Soil improvement effect analysis method and application

Abstract

The invention is applicable to the technical field of soil improvement, and provides a soil improvement effect analysis method and application, and the method comprises the following steps: after soil improvement is completed, collecting layered soil samples, determining the content of soil dissolved organic carbon, the relative molecular weight, aromaticity and maximum fluorescence intensity of soil dissolved organic matters, and identifying all organic components; constructing a partial least square path model of different soil depths, biochar addition proportions and biogas slurry retention and leaching loss of soluble organic matters; according to an operation result of the partial least square path model, explaining a regulation and control process and an improvement effect of the biochar addition proportion and biogas slurry replacement chemical fertilizer dressing on each component of the soil soluble organic matter. The method can systematically reveal an influence mechanism of improvement measures on soil carbon library stability, nutrient circulation and environmental risks, breaks through the limitation of traditional single index analysis, provides a data-driven decision model for optimizing a soil improvement scheme, and has important significance for improving soil quality and realizing agricultural green development.

Description

Technical Field

[0001] The present application belongs to the field of soil improvement technology, and in particular relates to a soil improvement effect analysis method and application. Background Art

[0002] Soils are a central hub of the Earth's carbon (C) cycle, holding approximately three times the atmospheric carbon reserve. They are also key contributors to soil health and the maintenance of numerous ecosystem services. Soil dissolved organic matter (DOM), one of the most mobile and active soil C reservoirs, has garnered significant attention due to its irreplaceable role in the global C cycle and its potentially profound impact. Furthermore, soil DOM determines the elemental cycling of C, nitrogen (N), phosphorus (P), and sulfur (S), microbial growth, development, and metabolism, and acts as an electron donor in numerous redox reactions. Furthermore, due to its complexity and diversity, soil DOM is more sensitive than total organic matter in determining soil biological activity, assessing soil quality, and its migration and transformation. Studies have also highlighted the potential of using the optical properties of DOM as a proxy for soil organic matter to assess its persistence. Therefore, elucidating the composition, transformation, and migration mechanisms of soil DOM is crucial for revealing the microscopic processes of soil C cycling and assessing its ecological effects.

[0003] Biochar, a carbon-rich material produced by pyrolyzing biomass under oxygen-limited conditions, is widely used in agricultural production to increase soil carbon stocks, improve soil structure and multifunctionality, and contribute to greenhouse gas emissions reduction and crop productivity improvement. The majority of biochar dissolved in soil, as well as its most active and critical component, is DOM. Its composition and properties are the most direct indicators of biochar application effectiveness. While releasing its own DOM, biochar's porous structure and abundant surface functional groups can adsorb and transform soil DOM, exerting a continuous and complex influence on soil DOM retention and leaching. In agricultural production, irrigation and rainfall are the primary and direct drivers of soil DOM release and migration. Fertilizer perturbations on soil microorganisms, nutrients, and the redox environment inevitably modulate DOM dynamics. Furthermore, water-fertilizer strategies (WFS) can directly or indirectly regulate the aromaticity, humus, and molecular weight of DOM leached from biochar. Biogas slurry, as an unconventional water and organic fertilizer source, is more aligned with the concepts of a circular economy and sustainable agricultural development. It contains rich nutrients and DOM components and contributes to soil carbon cycle turnover. Furthermore, the infiltration and migration process of biogas slurry differs from that of conventional chemical fertilizer strategies (CFS), and the addition of different biochars (BA) modulates the infiltration rate and attenuation rate due to differences in the number of adsorption sites, significantly affecting the water-borne behavior of DOM in soil. However, the extent to which biochar at different WFSs influences the migration and behavior of soil DOM requires further analysis and discussion.

[0004] As soils are stratified structures, the downward migration of DOM is accompanied by the remodeling of soil and leachate DOM. However, little is known about the vertical changes in soil DOM driven by DOM migration with water, and existing research often overlooks the behavior and patterns of DOM infiltration. Given the increasing intensity of agricultural production and the combined application of various strategies, such as biochar and biogas slurry, which have exacerbated the complexity and uncertainty of soil DOM composition and migration characteristics, it is necessary to investigate the interaction between BA and WFS on the leaching behavior of DOM and the vertical retention patterns in soils. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to provide a method for analyzing soil improvement effects, aiming to fill the research gap in the prior art on the leaching behavior of DOM and the vertical retention law in soil by the interaction between BA and WFS.

[0006] The embodiment of the present application is implemented as follows: a soil improvement effect analysis method, comprising:

[0007] After the soil improvement is completed, soil samples are collected and the soil dissolved organic carbon content, relative molecular weight, aromaticity, maximum fluorescence intensity of soil dissolved organic matter are measured, and each organic component is identified; the soil samples include at least surface soil and deep soil;

[0008] The plspm package in R software was used to construct a partial least squares path model for the effects of different soil depths, biochar addition rates, and biogas slurry on dissolved organic matter retention and leaching. The model was successfully established when both the biochar addition rate and biogas slurry significantly regulated the soil dissolved organic matter components and the goodness of fit (GOF) was greater than 0.5.

[0009] Based on the calculation results of the partial least squares path model, the regulation process and improvement effect of the biochar addition ratio and the application of biogas slurry instead of chemical fertilizer on the various components of soil dissolved organic matter were explained.

