil background condition dataset and a crop library dataset;evaluating chemical fertilizer application effect, determining a chemical fertilizer application optimal value;calculating organic fertilizer equivalent potential, and determining an organic fertilizer gradient replacement application amount.The application can relieve the acidification trend of brown soil, improve the soil fertility level, and reduce the chemical fertilizer application amount, can maintain stable crop yield and quality under test conditions, and is suitable for the standardized application of the northeast brown soil area planting and breeding circulation agriculture.

Description

Technical Field

[0001] This invention relates to the field of organic farming technology, specifically to a method and system for organic fertilizer gradient substitution of chemical fertilizer in the brown soil region of Northeast China. Background Technology

[0002] In the grain cultivation process of the brown soil region of Northeast China, farmers have long relied on excessive chemical fertilizer input in pursuit of high yields, leading to soil degradation problems such as increased soil acidification, reduced fertility, soil compaction, and nutrient imbalance. Simultaneously, the region has a large-scale livestock and poultry farming industry, producing a huge amount of livestock and poultry manure annually. However, the utilization rate of manure resources is insufficient, the methods of returning it to the field are extensive, and the fertilizer effect is unstable, easily causing non-point source pollution and resource waste. Reducing chemical fertilizer use, replacing it with organic fertilizer, and returning manure resources to the field are important technical paths to alleviate these problems. However, existing production models generally suffer from prominent problems such as reliance on farmers' experience for fertilization, low matching degree between crop types and fertilization methods, lack of scientific optimal value models for chemical fertilizer application, poor regional adaptability of organic fertilizer replacement ratios, and the absence of an integrated intelligent decision-making system for differentiated planting according to different plots.

[0003] Currently, technologies related to organic fertilizer substitution for chemical fertilizer mainly focus on application methods. For example, the technical solution in application number 2025107044988 focuses on selecting a suitable combination of solid and liquid organic fertilizers to improve the quality of tea leaves; application number 2024109601229 focuses on optimizing the application method and amount of commercial organic fertilizer to increase potato yield; application number 2022100477621 focuses on establishing a multi-objective optimization function to determine the ratio of organic fertilizer to chemical fertilizer; application number 2021105525701 provides different combination ratios of organic fertilizer and chemical fertilizer to explore suitable ratios that significantly improve the yield of red oranges; and application number 2018115680345 proposes a production technology method for replacing chemical fertilizer with organic fertilizer for greenhouse watermelons from three aspects: selection of organic fertilizer types, determination of substitution ratio, and matching of application technologies.

[0004] The aforementioned existing technologies have significant drawbacks: ① Most patents focus on optimizing the composition and application methods of fertilizers, but only at the level of fertilizer production and simple field application, without linking regional crop adaptation screening, soil background matching, and scientific calculation of the optimal fertilizer application rate; ② Most adopt a fixed ratio organic fertilizer substitution model and provide basic application steps, but lack standardized fertilizer and soil basic datasets, and there is no systematic quantitative fertilizer efficiency evaluation mechanism; ③ Some patents solve the organic fertilizer substitution ratio through function models, but do not take into account the background characteristics of acidification and low fertility of brown soil in Northeast China, and cannot specifically alleviate the actual production pain points such as regional soil degradation, excessive application of chemical fertilizers, inefficient use of organic fertilizers, and unstable crop yield and quality.

[0005] To address the shortcomings of existing technologies, this invention constructs a fertilizer basic information dataset and a soil baseline condition dataset, breaking away from the traditional experience-based fertilization model and achieving data-driven precision fertilization decisions. It establishes a dedicated crop database adapted to Northeast China's brown soil, enabling precise matching of crop types with soil conditions and fertilization patterns. It introduces an intelligent optimization model for optimal fertilizer values, quantitatively calculating the optimal application rates of nitrogen, phosphorus, and potassium fertilizers to avoid the risk of yield reduction caused by blindly reducing fertilizer use. Furthermore, it proposes a core evaluation index for the equivalent potential of organic fertilizer, distinguishing it from the extensive approach of simply replacing fertilizers with equal quality. This index incorporates fertilizer efficiency differences into quantitative considerations, serving as the core basis for determining the gradient replacement ratio of organic fertilizer, thus forming a complete, quantifiable, and dynamically adjustable green planting method and system. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for planting crops in the brown soil region of Northeast China that uses organic fertilizer to replace chemical fertilizer. This method can alleviate soil acidification, improve soil fertility, reduce the amount of chemical fertilizer used, and stabilize crop yield and quality under experimental conditions. It is suitable for large-scale, standardized, and green integrated farming in the brown soil region of Northeast China.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: On the one hand, a method for replacing chemical fertilizers with organic fertilizers in the brown soil region of Northeast China is provided, including the following steps: S1 collects basic information about the land parcels and establishes a dataset.

[0008] S2 evaluates the effect of fertilizer application and determines the optimal value of fertilizer application.

[0009] S3 calculates the equivalent potential of organic fertilizer and determines the gradient substitution rate of organic fertilizer.

[0010] In step S1, the basic information includes fertilizer basic information, soil background condition information, and crop basic information. The dataset includes a fertilizer basic information dataset, a soil background condition dataset, and a crop database dataset.

