Application of biochar in saline-alkali soil improvement and crop quality and yield improvement

Abstract

The invention discloses application of biochar in saline-alkali soil improvement and crop quality and yield improvement, and relates to the technical field of biochar soil improvement and crop yield and quality improvement. Comprising a biochar saline-alkali soil improvement and crop quality-improving and yield-increasing system which is used for acquiring degradation weight data of biochar and physical and chemical data of saline-alkali soil, acquiring correlation between saline-alkali soil data and biochar degradation degree by using a Pearson correlation coefficient, calculating the biochar degradation degree, constructing a biochar degradation monitoring model, and monitoring the quality of the saline-alkali soil in the biochar degradation monitoring model. According to the method, the soil bulk density measurement technology, the drying acquisition technology and the modern information technology are combined, the soil bulk density measurement technology and the drying acquisition technology are combined, and the soil bulk density measurement and the drying acquisition technology are combined; the consumption of biochar in saline-alkali soil at the interval of 24 hours and the soil bulk density, the water content, the pH value and the organic carbon content of the saline-alkali soil in a saline-alkali soil test area at the interval of 24 hours are accurately captured, and physical data and chemical data of the saline-alkali soil are monitored in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of biochar for improving soil and increasing the yield and quality of crops, and specifically to the application of biochar in improving saline-alkali soil and increasing the quality and yield of crops. Background Art

[0002] With the global population growth and the increasing shortage of arable land resources, the development and utilization of saline-alkali land has become an important direction for agricultural development. Saline-alkali soil has problems such as high salt, high alkalinity, compaction and nutrient imbalance, which seriously restrict the growth of crops, resulting in low yield and poor quality. Traditional saline-alkali land improvement methods such as chemical improvement are costly and may cause secondary pollution. Physical improvement often has limited effect and large engineering workload. Biochar came into being due to its unique physical and chemical properties. Biochar is a carbon-rich product formed by the pyrolysis of biomass under anaerobic conditions. It has a highly aromatic structure, rich pores and a large specific surface area. It can absorb salt in the soil, reduce soil conductivity, regulate soil pH, improve soil structure, increase soil aeration and water retention, promote microbial activity, and enhance the effectiveness of nutrients in the soil, creating a more favorable soil environment for crop growth, thereby achieving improved crop quality and increased yield. It has broad application prospects in the field of saline-alkali land improvement.

[0003] Although the existing application of biochar in saline-alkali soil improvement and crop quality and yield increase has made great progress, there are still some problems that need to be optimized. In the existing technology, it is difficult to evaluate the degradation degree of biochar in different saline-alkali soils. Since the action time of biochar in saline-alkali soil is limited, the improvement effect of saline-alkali soil gradually decreases with the consumption of biochar, affecting the sustainability of the improvement effect of biochar on saline-alkali soil, and thus affecting the sustainability of the process of improving crop quality and yield. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: application of biochar in saline-alkali soil improvement and crop quality and yield improvement, including a biochar saline-alkali soil improvement and crop quality and yield improvement system, the biochar saline-alkali soil improvement and crop quality and yield improvement system consisting of a biochar degradation weight sensing module, a saline-alkali soil collection module, a biochar degradation degree processing module, a monitoring and evaluation module, and a feedback execution module, wherein the modules are connected by electrical signals;

[0005] The biochar degradation weight sensing module is used to obtain the biochar degradation weight data to provide accurate data support for the subsequent calculation of the biochar degradation degree;

[0006] The saline-alkali soil collection module is used to obtain the physical and chemical data of saline-alkali soil and accurately monitor the relationship between the degree of biochar degradation and the physical and chemical conditions of different saline-alkali soils;

[0007] The biochar degradation degree processing module is used to deduce the saline-alkali soil correlation and generate the degradation degree of biochar in different saline-alkali soils, so as to achieve the effect of monitoring the biochar degradation degree, and provide key technical support for realizing the sustainable improvement of saline-alkali soil by biochar;

[0008] The monitoring and evaluation module is used to analyze the physical and chemical data of saline-alkali soil, evaluate the biochar degradation results, and realize the data output of the biochar degradation degree by the biochar degradation detection model;

[0009] The feedback execution module receives the biochar degradation result and takes corresponding measures to deal with it.

[0010] Preferably, in order to ensure the accuracy of the subsequent calculation of the degree of biochar degradation through biochar consumption monitoring, the biochar degradation weight data is the biochar consumption in the saline-alkali soil at intervals of 24 hours, and the acquisition process includes:

[0011] Select a saline-alkali land test area, collect soil samples from n saline-alkali land test areas 24 hours ago, dry them at 105℃ to constant weight, and record the mass of the dried soil samples, which is recorded as m1;

[0012] After an interval of 24 hours, soil samples were collected from n saline-alkali land test areas and dried at 105°C to constant weight. The mass of the dried soil samples was recorded as m2.

