Cultivation-fertilization combined treatment method and system based on cultivated land quality degradation analysis

Abstract

The invention provides a cultivation-fertilization combined treatment method and system based on cultivated land quality degradation analysis, relates to the technical field of planning management, and realizes quantitative management of soil quality through evaluation coefficients. Secondly, scientifically determining three types of plants suitable for crop rotation according to the soil fertility level, and generating an adaptability optimization coefficient of each type of plants through comprehensive analysis of nutrient absorption demand factors and soil fertility influence factors; the adaptability optimization coefficient is used for screening out two types of plants suitable for crop rotation from the three types of plants, and dynamic monitoring and continuous improvement of the soil quality are achieved; finally, targeted soil fertilization and crop rotation plant adjustment suggestions are provided for each sub-region through comparative analysis and adjustment strategies, so that long-term improvement of the soil fertility level and sustainable development of agricultural production are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of planning and management, and in particular to a farming-fertilization combined management method and system based on farmland quality degradation analysis. Background Art

[0002] Cultivated land degradation includes the decline of soil fertility, soil erosion, reduction of organic matter content and deterioration of soil structure. In order to solve this problem, a variety of technical means and management methods have been proposed, including soil improvement, crop rotation, and rational application of chemical fertilizers and organic fertilizers. These methods have alleviated the problem of soil degradation to a certain extent, but due to the lack of systematic analysis and comprehensive management methods, the effects of traditional methods are often difficult to sustain and have poor regional adaptability.

[0003] In the prior art, the announcement number is CN115953064B, and the name is a method for comprehensive management and optimal regulation of cultivated land quality. The steps of the method include: comprehensively evaluating the cultivated land in multiple dimensions, summarizing and weighting to form the management capacity of the cultivated land; quantitatively measuring the management capacity of the cultivated land to obtain the blocking level of the cultivated land, and regionally differentiating the cultivated land according to the subordinate relationship of the blocking level, and demarcating it into multiple blocking areas; simulating the management of the blocking areas respectively through the proposed multiple optimization elements to obtain the optimization coefficients of the blocking areas, arranging them in a set order in combination with the blocking level of the cultivated land and the optimization coefficients of the blocking areas, and selecting the maximum value of the comprehensive sequence as the optimal optimization strategy for each blocking area, distributing and regulating each blocking area, and determining the benchmark deviation of each blocking area, and performing benchmark maintenance on each blocking area based on the determination result until the optimal management of each blocking area is completed.

[0004] There are also several deficiencies in the existing technology, which restrict the overall improvement of soil quality. First, traditional soil quality assessment methods mostly rely on single parameters or limited indicators, which cannot fully reflect the actual fertility level of the soil and its changes. Second, existing agronomic measures such as crop rotation and fertilization strategies are mostly based on empirical methods, lacking scientific quantitative analysis, and it is difficult to accurately meet the soil improvement needs of different regions. Third, although crop rotation is widely used as an effective farming method, the lack of scientific evaluation of different crop rotation combinations leads to unsatisfactory crop rotation effects.

[0005] The above information disclosed in the above Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The object of the present invention is to provide a combined tillage-fertilization treatment method and system based on the analysis of cultivated land quality degradation, so as to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A combined tillage-fertilization treatment method based on the analysis of cultivated land quality degradation, the specific steps include:

[0009] Step S1: Divide the target cultivated land area into multiple sub-areas, collect the soil degradation parameters of multiple sample collection points in each sub-area, and analyze the soil degradation parameters of multiple sample collection points in each sub-area to generate a first cultivated land quality evaluation coefficient, and the first cultivated land quality evaluation coefficient is used to evaluate the soil fertility level of the corresponding sub-area;

[0010] Step S2: According to the soil fertility level of each sub-area, determine three types of plants suitable for rotation in the corresponding sub-area, and calculate the nutrient absorption demand factor and soil fertility impact factor corresponding to each type of plant;

[0011] Step S3: Conduct a comprehensive analysis of the nutrient absorption demand factor and the soil fertility impact factor to generate an adaptability optimization coefficient for each type of plant, and the adaptability optimization coefficient is used to screen out two types of plants suitable for rotation from the three types of plants;

[0012] Step S4: Rotate the two types of plants selected in each sub-area, and recalculate the first cultivated land quality evaluation coefficient of the corresponding sub-area after rotation. Compare and analyze the first cultivated land quality evaluation coefficients obtained from these two calculations to determine whether the soil fertility level of each sub-area has been improved. In the next planting cycle, according to the improvement situation, provide an adjustment strategy for soil fertilization and / or rotation of plants in each sub-area.