[0011] Preferably, the indicators in the fertilizer basic information dataset include: organic fertilizer type, organic fertilizer nutrient content, recommended field application rate of organic fertilizer, and suitable application time of organic fertilizer; nitrogen fertilizer type, nitrogen fertilizer N content, conventional nitrogen fertilizer application rate, and nitrogen fertilizer application time; phosphate fertilizer type, phosphate fertilizer P content, conventional phosphate fertilizer application rate, and phosphate fertilizer application time; potassium fertilizer type, potassium fertilizer K content, conventional potassium fertilizer application rate, and potassium fertilizer application time; compound fertilizer type, compound fertilizer nutrient content, conventional compound fertilizer application rate, and compound fertilizer application time.

[0012] Preferably, the indicators in the soil background data set include: geographical location, soil type, pH, EC, organic matter, available nitrogen, available phosphorus, available potassium, CEC, heavy metals, cropping system, and field management practices.

[0013] Preferably, the indicators in the crop database dataset include: crop type, historical sown area, and historical yield per unit area; the crop types include wheat, corn, sorghum, and millet. Among these, heavy metal indicators are used to verify the compliance of manure application; plots exceeding the standards are not included in the scope of manure application. Historical sown area is used for crop planting structure suitability analysis.

[0014] Step S2 includes the following steps: S21 determines the amount of fertilizer to be applied.

[0015] S22 promotes standardized crop cultivation.

[0016] S23 Establish a fertilizer application effect evaluation model.

[0017] S24 determines the optimal application rate of fertilizer.

[0018] In step S21, the application rates of four nitrogen fertilizers, four phosphorus fertilizers, and four potassium fertilizers are determined for the evaluation of fertilizer application effects in this plot. In the formula, n represents the number of years for the statistical data of historical fertilization data for this plot, i represents the type number of the corresponding single-element fertilizer, and j represents the type number of the compound fertilizer.

[0019] When compound fertilizer is not applied: ;

[0020] Wherein, GN represents the amount of nitrogen fertilizer applied in the evaluation of fertilizer application effectiveness in this plot; CDN in This refers to the standard application rate of type i nitrogen fertilizer for this plot in year n; CN in The N content of the i-th type of nitrogen fertilizer applied to this plot in year n; CDF jn This refers to the standard application rate of type j compound fertilizer for this plot in year n; CN jn CN0 represents the N content of compound fertilizer of type j applied in the nth year of this plot; CN0 represents the N content of nitrogen fertilizer applied in the evaluation of fertilizer application effect in this plot.

[0021] ;

[0022] Wherein, GP represents the amount of phosphate fertilizer applied in the evaluation of local fertilizer application effects; CDP in This refers to the standard application rate of type i phosphate fertilizer for this plot in year n; CP in The P content of the i-th type of phosphate fertilizer applied to this plot in year n; CDF jn The standard application rate of compound fertilizer of type j for this plot in year n; CP jn CP0 represents the P content of compound fertilizer of type j applied in the nth year of this plot; CP0 represents the P content of phosphate fertilizer applied in the evaluation of fertilizer application effect in this plot.

[0023] ;

[0024] Where GK represents the amount of potassium fertilizer applied in the evaluation of fertilizer application effect in this plot; CDK in The standard application rate of type i potassium fertilizer for this plot in year n; CK in The K content of the i-th type of potassium fertilizer applied to this plot in year n; CDF jn The standard application rate of compound fertilizer of type j for this plot in year n; CK jn CK0 represents the K content of compound fertilizer of type j applied in the nth year of this plot; CK0 represents the K content of potassium fertilizer applied in the evaluation of fertilizer application effect in this plot.

[0025] When applying compound fertilizer, first determine the amount of compound fertilizer to be applied for one nutrient element, and then deduct the amount of other nutrient elements in the compound fertilizer when calculating the amount of other fertilizers to be applied.

[0026] In step S22, fertilizer is applied according to the fertilizer application rate combination. Except for the fertilizer application rate, other aspects such as planting environment, planting density, crop type, fertilization time, irrigation, and pest and disease control are all carried out in accordance with the conventional field management measures for this plot.

[0027] [Table 1: Fertilizer Application Rate Combination Table for Local Fertilizer Application Effect Evaluation]

[0028] In step S23, measured data of application effect indicators corresponding to different fertilizer application combinations are obtained during the crop harvest period. Based on the principle of single nutrient effect fitting, fertilizer application effect evaluation models corresponding to nitrogen fertilizer, phosphorus fertilizer, and potassium fertilizer are established respectively.

[0029] Preferably, the application effect indicators include one or more of the following: crop yield, grain bulk density, grain starch content, soil available phosphorus content, soil available potassium content, soil available nitrogen content, soil pH, soil salinity, and soil cation exchange capacity.

[0030] The fertilizer application effect evaluation model includes a nitrogen fertilizer application effect evaluation model, a phosphate fertilizer application effect evaluation model, and a potash fertilizer application effect evaluation model. ;

[0031] Among them, FE ni A model for evaluating the effectiveness of nitrogen fertilizer application; a ni b ni c ni ε represents the coefficients of the univariate quadratic regression model for nitrogen fertilizer, fitted to the ni-th fertilizer application effect index; N represents the amount of nitrogen fertilizer applied in the local plot's fertilizer application effect evaluation; FE pi A model for evaluating the effectiveness of phosphate fertilizer application; a pi b pic pi FE represents the coefficients of the univariate quadratic regression model for phosphate fertilizer, fitted to the pi-th fertilizer application effect index; P represents the amount of phosphate fertilizer applied in the local plot's fertilizer application effect evaluation; ki A model for evaluating the effectiveness of potassium fertilizer application; a ki b ki c ki represents the coefficient of the univariate quadratic regression model for potassium fertilizer, fitted to the ki-th fertilizer application effect index; K represents the amount of potassium fertilizer applied in the evaluation of fertilizer application effect in this plot.