[0013] The mass difference m1-m2 of the soil samples after drying at intervals of 24 hours was calculated to obtain the consumption M of biochar in the saline-alkali soil at intervals of 24 hours.

[0014] Preferably, the physical data of the saline-alkali soil are the soil bulk density and water content of the saline-alkali soil in the saline-alkali land test area at intervals of 24 hours, and the acquisition process includes:

[0015] The knife ring method was used, and the knife ring weight m and knife ring volume V were recorded. The knife ring was vertically pressed into the saline-alkali soil in the saline-alkali land test area 24 hours before and 24 hours later, so that the knife ring was filled with saline-alkali soil. The knife ring was dried at high temperature to constant weight, and weighed using a balance. The total weight M of the knife ring and the dried soil was recorded. Formula, to obtain the bulk density of saline-alkali soil before and after 24 hours;

[0016] A neutron meter was used to collect the water content of the saline-alkali soil 24 hours before and after 24 hours through the functional relationship between the density of the neutron cloud and water molecules.

[0017] Preferably, the chemical data of the saline-alkali soil are the pH value and organic carbon content of the saline-alkali soil in the saline-alkali land test area at intervals of 24 hours, and the acquisition process includes:

[0018] A1. Collect n saline-alkali soil samples from the saline-alkali land test area 24 hours ago and n saline-alkali soil samples from the saline-alkali land test area 24 hours later, use a pH meter to measure the saline-alkali soil samples 24 hours ago and 24 hours later, and obtain the pH values ​​of the saline-alkali soil 24 hours ago and 24 hours later;

[0019] A2. Collect m0g of saline-alkali soil samples from the saline-alkali land test area n times 24 hours before and n times 24 hours after, and set up an experimental group and a control group. The experimental group is the saline-alkali soil samples collected before and after 24 hours, and the control group is the samples with only biochar;

[0020] A3. Dry and remove impurities in the saline-alkali soil samples, mix the experimental group samples and the control group samples with potassium dichromate-sulfuric acid solution to obtain the experimental group mixed solution and the control group mixed solution, and then heat the two groups of mixed solutions at 185°C to 190°C. After the two groups of mixed solutions are cooled to room temperature through redox reaction, the experimental group mixed solution and the control group mixed solution are respectively transferred to 100 ml volumetric flasks, and dilute to the volume scale of the volumetric flask with distilled water;

[0021] A4. Use a pipette to draw 20 ml of solution from a volumetric flask into a conical flask, add 5-10 drops of o-phenanthroline indicator, and titrate with ammonium ferrous sulfate standard solution. The solution color changes to brick red, which is the titration endpoint. Record the volume V of the ammonium ferrous sulfate standard solution consumed by the experimental group and the volume V0 of the ammonium ferrous sulfate standard solution consumed by the control group;

[0022] A5. Calculate the organic carbon content of the soil using the formula:

[0023]

[0024] Wherein, C is the organic carbon content of saline-alkali soil, V0 is the volume of ammonium ferrous sulfate standard solution consumed by saline-alkali soil samples without adding saline-alkali soil samples, V is the volume of ammonium ferrous sulfate standard solution consumed by saline-alkali soil samples, c is the concentration of ammonium ferrous sulfate standard solution, m0 is the weight of the saline-alkali soil sample weighed, and k0 is the multiple of fractionation.

[0025] Preferably, the Pearson correlation coefficient is used to obtain the correlation between the soil bulk density, water content, pH value, organic carbon content and biochar degradation degree of saline-alkali soil, which provides data support for the subsequent calculation of the degradation degree of biochar in different saline-alkali soils. The acquisition process includes:

[0026] Assuming soil bulk density as R, water content as H, pH value as Q, organic carbon content as P, biochar degradation degree as Y, sample number as n, the calculation formula of Pearson correlation coefficient is:

[0027]

[0028] in, is the Pearson correlation coefficient, specifically, and They are the Pearson correlation coefficient of soil bulk density, water content, pH value, and organic carbon content;

[0029] X 1i is the sample value of the i-th sample, specifically, R 1i , H 1i , Q 1i and P 1i are the soil bulk density, water content, pH value and organic carbon content of the i-th sample respectively;

[0030] is the average value of the sample value. Specifically, and are the average values ​​of soil bulk density, water content, pH value and organic carbon content respectively;

[0031] Y i is the consumption of biochar of the ith sample; is the average value of biochar consumption.