[0013] A combined tillage-fertilization treatment system based on the analysis of cultivated land quality degradation, the system is used to execute the combined tillage-fertilization treatment method based on the analysis of cultivated land quality degradation, including:

[0014] The first coefficient analysis module: used to divide the target cultivated land area into multiple sub-areas, collect the soil degradation parameters of multiple sample collection points in each sub-area, and analyze the soil degradation parameters of multiple sample collection points in each sub-area to generate a first cultivated land quality evaluation coefficient, and the first cultivated land quality evaluation coefficient is used to evaluate the soil fertility level of the corresponding sub-area;

[0015] The plant determination module: used to determine three types of plants suitable for rotation in the corresponding sub-area according to the soil fertility level of each sub-area, and calculate the nutrient absorption demand factor and soil fertility impact factor corresponding to each type of plant;

[0016] Optimization coefficient generation module: used to comprehensively analyze the nutrient absorption demand factor and the soil fertility impact factor to generate the adaptability optimization coefficient for each category of planted crops. The adaptability optimization coefficient is used to screen out two categories of planted crops suitable for rotation from the three categories of planted crops;

[0017] Judgment and adjustment module: used to rotate the two categories of planted crops screened out in each sub-region, and recalculate the first cultivated land quality evaluation coefficient of the corresponding sub-region after rotation. Compare and analyze the first cultivated land quality evaluation coefficients obtained from these two calculations to determine whether the soil fertility level of each sub-region has been improved. In the next planting cycle, provide adjustment strategies for soil fertilization and / or rotation of planted crops in each sub-region according to the improvement situation.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: by dividing sub-regions and collecting soil samples, detailed analysis of soil degradation parameters is carried out to generate the first cultivated land quality evaluation coefficient; this process not only fully considers the multi-dimensional characteristics of the soil, but also realizes the quantitative management of soil quality through the evaluation coefficient; secondly, according to the soil fertility level, three categories of planted crops suitable for rotation are scientifically determined, and the adaptability optimization coefficient for each category of planted crops is generated through the comprehensive analysis of the nutrient absorption demand factor and the soil fertility impact factor; the adaptability optimization coefficient is used to screen out two categories of planted crops suitable for rotation from the three categories of planted crops, realizing the dynamic monitoring and continuous improvement of soil quality; finally, through comparison and analysis and adjustment strategies, targeted soil fertilization and rotation of planted crop adjustment suggestions are provided for each sub-region, thus ensuring the long-term improvement of soil fertility level and the sustainable development of agricultural production. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic flow chart of the method for implementing the tillage-fertilization combined treatment method of the present invention;

[0020] Figure 2 It is a block diagram of the system module for implementing the tillage-fertilization combined treatment method of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0021] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with specific embodiments.

[0022] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those of ordinary skill in the field to which the present invention pertains. The "first", "second" and similar terms used in the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. The terms such as "comprising" or "including" mean that the elements or objects appearing before this term cover the elements or objects listed after this term and their equivalents, without excluding other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0023] Embodiment 1:

[0024] Please refer to Figure 1 , the present invention provides a technical solution:

[0025] A combined tillage-fertilization control method based on the analysis of cultivated land quality degradation, the specific steps include:

[0026] Step S1: Divide the target cultivated land area into multiple sub-areas, collect the soil degradation parameters of multiple sample collection points in each sub-area, and analyze the soil degradation parameters of multiple sample collection points in each sub-area to generate a first cultivated land quality evaluation coefficient, and the first cultivated land quality evaluation coefficient is used to evaluate the soil fertility level of the corresponding sub-area;

[0027] Further explanation: Different suitable plants are cultivated in each sub-area according to different soil fertility levels; multiple sample collection points are evenly distributed discretely in the corresponding sub-area;

[0028] The soil degradation parameters include soil organic matter content and soil aggregate stability index;

[0029] 1.1) Set the calculation formula of soil organic matter content as follows:

[0030]

[0031] Wherein, SOC i,j is the soil organic matter content of the j-th sample collection point in the i-th sub-area, and C organic,i,j is the organic carbon content (unit: g / kg) of the j-th sample collection point in the i-th sub-area; specifically, a portable soil organic matter analyzer is used to collect and analyze the soil organic carbon content;

[0032] M soil,i,jis the total mass of the soil sample at the j-th sample collection point in sub-region i (unit: g);

[0033] For SOC i,j perform normalization and denote it as SOC′ i,j ; SOC′ i,j is calculated as follows:

[0034]

[0035] where SOC min and SOC max are respectively the minimum and maximum values of the soil organic matter content at multiple sample collection points in sub-region i;

[0036] 1.2) Set the calculation formula of the soil aggregate stability index as follows:

[0037]

[0038] where, W stable,i,j is the mass of stable soil aggregates at the j-th sample collection point in sub-region i (unit: g);

[0039] It should be noted that the mass of stable soil aggregates and the mass of unstable soil aggregates are distinguished and determined in the following way:

[0040] Imersion stability test: Immerse the soil samples at the j sample collection points in water. After a period of time, observe which aggregates can maintain their structure and which aggregates are washed away or decomposed by water;

[0041] Mass of stable aggregates: During the immersion process, the mass of aggregates that remain intact is regarded as the mass of stable aggregates;

[0042] Mass of unstable aggregates: Aggregates that are easily washed away by water are regarded as the mass of unstable aggregates;

[0043] W total,i,j is the total mass of soil aggregates at the j-th sample collection point in sub-region i (unit: g);

[0044] ASI i,j is the soil aggregate stability index at the j-th sample collection point in sub-region i;

[0045] ASI i,j The higher the value, the more stable the soil structure and the stronger the anti-erosion ability;

[0046] For ASI i,j perform normalization and denote it as ASI′ i,j ; ASI′ i,j is calculated as follows:

[0047]

[0048] Among them, ASI min and ASI max are respectively the minimum and maximum values of the soil aggregate stability index at multiple sample collection points in sub-region i;

[0049] The normalized soil organic matter content and the soil aggregate stability index are comprehensively calculated and weighted to generate the first cultivated land quality evaluation coefficient;

[0050] Define the first cultivated land quality evaluation coefficient of sub-region i as FQEI i , and the calculation formula is as follows:

[0051]

[0052] Among them, SOC′ i,j represents the soil organic matter content after consistent dimensionless processing at the j-th sample collection point in sub-region i;

[0053] ASI′ i,j represents the soil aggregate stability index after consistent dimensionless processing at the j-th sample collection point in sub-region i; the larger the value of ASI′ i,j , the more stable the soil structure; the soil aggregate stability index is obtained by analyzing the mass of stable soil aggregates, the mass of unstable soil aggregates, and the total mass of soil aggregates within the sample collection point; M1 represents the total number of sample collection points; w1 and w2 are the weights of SOC′ i,j and ASI′ i,j respectively, and the value ranges of w1 and w2 are both in the interval (0, 1), and satisfy w1 + w2 = 1; it is set that the effective value range of FQEI i is (0, 1);

[0054] The same dimensionless standard is adopted for all the above-mentioned sub-regions;

[0055] If the value of SOC′ i,j and / or the value of ASI′ i,j is higher, the value of FQEI i is larger, which further represents a higher soil fertility level in sub-region i.

[0056] Step S2: According to the soil fertility levels of each sub-region, determine three types of plants suitable for rotation in the corresponding sub-region, and calculate the nutrient absorption demand factors and soil fertility impact factors corresponding to each type of plant;

[0057] The nutrient absorption demand factor includes the soil fertilization nitrogen concentration demand value, while the soil fertility influence factor characterizes the influence degree of the planted crops on the soil fertility level of the corresponding sub-region;

[0058] Further explanation: The determination methods of the three types of planted crops are as follows:

[0059] According to the output value range of FQEI i , the soil fertility level is divided into high fertility level, medium fertility level and low fertility level in turn;

[0060] Define the fertility division interval of FQEI i as [Q1 i , Q2 i , where Q1 i and Q2 i are respectively the lower limit value and the upper limit value of the medium fertility level; and [Q1 i , Q2 i is included in the interval (0, 1);

[0061] [Q1 i , Q2 i is determined by the strategy: respectively set the maximum and minimum reference expected values of SOC′ i,j and ASI′ i,j ;

[0062] When both SOC′ i,j and ASI′ i,j take the minimum reference expected values, the calculated FQEI i is used as Q1 i ;

[0063] When both SOC′ i,j and ASI′ i,j take the maximum reference expected values, the calculated FQEI i is used as Q2 i ;

[0064] When FQEI i > Q2 i , it means that the sub-region i is at a high fertility level;

[0065] When Q1 i ≤ FQEI i ≤ Q2 i , it means that the sub-region i is at a medium fertility level;

[0066] When FQEI i < Q1 i , it means that the sub-region i is at a low fertility level;

[0067] According to the division of different fertility levels, determine the rotation plants suitable for the current sub-region i, and the specific selection strategy is as follows:

[0068] The three types of planted crops are deep-rooted crops, shallow-rooted crops, and leguminous crops respectively;

[0069] If the current sub-region i is at a high fertility level, it means that the soil organic matter is rich and the aggregate stability is high, which is suitable for planting deep-rooted crops, shallow-rooted crops, and leguminous crops with high soil requirements;

[0070] The planted crops selected at the high fertility level in this embodiment are as follows:

[0071] Maize: A deep-rooted crop that can enhance soil structure and is suitable for high fertility conditions.

[0072] Wheat: Its roots absorb quickly and it is suitable for high-fertility soil.

[0073] Soybean: It can fix nitrogen and further improve soil fertility.