[0032] The model coefficients described are statistical parameters obtained through field gradient fertilization experiment data and least squares regression fitting. These are general parameters for modeling fertilization effects in this field and have no custom-defined special meanings. The specific fitting calculation method is as follows: for a single fertilizer nutrient, the fertilizer application rate is used as the independent variable, and the corresponding application effect index FE is... ni / FE pi / FE ki As the dependent variable, it is substituted into the corresponding quadratic model. Using the minimum sum of squared residuals as the optimal fitting criterion, the coefficients of the quadratic term (a) are obtained by solving multiple sets of gradient experimental sample data. ni / a pi / a ki ), coefficient of the first term (b) ni / b pi / b ki ) and constant term (c ni / c pi / c ki ).

[0033] This invention limits the data sources for fitting each nutrient model. The gradient nitrogen fertilizer application effect evaluation model uses only the experimental data of gradient groups 2, 3, 6, and 11 to fit and solve the corresponding coefficients; the gradient phosphate fertilizer application effect evaluation model uses only the experimental data of gradient groups 4, 5, 6, and 7 to fit and solve the corresponding coefficients; and the gradient potassium fertilizer application effect evaluation model uses only the experimental data of gradient groups 6, 8, 9, and 10 to fit and solve the corresponding coefficients.

[0034] In step S24, the target values ​​of the local fertilizer application effect indicators are selected and substituted into the fertilizer application effect evaluation model to calculate the optimal application rates of nitrogen, phosphorus, and potassium fertilizers. During the solution process, the lower limit values ​​of the application effect indicators are substituted into the corresponding nutrient effect equations to obtain the application rate range that satisfies the target effect. When multiple evaluation indicators exist, the intersection of the application rate ranges corresponding to each indicator is taken as the optimal application rate range; if there is no intersection, the crop yield indicator is used as the priority for determination.

[0035] The optimal values ​​for fertilizer application include the optimal application rates for nitrogen, phosphorus, and potassium fertilizers.

[0036] The target value of the application effect index is a range value. The present invention provides recommended values ​​for the application effect index in Table 2, which can be used directly or selected arbitrarily from it.

[0037] Recommended values ​​for application efficacy indicators (Table 2)

[0038] Step S3 includes the following steps: S31 calculates the equivalent potential of organic fertilizer.

[0039] S32 determines the application rate of organic fertilizer gradient substitution and the application rate of chemical fertilizer.

[0040] S33 promotes green planting by gradually replacing chemical fertilizers with organic fertilizers.

[0041] In step S31, the equivalent potential of organic fertilizer refers to the ratio of the effective nutrient content that can be released per unit mass of organic fertilizer to the effective nutrient content per unit mass of corresponding chemical fertilizer over a one-year period.

[0042] ;

[0043] Among them, P N The potential for nitrogen nutrient absorption in organic fertilizers; IN represents the inorganic nitrogen content in organic fertilizers; ON represents the organic nitrogen content in organic fertilizers; MR represents the nitrogen content in organic fertilizers. N The annual mineralization rate of organic nitrogen in organic fertilizer; P P The potential for phosphorus nutrient effects in organic fertilizers; IP represents the inorganic phosphorus content in organic fertilizers; OP represents the organic phosphorus content in organic fertilizers; MR represents the phosphorus nutrient content in organic fertilizers. P The annual mineralization rate of organic phosphorus in organic fertilizer; P K The potential for potassium nutrient effects in organic fertilizers; IK represents the inorganic potassium content in organic fertilizers; OK represents the organic potassium content in organic fertilizers; MR represents the potassium content in organic fertilizers. K The annual mineralization rate of organic potassium in organic fertilizer; the annual mineralization rate of organic nitrogen MR N MR of annual organic phosphorus mineralization P Organic potassium annual mineralization rate MR K Field cultivation experiments have determined that the recommended values ​​for decomposed commercial organic fertilizer in the brown soil region of Northeast China are 25%~35%, 15%~25%, and 20%~30%, respectively.

[0044] In step S32 ;

[0045] Where f is the gradient substitution rate of organic fertilizer; r is the proportion of organic fertilizer replacing chemical fertilizer, with a recommended range of 10% to 30%; N r The amount of nitrogen fertilizer applied in the gradient replacement of chemical fertilizers with organic fertilizers; P rThe amount of phosphate fertilizer applied in the gradient replacement of chemical fertilizers with organic fertilizers; K r The amount of potassium fertilizer applied in the gradient replacement of chemical fertilizers with organic fertilizers; N op The optimal application rate of nitrogen fertilizer; P op The optimal application rate of phosphate fertilizer; K op This is the optimal application rate for potassium fertilizer.

[0046] In step S33, fertilization is carried out according to the organic fertilizer gradient substitution rate and the chemical fertilizer application rate. Except for the amount of fertilizer, other planting environment, planting density, crop type, fertilization time, irrigation, and pest and disease control are all carried out in accordance with the conventional field management measures for this plot.