[0032] Preferably, the process of calculating the biochar degradation degree based on the weight coefficient method using the correlation between the soil bulk density, water content, pH value, organic carbon content and the biochar degradation degree of the saline-alkali soil includes:

[0033] According to the Pearson correlation coefficient between the soil bulk density, water content, pH value, organic carbon content and biochar consumption of saline-alkali soil, the larger the Pearson correlation coefficient, the higher the correlation, the correlation between the soil bulk density, water content, pH value and organic carbon content of saline-alkali soil and the degree of biochar degradation is obtained, and the weight coefficients w1, w2, w3 and w4 are assigned to the soil bulk density, water content, pH value and organic carbon content of saline-alkali soil respectively;

[0034] Calculate the changes in soil bulk density, water content, pH value, and organic carbon content before and after 24 hours:

[0035] ΔR=R2-R1

[0036] ΔH=H2-H1

[0037] ΔQ=Q2-Q1

[0038] ΔP=P2-P1

[0039] Among them, ΔR, ΔH, ΔQ and ΔP respectively represent the changes in soil bulk density, water content, pH value and organic carbon content before and after 24 hours; R1 and R2 represent the soil bulk density before and after 24 hours; H1 and H2 represent the water content before and after 24 hours; Q1 and Q2 represent the pH value before and after 24 hours; P1 and P2 represent the organic carbon content before and after 24 hours;

[0040] Using the weight coefficient method, the process of calculating the degree of biochar degradation according to the weight coefficient includes:

[0041] ΔZ=w1×ΔR+w2×ΔH+w3×ΔQ+w4×ΔP

[0042] Among them, ΔZ is the degree of biochar degradation.

[0043] Preferably, the process of constructing a biochar degradation monitoring model using a random forest algorithm includes:

[0044] The soil bulk density, water content, pH value, organic carbon content and corresponding biochar degradation degree of saline-alkali soil were used as a data set, and 80% of the data set was selected as a training set and 20% as a test set;

[0045] The random forest model is trained through the training set. According to the characteristics of soil bulk density, water content, pH value, organic carbon content and corresponding biochar degradation degree of saline-alkali soil, the relationship between soil bulk density, water content, pH value, organic carbon content and corresponding biochar degradation degree of saline-alkali soil is trained. The soil bulk density, water content, pH value and organic carbon content data of saline-alkali soil are input, and the random forest model outputs the corresponding biochar degradation degree.

[0046] The soil bulk density, moisture content, pH value, and organic carbon content of the saline-alkali soil in the test set were input into the trained random forest model, and the corresponding biochar degradation degree was output. The consistency between the biochar degradation degree corresponding to the actual saline-alkali soil data and the biochar degradation degree output by the test set was evaluated, and the model parameters were adjusted to optimize the random forest model to obtain the biochar degradation monitoring model.

[0047] Preferably, the monitoring and evaluation module analyzes the physical and chemical data of saline-alkali soil, evaluates the biochar degradation results, and realizes the process of outputting the biochar degradation detection model data, including:

[0048] The soil bulk density, water content, pH value and organic carbon content of saline-alkali soil were analyzed and combined with the biochar degradation monitoring model. When the biochar degradation degree ΔZ was between 0 and 0.2, the biochar degradation degree was low; when the biochar degradation degree ΔZ was between 0.2 and 0.5, the biochar degradation degree was medium; when the biochar degradation degree ΔZ was greater than 0.5, the biochar degradation degree was high, and the biochar degradation results were transmitted to the feedback execution module.

[0049] Preferably, the feedback execution module receives the biochar degradation result and takes corresponding measures to deal with the process including:

[0050] Receive biochar degradation results. When the biochar degradation level is low, continuously monitor saline-alkali soil data and its biochar degradation level, so that biochar can continue to play a role in saline-alkali soil improvement and crop quality and yield increase;

[0051] When the biochar degradation degree is moderate, the saline-alkali soil parameters are adjusted to increase the amount of biochar supplement according to the saline-alkali soil data;

[0052] When the degree of biochar degradation is high, a long-term saline-alkali soil monitoring system should be established, a biochar application plan should be formulated, and the amount of biochar supplement should be increased.

[0053] Preferably, the application of biochar in saline-alkali soil improvement and crop quality and yield improvement includes a memory and a processor, wherein the memory stores executable code, and when the executable code is executed by the processor, the processor executes the biochar saline-alkali soil improvement and crop quality and yield improvement system.