[0074] If the current sub-region i is at a medium fertility level, it means that the soil fertility is medium, which is suitable for planting deep-rooted crops, shallow-rooted crops, and leguminous crops with strong tolerance;

[0075] The planted crops selected at the medium fertility level in this embodiment are as follows:

[0076] Potato: It has strong adaptability and can grow under different soil conditions.

[0077] Oat: It is suitable for medium-fertility soil and has low water requirements.

[0078] Sorghum: It grows stably and has relatively loose soil requirements.

[0079] If the current sub-region i is at a low fertility level, it means that the soil quality is poor, and it is necessary to select deep-rooted crops, shallow-rooted crops, and leguminous crops that can improve soil quality;

[0080] The planted crops selected at the low fertility level in this embodiment are as follows:

[0081] Alfalfa (Medicago sativa): It can fix nitrogen and promote the improvement of soil fertility.

[0082] Sweet potato (Ipomoea batatas): It can adapt to poor soil and increase the organic matter content.

[0083] Gramineous weeds: They can improve soil structure and increase soil air permeability.

[0084] Define each category of planted crops in sub-region i as k, where k ∈ {p1, p2, p3};

[0085] The nutrient absorption demand factor includes the root absorption rate, and the soil fertilization concentration demand value is composed of the ratio of nitrogen, phosphorus, and potassium concentrations;

[0086] Denote the nutrient absorption demand factor corresponding to planting the k-th type of plant in sub-region i as NDF i,k , and the calculation formula is as follows:

[0087]

[0088] where, represents the standard soil nitrogen concentration (unit: mg / kg) required for planting the k-th type of plant corresponding to sub-region i; represents the actual soil nitrogen concentration (unit: mg / kg) of sub-region i when cultivating the k-th type of plant; and d and t in represent the "standard" and "actual" category indices of the k-th type of plant respectively;

[0089] represents the standard root absorption rate required for planting the k-th type of plant corresponding to sub-region i; represents the actual root absorption rate of sub-region i when cultivating the k-th type of plant;

[0090] α1 and α2 are the weight coefficients of the corresponding parameters, and the values of α1 and α2 are both in the interval (0, 1), and α1 + α2 = 1;

[0091] It should be noted that since is a fixed value relative to the k-th type of plant, when or the larger the value, the smaller the difference between the actual soil nitrogen concentration and the actual root absorption rate and the corresponding required values, and further indicates that the ratio of the nutrient demand of the k-th type of plant cultivated in sub-region i and the actual soil supply is becoming more and more coordinated, resulting in an increasing trend of NDF i,k ; it means that the current sub-region i can better meet the nutrient demand of the k-th type of plant, and the k-th type of plant can obtain sufficient nutrients from the soil of sub-region i to support its growth and yield; at this time, the fertilization strategy is effective and the environmental conditions are optimized;

[0092] The soil fertility influence factor includes the standard soil looseness and soil water holding capacity of the plant;

[0093] The soil water holding capacity is obtained by calculating the ratio of the volume of water in the soil to the volume of the soil. The larger the value of the soil water holding capacity, the larger the proportion of the corresponding water volume;

[0094] The soil looseness is determined by the bulk density measurement method. Specifically, the dry weight and the soil volume of the soil sample in the dry condition are recorded, and the ratio of the dry weight to the soil volume is calculated to obtain it.

[0095] The soil fertility influence factor corresponding to the selection of the k-th type of plant in the sub-region i is denoted as SFI. i,k , and the calculation formula is as follows:

[0096]

[0097] Among them, represents the standard soil looseness required for planting the k-th type of plant corresponding to the sub-region i; represents the actual soil looseness when cultivating the k-th type of plant in the sub-region i;

[0098] represents the standard soil water holding capacity required for planting the k-th type of plant corresponding to the sub-region i; represents the actual soil water holding capacity when cultivating the k-th type of plant in the sub-region i;

[0099] b1 and b2 are the weight coefficients of the corresponding parameters. The values of b1 and b2 are both in the interval (0, 1), and b1 + b2 = 1.

[0100] It should be noted that: when or The larger the value, the closer SFI i,k is to 1, indicating that the standard soil looseness and soil water holding capacity of the k-th type of plant are more in line with the actual growth requirements;

[0101] Step S3: Comprehensively analyze the nutrient absorption demand factor and the soil fertility influence factor to generate the adaptability optimization coefficient for each category of plant. The adaptability optimization coefficient is used to screen out two types of plants suitable for rotation from the three types of plants;

[0102] Further explanation: Generating the adaptability optimization coefficient for each category of plant includes:

[0103] The adaptability optimization coefficient of the k-th type of plant in the sub-region i is denoted as AOC i,k , AOC i,k , and the calculation formula is as follows:

[0104] AOC i,k = c1 × NDF′ i,k + c2 × SFI′ i,k

[0105] Among them, NDF′ i,k is NDF i,kAfter being preprocessed by the Sigmoid function, the output value is normalized to the range between 0 and 1; NDF′ i,k It reflects the comprehensive demand of the k-th type of plant for the soil fertilization concentration requirement value and the root absorption rate;

[0106] SFI′ i,k It is SFI i,k After being preprocessed by the Sigmoid function, the output value is normalized to the range between 0 and 1; SFI′ i,k It reflects the comprehensive demand of the k-th type of plant for the soil looseness and the soil water holding capacity;

[0107] c1 and c2 are the weight coefficients of the corresponding parameters respectively, and the values of c1 and c2 are both within the interval (0, 1), and c1 + c2 = 1;

[0108] In this embodiment, c1 = c2 is initially set; it represents NDF′ i,k and SFI′ i,k have the same contribution degree to AOC i,k ;

[0109] When NDF′ i,k and / or NDF i,k gets closer and closer to 1 / 2, AOC i,k gets closer and closer to 1 / 2, indicating that it is more suitable to cultivate the k-th type of plant in sub-region i;

[0110] When NDF′ i,k and / or NDF i,k gets closer and closer to 0, AOC i,k gets closer and closer to 0, indicating that it is less suitable to cultivate the k-th type of plant in sub-region i;

[0111] It should be noted that:

[0112] When AOC i,k gets closer and closer to 1 / 2, it indicates that AOC i,k = c1×NDF′ i,k + c2×SFI′ i,k the larger the value of SFI i,k or NDF i,k in it, and further represents that the standard soil looseness and soil water holding capacity of the k-th type of plant in sub-region i are more in line with the actual growth requirements, and sub-region i can better meet the nutrient requirements of the k-th type of plant;

[0113] When AOC i,k gets closer and closer to 0, it indicates that AOC i,k = c1×NDF′ i,k + c2×SFI′ i,k the larger the value of SFI i,k or NDFi,k The smaller the value, the less the standard soil looseness and water holding capacity of the k-th type of plant in sub-region i meet the actual growth requirements, and the less sub-region i can meet the nutrient requirements of the k-th type of plant.

[0114] The adaptation optimization coefficients corresponding to k ∈ {p1, p2, p3} are respectively denoted as AOC i,p1 , AOC i,p2 and AOC i,p3 ;

[0115] Select the top two types of plants with large values from AOC i,p1 , AOC i,p2 and AOC i,p3 .

[0116] Step S4: Rotate the two types of plants screened out in each sub-region, and recalculate the first cultivated land quality evaluation coefficient of the corresponding sub-region after rotation. Compare and analyze the two first cultivated land quality evaluation coefficients obtained by these two calculations to determine whether the soil fertility level of each sub-region has been improved. In the next planting cycle, according to the improvement situation, provide soil fertilization and / or rotation plant adjustment strategies for each sub-region.

[0117] Further explanation: Determine whether the soil fertility level of each sub-region has been improved. In the next planting cycle, according to the improvement situation, provide the nitrogen concentration demand value of soil fertilization and / or rotation plant adjustment strategies for each sub-region, specifically including:

[0118] When FQEI′ i > FQEI i + μ1, it indicates that the improvement amount of the soil fertility level in sub-region i is large, and the selected plant category for cultivation meets the requirements; μ1 is a fluctuation factor used to characterize whether the improvement amount of the soil fertility level reaches the expected requirement; 0.1 ≤ μ1 ≤ 0.25;

[0119] μ1 is determined by specific numerical values by the expert group based on experimental data and will not be elaborated here;

[0120] When FQEI′ i ≤ FQEI i + μ1, it indicates that the improvement amount of the soil fertility level in sub-region i is small or shows negative growth; it is necessary to change the rotation plants and adjust the soil fertilization ratio;

[0121] Adjusting the soil fertilization ratio includes: obtaining the standard ratio values of nitrogen, phosphorus, and potassium in sub-region i after rotation;

[0122] Collecting the actual ratio values of nitrogen, phosphorus, and potassium in sub-region i after rotation;

[0123] Generate a soil fertilization adjustment strategy based on the differences between the standard and actual ratio values of nitrogen, phosphorus, and potassium, so that the actual ratio values of nitrogen, phosphorus, and potassium ultimately approach the standard ratio values.

[0124] Regarding changing the rotation crops or the soil fertilization adjustment strategy, it should be noted that: changing the rotation crops will bring different tillage methods and have varying impacts on the soil fertility level.

[0125] The impacts of deep-rooted crops on the soil are as follows:

[0126] Deep tillage effect: Deep-rooted crops such as potatoes and cassavas have roots that penetrate deep into the soil, which can improve soil aeration and drainage by breaking the dense structure of the deep soil layer.