[0047] On the other hand, an organic fertilizer gradient substitution planting system for chemical fertilizers is also provided for the Northeast brown soil region. This system uses the aforementioned organic fertilizer gradient substitution green planting method suitable for the Northeast brown soil region to calculate the application rate of organic fertilizer gradient substitution and the amount of chemical fertilizer applied in the organic fertilizer gradient substitution. The system includes: The basic information acquisition module for land plots is used for data acquisition, structured storage, and optimized storage of basic fertilizer information, soil baseline information, and basic crop information for land plots. The optimal fertilizer application rate calculation module is used for data storage and retrieval, and for calculating the optimal application rates of nitrogen, phosphorus, and potassium fertilizers. The organic fertilizer gradient substitution calculation module is used for data storage and retrieval, and for calculating the equivalent potential of organic fertilizer, the gradient substitution application rate of organic fertilizer, and the amount of chemical fertilizer applied in the gradient substitution of organic fertilizer. The output of the basic information acquisition module is connected to the input of the optimal application rate calculation module for chemical fertilizer and the organic fertilizer gradient substitution calculation module, respectively; the output of the optimal application rate calculation module for chemical fertilizer is connected to the input of the organic fertilizer gradient substitution calculation module, realizing the step-by-step retrieval and calculation of data.

[0048] The land parcel basic information acquisition module includes: fertilizer basic information submodule, soil background condition information submodule, and crop basic information submodule.

[0049] The fertilizer basic information submodule includes: organic fertilizer type, organic fertilizer nutrient content, recommended field application rate of organic fertilizer, and suitable fertilization time of organic fertilizer; nitrogen fertilizer type, nitrogen fertilizer N content, conventional nitrogen fertilizer application rate, and nitrogen fertilizer application time; phosphate fertilizer type, phosphate fertilizer P content, conventional phosphate fertilizer application rate, and phosphate fertilizer application time; potassium fertilizer type, potassium fertilizer K content, conventional potassium fertilizer application rate, and potassium fertilizer application time; and compound fertilizer type, compound fertilizer nutrient content, conventional compound fertilizer application rate, and compound fertilizer application time. The soil baseline information submodule includes: geographical location, soil type, pH, EC, organic matter, available nitrogen, available phosphorus, available potassium, CEC, heavy metals, cropping system, and field management measures. The basic crop information submodule includes: crop type, sown area over the years, and yield per unit area over the years; crop types include wheat, corn, sorghum, and millet.

[0050] The optimal fertilizer application rate calculation module includes: a fertilizer application rate calculation submodule, a fertilizer application effect evaluation model fitting submodule, and an optimal fertilizer application rate calculation submodule.

[0051] The fertilizer application rate calculation submodule retrieves data from the plot basic information acquisition module to calculate the application rates of nitrogen, phosphorus, and potassium fertilizers for standardized crop planting when evaluating the fertilizer application effect of the local plot.

[0052] The fertilizer application effect evaluation model fitting submodule stores and calls the fertilizer application effect index data of local crop harvest period, uses regression analysis method, with the application effect index as the dependent variable and the single nutrient application amount as the independent variable to fit a univariate quadratic parabola equation, obtains the fitting parameters and stores them.

[0053] The optimal fertilizer application rate calculation submodule stores recommended values ​​for application effect indicators, retrieves fitting parameters, fills in the target range values ​​for local fertilizer application effect indicators, and calculates the optimal application rates for nitrogen, phosphorus, and potassium fertilizers.

[0054] The organic fertilizer gradient substitution calculation module includes: a sub-module for calculating the potential effect of organic fertilizer as a nutrient, a sub-module for calculating the application amount of organic fertilizer gradient substitution, and a sub-module for calculating the application amount of chemical fertilizer in organic fertilizer gradient substitution of chemical fertilizer.

[0055] Compared with the prior art, the present invention has the following beneficial effects: First, this invention collects basic information about land plots and constructs three standardized databases: a fertilizer basic information dataset, a soil baseline condition dataset, and a crop database dataset. This changes the extensive mode of blindly applying fertilizer based solely on farmers' experience in traditional agricultural production, and enables the digital and standardized management of soil, fertilizer, and crop information. It provides reliable underlying data support for subsequent precision fertilization, crop matching, and substitution ratio determination, and adapts to the differentiated and zoned planting decision-making needs of plots in the Northeast brown soil region.

[0056] Secondly, this invention selects key indicators from multiple dimensions, such as crop yield, grain bulk density, grain starch content, available phosphorus, available potassium, available nitrogen, soil pH, soil salinity, and cation exchange capacity, to comprehensively evaluate the effect of fertilizer application and solve for the optimal values ​​of nitrogen, phosphorus, and potassium fertilizer application. This overcomes the shortcomings of existing technologies, such as arbitrary fertilizer application, lack of basis for reduction, easy reduction of yield due to blind application, and soil degradation caused by excessive application. It achieves precise reduction of fertilizer application while ensuring stable crop yield, which helps to alleviate farmland degradation problems such as brown soil acidification, compaction, and nutrient imbalance.

[0057] Third, this invention proposes an organic fertilizer equivalent potential index, which uses an annual cycle as the evaluation scale to quantify the degree of nutrient release impact of a unit mass of organic fertilizer compared to chemical fertilizer. This differs from the traditional crude approach of simply replacing fertilizers by mass and ignoring differences in fertilizer efficiency. Instead, it uses the organic fertilizer equivalent potential as the core quantitative basis for determining the application amount of organic fertilizer gradient replacement, making the replacement scheme more scientific and the fertilizer efficiency matching more precise, effectively improving the resource utilization efficiency of organic fertilizer and livestock and poultry manure.