[0010] Preferably, the soil improvement method comprises:

[0011] Collect soil samples from different soil layers from top to bottom, measure the dissolved organic carbon content, relative molecular weight, aromaticity, and maximum fluorescence intensity of dissolved organic matter in each soil layer, and identify each organic component; the soil samples include at least surface soil and deep soil;

[0012] When the dissolved organic carbon content and the relative molecular weight of dissolved organic matter in the surface soil are lower than those in the deep soil, and the aromaticity and maximum fluorescence intensity are lower than those in the deep soil, and the organic components mainly exist in the form of humus-like substances, biochar is applied to the soil at a rate of 2-6% of the mass of the surface soil before sowing crops, and the soil is plowed to fully mix it with the biochar; at the same time, during the peak water and fertilizer demand periods of the crops, biogas slurry is used instead of chemical fertilizers with an equal amount of nitrogen for topdressing to complete soil improvement.

[0013] Another object of the embodiments of the present application is to apply the above-mentioned soil improvement effect analysis method to reduce the leaching of soil dissolved organic matter.

[0014] The embodiment of the present application provides a method for analyzing the effect of soil improvement based on multi-dimensional DOM characterization technology and partial least squares path model. By measuring the organic carbon content, relative molecular weight, aromaticity, fluorescent components and other parameters of DOM in soil at different depths, combined with the partial least squares path model to quantify the regulatory pathways of biochar addition ratio and biogas slurry topdressing on DOM retention and leaching, it can systematically reveal the impact mechanism of improvement measures on soil carbon pool stability, nutrient cycling and environmental risks. The method of the present application breaks through the limitations of traditional single indicator analysis and provides a data-driven decision-making model for optimizing soil improvement schemes (such as biochar application amount and biogas slurry replacement ratio). It is of great significance to improving soil quality, reducing non-point source pollution and achieving green agricultural development. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of the soil column test design provided in the examples of this application (a), as well as the organic components (b), UV-Vis index (c), and EEM index (d) of the water-fertilizer solution of CFS and BSS and the biochar extract;

[0016] Figure 2 The DOC concentration of each leachate in CFS (a) and BSS (b) provided in the examples of this application;

[0017] Figure 3 The UV-Vis index SUVA254 (a), SR (b), E2 / E3 (c) and A253 / A203 (d) and EEM index FI (e), β:α (f), BIX (g) and HIX (h) of each leachate DOM in CFS and BSS provided in the examples of the present application;

[0018] Figure 4 The four organic components of DOM screened by the PARAFAC model provided in the examples of this application (a) and the corresponding excitation / emission loads of each component (b), as well as the Fmax of DOM in each leachate in CFS and BSS (c) and the proportion of each organic component (d);

[0019] Figure 5 The DOC concentration (a) of each soil layer and the proportion of DOC content in each soil layer in the fertilizer strategy (b) and biogas slurry strategy (c) provided in the examples of this application;

[0020] Figure 6 The UV-Vis index SUVA of soil DOM in each soil layer in the fertilizer strategy and biogas slurry strategy provided in the embodiment of this application is 254 (a) S R (b), E2 / E3 (c) and A253 / A203 (d), as well as EEM index FI (e), β:α (f), BIX (g) and HIX (h) indices, where the light blue background on the left and the light purple background on the right represent the fertilizer strategy and biogas slurry strategy, respectively;

[0021] Figure 7 The five organic components of DOM (a) and their corresponding excitation / emission loads (b) screened by the parallel factor analysis model provided in the embodiment of the present application, the F in the initial soil extract before the experiment max and organic fraction (c), and the F of soil DOM in the fertilizer strategy and biogas slurry strategy max (d) and the proportion of its various organic components (e);

[0022] Figure 8 Principal component analysis of DOM parameters of leachate (a, b, e) and soil extract (c, d, f) in CFS (a, c) and BSS (b, d) provided in the examples of this application, as well as the corresponding values ​​under 1-axis and 2-axis conditions and significance analysis under the same conditions (e, f);

[0023] Figure 9 Correlation analysis between various DOM indicators in leachate (a) and soil extract (b) in CFS and BSS provided in the examples of this application;

[0024] Figure 10 The partial least squares path model provided for the embodiments of the present application reveals the causal relationship between the various DOM parameters in the leachate (a) and the soil extract (b), as well as the impact mechanism between each leachate on the soil extract of each soil layer (c); wherein the red and blue lines represent positive and negative significant effects, respectively, the numbers on the lines represent the path coefficients, and R2 is the degree of variance explained by the PLSPM model for each parameter. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0026] The present invention provides a method for analyzing soil improvement effects, which includes:

[0027] After the soil improvement is completed, soil samples are collected and the soil dissolved organic carbon content, relative molecular weight, aromaticity, maximum fluorescence intensity of soil dissolved organic matter are measured, and each organic component is identified; the soil samples include at least surface soil and deep soil;

[0028] The plspm package in R software was used to construct a partial least squares path model for the effects of different soil depths, biochar addition rates, and biogas slurry on dissolved organic matter retention and leaching. The model was successfully established when both the biochar addition rate and biogas slurry significantly regulated the soil dissolved organic matter components and the goodness of fit (GOF) was greater than 0.5.

[0029] Based on the calculation results of the partial least squares path model, the regulation process and improvement effect of the biochar addition ratio and the application of biogas slurry instead of chemical fertilizer on the various components of soil dissolved organic matter were explained.