[0127] Nutrient acquisition: Since deep-rooted crops can absorb water and nutrients from deep in the soil, they can utilize deep soil nutrients that shallow-rooted crops cannot.

[0128] Soil structure improvement: Promote the nutrient cycle in the deep soil, contribute to the increase of soil organic matter, and improve the soil structure.

[0129] The impacts of shallow-rooted crops on the soil are as follows:

[0130] Surface soil protection: Shallow-rooted crops such as wheat and corn are mostly grains and herbs, and the vegetation cover formed by these crops can effectively protect the surface soil from erosion.

[0131] Soil fertility concentration: The roots of these crops are concentrated in the surface soil layer and mainly consume the surface soil fertility. Therefore, in rotation, alternating with deep-rooted crops or leguminous crops can achieve the redistribution and balance of soil nutrients.

[0132] Simplification of tillage: Since the roots are relatively shallow, deep tillage is not required during the tillage process, reducing soil disturbance.

[0133] The impacts of leguminous crops on the soil are as follows:

[0134] Biological nitrogen fixation ability: Leguminous crops such as soybeans and peas can symbiose with rhizobia, convert nitrogen in the air into available nitrogen, increase the nitrogen content in the soil, and reduce the dependence on chemical fertilizers.

[0135] Improve soil fertility: The residues and root nodules of leguminous crops can increase the soil organic matter content and promote fertility restoration.

[0136] Interruption of continuous planting: Planting leguminous crops usually helps to break the growth cycles of certain pests, diseases, and weeds, and is conducive to the growth of subsequent crops.

[0137] In this embodiment, the changed rotation crops are selected in "The adaptability optimization coefficient is used to screen out two types of crops suitable for rotation from three types of crops" in step S3; increasing the soil fertilization concentration value is based on approaching 1 as the adjustment basis. Specifically, urea, ammonia water or organic nitrogen fertilizer is applied in sub-region i; when applying nitrogen fertilizer, the proportions of P3 (phosphorus), K3 (potassium) and organic matter need to be considered to ensure the balance of various nutrients in the soil; the recommended proportions in this embodiment are as follows:

[0138] In the fertilization plan, the ratio of nitrogen, phosphorus and potassium (N:P:K) is set to 1:0.5:0.5 or 1:1:1, specifically determined according to the requirements of the rotation crops.

[0139] Embodiment 2:

[0140] Please refer to Figure 2 , a tillage-fertilization combined treatment system based on the analysis of cultivated land quality degradation, the system is used to execute the tillage-fertilization combined treatment method based on the analysis of cultivated land quality degradation, including:

[0141] The first coefficient analysis module: used to divide the target cultivated land area into multiple sub-regions, collect the soil degradation parameters of multiple sample collection points in each sub-region, and analyze the soil degradation parameters of multiple sample collection points in each sub-region to generate the first cultivated land quality evaluation coefficient, and the first cultivated land quality evaluation coefficient is used to evaluate the soil fertility level of the corresponding sub-region;

[0142] The crop determination module: used to determine three types of crops suitable for rotation in each sub-region according to the soil fertility level of each sub-region, and calculate the nutrient absorption demand factor and soil fertility impact factor corresponding to each type of crop;

[0143] The optimization coefficient generation module: used to comprehensively analyze the nutrient absorption demand factor and soil fertility impact factor to generate the adaptability optimization coefficient of each type of crop, and the adaptability optimization coefficient is used to screen out two types of crops suitable for rotation from three types of crops;

[0144] The judgment and adjustment module: used to rotate the two types of crops screened out in each sub-region, and recalculate the first cultivated land quality evaluation coefficient of the corresponding sub-region after rotation, compare and analyze the first cultivated land quality evaluation coefficients obtained from these two calculations, judge whether the soil fertility level of each sub-region has been improved, and in the next planting cycle, provide adjustment strategies for soil fertilization and / or rotation crops in each sub-region according to the improvement situation.

[0145] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0146] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or by the combination of computer software and electronic hardware. Whether these functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0147] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units. They can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0148] As described above, only the specific implementation manners of this application are provided, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all of them should be covered by the protection scope of this application.