[0058] Fourth, this invention establishes an integrated technical logic of dataset, crop adaptation, fertilizer optimization, and organic fertilizer gradient substitution. It can flexibly and dynamically adjust and update the application amount and substitution ratio of chemical fertilizer and organic fertilizer according to actual planting goals, soil background conditions, and crop type requirements. It is suitable for Northeast brown soil plots with different acidification levels and fertility levels, and the method has regional adaptability and potential for promotion and application.

[0059] Fifth, this invention takes into account multiple benefits such as soil improvement, fertilizer reduction, stable crop yield and quality improvement, and manure resource utilization. It can effectively improve soil organic matter, nutrient availability and fertilizer retention capacity, continuously repair the problems of brown soil acidification and soil infertility, stabilize crop yield, improve grain bulk density and starch and other quality indicators, and efficiently dispose of regional livestock and poultry manure, reducing the risk of agricultural non-point source pollution, which meets the needs of high-quality development of green planting and breeding circular agriculture in the Northeast brown soil region. Attached Figure Description

[0060] Figure 1 This is a flowchart of the green planting method of organic fertilizer gradient substitution for chemical fertilizer applicable to the brown soil region of Northeast China, according to the present invention.

[0061] Figure 2 This is a module of the organic fertilizer gradient replacement chemical fertilizer green planting system applicable to the brown soil region of Northeast China.

[0062] Figure 3 This is a flowchart of the calculation of the application amount of organic fertilizer and chemical fertilizer in the organic fertilizer gradient substitution of chemical fertilizer according to the present invention.

[0063] Figure 4 This is a fitting diagram of the nitrogen fertilizer application effect evaluation model of the present invention; Figure 5 This is a fitting diagram of the phosphate fertilizer application effect evaluation model of the present invention; Figure 6 This is a fitting diagram of the potassium fertilizer application effect evaluation model of the present invention. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to figures and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0065] Example: This example provides a method for planting in the Northeast brown soil region using organic fertilizer in a gradient substitution of chemical fertilizer, including the following steps: S1 collects basic information about the land parcels and establishes a dataset.

[0066] S2 evaluates the effect of fertilizer application and determines the optimal value of fertilizer application.

[0067] S3 calculates the equivalent potential of organic fertilizer and determines the gradient substitution rate of organic fertilizer.

[0068] In step S1, the experimental area selected in this embodiment is a city in Liaoning Province. The historical fertilization data for the number of years n=2 was statistically analyzed, and the dataset was established as follows: [Fertilizer Basic Information Dataset (Table 3)]

[0069] [Soil background data set (Table 4)]

[0070]

Crop Database Dataset (Table 5)

[0071] Step S2 includes the following steps: S21 determines the amount of fertilizer to be applied.

[0072] S22 promotes standardized crop cultivation.

[0073] S23 Establish a fertilizer application effect evaluation model.

[0074] S24 determines the optimal application rate of fertilizer.

[0075] In step S21, the application rates of four nitrogen fertilizers, four phosphorus fertilizers, and four potassium fertilizers for the local fertilizer application effect evaluation are determined respectively. In this embodiment, the fertilizers applied include urea, potassium chloride, and diammonium phosphate, where diammonium phosphate is a compound fertilizer. Therefore, the application rate of the compound fertilizer is first determined for the phosphorus content, and then the application rates of the other fertilizers are calculated. ;

[0076] ; ; In step S22, fertilization is carried out according to the fertilizer application rate combination. Except for the fertilizer application rate, other aspects such as planting environment, planting density, crop type, fertilization time, irrigation, and pest and disease control are all carried out in accordance with the conventional field management measures for this plot. According to Table 5, the crop planted in the example is corn.

[0077] [Fertilizer Application Rate Combinations in the Evaluation of Fertilizer Application Effects in This Plot (Table 6)]

[0078] In step S23, the application effect indicators of different fertilizer application combinations are measured during the crop harvest period, and a fertilizer application effect evaluation model is established. Crop yield is selected as the application effect indicator, and the crop yield of each fertilizer combination is measured.

[0079] Establish evaluation models for nitrogen fertilizer application effects, phosphate fertilizer application effects, and potash fertilizer application effects: Crop yield = -0.0943N 2 +9.286N +405.07 Crop yield = -0.2138P 2 +10.658P +471.28 Crop yield = -0.5831K 2 +16.105K +483.51 In step S24, the target value of the local fertilizer application effect index is selected and input into the fertilizer application effect evaluation model to calculate the optimal application rates of nitrogen, phosphorus, and potassium fertilizers. In this example, the target value of the fertilizer application effect index is: crop yield ≥ 440 kg / mu.

[0080] Substituting the target lower limit of 440 kg / mu into the above quadratic equation, the application range that meets the yield requirements is obtained. The optimal application rates of nitrogen, phosphorus and potassium fertilizers are [3.92, 94.56], [0, 52.63], [0, 30.10] (unit: kg / mu).

[0081] Step S3 includes the following steps: S31 calculates the equivalent potential of organic fertilizer.

[0082] S32 determines the application rate of organic fertilizer gradient substitution and the application rate of chemical fertilizer.

[0083] S33 promotes green planting by gradually replacing chemical fertilizers with organic fertilizers.

[0084] In step S31, the equivalent potential of organic fertilizer is calculated. This embodiment uses well-rotted commercial organic fertilizer, combined with the results of field incubation experiments in Northeast brown soil, taking an annual mineralization rate of 30% for organic nitrogen, 20% for organic phosphorus, and 25% for organic potassium. ;

[0085] Preferably, in step S32, the ratio of organic fertilizer to chemical fertilizer is 15% and 30%.