[0054] Beneficial effects of the present invention: Compared with the traditional application of biochar in saline-alkali soil improvement and crop quality improvement and yield increase, the soil bulk density measurement technology and drying collection technology in the method of the present invention are closely combined with modern information technology, and the consumption of biochar in saline-alkali soil at intervals of 24 hours, the soil bulk density, water content, pH value and organic carbon content of saline-alkali soil in the saline-alkali land test area at intervals of 24 hours are accurately captured, and the real-time and comprehensive monitoring of the physical data and chemistry of saline-alkali soil is achieved. By using the Pearson correlation coefficient, the correlation between the soil bulk density, water content, pH value, organic carbon content and the degree of biochar degradation of saline-alkali soil is obtained, and the degree of biochar degradation is calculated based on the weight coefficient method. , using the random forest algorithm, a biochar degradation monitoring model was constructed to solve the problem that it is difficult to evaluate the degradation degree of biochar in different saline-alkali soils in the existing technology. Since the action time of biochar in saline-alkali soil is limited, the improvement effect of saline-alkali soil gradually decreases with the consumption of biochar, affecting the sustainability of the improvement effect of biochar on saline-alkali soil, and then affecting the sustainability of the process of improving the quality and yield of crops. The method of the present invention ensures that the dynamic monitoring standards for biochar in saline-alkali soil improvement and crop quality and yield improvement can be refined within a more precise range, making the monitoring data a more accurate indicator under the same conditions. The development and application of this method have significantly enhanced the intelligence level of biochar in the process of saline-alkali soil improvement and crop quality and yield improvement. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 The block diagram is for the application of the biochar of the present invention in improving saline-alkali soil and increasing the quality and yield of crops. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] like Figure 1 As shown, the present invention provides a technical solution: application of biochar in saline-alkali soil improvement and crop quality and yield improvement, including a biochar saline-alkali soil improvement and crop quality and yield improvement system, the biochar saline-alkali soil improvement and crop quality and yield improvement system is composed of a biochar degradation weight sensing module, a saline-alkali soil collection module, a biochar degradation degree processing module, a monitoring and evaluation module and a feedback execution module, wherein the modules are connected by electrical signals;

[0058] The biochar degradation weight sensing module is used to obtain the biochar degradation weight data and provide accurate data support for the subsequent calculation of the biochar degradation degree;

[0059] The saline-alkali soil collection module is used to obtain the physical and chemical data of saline-alkali soils and accurately monitor the relationship between the degree of biochar degradation and the physical and chemical conditions of different saline-alkali soils;

[0060] The biochar degradation degree processing module is used to deduce the saline-alkali soil correlation and generate the degradation degree of biochar in different saline-alkali soils, so as to achieve the effect of monitoring the degradation degree of biochar, and provide key technical support for the sustainable improvement of saline-alkali soil by biochar;

[0061] The monitoring and evaluation module analyzes the physical and chemical data of saline-alkali soil, evaluates the biochar degradation results, and realizes the data output of the biochar degradation degree by the biochar degradation detection model;

[0062] The feedback execution module receives the biochar degradation results and takes corresponding measures.

[0063] The biochar degradation weight data is the consumption of biochar in saline-alkali soil at intervals of 24 hours. The acquisition process includes:

[0064] In order to ensure the accuracy of the subsequent calculation of biochar degradation through biochar consumption monitoring, a saline-alkali land test area was selected, and soil samples from n saline-alkali land test areas 24 hours ago were collected and dried to constant weight at 105 °C. The mass of the dried soil samples was recorded and recorded as m1;

[0065] After an interval of 24 hours, soil samples were collected from n saline-alkali land test areas and dried at 105°C to constant weight. The mass of the dried soil samples was recorded as m2.

[0066] The mass difference m1-m2 of the soil samples after drying at intervals of 24 hours was calculated to obtain the consumption M of biochar in the saline-alkali soil at intervals of 24 hours.

[0067] Monitoring the physical conditions of saline-alkali soil for biochar degradation. The physical data of saline-alkali soil are the soil bulk density and water content of saline-alkali soil in the saline-alkali land test area at intervals of 24 hours. The acquisition process includes:

[0068] The knife ring method was used, and the knife ring weight m and knife ring volume V were recorded. The knife ring was vertically pressed into the saline-alkali soil in the saline-alkali land test area 24 hours before and 24 hours later, so that the knife ring was filled with saline-alkali soil. The knife ring was dried at high temperature to constant weight, and weighed using a balance. The total weight M of the knife ring and the dried soil was recorded. Formula, to obtain the bulk density of saline-alkali soil before and after 24 hours;

[0069] A neutron meter was used to collect the water content of the saline-alkali soil 24 hours before and after 24 hours through the functional relationship between the density of the neutron cloud and water molecules.

[0070] Monitoring the chemical conditions of saline-alkali soil for biochar degradation. The chemical data of saline-alkali soil are the pH value and organic carbon content of saline-alkali soil in the saline-alkali land test area at intervals of 24 hours. The acquisition process includes:

[0071] A1. Collect n saline-alkali soil samples from the saline-alkali land test area 24 hours ago and n saline-alkali soil samples from the saline-alkali land test area 24 hours later, use a pH meter to measure the saline-alkali soil samples 24 hours ago and 24 hours later, and obtain the pH values ​​of the saline-alkali soil 24 hours ago and 24 hours later;

[0072] A2. Collect m0g of saline-alkali soil samples from the saline-alkali land test area n times 24 hours before and n times 24 hours after, and set up an experimental group and a control group. The experimental group is the saline-alkali soil samples collected before and after 24 hours, and the control group is the samples with only biochar;

