Automatic blood analysis method and system for livestock farm

Abstract

The invention relates to the technical field of blood analysis, in particular to an automatic blood analysis method and system for livestock farms, which comprises the following steps: acquiring red cell membrane phase transition temperature data in blood, detecting the temperature change of red cell membrane phospholipid bilayer, recording the change of the membrane phase transition temperature in blood coagulation, and calculating the blood coagulation temperature. And screening synchronous change nodes of the membrane phase change temperature drift point and the charge mutation point to obtain the erythrocyte membrane phase change characteristic parameters. According to the invention, the biochemical state in the blood sample is identified to carry out early diagnosis and monitoring on the disease, and the temperature and charge change is comprehensively analyzed to accurately identify and predict the key point of blood coagulation, provide key data for clinic and support more effective recovery decision. Red blood cell morphological recovery and membrane tension change are monitored, new parameters are provided for evaluating the physiological status of red blood cells, the dynamic change of blood can be better understood, and the accuracy and efficiency of blood health evaluation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of blood analysis, and in particular to an automated blood analysis method and system for livestock farms. Background Art

[0002] The field of blood analysis technology involves the detection and analysis of chemical, biological or physical properties of blood samples. The core content of this technology is to evaluate and monitor the health status of humans or animals through various analytical techniques, such as blood cell counting, biochemical analysis and blood component determination. When systematically introducing this technology, it can be seen that blood analysis is mainly used for disease diagnosis, recovery effect monitoring and health status assessment. The technology application covers medical and health, clinical research and veterinary occasions.

[0003] Among them, the automated blood analysis method for livestock farms refers to the automated blood testing technology developed for animal health monitoring in the livestock industry. The technical matters targeted by the patent subject cover automated sampling, rapid analysis of blood components and data management, etc. Specifically, the blood collection, analysis and result output are completed by automated instruments. The means include automated sample processing equipment, sensors for biochemical analysis, and software systems for data recording and processing.

[0004] Existing blood analysis technologies have limitations in dynamically monitoring blood biochemical changes. They mainly focus on static analysis of blood samples, such as blood cell counts and biochemical analysis, ignoring the dynamic changes in cell status over time. This static analysis method lacks continuous monitoring of cell state changes during blood coagulation, making it difficult to capture subtle changes in blood samples during disease progression. Existing technologies fail to take into account key factors such as membrane phase transitions and charge distribution when analyzing the biophysical properties of red blood cells, limiting a comprehensive understanding of the complexity of blood samples and leading to errors in the diagnosis of some diseases. The lack of monitoring of dynamic and microscopic biophysical properties results in inaccurate recovery strategies, affecting disease management and optimization of recovery effects. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an automated blood analysis method and system for livestock farms.

[0006] In order to achieve the above object, the present invention adopts the following technical solution, an automated blood analysis method for livestock farms, comprising the following steps: S1: Obtain the phase transition temperature data of the red blood cell membrane in the blood, detect the temperature change of the red blood cell membrane phospholipid bilayer, record the change of the membrane phase transition temperature during blood coagulation, screen the synchronous change nodes of the membrane phase transition temperature drift point and the charge mutation point, and obtain the red blood cell membrane phase transition characteristic parameters; S2: using the red blood cell membrane phase change characteristic parameters, extracting the red blood cell membrane phase change temperature change curve and the charge mutation curve, analyzing the red blood cell membrane phase change temperature drift range, comparing the charge mutation interval with the temperature change synchronization section, screening the change nodes that meet the conditions, and obtaining the blood coagulation critical point data; S3: using the blood coagulation critical point data, applying a constant shear stress, and after releasing the shear stress, recording the red blood cell contour recovery time series, extracting the key frames in the recovery, evaluating the morphological symmetry from the recovery initial state to the recovery end state, and obtaining the red blood cell morphological recovery data; S4: Based on the red blood cell morphology recovery data, monitor the recovery of red blood cell membrane tension in the blood, record the membrane tension change, calculate the membrane stretch relaxation time, set the ratio of the recovery time constant to the membrane stretch relaxation time, obtain the red blood cell membrane tension change data, and issue an early warning for abnormal blood samples.

[0007] As a further scheme of the present invention, the red blood cell membrane phase change characteristic parameters include membrane phase change temperature drift rate, charge mutation rate, and temperature-charge synchronization node; the blood coagulation critical point data include membrane fluidity turning point, temperature drift boundary, charge change synchronization interval, and curve inflection point position; the red blood cell morphology recovery data include recovery symmetry index, contour recovery key frame, and morphology recovery duration; the red blood cell membrane tension change data include membrane tension recovery rate, stretch relaxation time constant, and tension-time matching node.