[0086] When the ratio of organic fertilizer to chemical fertilizer is 15%, ;

[0087] When the ratio of organic fertilizer to chemical fertilizer is 30%, ;

[0088] Preferably, in step S33, fertilization is carried out according to the organic fertilizer gradient substitution application rate and the chemical fertilizer application rate. Except for the amount of fertilizer, other planting environment, planting density, crop type, fertilization time, irrigation, pest and disease control, etc. are all carried out in accordance with the conventional field management measures of the plot.

[0089] [Graded application rates of organic fertilizer and chemical fertilizer (Table 7)]

[0090] [Fertilizer efficiency indicators were measured for each group after harvest (Table 8)]

[0091]

[0092] Compared with the control group, the two gradient groups in this embodiment significantly improved crop yield and grain bulk density, and improved soil pH and available nutrient content under the experimental conditions.

Claims

1. A method for planting in the brown soil region of Northeast China that uses organic fertilizer in a gradient substitution of chemical fertilizer, characterized in that... Includes the following steps: S1 collects basic information about the land plots and establishes a dataset; the basic information includes basic fertilizer information, soil baseline information, and crop basic information; the dataset includes a fertilizer basic information dataset, a soil baseline information dataset, and a crop database dataset; S2 evaluates the effect of fertilizer application and determines the optimal value of fertilizer application; the indicators of fertilizer application effect are one or more of the following: crop yield, grain bulk density, grain starch content, soil available phosphorus content, soil available potassium content, soil available nitrogen content, soil pH, soil salinity, soil cation exchange capacity, etc. S3 calculates the equivalent potential of organic fertilizer and determines the gradient substitution application rate of organic fertilizer; the equivalent potential of organic fertilizer refers to the ratio of the effective nutrients that can be released by a unit mass of organic fertilizer to the effective nutrients of a unit mass of corresponding chemical fertilizer over a one-year period.

2. The method according to claim 1, characterized in that, The indicators in the fertilizer basic information dataset mentioned in step S1 include: organic fertilizer type, organic fertilizer nutrient content, recommended field application rate of organic fertilizer, and suitable application time of organic fertilizer; nitrogen fertilizer type, nitrogen fertilizer N content, conventional nitrogen fertilizer application rate, and nitrogen fertilizer application time; phosphate fertilizer type, phosphate fertilizer P content, conventional phosphate fertilizer application rate, and phosphate fertilizer application time; potassium fertilizer type, potassium fertilizer K content, conventional potassium fertilizer application rate, and potassium fertilizer application time; compound fertilizer type, compound fertilizer nutrient content, conventional compound fertilizer application rate, and compound fertilizer application time. The indicators in the soil background data set include: geographical location, soil type, pH, EC, organic matter, available nitrogen, available phosphorus, available potassium, CEC, heavy metals, cropping system, and field management practices. The indicators in the crop database dataset include: crop type, historical sown area, and historical yield per unit area; crop types include wheat, corn, sorghum, and millet; among them, heavy metal indicators are used for compliance verification of manure return to the field, and historical sown area is used for crop planting structure adaptability analysis.