[0030] Preferably, in order to solve the problems of existing soil improvement methods such as cumbersome operation, easy nutrient leaching, eutrophication of water bodies, destruction of soil structure, reduced soil aeration and water permeability, and potential threats to the soil ecological environment, the present application proposes a soil improvement method, including:

[0031] Collect soil samples from different soil layers from top to bottom, measure the dissolved organic carbon content, relative molecular weight, aromaticity, and maximum fluorescence intensity of dissolved organic matter in each soil layer, and identify each organic component; the soil samples include at least surface soil and deep soil;

[0032] When the dissolved organic carbon content and the relative molecular weight of dissolved organic matter in the surface soil are lower than those in the deep soil, and the aromaticity and maximum fluorescence intensity are lower than those in the deep soil, and the organic components mainly exist in the form of humus-like substances, biochar is applied to the soil at a rate of 2-6% of the mass of the surface soil before sowing crops, and the soil is plowed to fully mix it with the biochar; at the same time, during the peak water and fertilizer demand periods of the crops, biogas slurry is used instead of chemical fertilizers with an equal amount of nitrogen for topdressing, and the volume ratio of biogas slurry to water is controlled to be no higher than 1:4 to complete soil improvement.

[0033] This application determines the amount of biochar to be added before crop sowing through the dissolved organic carbon content in soil samples of different depths, the relative molecular weight, aromaticity and maximum fluorescence intensity of soil dissolved organic matter, and then uses biogas slurry for topdressing during the peak water and fertilizer demand periods of crops to complete soil improvement. This application can optimize the distribution and migration of soil dissolved organic matter, improve soil quality, promote crop growth, and reduce potential risks to the environment, thereby achieving safe and efficient soil improvement, simply by determining to change the water and fertilizer strategy pattern and accurately adjusting the addition ratio of biochar. In addition, this application adjusts the traditional chemical fertilizer strategy to a biogas slurry strategy, which increases the DOC content of each soil layer while also increasing the proportion of surface soil in the DOC content of all soil layers, and the biogas slurry strategy also increases F max , optimized the proportion of various organic components in soil DOM, ensured the efficiency of soil microbial activity, and improved soil quality and nutrient supply capacity.

[0034] Optionally, the dissolved organic carbon content, relative molecular weight, aromaticity, and maximum fluorescence intensity of soil dissolved organic matter in soil samples of each soil layer are measured and each organic component is identified, including:

[0035] Soil from each soil layer was extracted by mixing it with ultrapure water at a mass-to-volume ratio of 1:5 in a thermostatic oscillator at 30°C and 180 rpm for 40 minutes. The extracts were then centrifuged at 6000 rpm and 25°C for 10 minutes. The supernatant was then filtered through a 0.45 μm filter membrane to obtain the soil extracts corresponding to each soil layer. The dissolved organic carbon content in each soil extract was determined using a total organic carbon analyzer.

[0036] Using ultrapure water as a control, a UV-visible spectrophotometer was used to scan the photometric values ​​of ultrapure water and each soil extract in the range of 190-400 nm. The ratio of the absorbance at 254 nm to the dissolved organic carbon concentration was calculated to characterize the aromaticity of the soil dissolved organic matter. The relative molecular weight of the soil dissolved organic matter was characterized by the spectral slope ratio of the slope in the 275-295 nm region divided by the slope in the 350-400 nm region.

[0037] The three-dimensional fluorescence spectra of each soil extract were measured using a fluorescence spectrometer, and the fluorescence index, freshness index, humification index, and autogenic index were calculated. At the same time, the data of the three-dimensional fluorescence spectrum were combined with parallel factor analysis to identify the maximum fluorescence intensity value.

[0038] Alternatively, the biochar is produced by pyrolysis of corn straw at 450°C for 2h, and its total C, total N and specific surface area are 43.4%, 1.17% and 342.3m respectively. 2 / g.

[0039] Optionally, the biogas slurry is produced by anaerobic fermentation of organic waste, and its TC, TN, TP, TK and DOC contents are 16.13 g / L, 2.66 g / L, 165 mg / L, 2.79 g / L and 3.36 g / L, respectively.

[0040] Preferably, the soil sample includes surface soil with a thickness of 0-10 cm from top to bottom and deep soil covering at least one layer, such as 10-20 cm.

[0041] Preferably, when the dissolved organic carbon content and the relative molecular weight of dissolved organic matter in the surface soil are smaller than those in the deep soil, and the aromaticity and maximum fluorescence intensity are lower than those in the deep soil, and the organic components exist in the form of humus-like substances, biochar is applied to the soil at a concentration of 6% of the mass of the surface soil before sowing crops, and the soil is plowed to fully mix it with the biochar.

[0042] Optionally, the amount of biogas slurry required for each topdressing is calculated based on the nitrogen content of each topdressing in a traditional chemical fertilizer mode combined with nutrients in the biogas slurry.

[0043] The embodiments of the present application also provide an application of the above-mentioned soil improvement effect analysis method in reducing the leaching loss of soil dissolved organic matter.

[0044] The following is a detailed description of the soil improvement effect analysis method and its application in the present application using specific examples, as shown below. The experimental methods used in the following examples are conventional methods unless otherwise specified; the materials and reagents used are all commercially available unless otherwise specified.

[0045] 1. Materials and Methods

[0046] 1.1 Implementation Example Design

[0047] The test equipment is made of acrylic material with dimensions of 0.5 × 10 × 60 cm (wall thickness × inner diameter × height). A valve is installed on the bottom plate to collect leachate. Vaseline is evenly coated on the inner wall of the organic glass column to reduce the pipe wall effect. At the same time, the soil is compacted every 2 cm to control the bulk density. From the top of the organic glass column downward, the soil bulk density of each soil layer is shown in the figure. Figure 1a. The water-fertilizer strategy (WFS) of the experiment includes the traditional chemical fertilizer strategy (CFS) and the biogas slurry strategy (BSS). At the same time, 0, 2, 4 and 6% BA (C0, C2, C4 and C6, respectively) were set at the top layer of soil, for a total of 8 treatments, and each treatment was repeated 3 times. First, pure irrigation water was added to the plexiglass column to make each soil layer reach the field supersaturation level of the soil and stabilize for 2 days. Then, a uniformly mixed water and fertilizer solution was added to the plexiglass column every 5 days (a total of 3 cycles). The experiment was ended on the 10th day after the last addition of the water and fertilizer solution. Before adding the next water and fertilizer solution, the valve was opened to collect the leachate, and a total of 4 collections were made (initial saturated liquid + 3 times of water and fertilizer leachate). After the experiment, the soil of each soil layer was collected and further analysis and measurement were carried out.