[0073] A3. Dry and remove impurities in the saline-alkali soil samples, mix the experimental group samples and the control group samples with potassium dichromate-sulfuric acid solution to obtain the experimental group mixed solution and the control group mixed solution, and then heat the two groups of mixed solutions at 185°C to 190°C. After the two groups of mixed solutions are cooled to room temperature through redox reaction, the experimental group mixed solution and the control group mixed solution are respectively transferred to 100 ml volumetric flasks, and dilute to the volume scale of the volumetric flask with distilled water;

[0074] A4. Use a pipette to draw 20 ml of solution from a volumetric flask into a conical flask, add 5-10 drops of o-phenanthroline indicator, and titrate with ammonium ferrous sulfate standard solution. The solution color changes to brick red, which is the titration endpoint. Record the volume V of the ammonium ferrous sulfate standard solution consumed by the experimental group and the volume V0 of the ammonium ferrous sulfate standard solution consumed by the control group;

[0075] A5. Calculate the organic carbon content of the soil using the formula:

[0076]

[0077] Wherein, C is the organic carbon content of saline-alkali soil, V0 is the volume of ammonium ferrous sulfate standard solution consumed by saline-alkali soil samples without adding saline-alkali soil samples, V is the volume of ammonium ferrous sulfate standard solution consumed by saline-alkali soil samples, c is the concentration of ammonium ferrous sulfate standard solution, m0 is the weight of the saline-alkali soil sample weighed, and k0 is the multiple of fractionation.

[0078] The process of obtaining the correlation between soil bulk density, water content, pH value, organic carbon content and biochar degradation degree of saline-alkali soil using Pearson correlation coefficient includes:

[0079] Assuming soil bulk density as R, water content as H, pH value as Q, organic carbon content as P, biochar degradation degree as Y, sample number as n, the calculation formula of Pearson correlation coefficient is:

[0080]

[0081] in, is the Pearson correlation coefficient, specifically, and They are the Pearson correlation coefficient of soil bulk density, water content, pH value, and organic carbon content;

[0082] X 1i is the sample value of the i-th sample, specifically, R 1i , H 1i , Q 1i and P 1i are the soil bulk density, water content, pH value and organic carbon content of the i-th sample respectively;

[0083] is the average value of the sample value. Specifically, and are the average values ​​of soil bulk density, water content, pH value and organic carbon content respectively;

[0084] Y i is the consumption of biochar of the ith sample; is the average value of biochar consumption.

[0085] Using the correlation between the soil bulk density, water content, pH value, organic carbon content and biochar degradation degree of the above saline-alkali soil, the process of calculating the biochar degradation degree based on the weight coefficient method includes:

[0086] According to the Pearson correlation coefficient between the soil bulk density, water content, pH value, organic carbon content and biochar consumption of saline-alkali soil, the larger the Pearson correlation coefficient, the higher the correlation, the correlation between the soil bulk density, water content, pH value and organic carbon content of saline-alkali soil and the degree of biochar degradation is obtained, and the weight coefficients w1, w2, w3 and w4 are assigned to the soil bulk density, water content, pH value and organic carbon content of saline-alkali soil respectively;

[0087] Calculate the changes in soil bulk density, water content, pH value, and organic carbon content before and after 24 hours:

[0088] ΔR=R2-R1

[0089] ΔH=H2-H1

[0090] ΔQ=Q2-Q1

[0091] ΔP=P2-P1

[0092] Among them, ΔR, ΔH, ΔQ and ΔP respectively represent the changes in soil bulk density, water content, pH value and organic carbon content before and after 24 hours; R1 and R2 represent the soil bulk density before and after 24 hours; H1 and H2 represent the water content before and after 24 hours; Q1 and Q2 represent the pH value before and after 24 hours; P1 and P2 represent the organic carbon content before and after 24 hours;

[0093] Using the weight coefficient method, the process of calculating the degree of biochar degradation according to the weight coefficient includes:

[0094] ΔZ=w1×ΔR+w2×ΔH+w3×ΔQ+w4×ΔP

[0095] Among them, ΔZ is the degree of biochar degradation.

[0096] Using the random forest algorithm, the process of building a biochar degradation monitoring model includes:

[0097] The soil bulk density, water content, pH value, organic carbon content and corresponding biochar degradation degree of saline-alkali soil were used as a data set, and 80% of the data set was selected as a training set and 20% as a test set;

[0098] The random forest model is trained through the training set. According to the characteristics of soil bulk density, water content, pH value, organic carbon content and corresponding biochar degradation degree of saline-alkali soil, the relationship between soil bulk density, water content, pH value, organic carbon content and corresponding biochar degradation degree of saline-alkali soil is trained. The soil bulk density, water content, pH value and organic carbon content data of saline-alkali soil are input, and the random forest model outputs the corresponding biochar degradation degree.