3. The method according to claim 1, characterized in that, Step S2 includes the following steps: S21 Determine the amount of fertilizer applied; determine the application amounts of 4 nitrogen fertilizers, 4 phosphorus fertilizers, and 4 potassium fertilizers in the evaluation of fertilizer application effects in this plot respectively; When compound fertilizer is not applied: ； Wherein, GN represents the amount of nitrogen fertilizer applied in the evaluation of fertilizer application effectiveness in this plot; CDN in This refers to the standard application rate of type i nitrogen fertilizer for this plot in year n; CN in The N content of the i-th type of nitrogen fertilizer applied to this plot in year n; CDF jn This refers to the standard application rate of type j compound fertilizer for this plot in year n; CN jn CN0 represents the N content of the type j compound fertilizer applied in the nth year of this plot; CN0 represents the N content of the nitrogen fertilizer applied in the evaluation of fertilizer application effect in this plot; where n is the number of years of statistical data on the fertilization history of this plot, i is the type number of single nitrogen fertilizer, and j is the type number of compound fertilizer. ； Wherein, GP represents the amount of phosphate fertilizer applied in the evaluation of local fertilizer application effects; CDP in This refers to the standard application rate of type i phosphate fertilizer for this plot in year n; CP in The P content of the i-th type of phosphate fertilizer applied to this plot in year n; CDF jn The standard application rate of compound fertilizer of type j for this plot in year n; CP jn CP0 represents the P content of compound fertilizer of type j applied in the nth year of this plot; CP0 represents the P content of phosphate fertilizer applied in the evaluation of fertilizer application effect in this plot. ； Where GK represents the amount of potassium fertilizer applied in the evaluation of fertilizer application effect in this plot; CDK in The standard application rate of type i potassium fertilizer for this plot in year n; CK in The K content of the i-th type of potassium fertilizer applied to this plot in year n; CDF jn The standard application rate of compound fertilizer of type j for this plot in year n; CK jn CK0 represents the K content of compound fertilizer of type j applied in the nth year of this plot; CK0 represents the K content of potassium fertilizer applied in the evaluation of fertilizer application effect in this plot. When applying compound fertilizer, first determine the amount of compound fertilizer to be applied for one nutrient element, and then deduct the amount of other nutrient elements in the compound fertilizer when calculating the amount of other fertilizers to be applied. S22 implements standardized crop planting; fertilizers are applied according to the combination of fertilizer application rates. Except for the amount of fertilizer, other aspects such as planting environment, planting density, crop type, fertilization time, irrigation, and pest and disease control are all carried out in accordance with the conventional field management measures for this plot. The fertilizer application rate combinations are set into 11 groups, with the standard combinations of nitrogen fertilizer GN3, phosphorus fertilizer GP3, and potassium fertilizer GK3 at conventional application rates. The remaining combinations only adjust the application rate gradient of a single nutrient, as follows: Combination 1: Nitrogen fertilizer application rate GN1, Phosphorus fertilizer application rate GP1, Potassium fertilizer application rate GK1; Combination 2: Nitrogen fertilizer application rate GN1, Phosphorus fertilizer application rate GP3, Potassium fertilizer application rate GK3; Combination 3: Nitrogen fertilizer application rate GN2, Phosphorus fertilizer application rate GP3, Potassium fertilizer application rate GK3; Combination 4: Nitrogen fertilizer application rate GN3, Phosphorus fertilizer application rate GP1, Potassium fertilizer application rate GK3; Combination 5: Nitrogen fertilizer application rate GN3, Phosphorus fertilizer application rate GP2, Potassium fertilizer application rate GK3; Combination 6: Nitrogen fertilizer application rate GN3, Phosphorus fertilizer application rate GP3, Potassium fertilizer application rate GK3; Combination 7: Nitrogen fertilizer application rate GN3, Phosphorus fertilizer application rate GP4, Potassium fertilizer application rate GK3; Combination 8: Nitrogen fertilizer application rate GN3, Phosphorus fertilizer application rate GP3, Potassium fertilizer application rate GK1; Combination 9: Nitrogen fertilizer application rate GN3, Phosphorus fertilizer application rate GP3, Potassium fertilizer application rate GK2; Combination 10: Nitrogen fertilizer application rate GN3, Phosphorus fertilizer application rate GP3, Potassium fertilizer application rate GK4; Combination 11: Nitrogen fertilizer application rate GN4, Phosphorus fertilizer application rate GP3, Potassium fertilizer application rate GK3; S23 Establish a fertilizer application effect evaluation model; measure the application effect indicators of different fertilizer application combinations during crop harvest period, and establish a fertilizer application effect evaluation model; the fertilizer application effect evaluation model includes a nitrogen fertilizer application effect evaluation model, a phosphate fertilizer application effect evaluation model, and a potash fertilizer application effect evaluation model: ; Among them, FE ni A model for evaluating the effectiveness of nitrogen fertilizer application; a ni b ni c ni ε represents the coefficients of the univariate quadratic regression model for nitrogen fertilizer, fitted to the ni-th fertilizer application effect index; N represents the amount of nitrogen fertilizer applied in the local plot's fertilizer application effect evaluation; FE pi A model for evaluating the effectiveness of phosphate fertilizer application; a pi b pi c pi FE represents the coefficients of the univariate quadratic regression model for phosphate fertilizer, fitted to the pi-th fertilizer application effect index; P represents the amount of phosphate fertilizer applied in the local plot's fertilizer application effect evaluation; ki A model for evaluating the effectiveness of potassium fertilizer application; a ki b ki c ki , where represents the coefficient of the univariate quadratic regression model for potassium fertilizer, fitted to the ki-th fertilizer application effect index; K represents the amount of potassium fertilizer applied in the evaluation of fertilizer application effect in this plot. S24 determines the optimal fertilizer application rate; selects the target value of the local plot's fertilizer application effect index, substitutes it into the fertilizer application effect evaluation model, and calculates the optimal application rates of nitrogen, phosphorus, and potassium fertilizers; the target value of the application effect index is a range value; when solving, substitutes the target lower limit value of the application effect index into the effect equation of the corresponding nutrient to obtain the application rate range that satisfies the target effect; when there are multiple evaluation indicators, the intersection of the application rate ranges corresponding to each indicator is taken as the optimal application rate range, and when there is no intersection, the crop yield index is given priority in the determination.

4. The method according to claim 3, characterized in that, The nitrogen fertilizer application effect evaluation model in step S23 is fitted with the data from combinations 2, 3, 6, and 11 in step S22; the phosphate fertilizer application effect evaluation model is fitted with the data from combinations 4, 5, 6, and 7 in step S22; and the potassium fertilizer application effect evaluation model is fitted with the data from combinations 6, 8, 9, and 10 in step S22.

