Method and system for analyzing characteristics of dissolved organic matters in aquaculture tail water

Abstract

The invention discloses a culture tail water soluble organic matter characteristic analysis method and system, particularly relates to the technical field of water quality monitoring and analysis, and aims to solve the problem that an existing soluble organic matter characterization method is difficult to effectively associate and predict the actual degradation behavior of the soluble organic matter in the biological treatment process. Three-dimensional fluorescence spectrum data and liquid chromatography-organic carbon detection combined analysis data of a water sample to be detected are synchronously obtained, the proportion of hydrophilic and hydrophobic components and the proportion of tyrosine-like and humus-like fluorescence components are obtained through analysis, and then whether remarkable humus-like components exist or not is judged. According to a judgment result, deep analysis on the molecular aggregation state of the humus-like component is selectively started, and related proportion parameters and aggregation state information are integrated, so that evaluation on the biodegradation potential trend of the soluble organic matter is finally realized, and a key basis is provided for stability early warning of a biological treatment system.

Description

Technical Field

[0001] This invention relates to the field of water quality monitoring and analysis technology, and more specifically, to a method and system for analyzing the characteristics of dissolved organic matter in aquaculture wastewater. Background Technology

[0002] In the field of aquaculture wastewater treatment, biological treatment technologies are widely used to achieve water reuse and compliant discharge. To ensure the operational efficiency and stability of biological treatment systems, such as activated sludge and biofilm processes, effective monitoring of dissolved organic matter entering the system is necessary. Currently, in addition to conventional comprehensive indicators such as chemical oxygen demand (COD) and biological oxygen demand (BOD), analytical techniques such as spectroscopy and chromatography can be used to characterize the composition and sources of dissolved organic matter, obtaining detailed information on functional groups, molecular weight distribution, and fluorescent components, which can be used to assess the overall water quality.

[0003] However, existing methods for analyzing dissolved organic matter mainly focus on characterizing its static composition and structure. When applied to the monitoring and early warning of aquaculture wastewater biological treatment processes, the compositional information obtained by existing methods is difficult to effectively correlate and deduce the actual degradation behavior and potential of the organic matter in subsequent dynamic biological treatment processes. This results in the inability to make advance predictions on the stability changes of biological treatment units based on current analysis results. Process control often lags behind the substantial deterioration of treatment effects, thereby increasing the risk of system operation and control costs. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a method and system for analyzing the characteristics of dissolved organic matter in aquaculture wastewater to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for analyzing the characteristics of dissolved organic matter in aquaculture wastewater includes the following steps:

[0007] S1. Obtain the three-dimensional fluorescence spectral data of the aquaculture wastewater sample to be tested and analyze the data using liquid chromatography-organic carbon detection coupled with the analysis data;

[0008] S2. Based on the analysis data from liquid chromatography-organic carbon detection, the proportions of hydrophilic and hydrophobic components of soluble organic matter in the sample are obtained;

[0009] S3. Based on the three-dimensional fluorescence spectral data, obtain the ratio of tyrosine-like fluorescent components to humic-like fluorescent components of dissolved organic matter in the sample;

[0010] S4. Determine whether the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components indicates the presence of significant humic substance-like components.

[0011] S5. If not, the biodegradation potential trend of dissolved organic matter in the sample is judged based on the ratio of hydrophilic and hydrophobic components and the ratio of tyrosine-like fluorescent components to humic-like fluorescent components; if yes, the molecular aggregation state of humic-like fluorescent components is analyzed, and the biodegradation potential trend of dissolved organic matter in the sample is judged based on the ratio of hydrophilic and hydrophobic components, the ratio of tyrosine-like fluorescent components to humic-like fluorescent components, and the molecular aggregation state.

[0012] Furthermore, S1 includes:

[0013] The aquaculture wastewater sample to be tested was filtered to obtain the filtered water sample;

[0014] The filtered water sample was scanned at all wavelengths using a fluorescence spectrophotometer to obtain three-dimensional fluorescence spectral data;

[0015] The filtered water sample was analyzed using a liquid chromatography-organic carbon detector coupled with a liquid chromatography-organic carbon detector to obtain the analytical data.

[0016] Furthermore, S2 includes:

[0017] In the chromatograms corresponding to the data from liquid chromatography-organic carbon detection, the regions of hydrophobic components and hydrophilic components are divided according to the retention time.

[0018] The chromatographic peaks of the hydrophobic and hydrophilic component regions were integrated separately to obtain the organic carbon response values ​​of the hydrophobic and hydrophilic components.

[0019] The ratio of hydrophilic to hydrophobic components is calculated based on the organic carbon response values ​​of the hydrophobic and hydrophilic components.

[0020] Furthermore, S3 includes:

[0021] In the contour plot corresponding to the three-dimensional fluorescence spectral data, regions of tyrosine-like fluorescent components and regions of humic substances-like fluorescent components were identified.

[0022] The fluorescence intensity of the tyrosine-like fluorescent component region and the humic substance-like fluorescent component region were integrated by volume to obtain the response values ​​of the tyrosine-like fluorescent component and the humic substance-like fluorescent component.

[0023] The ratio of tyrosine-like fluorescent components to humic-like fluorescent components was calculated based on their response values.

[0024] Furthermore, S4 includes:

[0025] Obtain the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components;

[0026] The ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components is compared with a preset judgment threshold.

[0027] If the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components is less than or equal to the judgment threshold, it is determined that there are significant humic substance-like components.

[0028] If the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components is greater than the judgment threshold, it is determined that there are no significant humic substance-like components.