[0099] The soil bulk density, moisture content, pH value, and organic carbon content of the saline-alkali soil in the test set were input into the trained random forest model, and the corresponding biochar degradation degree was output. The consistency between the biochar degradation degree corresponding to the actual saline-alkali soil data and the biochar degradation degree output by the test set was evaluated, and the model parameters were adjusted to optimize the random forest model to obtain the biochar degradation monitoring model.

[0100] The process of analyzing the physical and chemical data of saline-alkali soil, evaluating the biochar degradation results, and realizing the data output of the biochar degradation degree by the biochar degradation monitoring model includes:

[0101] The soil bulk density, water content, pH value and organic carbon content of saline-alkali soil were analyzed and combined with the biochar degradation monitoring model. When the biochar degradation degree ΔZ was between 0 and 0.2, the biochar degradation degree was low; when the biochar degradation degree ΔZ was between 0.2 and 0.5, the biochar degradation degree was medium; when the biochar degradation degree ΔZ was greater than 0.5, the biochar degradation degree was high, and the biochar degradation results were transmitted to the feedback execution module.

[0102] The feedback execution module receives the biochar degradation results and takes corresponding measures to deal with the process, including:

[0103] Receive biochar degradation results. When the biochar degradation level is low, continuously monitor saline-alkali soil data and its biochar degradation level, so that biochar can continue to play a role in saline-alkali soil improvement and crop quality and yield increase;

[0104] When the biochar degradation degree is moderate, the saline-alkali soil parameters are adjusted to increase the amount of biochar supplement according to the saline-alkali soil data;

[0105] When the degree of biochar degradation is high, a long-term saline-alkali soil monitoring system should be established, a biochar application plan should be formulated, and the amount of biochar supplement should be increased.

[0106] The application of biochar in saline-alkali soil improvement and crop quality and yield increase includes a memory and a processor. The memory stores executable code. When the executable code is executed by the processor, the processor executes the biochar saline-alkali soil improvement and crop quality and yield increase system.

[0107] Firstly, the drying mass measurement method was used to collect the biochar consumption in saline-alkali soil at intervals of 24 hours; the ring knife method was used to collect the soil bulk density data of saline-alkali soil; the neutron meter was used to collect the water content of saline-alkali soil; the pH value of saline-alkali soil was measured by a pH meter; the consumption of ammonium ferrous sulfate standard solution was measured by chemical oxidation-reduction reaction, and the organic carbon content of saline-alkali soil was calculated; then, the Pearson correlation coefficient was used to obtain the correlation between the soil bulk density, water content, pH value, organic carbon content and the degree of biochar degradation of saline-alkali soil, and then the weight coefficient method was used to calculate the biochar degradation rate. The degree of biochar degradation is measured, and then the random forest algorithm is used to construct a biochar degradation monitoring model; finally, the physical and chemical data of saline-alkali soil are analyzed to evaluate the biochar degradation results. When the degree of biochar degradation is low, the saline-alkali soil data and its biochar degradation degree are continuously monitored to ensure that biochar continues to play a role in saline-alkali soil improvement and crop quality improvement and yield increase; when the degree of biochar degradation is medium, the saline-alkali soil parameters are adjusted according to the saline-alkali soil data to increase the amount of biochar supplement; when the degree of biochar degradation is high, a long-term saline-alkali soil monitoring system is established, a biochar application plan is formulated, and the amount of biochar supplement is increased.

[0108] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions. The sentence "includes an element defined by ... does not exclude the existence of other identical elements in the process, method, article or device including the element".

[0109] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The application of biochar in saline-alkali soil improvement and crop quality and yield improvement is characterized by: It includes a biochar saline-alkali soil improvement and crop quality improvement and yield increase system, which is composed of a biochar degradation weight sensing module, a saline-alkali soil collection module, a biochar degradation degree processing module, a monitoring and evaluation module, and a feedback execution module, wherein the electrical signals between the modules are connected, and is characterized in that: The biochar degradation weight sensing module is used to obtain the biochar degradation weight data; The saline-alkali soil collection module is used to obtain physical data and chemical data of the saline-alkali soil; The biochar degradation degree processing module is divided into a saline-alkali soil data correlation derivation unit, a biochar degradation degree calculation unit and a biochar degradation monitoring model construction unit, wherein the saline-alkali soil data correlation derivation unit is used to obtain the correlation between the soil bulk density, water content, pH value, organic carbon content and the biochar degradation degree of the saline-alkali soil by using the Pearson correlation coefficient; the biochar degradation degree association unit calculates the biochar degradation degree based on the weight coefficient method; the biochar degradation monitoring model construction unit constructs a biochar degradation monitoring model by using a random forest algorithm; The monitoring and evaluation module analyzes the physical and chemical data of saline-alkali soil and evaluates the biochar degradation results; The feedback execution module receives the biochar degradation result and takes corresponding measures to deal with it.