[0048] 1.2 Nutrient content of water and fertilizer injection

[0049] Based on the field experiments conducted, we selected the total amount of water and fertilizer applied per unit area equivalent to that in the field experiments. During the experiment, the amount of water and fertilizer solution added to each soil column was 172 mL each time, containing 117.8 mg of pure N. At the same time, we supplemented the PK content of CFS with superphosphate (P2O5 content of 12%) and potassium sulfate (K2O content of 52%) according to the PK content in BSS to ensure that the total amount of NPK in the two water and fertilizer strategies remained consistent.

[0050] 1.3 Basic properties of soil, biochar and biogas slurry

[0051] The experimental soil was obtained from the normally cultivated topsoil (0-20 cm) at the Field Observation and Experimental Station of the Chinese Academy of Agricultural Sciences in Shouyang County, Shanxi Province, and air-dried after passing through a 2.50 mm sieve. The biochar was produced by pyrolysis of corn straw at 450°C for 2 hours. Its total carbon, total nitrogen, and specific surface area were 43.4%, 1.17%, and 342.3 m2 / g, respectively. The biogas slurry used in the experiment was derived from anaerobic fermentation of waste streams such as cow dung and cow urine. Its TC, TN, TP, TK, and DOC contents were 16.13 g / L, 2.66 g / L, 165 mg / L, 2.79 g / L, and 3.36 g / L, respectively.

[0052] 1.4 Extraction of DOM (soil dissolved organic matter) and determination of DOC (dissolved organic carbon)

[0053] Soil and ultrapure water were extracted in a constant temperature oscillator at a ratio of 1:5 (W / V) at 30°C and 180 rpm for 40 min, and then centrifuged at 6000 r / min at 25°C for 10 min. The supernatant was then filtered through a 0.45 μm glass fiber filter to obtain the soil extract; the clear light brown leachate was directly filtered through a 0.45 μm glass fiber filter. The DOC content in the soil extract and leachate was determined using a TOC analyzer (Shimadzu, TOC-VCPH, Japan).

[0054] 1.5 UV-Vis Spectroscopy

[0055] A UV-Vis spectrophotometer (UV-1901, Persee General, China) was used to scan the 190-400 nm range at a 1 nm scan interval, using up-water as a blank. UV-Vis parameters were calculated: the ratio of absorbance at 254 nm (Abs) to DOC concentration (SUVA254) characterizes the aromaticity of DOC; the spectral slope ratio (SR), expressed as the slope of the 275-295 nm region divided by the slope of the 350-400 nm region, indicates the relative molecular weight of DOM; E2 / E3 and A253 / A203, the ratios of Abs at wavelengths of 250 nm to 365 nm and 253 nm to 203 nm, respectively, indicate the organic matter source (<3.5 and >3.5 reflect the absorption characteristics of humic acid and fulvic acid, respectively) and the degree of substitution on the aromatic ring.

[0056] 1.6 Three-dimensional fluorescence spectroscopy

[0057] An EEM instrument (RF-6000, Shimadzu, Japan) was used to measure the excitation wavelength (Ex) and fluorescence emission wavelength (Em) of the samples. The excitation wavelength range (Ex) was 200–550 nm, and the fluorescence emission wavelength (Em) range was 250–600 nm. The scanning intervals were 5 nm and 2 nm, respectively, and the scanning speed was set to 2000 nm / min. The fluorescence index (FI), freshness index (β:α), humification index (HIX), and biological index (BIX) were calculated.

[0058] 1.7 Parallel Factor Modeling and Regional Integration Method

[0059] We modeled 96 samples of leachate and 99 samples of soil extract (including original soil samples) separately. We first used the DOMfluor toolbox in Matlab2021a to subtract blanks and clean Rayleigh scattering, perform core consistency diagnostics, split-half validation, and explanation rate, and then determine the maximum fluorescence intensity (Fmax) value to represent the relative intensity of a single component. Finally, the results of the PARAFAC model obtained in this study were compared with previously published and validated PARAFAC models in the OpenFluor database to identify each organic component. In addition, the fluorescence regional integral method (FRI) was used to identify five organic components in the two input water fertilizer solutions and biochar extracts.

[0060] 1.8 Statistical analysis

[0061] Data were analyzed using one-way ANOVA and Duncan's multiple range test in SPSS 27.0 to determine statistically significant differences (P < 0.05) for each parameter. Multivariate ANOVA was performed, denoting the number of leachate events, soil depth, WFS, and BA ratio as T, F, B, and D, respectively. After standardizing each parameter using StandardScaler, principal component analysis (PCA) was performed on leachate and soil DOM under the two WFS conditions. A partial least squares path model (PLSPM) was constructed using the "plspm" package in R4.4.1 to assess the direct and indirect effects of water and fertilizer strategies and biochar gradients on various DOM characteristics in leachate and soil extracts. The PLSPM model was used to reveal the causal relationship between leachate and soil extracts. PCA and correlation analysis were performed using Origin 2024, and correlation plots were drawn. CFS and BSS are represented in light blue and light purple.