[0029] Furthermore, when step S4 determines that there are no significant humic substances, the following steps are performed: obtain the ratio of hydrophilic and hydrophobic components obtained in step S2 and the ratio of tyrosine-like fluorescent components to humic substances obtained in step S3; based on the ratio of hydrophilic and hydrophobic components and the ratio of tyrosine-like fluorescent components to humic substances, determine the biodegradation potential trend of dissolved organic matter in the sample.

[0030] Further, when step S4 determines the presence of significant humic substances, the following steps are performed: analyze the molecular aggregation state of the humic fluorescent components; obtain the ratio of hydrophilic to hydrophobic components obtained in step S2, the ratio of tyrosine-like fluorescent components to humic fluorescent components obtained in step S3, and the molecular aggregation state of the analyzed humic fluorescent components; based on the ratio of hydrophilic to hydrophobic components, the ratio of tyrosine-like fluorescent components to humic fluorescent components, and the molecular aggregation state, determine the biodegradation potential trend of dissolved organic matter in the sample.

[0031] Furthermore, in step S5, the molecular aggregation state of the humic substance-like fluorescent component is analyzed. Specifically, based on three-dimensional fluorescence spectral data, the presence of a fluorescence self-quenching effect in the humic substance-like fluorescent component, where the fluorescence intensity decreases nonlinearly with increasing concentration, is detected to determine the molecular aggregation state of the humic substance-like fluorescent component.

[0032] Further, in step S5, the biodegradation potential trend of dissolved organic matter in the sample is judged by comparing the ratio of hydrophilic and hydrophobic components, the ratio of tyrosine-like fluorescent components to humic-like fluorescent components, and the molecular aggregation state with preset benchmarks, and drawing a conclusion on the biodegradation potential trend by combining the comparison results.

[0033] On the other hand, the present invention provides a system for analyzing the characteristics of dissolved organic matter in aquaculture wastewater, comprising the following modules:

[0034] The data acquisition module is used to acquire the three-dimensional fluorescence spectral data and the liquid chromatography-organic carbon detection coupled analysis data of the aquaculture wastewater sample to be tested;

[0035] The first calculation module is used to obtain the proportion of hydrophilic and hydrophobic components of dissolved organic matter in the sample based on the analysis data of liquid chromatography-organic carbon detection coupled analysis;

[0036] The second calculation module is used to obtain the ratio of tyrosine-like fluorescent components to humic-like fluorescent components of dissolved organic matter in the sample based on the three-dimensional fluorescence spectral data.

[0037] The significant judgment module is used to determine whether the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components indicates the presence of significant humic substance-like components.

[0038] The trend judgment module is used to determine the biodegradation potential trend of dissolved organic matter in the sample based on the ratio of hydrophilic and hydrophobic components and the ratio of tyrosine-like fluorescent components to humic-like fluorescent components if the trend is negative; otherwise, it analyzes the molecular aggregation state of humic-like fluorescent components and determines the biodegradation potential trend of dissolved organic matter in the sample based on the ratio of hydrophilic and hydrophobic components, the ratio of tyrosine-like fluorescent components to humic-like fluorescent components, and the molecular aggregation state.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] 1. By integrating multi-dimensional component characteristic information and establishing an analytical path with discriminative branches, the static composition characterization of dissolved organic matter can be dynamically linked to its future biological treatment behavior, thereby enabling effective and proactive prediction of the operational stability of biological treatment units. First, three-dimensional fluorescence spectral data reflecting functional group characteristics and liquid chromatography-organic carbon detection coupled analysis data reflecting polarity distribution are simultaneously acquired. From these, key tyrosine-like and humic-like fluorescent component ratios, as well as hydrophilic and hydrophobic component ratios, are extracted, forming a multi-parameter basis for assessing degradation potential. Going beyond parameter acquisition, a significance judgment step based on the ratio of tyrosine-like and humic-like fluorescent components is introduced, serving as a logical branch point to guide subsequent differentiated in-depth analytical paths. This enables the analytical process to possess intelligent screening and focusing capabilities, automatically identifying water quality conditions requiring priority attention and posing higher potential hazards.

[0041] 2. When the humic component is determined to be insignificant, the system can perform rapid trend assessment based on a relatively simple component ratio, achieving efficient screening. However, when the presence of a significant humic component is determined, the system further initiates analysis of its molecular aggregation state, more precisely assessing its potential inhibitory risk to the biodegradation process at the molecular interaction level. Ultimately, it integrates multi-source information to make a more accurate judgment on the biodegradation potential trend. This transforms previously isolated static component parameters into dynamic early warning signals that can directly serve process control decisions through a logically rigorous process. This effectively overcomes the control lag problem caused by the disconnect between analysis and process in existing technologies, providing crucial monitoring technology support for the stable and low-consumption operation of aquaculture wastewater biological treatment systems. Attached Figure Description

[0042] Figure 1 This is a flowchart of a method for analyzing the characteristics of dissolved organic matter in aquaculture wastewater according to the present invention;

[0043] Figure 2 This is a schematic diagram of the structure of a system for analyzing the characteristics of dissolved organic matter in aquaculture wastewater according to the present invention. Detailed Implementation

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0045] Example 1: Figure 1 This invention provides a method for analyzing the characteristics of dissolved organic matter in aquaculture wastewater, comprising the following steps:

[0046] S1. Obtain the three-dimensional fluorescence spectral data of the aquaculture wastewater sample to be tested and analyze the data using liquid chromatography-organic carbon detection coupled with the analysis data;

[0047] S2. Based on the analysis data from liquid chromatography-organic carbon detection, the proportions of hydrophilic and hydrophobic components of soluble organic matter in the sample are obtained;

[0048] S3. Based on the three-dimensional fluorescence spectral data, obtain the ratio of tyrosine-like fluorescent components to humic-like fluorescent components of dissolved organic matter in the sample;

[0049] S4. Determine whether the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components indicates the presence of significant humic substance-like components.