5. The method according to claim 1, characterized in that, Step S3 includes the following steps: S31 calculates the equivalent potential of organic fertilizer; ； Among them, P N The potential for nitrogen nutrient absorption in organic fertilizers; IN represents the inorganic nitrogen content in organic fertilizers; ON represents the organic nitrogen content in organic fertilizers; MR represents the nitrogen content in organic fertilizers. N The annual mineralization rate of organic nitrogen in organic fertilizer; P P The potential for phosphorus nutrient effects in organic fertilizers; IP represents the inorganic phosphorus content in organic fertilizers; OP represents the organic phosphorus content in organic fertilizers; MR represents the phosphorus nutrient content in organic fertilizers. P The annual mineralization rate of organic phosphorus in organic fertilizer; P K The potential for potassium nutrient effects in organic fertilizers; IK represents the inorganic potassium content in organic fertilizers; OK represents the organic potassium content in organic fertilizers; MR represents the potassium content in organic fertilizers. K The annual mineralization rate of organic potassium in organic fertilizer; the annual mineralization rate of organic nitrogen MR N MR of annual organic phosphorus mineralization P Organic potassium annual mineralization rate MR K Field cultivation experiments determined that the recommended values ​​for well-rotted commercial organic fertilizer in the Northeast brown soil region are 25%~35%, 15%~25%, and 20%~30%, respectively. S32 determines the gradient substitution rate of organic fertilizer and the application rate of chemical fertilizer; ； Where f represents the gradient substitution rate of organic fertilizer; r represents the proportion of organic fertilizer replacing chemical fertilizer, with a recommended value of 10%–30%; N r The amount of nitrogen fertilizer applied in the gradient replacement of chemical fertilizers with organic fertilizers; P r The amount of phosphate fertilizer applied in the gradient replacement of chemical fertilizers with organic fertilizers; K r The amount of potassium fertilizer applied in the gradient replacement of chemical fertilizers with organic fertilizers; N op The optimal application rate of nitrogen fertilizer; P op The optimal application rate of phosphate fertilizer; K op This represents the optimal application rate of potassium fertilizer. S33 promotes green planting by replacing chemical fertilizers with organic fertilizers in a gradient manner; fertilization is carried out according to the application rates of organic fertilizers and chemical fertilizers. Except for the amount of fertilizer, other aspects such as planting environment, planting density, crop type, fertilization time, irrigation, and pest and disease control are carried out in accordance with the conventional field management measures for this plot.

6. An organic fertilizer gradient substitution system for chemical fertilizer planting in the brown soil region of Northeast China, characterized in that, The organic fertilizer gradient substitution method for chemical fertilizer in the Northeast brown soil region, as described in any one of claims 1-5, is used to calculate the application amount of organic fertilizer gradient substitution and the amount of chemical fertilizer applied in organic fertilizer gradient substitution.

7. The system according to claim 6, characterized in that, include: The basic information acquisition module for land plots is used for data acquisition, structured storage, and optimized storage of basic fertilizer information, soil baseline information, and basic crop information for land plots. The optimal fertilizer application rate calculation module is used for data storage and retrieval, and for calculating the optimal application rates of nitrogen, phosphorus, and potassium fertilizers. The organic fertilizer gradient substitution calculation module is used for data storage and retrieval, and for calculating the equivalent potential of organic fertilizer, the application amount of organic fertilizer gradient substitution, and the amount of chemical fertilizer applied in organic fertilizer gradient substitution. The output of the land parcel basic information acquisition module is connected to the input of the optimal fertilizer application rate calculation module and the organic fertilizer gradient substitution rate calculation module, respectively. The output of the optimal fertilizer application rate calculation module is connected to the input of the organic fertilizer gradient substitution rate calculation module to realize the step-by-step data retrieval and calculation.

8. The system according to claim 6, characterized in that, The basic information acquisition module for land parcels includes: a fertilizer basic information submodule, a soil baseline information submodule, and a crop basic information submodule; The fertilizer basic information submodule includes: organic fertilizer type, organic fertilizer nutrient content, recommended field application rate of organic fertilizer, and suitable fertilization time of organic fertilizer; nitrogen fertilizer type, nitrogen fertilizer N content, conventional nitrogen fertilizer application rate, and nitrogen fertilizer application time; phosphate fertilizer type, phosphate fertilizer P content, conventional phosphate fertilizer application rate, and phosphate fertilizer application time; potassium fertilizer type, potassium fertilizer K content, conventional potassium fertilizer application rate, and potassium fertilizer application time; and compound fertilizer type, compound fertilizer nutrient content, conventional compound fertilizer application rate, and compound fertilizer application time. The soil baseline information submodule includes: geographical location, soil type, pH, EC, organic matter, available nitrogen, available phosphorus, available potassium, CEC, heavy metals, cropping system, and field management measures. The basic crop information submodule includes: crop type, sown area over the years, and yield per unit area over the years; crop types include wheat, corn, sorghum, and millet.

9. The system according to claim 6, characterized in that, The optimal fertilizer application rate calculation module includes: a fertilizer application rate calculation submodule, a fertilizer application effect evaluation model fitting submodule, and an optimal fertilizer application rate calculation submodule. The fertilizer application rate calculation submodule retrieves data from the plot basic information acquisition module to calculate the application rates of nitrogen, phosphorus, and potassium fertilizers for standardized crop planting when evaluating the fertilizer application effect of the local plot. The fertilizer application effect evaluation model fitting submodule stores and calls the fertilizer application effect index data of the local plot crop harvest period, uses regression analysis method, takes the application effect index as the dependent variable and the single nutrient application amount as the independent variable to fit a univariate quadratic parabola equation, obtains the fitting parameters and stores them. The optimal fertilizer application rate calculation submodule stores recommended values ​​for application effect indicators, retrieves fitting parameters, fills in the target range values ​​for local fertilizer application effect indicators, and calculates the optimal application rates for nitrogen, phosphorus, and potassium fertilizers.

10. The system according to claim 6, characterized in that, The organic fertilizer gradient substitution calculation module includes: a sub-module for calculating the potential effect of organic fertilizer on other nutrients, a sub-module for calculating the application amount of organic fertilizer gradient substitution, and a sub-module for calculating the application amount of chemical fertilizer in organic fertilizer gradient substitution of chemical fertilizer.

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