[0062] 2. Test results

[0063] 2.1 Spectral properties of two water-fertilizer solutions and biochar extract

[0064] Through FRI analysis, we can conclude that the total FRI intensity of BSS input solution and biochar extract is 21.15 times and 6.96 times that of CFS input water fertilizer solution, respectively ( Figure 1bd). Furthermore, the proportion of humic acids in the BSS input solution was 3.11 times that of the CFS input solution. The biochar extract had higher proportions of protein II, fulvic acids, and soluble microbial byproducts compared to the CFS input solution. The UV-Vis indices of the biochar extract were generally intermediate between those of the BSS and CFS input solutions. The SUVA254 and A253 / A203 ratios of the CFS input solution were both close to 0. The SR and E2 / E3 ratios of the BSS input solution were 36.93% and 15.12% lower, respectively, than those of the CFS input solution. Furthermore, the HIX index was higher in the BSS input solution, while the β:α and BIX indices were lower. The EEM indices of the BSS input solution and the biochar extract were similar.

[0065] 2.2 DOM concentration and characteristics of leachate

[0066] 2.2.1. Leachate DOC concentration

[0067] Different times of leachate, WFS, BA and their interactions all have a significant effect on the DOC concentration of the leachate ( Figure 2 BA increased the DOC concentration of the initial leachate by 4.41-20.06%, while the DOC concentration of the second leachate in CFS and BSS decreased (45.26-50.32%) and increased (11.93-152.30%), respectively. In both WFS, the DOC concentration of the third leachate in C6 treatment increased significantly compared with that in C0 treatment, while that in C2 treatment decreased. BA treatment increased the DOC concentration of the fourth leachate in both CFS and BSS, with the largest increase in C2 treatment (41.89% and 182.06%), followed by C4 treatment (37.03% and 35.46%). In addition, in the second to fourth leachates, the DOC concentration of BSS was generally increased compared with that in CFS at the same BA level, and only the DOC concentration of the second leachate in C0 treatment decreased.

[0068] UV-Vis and EEM indices of leachate DOM

[0069] Different times of leachate, WFS, BA and their interactions generally have significant effects on the UV-Vis and EEM indices of leachate DOM ( Figure 3ah). BA treatment increased SUVA254 (20.85%), SR (71.08%), A253 / A203 (58.38%), FI (1.06%), β:α (7.95%), and BIX (8.68%) in the initial leachate, while decreasing E2 / E3 (31.35%) and HIX (5.54%). With increasing leachate times, SUVA254 showed a decrease-stable trend in the C0 and C2 treatments of both WFSs, a decrease-stable-increase trend in the C6 treatment, and a decrease-stable-increase trend in the CFS and BSS treatments, respectively. Compared with the initial leachate, the β:α and BIX of the 2nd-4th leachates of both WFSs decreased, while the E2 / E3, A253 / A203, and HIX indices increased.

[0070] BA treatment increased the SUVA254 and E2 / E3 index of the second leachate by an average of 82.24% and 46.71%, respectively ( Figure 3 ah), while in BSS they decreased by an average of 26.28% and 13.81%, respectively. BA also reduced the SR index by 37.83% in CFS and 18.25% in BSS. In the third leachate, BA increased and decreased SR and E2 / E3 in both WFSs, respectively. Compared with the C0 treatment, SUVA254 was increased and decreased in the C2 and C6 treatments, respectively. In the fourth leachate from both WFSs, SUVA254, SR, and A253 / A203 were significantly decreased in the C2 treatment compared to the C0 treatment, while E2 / E3 was significantly increased. The C6 treatment in BSS had the opposite effect on these four parameters. BA contributed to the increase in β:α and BIX in the second leachate from both WFSs, but decreased them in the third and fourth leachates from BSS. The leachate from the 2nd to the 4th time showed a significant decrease in all BA treatments of CFS and C2 and C4 treatments of BSS compared with the C0 treatment in HIX, while the C6 treatment in BSS showed a significant increase, with an average increase of 2.98% over the three treatments.

[0071] 2.2.3. Organic components of leachate

[0072] Four organic components of leachate DOM were identified by EEM-PARAFAC model ( Figure 4ad), using the OpenFlour online database to compare with available fluorescent components in the literature, LC1, LC2, and LC3 can all be classified as terrestrial humic components, and LC4 can be identified as a protein and tryptophan substance. BA in the initial leachate reduced the relative percentages of LC1 and LC2 by 6.96% and 6.45%, respectively, while the relative percentage of LC4 increased by an average of 13.11%. The 2nd to 4th leachates were compared with the initial leachate F max The concentrations of LC1 and LC2 components decreased in the CFS and increased in the third and fourth leachates of the BSS. The proportions of LC1 and LC2 components remained stable across all leachates, while the proportion of LC3 was almost zero in the initial leachate. The Fmax increase in the BSS relative to the CFS gradually increased with increasing leachate number, reaching 1.86%, 9.65%, and 13.67% in leachates from leachates 2-4, respectively. In the CFS, the proportion of LC4 generally increased with increasing BA proportions in leachates from 2-4, while in the BSS, the proportion of LC4 initially increased and then decreased with increasing BA proportions.