[0050] S5. If not, the biodegradation potential trend of dissolved organic matter in the sample is judged based on the ratio of hydrophilic and hydrophobic components and the ratio of tyrosine-like fluorescent components to humic-like fluorescent components; if yes, the molecular aggregation state of humic-like fluorescent components is analyzed, and the biodegradation potential trend of dissolved organic matter in the sample is judged based on the ratio of hydrophilic and hydrophobic components, the ratio of tyrosine-like fluorescent components to humic-like fluorescent components, and the molecular aggregation state.

[0051] S1. Obtain the three-dimensional fluorescence spectral data of the aquaculture wastewater sample to be tested and analyze the data using liquid chromatography-organic carbon detection coupled with the analysis data. The specific implementation is as follows:

[0052] First, the aquaculture wastewater sample to be tested is filtered to obtain a filtered water sample. Specifically, the aquaculture wastewater sample collected on-site is allowed to stand for a period of time, such as 30 minutes, to allow large suspended particles to settle naturally. Then, the supernatant is collected and filtered. The filtration process uses a mixed cellulose ester filter membrane with a pore size of 0.45 micrometers. This membrane can effectively trap particulate matter, bacteria, and most colloidal substances in the sample, so that the permeate mainly contains dissolved organic matter and inorganic ions. This permeate is the filtered water sample. The filtration operation is carried out on a vacuum filtration device to provide a stable filtration driving force, ensuring filtration efficiency and consistency. After filtration, the filtered water sample is immediately transferred to a clean sample bottle and stored at 4 degrees Celsius in the dark to inhibit the biological or chemical degradation of dissolved organic matter. Subsequent spectroscopic and chromatographic analyses must be completed within 24 hours to ensure the representativeness of the analytical results.

[0053] After obtaining the filtered water sample, a fluorescence spectrophotometer was used to perform a full-wavelength scan to obtain three-dimensional fluorescence spectral data. In practice, the filtered water sample was placed in a standard quartz cuvette and then placed in the sample chamber of the preheated and stabilized fluorescence spectrophotometer. The instrument's excitation wavelength scanning range was set to 200 nm to 450 nm, and the emission wavelength scanning range to 250 nm to 550 nm, with a scanning interval of, for example, 5 nm, and an integration time of, for example, 0.5 seconds. During the scan, the instrument sequentially irradiated the sample at each set excitation wavelength and simultaneously recorded the fluorescence intensity signals at the corresponding emission wavelengths. Finally, a data matrix with excitation wavelength, emission wavelength, and fluorescence intensity as three dimensions was obtained; this data matrix represents the three-dimensional fluorescence spectral data. To eliminate background signal interference from the instrument itself and the solvent, a blank scan was performed using ultrapure water before sample scanning, and this blank background was subtracted from the obtained three-dimensional fluorescence spectral data. In addition, to correct for minor differences in instrument response on different dates, the fluorescence intensity of the quinine sulfate standard solution needs to be measured and recorded in each analysis sequence. The known fluorescence characteristics of this standard solution are then used to standardize and correct the three-dimensional fluorescence spectral data of the samples. The final obtained and stored three-dimensional fluorescence spectral data will be used for subsequent identification and quantitative analysis of fluorescent components.

[0054] After acquiring three-dimensional fluorescence spectroscopy data, a liquid chromatography-organic carbon detector (LC-OCC detector) was used to analyze the same filtered water sample to obtain LC-OCC coupled analysis data. Before analysis, the LC system was equilibrated using a degassed phosphate buffer solution as the mobile phase, with the pH adjusted to, for example, 6.8. A hydrophilic column was selected, and the column oven temperature was maintained at, for example, 30 degrees Celsius. The sample injection volume was set to, for example, 1000 μL. After starting the analysis program, the dissolved organic components in the filtered water sample were separated in the column according to their polarity and molecular size, and then elute sequentially from the column and enter the organic carbon detector. The organic carbon detector first oxidizes the eluting organic matter into carbon dioxide using ultraviolet light. Then, a thin-film conductivity detector measures the change in conductivity caused by the generated carbon dioxide; this change is proportional to the organic carbon content. This allows for real-time recording of the organic carbon response signal at different retention times, forming a chromatogram with retention time on the x-axis and organic carbon response value on the y-axis. This chromatogram and its complete dataset constitute the liquid chromatography-organic carbon detection (LC-OCDetection) analysis data. To ensure the accuracy and comparability of the analytical data, the system is calibrated before each batch of sample analysis using a known concentration of organic carbon standard solution, such as potassium hydrogen phthalate solution. A quantitative relationship curve between the organic carbon response value and the actual concentration is established by measuring the response values ​​of standard solutions at different concentrations. The entire analytical process must be conducted in a temperature-controlled laboratory to minimize the impact of environmental temperature fluctuations on chromatographic separation and detector stability. The obtained LC-OCDetection analysis data will serve as input for subsequent calculations of the ratio of hydrophilic to hydrophobic components.