[0008] As a further solution of the present invention, the step of obtaining the red blood cell membrane phase change characteristic parameters is specifically as follows: S111: obtaining the phase transition temperature data of the red blood cell membrane in the blood, detecting the temperature change of the red blood cell membrane phospholipid bilayer, recording the membrane phase transition temperature of the red blood cell membrane during blood coagulation, recording the temperature change of the red blood cell membrane surface, establishing a temperature change curve, calculating the temperature change gradient, and obtaining the temperature change gradient value; S112: Based on the temperature change gradient value, measure the charge distribution on the surface of the red blood cell membrane, calculate the charge change rate per unit time, screen the charge change mutation point, and obtain the charge change rate value; S113: Call the temperature change gradient value and the charge change rate value, select the nodes where the two change synchronously, and use the formula: ; Calculate the deviation value of synchronous change, extract the synchronous change node, and obtain the phase change characteristic parameters of red blood cell membrane; in, Represents the synchronous change deviation value, Representative The temperature change at a time point, represents the time interval, represents the coupling coefficient between temperature change and charge change, Representative The charge change at a time point, Represents the total number of time points.

[0009] As a further solution of the present invention, the step of acquiring the blood coagulation critical point data is specifically as follows: S211: calling the red blood cell membrane phase change characteristic parameters, extracting the red blood cell membrane phase change temperature change curve and the charge mutation curve, identifying the location where the membrane fluidity decreases, calculating the membrane fluidity change rate, screening the interval of the change rate deviation, and obtaining the membrane fluidity change rate value; S212: Based on the membrane fluidity change rate value, analyze the temperature drift range of the red blood cell membrane phase change, calculate the temperature gradient of the drift interval, identify the charge mutation interval, and compare the temperature change synchronization section to select the change nodes that meet the synchronization change conditions and obtain the synchronization change node set; S213: Using the synchronous change node set, combined with the red blood cell membrane phase transition temperature change curve and the charge mutation curve inflection point change, the formula is used: ; Calculate blood coagulation parameters, screen inflection point mutation areas, and obtain blood coagulation critical point data; in, represents blood coagulation parameters, Representative The temperature change at a time point, Representative The charge change at a time point, Representative The change in membrane fluidity at each time point is Represents the total number of time points.

[0010] As a further solution of the present invention, the step of acquiring the red blood cell morphology recovery data is specifically as follows: S311: Based on the blood coagulation critical point data, a constant shear stress is applied to the red blood cells, a contour recovery time series of the red blood cell morphology after the shear force is released is recorded, the morphological change trajectory is identified, and the morphological parameter change rate at the differentiated time point is calculated to obtain the morphological parameter change rate data; S312: calling the morphological parameter change rate data, screening key frames representing key states of morphological changes during restoration, analyzing time intervals and positions corresponding to the key frames, and obtaining a key frame data set; S313: Using the key frame data set, combined with the morphological features of the initial state and the final state, the formula is adopted: ; Calculate the morphological symmetry offset and obtain the red blood cell morphological restoration data; in, Represents the symmetry offset of the shape, Represents a key frame The number of Represents the initial state morphological parameters corresponding to the a-th key frame, Represents the endpoint state morphological parameters corresponding to the a-th key frame.

[0011] As a further solution of the present invention, the step of acquiring the red blood cell membrane tension change data is specifically as follows: S411: Based on the red blood cell morphology recovery data, monitor the recovery of red blood cell membrane tension in the blood, calculate the red blood cell membrane tension change at the differentiated time points, screen the key points in the membrane tension recovery curve, identify the membrane tension change trend, and obtain the membrane tension change trend characteristic value; S412: calling the membrane tension change trend characteristic value, calculating the stretch relaxation time of the red blood cell membrane at the differentiated time point, setting the recovery time constant, and calculating the ratio of the recovery time constant to the membrane stretch relaxation time, using the formula: ; Calculate and obtain the membrane tension recovery ratio; in, represents the membrane tension recovery ratio, Representative The recovery time constant at the time point, Representative The membrane stretch relaxation time at a time point, represents the total number of time points; S413: calling the membrane tension recovery ratio, extracting key time points in the recovery that match the membrane tension change trend, screening and recording the membrane tension changes at the key time points, and obtaining red blood cell membrane tension change data.

[0012] As a further solution of the present invention, the method further comprises step S5: S5: Using the red blood cell membrane tension change data, set blood health assessment standards, classify and label blood samples, evaluate the correlation between blood coagulation critical point data and red blood cell morphology, screen typical blood characteristic data under differentiated diseases and health conditions, and obtain livestock blood health assessment results; The livestock blood health assessment results include coagulation state classification, disease characteristic markers, red blood cell morphology correlation degree, and blood health characteristic data.