[0073] 3.3 Soil DOM content and characteristics

[0074] 3.3.1 Soil DOC concentration and DOC content ratio in each soil layer

[0075] Soil DOC concentration was significantly affected by soil depth, water and fertilizer strategy, biochar addition, and their interactions ( Figure 5Compared with the pre-experimental level, the soil DOC concentrations in the 0-10 cm soil layer of the C0, C2, and C4 treatments in the chemical fertilizer strategy decreased, while the C0 treatment only slightly increased in the 20-30 cm soil layer. In the biogas slurry strategy, the soil DOC concentrations in all soil layers and treatments were higher than those before the experiment. In the chemical fertilizer strategy, the addition of biochar increased the DOC concentration in the 0-10cm, 10-20cm, 20-30cm and 30-40cm soil layers by 46.80-172.62%, 25.38-157.78%, 17.93%-125.06% and 48.80-193.84%, respectively; in the sludge strategy, the addition of biochar significantly increased the DOC concentration in the 0-10cm and 10-20cm depths by 14.77-24.44% and 55.34-80.99%, respectively. At the 20-30cm and 30-40cm depths, the C2 treatment increased significantly by 22.91% and 10.79%, respectively, compared with the C0 treatment. At the 30-40cm depth, the C4 and C6 treatments decreased significantly by 19.30-22.76% compared with the C0 treatment. The order of DOC content in each soil layer in the chemical fertilizer strategy is 20-30cm>30-40cm>10-20cm>0-10cm, while in the biogas slurry strategy it is 0-10cm>30-40cm>20-30cm>10-20cm.

[0076] 3.3.2 UV-Vis and EEM indices of soil DOM

[0077] Soil depth, water and fertilizer strategy, biochar addition, and their interactions generally had significant effects on the UV-Vis and EEM indices of soil DOM ( Figure 6 Compared with the initial soil, the SUVA of soil DOM in each soil layer under the two water and fertilizer strategies 254 The addition of biochar to the fertilizer strategy increased SUVA in the 0-20 cm soil layer. 254 The SUVA of C2 treatment at 20-30cm soil layer and C6 treatment at 20-40cm soil layer was lower than that of C0 treatment. 254 In contrast, the SUVA of C6 treatment in the biogas slurry strategy was higher than that of C0 treatment in the 10-40cm soil layer. 254 The soil S of C2 and C4 treatments were significantly reduced by 15.48-37.48%, while the soil S of C2 and C4 treatments were increased at 30-40 cm. R The results showed that the S RIt was decreased and increased at soil depths of 0-30 cm and 30-40 cm, respectively.

[0078] For E2 / E3, the C4 treatment increased compared to the C0 treatment in the 0-40 cm depth, while the C2 and C6 treatments significantly decreased at 0-10 cm. In contrast, biochar addition significantly increased E2 / E3 at the 10-30 cm depth in the biogas slurry strategy, but significantly decreased E2 / E3 at 30-40 cm in the C4 treatment compared to the C0 treatment by 18.44%. A253 / A203 was lower in the 0-10 cm depth than in the initial soil and other soil layers in the chemical fertilizer strategy, while biochar addition reduced A253 / A203 at both the 10-20 cm and 30-40 cm depths. In the biogas slurry strategy, A253 / A203 increased by 1.78-28.91% in the C4 treatment compared to the C0 treatment at 0-40 cm, but significantly decreased and increased in the C2 treatment at 0-20 cm and 20-40 cm, respectively. Biochar addition increased FI across all soil layers in the chemical fertilizer strategy, but decreased it by 1.70-4.81% in the 20-30 cm layer in the biogas slurry strategy. Biochar addition increased β:α in the 0-20 cm and 30-40 cm layers, respectively, in the chemical fertilizer strategy. In contrast, biochar addition significantly decreased β:α by 4.55-7.22% in the 20-30 cm layer in the biogas slurry strategy. Furthermore, the C4 treatment significantly decreased β:α by 6.54% in the 10-20 cm layer compared to the C0 treatment. The effects of biochar addition on BIX across all soil layers were consistent with those of β:α in both water and fertilizer strategies. Biochar addition increased HIX in all soil layers in the chemical fertilizer strategy and in the 0-30 cm layer in the biogas slurry strategy, but significantly decreased HIX in the 30-40 cm layer in the C4 and C6 treatments compared to the C0 treatment in the biogas slurry strategy.

[0079] 3.3.3 Soil DOM organic components

[0080] DOM in soil extract can be divided into five components ( Figure 7 ad), SC1 and SC2 are humus of terrestrial origin, SC3 is the coexistence of amino acids and humus, SC4 is protein and tyrosine components, and SC5 is not identified. Before the test, the order of the size of the components of the soil extract was SC3>SC4>SC1>SC5>SC2, F max The F of C0 treatment increased with the increase of soil depth in the fertilizer strategy. max gradually increased, while the biochar addition treatment increased first and then decreased. max The size of the fertilizer strategy is 20-30cm>30-40cm>10-20cm>initial value>0-10cm. At the same time, the addition of biochar in the fertilizer strategy makes F maxThe soil layer of 20-30 cm increased by 9.64-20.47%, but the soil layer of 0-10 cm and 30-40 cm decreased significantly, and the soil layer of 10-20 cm was significantly decreased by C6 treatment F. max Compared with the C0 treatment, the C4 treatment showed a significant improvement in the F max The C2 treatment showed a significant decrease and increase at 0-10 cm (33.70%) and 20-40 cm (24.44-29.41%), respectively. The C6 treatment showed a significant increase of 16.18% at 0-10 cm. max is lower than the initial value, and with the increase of soil depth F max In C2 and C6, the levels gradually increased and decreased, respectively.