[0055] S2. Based on the analysis data from liquid chromatography-organic carbon detection, the proportions of hydrophilic and hydrophobic components of dissolved organic matter in the sample are obtained. The specific implementation is as follows:

[0056] First, the liquid chromatography-organic carbon detection (LC-OCC) analysis data obtained in step S1 is acquired. This data is represented as a chromatogram with retention time on the x-axis and organic carbon response value on the y-axis. In the chromatogram, hydrophobic and hydrophilic component regions are distinguished based on the differences in retention behavior of different organic components on the chromatographic column. Specifically, this distinction is achieved by determining a time boundary point based on the retention times of known standard substances or statistical patterns established through analysis of a large number of aquaculture wastewater samples. For example, the chromatographic signal region with retention times between, for example, 8 minutes and 15 minutes is defined as the hydrophobic component region, which typically includes components with larger molecular weights and weaker polarity, such as humic acid and fulvic acid. Simultaneously, the chromatographic signal region with retention times between, for example, 2 minutes and 8 minutes is defined as the hydrophilic component region, which mainly includes components with stronger polarity, such as small molecule organic acids, carbohydrates, and protein degradation products. This distinction is based on the fact that, under the conditions of the hydrophilic column and specific mobile phase, substances with stronger polarity interact weaker with the stationary phase, resulting in shorter retention times, and vice versa. When determining the range of the region, it is necessary to ensure that the baseline between the two regions is straight and stable to guarantee the accuracy of subsequent integration calculations.

[0057] After clearly defining the hydrophobic and hydrophilic component regions, the chromatographic peaks in these two regions are integrated to obtain quantitative data. The integration process is typically performed by the instrument's data processing software, the core of which is calculating the area enclosed by the chromatographic peak curve and the baseline. Specifically, the software manually or automatically sets the start and end points for each region. It then automatically identifies and tracks the baseline of the chromatographic peak, and sums the organic carbon response values ​​of all data points within the selected region. This yields a value representing the total amount of hydrophobic components (hydrophobic component organic carbon response value) and a value representing the total amount of hydrophilic components (hydrophilic component organic carbon response value). The organic carbon response value is a dimensionless relative response intensity value, its magnitude being directly proportional to the organic carbon content of the corresponding component. During integration, care must be taken to handle potential peak overlap, for example, by setting vertical dividing lines or utilizing peak segmentation algorithms provided by the software, to ensure that the signal of each component is accurately assigned and quantified. The obtained hydrophobic and hydrophilic component organic carbon response values ​​will serve as direct input parameters for the next calculation.

[0058] After obtaining the organic carbon response values ​​of the hydrophobic and hydrophilic components, the ratio of hydrophilic to hydrophobic components is calculated based on these two values. The hydrophilic-hydrophobic component ratio is an indicator used to quantify the relative abundance relationship between hydrophilic and hydrophobic components in a sample. The specific implementation of this ratio is as follows: the organic carbon response value of the hydrophilic component is used as the numerator, and the organic carbon response value of the hydrophobic component is used as the denominator, followed by a division operation. The calculation can be described as: the hydrophilic-hydrophobic component ratio equals the organic carbon response value of the hydrophilic component divided by the organic carbon response value of the hydrophobic component. If the ratio obtained through this calculation is greater than 1, it indicates that the hydrophilic component is dominant in the current sample; if the ratio is less than 1, it indicates that the hydrophobic component is dominant. This ratio calculation process does not involve complex iterative conditions or weight settings; its core logic is to directly compare the relative response intensities of the two types of components. In practice, to ensure the reliability of the calculation results, it is necessary to confirm that the organic carbon response value of the hydrophobic component used for calculation is not zero. If the organic carbon response value of the hydrophobic component is extremely low, such as below the instrument detection limit, it can be set to a very small positive number, such as 0.001, much smaller than the organic carbon response value of the hydrophilic component, before calculation to avoid mathematical errors. The final calculated ratio of hydrophilic and hydrophobic components will serve as a key characteristic parameter for the comprehensive assessment of the biodegradation potential of dissolved organic matter in subsequent steps.

[0059] S3. Based on the three-dimensional fluorescence spectral data, the ratio of tyrosine-like fluorescent components to humic-like fluorescent components of dissolved organic matter in the sample is obtained, specifically as follows:

[0060] First, the three-dimensional fluorescence spectral data obtained in step S1 and processed by blank correction and normalization are acquired. This data is a data matrix containing three dimensions: excitation wavelength, emission wavelength, and fluorescence intensity. Based on this data matrix, a fluorescence contour plot can be drawn. In this plot, the tyrosine-like fluorescent component region and the humic substance-like fluorescent component region are identified according to the characteristic excitation and emission wavelength positions of different fluorophores in the dissolved organic matter. The characteristic peaks of the tyrosine-like fluorescent component usually appear in the range where both the excitation and emission wavelengths are relatively low. The identification method is to define the closed region enclosed by the excitation wavelength range, for example, 220 nm to 250 nm, and the emission wavelength range, for example, 300 nm to 330 nm, on the contour plot as the tyrosine-like fluorescent component region. The fluorescence signal in this region mainly originates from the fluorescence characteristics of tyrosine amino acid residues in protein-like substances. The characteristic peaks of humic-like fluorescent components appear in the range where both excitation and emission wavelengths are relatively high. The identification method involves defining the enclosed region on a contour plot, bounded by an excitation wavelength range of, for example, 330 nm to 350 nm and an emission wavelength range of, for example, 420 nm to 450 nm, as the humic-like fluorescent component region. The fluorescence signal within this region is typically associated with complex macromolecular organic molecules similar to humic substances. The specific boundary values ​​for this region are determined based on a large database of known standard samples or internationally recognized fluorescence region delineation maps. In practice, precise delineation can be achieved using the default region template built into professional spectral analysis software or by user-defined boundaries based on sample characteristics.