Claims

1. A method for combined tillage and fertilization based on farmland quality degradation analysis, characterized in that: The specific steps include: Step S1: dividing the target cultivated land area into multiple sub-areas, collecting soil degradation parameters of multiple sample collection points in each sub-area, and analyzing the soil degradation parameters of multiple sample collection points in each sub-area to generate a first cultivated land quality evaluation coefficient, and the first cultivated land quality evaluation coefficient is used to evaluate the soil fertility level of the corresponding sub-area; Step S2: according to the soil fertility level of each sub-region, determine the three types of plants suitable for crop rotation in the corresponding sub-region, and calculate the nutrient absorption demand factor and soil fertility influencing factor corresponding to each type of plant; Step S3: Comprehensively analyzing the nutrient absorption demand factor and the soil fertility influencing factor to generate the adaptability optimization coefficient of each type of plant, and the adaptability optimization coefficient is used to select two types of plants suitable for crop rotation from the three types of plants; Step S4: Rotate the two types of plants screened out in each sub-area, and recalculate the first arable land quality evaluation coefficient of the corresponding sub-area after the rotation, compare and analyze the first arable land quality evaluation coefficients calculated twice to determine whether the soil fertility level of each sub-area is improved, and in the next planting cycle, provide each sub-area with an adjustment strategy for soil fertilization and / or rotation of plants based on the improvement situation.

2. The method for combined tillage and fertilization based on farmland quality degradation analysis according to claim 1 is characterized in that: Multiple sample collection points are evenly distributed in the corresponding sub-areas in a discrete manner; Soil degradation parameters include soil organic matter content and soil aggregate stability index; Define the first farmland quality evaluation coefficient of sub-region i as FQEI i , the calculation formula is as follows: Among them, SOC′ i,j It represents the soil organic matter content of the jth sample collection point in sub-area i after consistent dimensionless processing; ASI′ i,j ASI′ represents the soil aggregate stability index of the jth sample collection point in sub-region i after consistent dimensionless processing; i,j The larger the value, the more stable the soil structure. The soil aggregate stability index is obtained by analyzing the mass of stable soil aggregates, the mass of unstable soil aggregates and the mass of total soil aggregates in the sample collection point. M1 represents the total number of sample collection points. w1 and w2 are SOC′, respectively. i,j and ASI′ i,j The weights of w1 and w2 are both in the interval (0,1), and satisfy w1+w2=1; set FQEI i The valid value range of is (0,1); The multiple sub-regions all adopt the same dimensionless standard; If SOC′ i,j and / or ASI′ i,j The higher the value, the higher the FQEI i The larger the value, the higher the soil fertility level of sub-region i.

3. The method for combined tillage and fertilization based on farmland quality degradation analysis according to claim 2 is characterized in that: The three types of plants are determined as follows: According to FQEI i The output value range of the soil fertility level is divided into high fertility level, medium fertility level and low fertility level; Defining FQEI i The interval representing the medium fertility level is [Q1 i ,Q2 i ],Q1 i With Q2 i are the lower and upper limits of the medium fertility level respectively; and [Q1 i ,Q2 i ] is included in the interval (0,1); When FQEI i >Q2 i When , it means that sub-region i is at a high fertility level; When Q1 i ≤FQEI i ≤Q2 i When , it means that sub-region i is at a medium fertility level; When FQEI i <Q1 i When , it means that sub-region i is at a low fertility level; According to the classification of different fertility levels, the rotation plants suitable for the current sub-area i are determined. The specific selection strategy is as follows: The three types of plants are deep-rooted crops, shallow-rooted crops and leguminous crops; If the current sub-region i is at a high fertility level, it means that the soil is rich in organic matter and has high aggregate stability, which is suitable for planting deep-rooted crops, shallow-rooted crops and legume crops that have high soil requirements; If the current sub-region i is of medium fertility level, it is suitable for planting deep-rooted crops, shallow-rooted crops and legume crops with strong tolerance; If the current sub-region i is at a low fertility level, it means that the soil quality is poor, and it is necessary to select deep-rooted crops, shallow-rooted crops, and legume crops that can improve soil quality; The nutrient absorption demand factor corresponding to the k-th type of plant selected in sub-area i is recorded as NDF i,k , the calculation formula is as follows: in, represents the standard soil nitrogen concentration required for planting the k-th type of plant corresponding to sub-area i, k is the index of the plant category, and k∈{p1,p2,p3}; p1,p2,p3 represent deep-rooted crops, shallow-rooted crops and leguminous crops respectively; represents the actual soil nitrogen concentration in sub-area i when the k-th type of plant is cultivated in sub-area i; and The d and t in it represent the "standard" and "actual" category indexes of the k-th plant, respectively; represents the standard root absorption rate required for planting the k-th type of plant corresponding to sub-area i; represents the actual root absorption rate of the k-th type of plant when planted in sub-area i; α1, α2 are weight coefficients of the corresponding parameters, the values ​​of α1, α2 are both in the interval (0, 1), and α1+α2=1; The soil fertility influencing factor corresponding to the selection of the kth type of plant in sub-region i is recorded as SFI i,k , the calculation formula is as follows: in, represents the standard soil looseness required for planting the k-th type of plant corresponding to sub-area i; It represents the actual soil looseness when the k-th type of plant is cultivated in sub-area i; represents the standard soil water holding capacity required for planting the k-th type of plant corresponding to sub-area i; It represents the actual soil water holding capacity when the k-th type of plant is cultivated in sub-area i; b1 and b2 are weight coefficients of the corresponding parameters. The values ​​of b1 and b2 are both in the interval (0,1), and b1+b2=1.