[0081] The addition of biochar in the fertilizer strategy can help to increase the content of humus-like substances (SC1+SC2+SC3) and their components in the soil DOM of each soil layer ( Figure 7 e), and the higher the biochar addition, the better the improvement effect. At the same time, with the increase of soil layer, the proportion of humus-like components in the C0 treatment gradually decreased, while the addition of biochar made the proportion of humus-like components show a trend of first decreasing and then increasing with the increase of soil layer, and the lowest point was generally located at the 20-30cm soil layer. In contrast, compared with the C0 treatment in the biogas slurry strategy, the C2 treatment helped to increase the SC1 and SC2 components in the 0-30cm soil layer and reduce the SC4 component, while the SC1 and SC2 components in the C4 and C6 treatments decreased at the depths of 0-10cm and 30-40cm, and increased at the depth of 10-20cm. Reflecting on the proportion of humus-like components, the addition of biochar in the biogas slurry strategy increased the humus-like components in the 10-20cm and 30-40cm soil layers. However, in the 0-10cm and 20-30cm soil layers, the proportion of humus-like components in the C2 treatment increased (34.18%) and decreased (9.09%), respectively, compared with the C0 treatment, and the C4 treatment decreased (4.27% and 45.54%), while the C6 treatment decreased (22.39%) and increased (2.27%).

[0082] 3.4 Vertical distribution of DOM in soil

[0083] 3.4.1 DOM Difference Visualization

[0084] PCA analysis was used to visualize the differences in DOM components of each treatment at different leachate times or soil depths ( Figure 8af), significant differences were found between the initial leachate and the second to fourth leachates in both WFSs. The third and fourth leachates were closer together, and significant differences were found between the 0-10 cm soil layer and the 10-40 cm soil layer. The values ​​on the first axis of the PCA reveal significant differences in the DOM components of the initial leachate between the BA and C0 treatments. In the CFS, significant differences were also found between the BA and C0 treatments in the third leachate, while significant differences were found between the C6 treatment and the other treatments in the second and fourth leachates. In contrast, in the BSS, significant differences were found between the BA and C0 treatments in the second leachate, while only the C4 and C0 treatments showed significant differences in the third leachate. However, no significant differences were found between the C4 and C0 treatments in the fourth leachate.

[0085] On the first axis of PCA, soil DOM components in the BA and C0 treatments in both WFSs were significantly different at the 0-20 cm depth ( Figure 8 f). At the same time, there were significant differences in soil DOM components between the BA and C0 treatments in CFS at a depth of 30-40 cm, but no significant differences between the C0 and C2 treatments at a soil depth of 20-30 cm. At the same time, in CFS, the higher the BA proportion, the greater the impact on DOM components at each soil depth. In contrast, at the depths of 20-30 cm and 30-40 cm in BSS, there were no significant differences in soil DOM components between the C0 treatment and the C4 and C2 treatments, respectively. At the same time, at a depth of 0-30 cm, the C2 treatment was farther away from the C0 treatment.

[0086] 3.4.2 Correlations between DOM features

[0087] like Figure 9 As shown in the figure, the light blue background in the upper right corner and the light purple background in the lower left corner represent the fertilizer strategy and the biogas slurry strategy respectively. In both WFS, the number of leachate is significantly positively correlated with humus-like substances, and both are significantly positively correlated with E2 / E3, A253 / A203, HIX and LC3, and are all positively correlated with SUVA. 254 , β:α, BIX and LC4 were significantly negatively correlated. At the same time, the number of percolation in the two WFSs was also significantly correlated with S R and LC2 were significantly negatively correlated; in CFS, the number of leachates and humic substances were significantly negatively correlated with LC1, the number of leachates was significantly negatively correlated with SR and FI, and the BA ratio was significantly positively correlated with DOC; in contrast, in BSS, the number of leachates, DOC and F were significantly negatively correlated with LC1. maxThe two were significantly positively correlated with each other, the BA ratio was significantly positively correlated with SR and LC1, and DOC was significantly positively correlated and negatively correlated with E2 / E3 and LC2, respectively. For soil extracts, DOC in both WFSs was significantly positively correlated with HIX, and humus-like substances were significantly positively correlated with A253 / A203 and F max , SC4 and SC5, and were significantly negatively correlated with SC1, SC2 and SC3, soil depth was significantly negatively correlated with SC1 and SC2, and significantly positively correlated with SC4; in CFS, humic acid-like acids were significantly positively correlated with BA ratio, and both were significantly positively correlated with HIX, and significantly negatively correlated with soil depth; in contrast, in BSS, BA ratio was significantly negatively correlated and positively correlated with SUVA254 and E2 / E3, respectively, and soil depth was significantly negatively correlated with FI, β:α, HIX and BIX; at the same time, the correlation directions of BA ratio and SR, soil depth and DOC, and soil depth and SC3 in the two WFS were exactly opposite.

[0088] 3.4.3 Effects of biochar addition and water and fertilizer strategies on DOM components and soil retention and leaching

[0089] Combining PCA and correlation analysis, the PLSPM model was used to establish the relationship between BA and WFS on the components of DOM in leachate and soil extract, as well as the causal relationship between leachate loss and soil retention ( Figure 10 ac). DOC and F in leachate and soil extract max Both were significantly positively regulated by the EEM index and BA gradient and significantly negatively regulated by the UV-Vis index. The EEM index was significantly positively regulated by the organic component. Both the organic component and the UV-Vis index were significantly negatively regulated by the number of leachates or soil depth. At the same time, BSS significantly regulated the UV-Vis index (negative) and organic component (positive). The organic component and the UV-Vis index were also significantly positively regulated by the BA gradient and organic component, respectively. In addition, the regulation direction of UV-Vis on the EEM index was opposite in leachate (positive) and soil extract (negative). In soil extract, the EEM index was also significantly regulated by BSS (positive), BA ratio (positive) and soil depth (negative). BSS also significantly positively regulated DOC and F. max Both BSS and BA gradients had a significant positive effect on the second and third leachates. At the same time, the initial leachate and the fourth leachate were also significantly positively regulated by the BA gradient and BSS, respectively. Both BSS and the initial leachate had a significant positive regulatory effect on the soil extract in the 0-10 cm soil layer. The soil extract in the 10-20 cm soil layer was significantly positively affected by the third leachate and the 0-10 cm soil layer. At the same time, the second to fourth leachates significantly negatively regulated the soil extract in the 20-30 cm soil layer.