[0061] After accurately identifying the tyrosine-like fluorescent component region and the humic substance-like fluorescent component region, it is necessary to perform volume integration on the fluorescence intensity signals in these two three-dimensional spatial regions to obtain quantitative response values. Mathematically, volume integration is a triple summation or integration operation of function values ​​within a three-dimensional spatial domain; specifically, it involves accumulating the fluorescence intensity values ​​of all data points within the selected region. The specific implementation involves using three-dimensional fluorescence spectroscopy data processing software. First, the excitation and emission wavelength boundaries of the identified region are manually or automatically set. The software automatically extracts the fluorescence intensity values ​​corresponding to all discrete data points within this boundary range. Then, these fluorescence intensity values ​​are multiplied by a small area unit formed by the corresponding excitation and emission wavelength step sizes. This is then double-summed along the excitation and emission wavelength directions to finally calculate the value representing the total fluorescence signal intensity of the region, i.e., the tyrosine-like fluorescent component response value and the humic substance-like fluorescent component response value. Here, the step size is the excitation wavelength scanning interval and the emission wavelength scanning interval set during data acquisition, for example, both are 5 nanometers. The volume integration process is entirely executed by software according to a pre-defined algorithm. Its core principle is to accumulate all valid signals within a specific spectral region, thereby avoiding random errors that might arise from a single peak and more comprehensively reflecting the overall abundance of the fluorescent component. The obtained tyrosine-like fluorescent component response values ​​and humic substance-like fluorescent component response values ​​are two comparable values ​​with the same dimensions and units.

[0062] After obtaining the response values ​​of tyrosine-like and humic-like fluorescent components, the ratio of tyrosine-like to humic-like fluorescent components is calculated based on these two values. This ratio is an important indicator for quantifying the relative abundance of humic-like components relative to tyrosine-like components in a sample. The specific method for calculating this ratio is to use the humic-like fluorescent component response value as the numerator and the tyrosine-like fluorescent component response value as the denominator, and then perform a division operation. The calculation relationship is described as follows: the ratio of tyrosine-like to humic-like fluorescent components equals the humic-like fluorescent component response value divided by the tyrosine-like fluorescent component response value. A larger ratio indicates a higher relative abundance of humic substances in the current sample; a smaller ratio indicates a higher relative abundance of protein-derived substances. This calculation is a direct arithmetic operation and does not involve iteration or complex weighting coefficients. In practice, to ensure the feasibility of the mathematical calculation, it is necessary to confirm that the tyrosine-like fluorescent component response value used for the calculation is not zero. In extreme cases, if the response value of the tyrosine-like fluorescent component is extremely low, such as below the instrument's detection limit, this value can be set to a very small positive number much smaller than the response value of the humic substance-like fluorescent component before calculation, to prevent invalid calculations with a denominator of zero. The final calculated ratio of the tyrosine-like fluorescent component to the humic substance-like fluorescent component will serve as a key spectral characteristic parameter, directly used in subsequent steps to determine the presence of a significant humic substance-like component.

[0063] S4. Determine whether the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components indicates the presence of significant humic substance-like components. The specific implementation is as follows:

[0064] First, the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components, calculated in step S3, is obtained. This ratio is a specific numerical value, obtained through region identification and volume integration calculation of the three-dimensional fluorescence spectral data in the aforementioned steps. After obtaining this ratio, it is compared with a preset judgment threshold. The preset judgment threshold is a pre-set critical value used to distinguish the presence or absence of significant humic substance-like components. This threshold is not arbitrarily set, but is determined based on the analysis data of a large number of historical aquaculture wastewater samples and the correlation analysis of the operational efficiency of related biological treatment units. The specific implementation method for obtaining and setting this threshold is as follows: First, a representative aquaculture wastewater sample library is collected, covering wastewater samples from different seasons, different aquaculture species, and different treatment stages. Then, the ratio of tyrosine-like fluorescent components to humic-like fluorescent components in each sample is strictly determined according to steps S1 to S3. Simultaneously, through parallel biodegradation experiments or long-term monitoring of the actual organic matter removal efficiency of the corresponding biological treatment unit, such as an activated sludge system, the actual biodegradability data of dissolved organic matter represented by each sample is obtained. Finally, through statistical analysis, the correlation between the ratio of tyrosine-like fluorescent components to humic-like fluorescent components and actual biodegradability is sought. The critical ratio value that can clearly distinguish between easily degradable and difficult-to-degrade samples is determined as the preset judgment threshold. For example, analysis may reveal that when this ratio is below 1.2, the organic matter in the sample exhibits slow degradation and easy accumulation characteristics in subsequent biological treatment; therefore, 1.2 can be set as an exemplary preset judgment threshold. This threshold can be fine-tuned based on specific aquaculture processes, water quality characteristics, and treatment objectives, but its core setting basis is always the correlation between the ratio and the biodegradation potential.

[0065] After determining the preset judgment threshold, a comparison operation is performed. This comparison involves comparing the ratio of the obtained tyrosine-like fluorescent component to the humic substance-like fluorescent component with the preset judgment threshold. This is a simple mathematical comparison process designed to determine whether the ratio of the current sample is greater than, less than, or equal to the preset judgment threshold. In practice, this can be done in data processing software or simple comparison logic. The input parameters are two numerical values, and the output is a logical judgment, either yes or no, corresponding to whether the ratio is less than or equal to the threshold. This step does not involve complex iterative calculations, but it requires that the two compared objects have the same dimensions, both being dimensionless ratios.