4. The method for combined tillage and fertilization based on farmland quality degradation analysis according to claim 3 is characterized in that: Generate the adaptive optimization coefficients for each type of plant, including: The adaptive optimization coefficient of the kth type of plant in sub-region i is recorded as AOC i,k , AOC i,k The calculation formula is as follows: AOC i,k =c1×NDF′ i,k +c2×SFI′ i,k Among them, NDF′ i,k NDF i,k After Sigmoid function preprocessing, the output value is normalized to the range between 0 and 1; NDF′ i,k Reflects the comprehensive demand of the k-th type of plants for soil fertilizer concentration and root absorption rate; SFI′ i,k Yes SFI i,k After Sigmoid function preprocessing, the output value is normalized to the range between 0 and 1; SFI′ i,k Reflects the comprehensive requirements of the k-th type of plants for soil looseness and soil water holding capacity; c1 and c2 are weight coefficients of the corresponding parameters, and the values ​​of c1 and c2 are both in the interval (0,1), c1+c2=1; When NDF′ i,k and / or NDF i,k As AOC approaches 1 / 2, i,k The closer it is to 1 / 2, the more suitable the sub-region i is for growing the k-th type of plants; When NDF′ i,k and / or NDF i,k As AOC approaches 0, i,k The closer it is to 0, the less suitable it is for growing the kth type of plant in sub-region i; The adaptive optimization coefficients corresponding to k∈{p1,p2,p3} are denoted as AOC i,p1 , AOC i,p2 and AOC i,p3 ; From AOC i,p1 , AOC i,p2 and AOC i,p3 Select the first two types of plants with larger values.

5. The method for combined tillage and fertilization based on farmland quality degradation analysis according to claim 4 is characterized in that: Determine whether the soil fertility level of each sub-region has been improved. In the next planting cycle, based on the improvement, provide each sub-region with soil fertilization nitrogen concentration requirements and / or crop rotation adjustment strategies, including: Define the first cultivated land quality evaluation coefficient of sub-region i after crop rotation as FQEI′ i ; When FQEI′ i >FQEI i +μ1, it means that the improvement of soil fertility level in sub-area i is large, and the plant species selected for cultivation meet the requirements; μ1 is a fluctuation factor, which is used to characterize whether the improvement of soil fertility level meets the expected requirements; 0.1≤μ1≤0.25; When FQEI′ i ≤FQEI i When +μ1, it means that the improvement of soil fertility level in sub-area i is small or negative; it is necessary to change crop rotation and adjust soil fertilization ratio; Adjusting the soil fertilizer ratio includes: obtaining the standard ratio values ​​of nitrogen, phosphorus and potassium in sub-area i after crop rotation; Collect the actual ratios of nitrogen, phosphorus and potassium in sub-area i after crop rotation; According to the difference between the standard ratio and the actual ratio of nitrogen, phosphorus and potassium, a soil fertilization adjustment strategy is generated to ultimately make the actual ratio of nitrogen, phosphorus and potassium approach the standard ratio.

6. A farming-fertilization combined management system based on farmland quality degradation analysis, characterized by: The system is used to implement the tillage-fertilization combined management method based on cultivated land quality degradation analysis according to any one of claims 1 to 5, comprising: The first coefficient analysis module is used to divide the target cultivated land area into multiple sub-areas, collect soil degradation parameters of multiple sample collection points in each sub-area, and analyze the soil degradation parameters of multiple sample collection points in each sub-area to generate a first cultivated land quality evaluation coefficient, and the first cultivated land quality evaluation coefficient is used to evaluate the soil fertility level of the corresponding sub-area; Plant determination module: used to determine the three types of plants suitable for crop rotation in the corresponding sub-area according to the soil fertility level of each sub-area, and calculate the nutrient absorption demand factor and soil fertility influencing factor corresponding to each type of plant; Optimization coefficient generation module: used to comprehensively analyze the nutrient absorption demand factor and the soil fertility influencing factor to generate the adaptability optimization coefficient of each type of plant. The adaptability optimization coefficient is used to select two types of plants suitable for crop rotation from three types of plants. Judgment and adjustment module: It is used to rotate the two types of plants screened out in each sub-area, and recalculate the first arable land quality evaluation coefficient of the corresponding sub-area after the rotation, compare and analyze the first arable land quality evaluation coefficients calculated twice, and judge whether the soil fertility level of each sub-area has been improved. In the next planting cycle, according to the improvement situation, provide each sub-area with an adjustment strategy for soil fertilization and / or rotation plants.

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