[0090] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

[0091] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A soil improvement effect analysis method, characterized in that: include: After the soil improvement is completed, soil samples are collected and the soil dissolved organic carbon content, relative molecular weight, aromaticity, maximum fluorescence intensity of soil dissolved organic matter are measured, and each organic component is identified; the soil samples include at least surface soil and deep soil; The plspm package in R software was used to construct a partial least squares path model for the effects of different soil depths, biochar addition rates, and biogas slurry on dissolved organic matter retention and leaching. The model was successfully established when both the biochar addition rate and biogas slurry significantly regulated the soil dissolved organic matter components and the goodness of fit (GOF) was greater than 0.

5. Based on the calculation results of the partial least squares path model, the regulation process and improvement effect of the biochar addition ratio and the application of biogas slurry instead of chemical fertilizer on the various components of soil dissolved organic matter were explained.

2. The soil improvement effect analysis method according to claim 1, characterized in that: The soil improvement method comprises: Collect soil samples from different soil layers from top to bottom, measure the dissolved organic carbon content, relative molecular weight, aromaticity, and maximum fluorescence intensity of dissolved organic matter in each soil layer, and identify each organic component; the soil samples include at least surface soil and deep soil; When the dissolved organic carbon content and the relative molecular weight of dissolved organic matter in the surface soil are lower than those in the deep soil, and the aromaticity and maximum fluorescence intensity are lower than those in the deep soil, and the organic components mainly exist in the form of humus-like substances, biochar is applied to the soil at a rate of 2-6% of the mass of the surface soil before sowing crops, and the soil is plowed to fully mix it with the biochar; at the same time, during the peak water and fertilizer demand periods of the crops, biogas slurry is used instead of chemical fertilizers with an equal amount of nitrogen for topdressing to complete soil improvement.

3. The soil improvement effect analysis method according to claim 2, characterized in that: The dissolved organic carbon content, relative molecular weight, aromaticity and maximum fluorescence intensity of soil dissolved organic matter in soil samples of each soil layer were determined, including: Soil from each soil layer was extracted by mixing it with ultrapure water at a mass ratio of 1:5 in a thermostatic oscillator at 30°C and 180 rpm for 40 min. The extract was then centrifuged at 6000 rpm and 25°C for 10 min. The supernatant was then filtered through a 0.45 μm filter membrane to obtain the soil extract corresponding to each soil layer. The dissolved organic carbon content in each soil extract was determined using a total organic carbon analyzer. Using ultrapure water as a control, a UV-visible spectrophotometer was used to scan the photometric values ​​of ultrapure water and each soil extract in the range of 190-400 nm. The ratio of the absorbance at 254 nm to the dissolved organic carbon concentration was calculated to characterize the aromaticity of the soil dissolved organic matter. The relative molecular weight of the soil dissolved organic matter was characterized by the spectral slope ratio of the slope in the 275-295 nm region divided by the slope in the 350-400 nm region. The three-dimensional fluorescence spectra of each soil extract were measured using a fluorescence spectrometer, and the fluorescence index, freshness index, humification index, and autogenic index were calculated. At the same time, the data of the three-dimensional fluorescence spectrum were combined with parallel factor analysis to identify the maximum fluorescence intensity value.

4. The soil improvement effect analysis method according to claim 2, characterized in that: The biochar was produced by pyrolysis of corn straw at 450°C for 2 h, and its total carbon, total nitrogen and specific surface area were 43.4%, 1.17% and 342.3 m 2 / g.

5. The soil improvement effect analysis method according to claim 2, characterized in that: The biogas slurry is produced by anaerobic fermentation of organic waste, and its total carbon, total nitrogen, total phosphorus, total potassium and dissolved organic carbon contents are 16.13 g / L, 2.66 g / L, 165 mg / L, 2.79 g / L and 3.36 g / L, respectively.

6. The soil improvement effect analysis method according to claim 2, characterized in that: The soil sample includes surface soil with a thickness of 0-10 cm from top to bottom and deep soil covering no less than one layer.

7. The soil improvement effect analysis method according to claim 2, characterized in that: When the dissolved organic carbon content and the relative molecular weight of dissolved organic matter in the surface soil are lower than those in the deep soil, and the aromaticity and maximum fluorescence intensity are lower than those in the deep soil, and the organic components exist in the form of humus-like substances, biochar is applied to the soil at a concentration of 6% of the mass of the surface soil before crop sowing, and the soil is plowed to fully mix it with the biochar.

8. The soil improvement effect analysis method according to claim 2, characterized in that: The amount of biogas slurry required for each topdressing is calculated based on the equal nitrogen amount of each topdressing under the traditional chemical fertilizer model and the nutrients in the biogas slurry.

9. Use of the soil improvement effect analysis method according to any one of claims 1 to 8 in reducing soil dissolved organic matter leaching.

Images