[0066] Based on the comparison results, a final determination is made. If the ratio of tyrosine-like fluorescent components to humic-like fluorescent components is less than or equal to a preset determination threshold, it is determined that significant humic-like components are present. "Significant" here is a technical term specifically referring to a critical level in the current sample where the relative abundance of humic-like components has reached a level that indicates a potential risk to the stability and degradation efficiency of subsequent biological treatment processes, requiring additional attention. Conversely, if the ratio of tyrosine-like fluorescent components to humic-like fluorescent components is greater than the preset determination threshold, it is determined that no significant humic-like components are present. This means that the dissolved organic matter in the sample is mainly composed of easily degradable components such as tyrosine, and its biodegradation potential is expected to be high. This determination step is the conclusive step in the entire determination process, transforming a continuous numerical ratio into a discrete classification decision, thus providing a clear basis for selecting different analytical paths in subsequent steps.

[0067] S5. If not, then the biodegradation potential trend of dissolved organic matter in the sample is judged based on the ratio of hydrophilic and hydrophobic components and the ratio of tyrosine-like fluorescent components to humic-like fluorescent components; if yes, then the molecular aggregation state of humic-like fluorescent components is analyzed, and the biodegradation potential trend of dissolved organic matter in the sample is judged based on the ratio of hydrophilic and hydrophobic components, the ratio of tyrosine-like fluorescent components to humic-like fluorescent components, and the molecular aggregation state. Specifically, the implementation is as follows:

[0068] First, the subsequent analysis path is selected based on the judgment conclusion made in step S4. The judgment conclusion in step S4 falls into two categories: the presence of significant humic substances or the absence of significant humic substances. The execution logic of the entire step S5 depends entirely on this judgment conclusion, and is therefore divided into two parallel and mutually exclusive technical branches.

[0069] When step S4 determines that no significant humic substances are present, the first analytical path is executed. In this path, the proportions of hydrophilic and hydrophobic components calculated in step S2, and the proportions of tyrosine-like fluorescent components and humic substances-like fluorescent components calculated in step S3, are first obtained. After obtaining these two proportion parameters, the biodegradation potential trend of dissolved organic matter in the sample is assessed based on them. This assessment is a comprehensive evaluation process, and its implementation is not a simple mathematical operation, but rather based on pre-established empirical rules or decision matrices. These rules or matrices are established based on statistical analysis of a large number of aquaculture wastewater samples with known biodegradation behaviors. For example, the following judgment logic can be set: when the proportion of hydrophilic and hydrophobic components is greater than an empirical value, and the proportions of tyrosine-like fluorescent components and humic-like fluorescent components are simultaneously greater than another empirical value, the biodegradation potential trend is judged to be high; if the proportion of hydrophilic and hydrophobic components is between, for example, 1.0 and 1.5, and the proportions of tyrosine-like fluorescent components and humic-like fluorescent components are greater than 1.0, the trend is judged to be medium; if the proportion of hydrophilic and hydrophobic components is less than 1.0, regardless of the proportions of tyrosine-like fluorescent components and humic-like fluorescent components, the trend is judged to be low. The empirical values ​​here are the preset benchmarks, and these benchmark values ​​are set from the correlation summary between different parameter ranges in historical data and the actual observed biological treatment efficiency. The judgment process involves comparing the two measured proportion values ​​of the current sample with the corresponding preset benchmarks, and based on the combination of the numerical intervals they fall into, referring to a predefined rule table, ultimately arriving at a qualitative or semi-quantitative conclusion regarding the biodegradation potential trend, such as high, medium, low, or increasing, stable, decreasing. In this approach, since the humic components have been determined to be insignificant, there is no need to examine their molecular state, which simplifies the analytical model and focuses on evaluating the relative advantage of easily degradable components.

[0070] When step S4 determines the presence of a significant humic substance-like component, the second analytical path is executed. Under this path, the analysis is more in-depth. First, it is necessary to further analyze the molecular aggregation state of this humic substance-like fluorescent component. As further defined in the dependent claims, the analysis of the molecular aggregation state of the humic substance-like fluorescent component is specifically achieved by detecting, based on three-dimensional fluorescence spectroscopy data, whether the fluorescence intensity of this humic substance-like fluorescent component exhibits a fluorescence self-quenching effect that decreases non-linearly with increasing concentration. The specific implementation method is as follows: The same filtered water sample obtained in step S1 is diluted to different degrees, for example, to prepare a stock solution and samples diluted 2 times, 4 times, 8 times, etc., at a series of concentration gradients. Then, strictly following the three-dimensional fluorescence spectroscopy acquisition conditions in step S1, the fluorescence intensity of each diluted sample at the characteristic excitation and emission wavelengths of the humic substance-like fluorescent component is measured. Subsequently, the change in fluorescence intensity with increasing sample dilution factor, i.e., decreasing concentration, is observed and analyzed. If the fluorescence intensity increases significantly and disproportionately with decreasing concentration, meaning the relationship between intensity and concentration deviates from linearity, indicating suppression of intensity at higher concentrations, then a fluorescence self-quenching effect is identified, suggesting that the fluorescent component of this type of humic substance is in a strong molecular aggregated state or exhibits intermolecular interactions. Conversely, if the fluorescence intensity shows a good linear relationship with concentration, then no significant self-quenching effect is identified, indicating that the molecules are predominantly in a dispersed state. The judgment of nonlinear decrease can be achieved by calculating whether the ratio of fluorescence intensity to concentration remains constant at different concentration points, or by plotting a fluorescence intensity-concentration curve and observing whether it deviates from a straight line passing through the origin. The final judgment of the molecular aggregation state can be a qualitative conclusion, such as whether the aggregation state is significant or insignificant, or a semi-quantitative indicator, such as classifying the level based on the degree to which the correlation coefficient of the linear regression between concentration and fluorescence intensity deviates from 1.0.