[0013] As a further solution of the present invention, the steps for obtaining the livestock blood health assessment results are specifically as follows: S511: Based on the red blood cell membrane tension change data, calculate the red blood cell membrane tension fluctuation rate of the differentiated blood sample, perform numerical processing, and extract the peak value, trough value and deviation value to obtain the red blood cell membrane tension characteristic parameter; S512: Call the red blood cell membrane tension characteristic parameter, combine it with the blood coagulation critical point data, and use the formula: ; Calculate the membrane tension-coagulation critical point deviation, perform classification and labeling, and obtain the classification and labeling data of the coagulation state of the blood sample; in, Represents the membrane tension-solidification critical point deviation, Representative The red blood cell membrane tension characteristic parameters of blood samples, Representative Blood coagulation critical point data for blood samples, Represents the total number of blood samples, Representative The peak shift ratio of the blood samples, Representative Bias scaling factor for each blood sample; S513: Classify and label the blood sample coagulation state data according to the blood sample, combine with the red blood cell morphology data, analyze the morphological characteristics of the blood samples under differentiated health states, screen the characteristic morphological parameters under healthy and diseased blood states, extract the typical blood morphological characteristics under healthy and diseased states, and obtain the blood health assessment results of livestock.

[0014] The automated blood analysis system for livestock farms is used to perform the automated blood analysis method for livestock farms, and the system comprises: The red blood cell membrane phase change detection module obtains the red blood cell membrane phase change temperature data in the blood sample, measures the temperature change of the phospholipid bilayer, records the change of the membrane phase change temperature during coagulation, detects the charge distribution on the membrane surface, and selects the synchronous change nodes of the membrane phase change temperature drift point and the charge mutation point to obtain the red blood cell membrane phase change characteristic parameters; The red blood cell charge mutation analysis module extracts the temperature change curve and the charge mutation curve based on the red blood cell membrane phase change characteristic parameters, analyzes the charge mutation rate, identifies the charge mutation amplitude, screens the membrane phase change temperature drift and charge mutation synchronization point, and obtains the blood coagulation critical point data; The red blood cell morphology recovery determination module applies shear stress according to the blood coagulation critical point data, records the red blood cell recovery time series, extracts the recovery key frames, calculates the morphology symmetry, and obtains the red blood cell morphology recovery data; The tension change analysis module monitors the red blood cell membrane tension recovery process based on the red blood cell morphology recovery data, records the membrane tension change, calculates the membrane stretch relaxation time, evaluates the correlation between the recovery time constant and the membrane stretch relaxation time, and obtains the red blood cell membrane tension change data; The blood health assessment module calls the red blood cell membrane tension change data, analyzes the membrane tension change trend, calculates the membrane stretch relaxation time, screens the membrane tension change difference between healthy samples and abnormal samples, and obtains the blood health assessment result of livestock.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by obtaining the red blood cell membrane phase transition temperature data and measuring the charge distribution on the red blood cell membrane surface, a more accurate monitoring method is provided for blood coagulation. By recording the changes in the membrane phase transition temperature and charge distribution, the biochemical state in the blood sample can be more accurately identified, thereby enabling early diagnosis and monitoring of the disease. By comprehensively analyzing the changes in temperature and charge, the key points of blood coagulation can be more accurately identified and predicted, providing key data for clinicians and supporting more effective recovery decisions. Monitoring the recovery of red blood cell morphology and changes in membrane tension provides new parameters for evaluating the physiological state of red blood cells, which helps to better understand the dynamic changes of blood and improve the accuracy and efficiency of blood health assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the workflow of the present invention; Figure 2 It is a flow chart for obtaining the phase change characteristic parameters of the red blood cell membrane in the present invention; Figure 3 This is a flow chart for obtaining blood coagulation critical point data in the present invention; Figure 4 This is a flow chart for obtaining red blood cell morphology recovery data in the present invention; Figure 5 It is a flow chart for obtaining red blood cell membrane tension change data in the present invention; Figure 6 The present invention is a flowchart for obtaining the blood health assessment results of livestock animals. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0019] See also Figure 1 The present invention provides a technical solution, an automated blood analysis method for livestock farms, comprising the following steps: S1: Obtain the phase transition temperature data of the red blood cell membrane in the blood, detect the temperature change of the red blood cell membrane phospholipid bilayer, record the change of the membrane phase transition temperature during blood coagulation, measure the charge distribution on the surface of the red blood cell membrane, calculate the charge change rate, screen the synchronous change nodes of the membrane phase transition temperature drift point and the charge mutation point, and obtain the red blood cell membrane phase transition characteristic parameters; S2: Using the red blood cell membrane phase change characteristic parameters, extracting the red blood cell membrane phase change temperature change curve and charge mutation curve, identifying the location of membrane fluidity decline, analyzing the red blood cell membrane phase change temperature drift range, comparing the charge mutation interval and the temperature change synchronization section, screening the change nodes that meet the conditions, and calculating the blood coagulation parameters based on the curve inflection point changes to obtain the blood coagulation critical point data; S3: Using the blood coagulation critical point data, a constant shear stress is applied. After the shear stress is released, the red blood cell contour recovery time series is recorded, the key frames in the recovery are extracted, and the morphological symmetry from the initial state to the final state of the recovery is evaluated to obtain the red blood cell morphological recovery data; S4: Based on the red blood cell morphology recovery data, monitor the recovery of red blood cell membrane tension in the blood, record the membrane tension change, calculate the membrane stretch relaxation time, set the ratio of the recovery time constant to the membrane stretch relaxation time, extract the key moment when the change trends of the two in the recovery match, and obtain the red blood cell membrane tension change data; S5: Through the data of changes in red blood cell membrane tension, blood health assessment standards are set, blood samples are classified and labeled, the correlation between blood coagulation critical point data and red blood cell morphology is evaluated, typical blood characteristic data under differentiated diseases and health conditions are screened, and the blood health assessment results of livestock are obtained; The phase change characteristic parameters of red blood cell membrane include membrane phase change temperature drift rate, charge mutation rate, and temperature-charge synchronization node. The blood coagulation critical point data include membrane fluidity turning point, temperature drift boundary, charge change synchronization interval, and curve inflection point position. The red blood cell morphology recovery data include recovery symmetry index, contour recovery key frame, and morphology recovery duration. The red blood cell membrane tension change data include membrane tension recovery rate, stretch relaxation time constant, and tension-time matching node. The livestock blood health assessment results include coagulation state classification, disease characteristic markers, red blood cell morphology correlation degree, and blood health characteristic data.