2. The use of biochar in saline-alkali soil improvement and crop quality and yield improvement according to claim 1 is characterized by: The biochar degradation weight data is the consumption of biochar in saline-alkali soil at intervals of 24 hours, and the acquisition process includes: Select a saline-alkali land test area, collect soil samples from n saline-alkali land test areas 24 hours ago, dry them at 105℃ to constant weight, and record the mass of the dried soil samples, which is recorded as m1; After an interval of 24 hours, soil samples were collected from n saline-alkali land test areas and dried at 105°C to constant weight. The mass of the dried soil samples was recorded as m2. The mass difference m1-m2 of the soil samples after drying at intervals of 24 hours was calculated to obtain the consumption M of biochar in the saline-alkali soil at intervals of 24 hours.

3. The use of biochar in saline-alkali soil improvement and crop quality and yield improvement according to claim 2 is characterized by: The physical data of saline-alkali soil are the soil bulk density and water content of saline-alkali soil in the saline-alkali land test area at intervals of 24 hours, and the acquisition process includes: The knife ring method was used, and the knife ring weight m and knife ring volume V were recorded. The knife ring was vertically pressed into the saline-alkali soil in the saline-alkali land test area 24 hours before and 24 hours later, so that the knife ring was filled with saline-alkali soil. The knife ring was dried at high temperature to constant weight, and weighed using a balance. The total weight M of the knife ring and the dried soil was recorded. Formula, to obtain the bulk density of saline-alkali soil before and after 24 hours; A neutron meter was used to collect the water content of the saline-alkali soil 24 hours before and after 24 hours through the functional relationship between the density of the neutron cloud and water molecules.

4. The use of biochar in saline-alkali soil improvement and crop quality and yield improvement according to claim 3 is characterized by: The chemical data of the saline-alkali soil are the pH value and organic carbon content of the saline-alkali soil in the saline-alkali land test area at intervals of 24 hours, and the acquisition process includes: A1. Collect n saline-alkali soil samples from the saline-alkali land test area 24 hours ago and n saline-alkali soil samples from the saline-alkali land test area 24 hours later, use a pH meter to measure the saline-alkali soil samples 24 hours ago and 24 hours later, and obtain the pH values ​​of the saline-alkali soil 24 hours ago and 24 hours later; A2. Collect m0g of saline-alkali soil samples from the saline-alkali land test area n times 24 hours before and n times 24 hours after, and set up an experimental group and a control group. The experimental group is the saline-alkali soil samples collected before and after 24 hours, and the control group is the samples with only biochar; A3. Dry and remove impurities in the saline-alkali soil samples, mix the experimental group samples and the control group samples with potassium dichromate-sulfuric acid solution to obtain the experimental group mixed solution and the control group mixed solution, and then heat the two groups of mixed solutions at 185°C to 190°C. After the two groups of mixed solutions are cooled to room temperature through redox reaction, the experimental group mixed solution and the control group mixed solution are respectively transferred to 100 ml volumetric flasks, and dilute to the volume scale of the volumetric flask with distilled water; A4. Use a pipette to draw 20 ml of solution from a volumetric flask into a conical flask, add 5-10 drops of o-phenanthroline indicator, and titrate with ammonium ferrous sulfate standard solution. The solution color changes to brick red, which is the titration endpoint. Record the volume V of the ammonium ferrous sulfate standard solution consumed by the experimental group and the volume V0 of the ammonium ferrous sulfate standard solution consumed by the control group; A5. Calculate the organic carbon content of the soil using the formula: Wherein, C is the organic carbon content of saline-alkali soil, V0 is the volume of ammonium ferrous sulfate standard solution consumed by saline-alkali soil samples without adding saline-alkali soil samples, V is the volume of ammonium ferrous sulfate standard solution consumed by saline-alkali soil samples, c is the concentration of ammonium ferrous sulfate standard solution, m0 is the weight of the saline-alkali soil sample weighed, and k0 is the multiple of fractionation.

5. The use of biochar in saline-alkali soil improvement and crop quality and yield improvement according to claim 4 is characterized by: The process of the saline-alkali soil data correlation derivation unit for obtaining the correlation between the soil bulk density, water content, pH value, organic carbon content and biochar degradation degree of the saline-alkali soil by using the Pearson correlation coefficient includes: Assuming soil bulk density as R, water content as H, pH value as Q, organic carbon content as P, biochar degradation degree as Y, sample number as n, the calculation formula of Pearson correlation coefficient is: in, is the Pearson correlation coefficient, specifically, and They are the Pearson correlation coefficient of soil bulk density, water content, pH value, and organic carbon content; X 1i is the sample value of the i-th sample, specifically, R 1i , H 1i , Q 1i and P 1i are the soil bulk density, water content, pH value and organic carbon content of the i-th sample respectively; is the average value of the sample value. Specifically, and are the average values ​​of soil bulk density, water content, pH value and organic carbon content respectively; Y i is the consumption of biochar of the ith sample; is the average value of biochar consumption.