[0071] After completing the molecular aggregation state analysis of the humic substance-like fluorescent component, three key parameters need to be obtained for comprehensive judgment under this second path. These three parameters are: the ratio of hydrophilic to hydrophobic components obtained in step S2, the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components obtained in step S3, and the molecular aggregation state information of the humic substance-like fluorescent component obtained through analysis. Based on these three parameters, the biodegradation potential trend of dissolved organic matter in the sample is judged. As further defined in the dependent claims, this judgment specifically involves comparing the ratio of hydrophilic to hydrophobic components, the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components, and the molecular aggregation state with preset benchmarks, and drawing a judgment conclusion by comprehensively considering the comparison results. The preset benchmarks here include benchmarks for the ratio of hydrophilic to hydrophobic components, benchmarks for the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components, and benchmarks for the molecular aggregation state. The specific implementation of the comprehensive judgment can be a weighted scoring or a hierarchical decision tree. For example, different levels and scores can be assigned to each parameter: a high score for the proportion of hydrophilic and hydrophobic components above a certain value, and a low score for those below a certain value; a high score for the proportion of tyrosine-like fluorescent components to humic-like fluorescent components above a certain value, and a low score for those below a certain value; a low score for a significant molecular aggregation state, and a high score for an insignificant aggregation state. Then, the scores of the three parameters are added together or weighted according to preset weights to obtain a total score. Finally, this total score is compared with a preset total score threshold to determine the final trend judgment; for example, a total score above a certain threshold indicates a acceptable trend, while a total score below a certain threshold indicates a worrying trend. Another implementation method is to use decision rules, for example: if the molecular aggregation state is determined to be significant, then regardless of the other two parameters, the biodegradation potential trend is directly judged as low; if the molecular aggregation state is insignificant, then the proportions of the other two parameters are considered, and a judgment is made according to a similar rule as in the first path. All preset benchmarks and thresholds, including the level cutoff values, weighting coefficients, and total score thresholds for each parameter, must be determined through calibration experiments with a large number of samples. This involves establishing a mapping relationship between parameter combinations and the actual biodegradability performance database, thereby extracting effective classification rules or scoring criteria. Through this multi-parameter, hierarchical comprehensive judgment, even when humic components are significantly present, the potential additional degradation resistance due to their aggregation state can be more accurately assessed, thus providing a more reliable and robust early warning conclusion regarding biodegradation potential trends. The output of the entire step S5 is a clear trend judgment on the degradation behavior of dissolved organic matter in the tested aquaculture wastewater sample during subsequent biological treatment. This conclusion directly serves as an early warning and control decision for the stability of the treatment process.

[0072] Example 2: Figure 2A schematic diagram of the structure of a system for analyzing the characteristics of dissolved organic matter in aquaculture wastewater according to the present invention is provided. The system includes the following modules:

[0073] The data acquisition module is used to acquire the three-dimensional fluorescence spectral data and the liquid chromatography-organic carbon detection coupled analysis data of the aquaculture wastewater sample to be tested;

[0074] The first calculation module is used to obtain the proportion of hydrophilic and hydrophobic components of dissolved organic matter in the sample based on the analysis data of liquid chromatography-organic carbon detection coupled analysis;

[0075] The second calculation module is used to obtain the ratio of tyrosine-like fluorescent components to humic-like fluorescent components of dissolved organic matter in the sample based on the three-dimensional fluorescence spectral data.

[0076] The significant judgment module is used to determine whether the ratio of tyrosine-like fluorescent components to humic substance-like fluorescent components indicates the presence of significant humic substance-like components.

[0077] The trend judgment module is used to determine the biodegradation potential trend of dissolved organic matter in the sample based on the ratio of hydrophilic and hydrophobic components and the ratio of tyrosine-like fluorescent components to humic-like fluorescent components if the trend is negative; otherwise, it analyzes the molecular aggregation state of humic-like fluorescent components and determines the biodegradation potential trend of dissolved organic matter in the sample based on the ratio of hydrophilic and hydrophobic components, the ratio of tyrosine-like fluorescent components to humic-like fluorescent components, and the molecular aggregation state.

[0078] All calculations involved in the embodiments are dimensionless numerical calculations, and the preset parameters and thresholds in the calculations are set by those skilled in the art according to the actual situation.

[0079] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0080] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and inventive constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0081] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0082] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0083] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0084] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for analyzing characteristics of dissolved organic matter in aquaculture effluent, characterized by, The method comprises the following steps: S1, obtaining three-dimensional fluorescence spectrum data and liquid chromatography-organic carbon detection combined analysis data of the aquaculture tail water sample to be tested; S2, obtaining the hydrophilic-hydrophobic component ratio of the dissolved organic matter in the sample according to the liquid chromatography-organic carbon detection combined analysis data; S3, obtaining the ratio of the tyrosine-like fluorescence component and the humus-like fluorescence component of the dissolved organic matter in the sample according to the three-dimensional fluorescence spectrum data; S4, judging whether the ratio of the tyrosine-like fluorescence component and the humus-like fluorescence component indicates the presence of significant humus-like components; S5, if not, judging the biodegradation potential trend of the dissolved organic matter in the sample based on the hydrophilic-hydrophobic component ratio and the ratio of the tyrosine-like fluorescence component and the humus-like fluorescence component; if yes, analyzing the molecular aggregation state of the humus-like fluorescence component, and judging the biodegradation potential trend of the dissolved organic matter in the sample based on the hydrophilic-hydrophobic component ratio, the ratio of the tyrosine-like fluorescence component and the humus-like fluorescence component, and the molecular aggregation state. S1 comprises:

2. The method according to claim 1, wherein, filtering the aquaculture tail water sample to be tested to obtain a filtered water sample; performing full-wavelength scanning on the filtered water sample by using a fluorescence spectrophotometer to obtain three-dimensional fluorescence spectrum data; performing analysis on the filtered water sample by using a liquid chromatograph combined with an organic carbon detector to obtain liquid chromatography-organic carbon detection combined analysis data. comprises:

3. The method according to claim 1, wherein S2 in the chromatogram corresponding to the liquid chromatography-organic carbon detection combined analysis data, dividing a hydrophobic component region and a hydrophilic component region according to the retention time; integrating the chromatographic peaks of the hydrophobic component region and the hydrophilic component region respectively to obtain hydrophobic component organic carbon response value and hydrophilic component organic carbon response value; calculating the hydrophilic-hydrophobic component ratio according to the hydrophobic component organic carbon response value and the hydrophilic component organic carbon response value. comprises:

4. The method for analyzing the characteristics of dissolved organic matter in aquaculture tail water according to claim 1, characterized in that S3 in the contour map corresponding to the three-dimensional fluorescence spectrum data, identifying a tyrosine-like fluorescence component region and a humus-like fluorescence component region; integrating the fluorescence intensities of the tyrosine-like fluorescence component region and the humus-like fluorescence component region respectively to obtain tyrosine-like fluorescence component response value and humus-like fluorescence component response value; calculating the ratio of the tyrosine-like fluorescence component and the humus-like fluorescence component according to the tyrosine-like fluorescence component response value and the humus-like fluorescence component response value. comprises:

5. The method for analyzing the characteristics of the dissolved organic matter in the aquaculture tail water according to claim 1, wherein S4 obtaining the ratio of the tyrosine-like fluorescence component and the humus-like fluorescence component; comparing the ratio of the tyrosine-like fluorescence component and the humus-like fluorescence component with a preset determination threshold value; if the ratio of the tyrosine-like fluorescence component and the humus-like fluorescence component is less than or equal to the determination threshold value, it is determined that there are significant humus-like components; if the ratio of the tyrosine-like fluorescence component and the humus-like fluorescence component is greater than the determination threshold value, it is determined that there are no significant humus-like components. ​ 6. The method according to claim 1, wherein, When the step S4 determines that the significant humus-like component does not exist, the following steps are performed: obtaining the hydrophilic-hydrophobic component ratio obtained in the step S2 and the ratio of the tyrosine-like fluorescent component to the humus-like fluorescent component obtained in the step S3; determining the biodegradability potential trend of the dissolved organic matter in the sample based on the hydrophilic-hydrophobic component ratio and the ratio of the tyrosine-like fluorescent component to the humus-like fluorescent component.

7. The method according to claim 1, wherein, When the step S4 determines that the significant humus-like component exists, the following steps are performed: analyzing the molecular aggregation state of the humus-like fluorescent component; obtaining the hydrophilic-hydrophobic component ratio obtained in the step S2, the ratio of the tyrosine-like fluorescent component to the humus-like fluorescent component obtained in the step S3, and the analyzed molecular aggregation state of the humus-like fluorescent component; determining the biodegradability potential trend of the dissolved organic matter in the sample based on the hydrophilic-hydrophobic component ratio, the ratio of the tyrosine-like fluorescent component to the humus-like fluorescent component, and the molecular aggregation state.

8. The method according to claim 6, wherein the method is characterized by, In the step S5, the molecular aggregation state of the humus-like fluorescent component is analyzed, specifically: based on the three-dimensional fluorescence spectrum data, it is detected whether the humus-like fluorescent component has a fluorescence self-quenching effect of non-linear reduction of fluorescence intensity with the increase of concentration, so as to determine the molecular aggregation state of the humus-like fluorescent component.

9. The method according to claim 7, wherein the method is characterized by, In the step S5, the biodegradability potential trend of the dissolved organic matter in the sample is determined, specifically: the hydrophilic-hydrophobic component ratio, the ratio of the tyrosine-like fluorescent component to the humus-like fluorescent component, and the molecular aggregation state are compared with the preset reference respectively, and the comparison results are comprehensively analyzed to obtain the judgment conclusion of the biodegradability potential trend.

10. A system for analyzing characteristics of dissolved organic matter in aquaculture effluent, for implementing the method for analyzing characteristics of dissolved organic matter in aquaculture effluent according to any one of claims 1-9, characterized in that, The method comprises the following modules: a data acquisition module, configured to acquire three-dimensional fluorescence spectrum data and liquid chromatography-organic carbon detection combined analysis data of a sample of aquaculture tail water to be tested; a first calculation module, configured to obtain a hydrophilic-hydrophobic component ratio of dissolved organic matter in the sample according to the liquid chromatography-organic carbon detection combined analysis data; a second calculation module, configured to obtain a ratio of a tyrosine-like fluorescent component to a humus-like fluorescent component of the dissolved organic matter in the sample according to the three-dimensional fluorescence spectrum data; a significant determination module, configured to determine whether the ratio of the tyrosine-like fluorescent component to the humus-like fluorescent component indicates that a significant humus-like component exists; a trend determination module, configured to, if not, determine a biodegradability potential trend of the dissolved organic matter in the sample based on the hydrophilic-hydrophobic component ratio and the ratio of the tyrosine-like fluorescent component to the humus-like fluorescent component; if yes, analyze the molecular aggregation state of the humus-like fluorescent component, and determine the biodegradability potential trend of the dissolved organic matter in the sample based on the hydrophilic-hydrophobic component ratio, the ratio of the tyrosine-like fluorescent component to the humus-like fluorescent component, and the molecular aggregation state.

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