6. The use of biochar in saline-alkali soil improvement and crop quality and yield improvement according to claim 5, characterized in that: The biochar degradation degree correlation unit calculates the biochar degradation degree based on the weight coefficient method, and the process includes: According to the Pearson correlation coefficient between the soil bulk density, water content, pH value, organic carbon content and biochar consumption of saline-alkali soil, the larger the Pearson correlation coefficient, the higher the correlation, the correlation between the soil bulk density, water content, pH value and organic carbon content of saline-alkali soil and the degree of biochar degradation is obtained, and the weight coefficients w1, w2, w3 and w4 are assigned to the soil bulk density, water content, pH value and organic carbon content of saline-alkali soil respectively; Calculate the changes in soil bulk density, water content, pH value, and organic carbon content before and after 24 hours: ΔR=R2-R1 ΔH=H2-H1 ΔQ=Q2-Q1 ΔP=P2-P1 Among them, ΔR, ΔH, ΔQ and ΔP respectively represent the changes in soil bulk density, water content, pH value and organic carbon content before and after 24 hours; R1 and R2 represent the soil bulk density before and after 24 hours; H1 and H2 represent the water content before and after 24 hours; Q1 and Q2 represent the pH value before and after 24 hours; P1 and P2 represent the organic carbon content before and after 24 hours; Using the weight coefficient method, the process of calculating the degree of biochar degradation according to the weight coefficient includes: ΔZ=w1×ΔR+w2×ΔH+w3×ΔQ+w4×ΔP Among them, ΔZ is the degree of biochar degradation.

7. The use of biochar in saline-alkali soil improvement and crop quality and yield improvement according to claim 6, characterized in that: The biochar degradation monitoring model construction unit uses a random forest algorithm to construct a biochar degradation monitoring model, and the process includes: The soil bulk density, water content, pH value, organic carbon content and corresponding biochar degradation degree of saline-alkali soil were used as a data set, and 80% of the data set was selected as a training set and 20% as a test set; The random forest model is trained through the training set. According to the characteristics of soil bulk density, water content, pH value, organic carbon content and corresponding biochar degradation degree of saline-alkali soil, the relationship between soil bulk density, water content, pH value, organic carbon content and corresponding biochar degradation degree of saline-alkali soil is trained. The soil bulk density, water content, pH value and organic carbon content data of saline-alkali soil are input, and the random forest model outputs the corresponding biochar degradation degree. The soil bulk density, moisture content, pH value, and organic carbon content of the saline-alkali soil in the test set were input into the trained random forest model, and the corresponding biochar degradation degree was output. The consistency between the biochar degradation degree corresponding to the actual saline-alkali soil data and the biochar degradation degree output by the test set was evaluated, and the model parameters were adjusted to optimize the random forest model to obtain the biochar degradation monitoring model.

8. The use of biochar in saline-alkali soil improvement and crop quality and yield improvement according to claim 7, characterized in that: The monitoring and evaluation module analyzes the physical and chemical data of saline-alkali soil and evaluates the biochar degradation results, including: The soil bulk density, water content, pH value and organic carbon content of saline-alkali soil were analyzed and combined with the biochar degradation monitoring model. When the biochar degradation degree ΔZ was between 0 and 0.2, the biochar degradation degree was low; when the biochar degradation degree ΔZ was between 0.2 and 0.5, the biochar degradation degree was medium; when the biochar degradation degree ΔZ was greater than 0.5, the biochar degradation degree was high, and the biochar degradation results were transmitted to the feedback execution module.

9. The use of biochar in saline-alkali soil improvement and crop quality and yield improvement according to claim 8, characterized in that: The feedback execution module receives the biochar degradation result and takes corresponding measures to deal with it, including: Receive the results of biochar degradation. When the biochar degradation degree is low, continuously monitor the saline-alkali soil data and its biochar degradation degree, so that biochar can continue to play a role in saline-alkali soil improvement and crop quality and yield increase. When the biochar degradation degree is medium, adjust the saline-alkali soil parameters according to the saline-alkali soil data to increase the amount of biochar supplement. When the biochar degradation degree is high, establish a long-term saline-alkali soil monitoring system, formulate a biochar application plan, and increase the amount of biochar supplement.

10. The use of biochar in saline-alkali soil improvement and crop quality and yield improvement according to claim 9, characterized in that: It includes a memory and a processor, wherein the memory stores executable code, and when the executable code is executed by the processor, the processor executes the biochar saline-alkali soil improvement and crop quality and yield increase system as described in any one of Claims 1 to 9.

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