[0020] See also Figure 2 , the specific steps for obtaining the phase transition characteristic parameters of red blood cell membrane are as follows: S111: obtaining the phase transition temperature data of the red blood cell membrane in the blood, detecting the temperature change of the red blood cell membrane phospholipid bilayer, recording the membrane phase transition temperature of the red blood cell membrane during blood coagulation, recording the temperature change of the red blood cell membrane surface, establishing a temperature change curve, calculating the temperature change gradient, and obtaining the temperature change gradient value; Obtain blood samples from livestock animals, ensure that the samples are fresh and uncontaminated, and draw blood from the veins of livestock animals mL of blood, use anticoagulants such as EDTA to prevent blood coagulation, use differential scanning calorimetry (DSC) to detect the temperature changes of the phospholipid bilayer of the red blood cell membrane, place the blood sample in the DSC, gradually increase the temperature, record the heat flow changes to determine the membrane phase transition temperature, set When the endothermic peak is observed, it indicates that this temperature is the membrane phase transition temperature. Use a high-precision temperature sensor, such as a thermocouple or infrared thermometer, to measure the temperature change rate on the surface of the red blood cell membrane. Touch the sensor probe to the red blood cell membrane and record the temperature change data over time. to Within seconds, the temperature Increase to , the temperature change rate is calculated as follows: ; Based on the data, a temperature change curve is established with time is the horizontal axis, temperature As the ordinate, draw a curve to reflect the trend of temperature change over time, and calculate the temperature gradient, which is defined as the derivative of the temperature change rate with respect to time: ; If the temperature change rate remains constant, the temperature change gradient is If the temperature change rate increases or decreases, the temperature change gradient is positive or negative. The temperature change gradient value is calculated and set to , get the temperature change gradient value.

[0021] S112: Based on the temperature change gradient value, measure the charge distribution on the surface of the red blood cell membrane, calculate the charge change rate per unit time, screen the charge change mutation point, and obtain the charge change rate value; Based on the temperature change gradient value, set to , it is inferred that the red blood cell membrane undergoes a phase change, which in turn affects the charge distribution on the membrane surface. A potential detection device, such as a Zeta potential analyzer, is used to measure the charge distribution on the red blood cell membrane surface. The red blood cells are suspended in a solution of low ionic strength, such as + Glucose solution, ensure that the cell morphology is normal to avoid morphological changes affecting the measurement results, start the Zeta potential analyzer, apply an electric field, measure the electrophoretic mobility of red blood cells, calculate the surface Zeta potential, and set the measured Zeta potential to mV, indicating that the red blood cell membrane surface is negatively charged, and the charge distribution data is continuously recorded. Measure once per second, continuously seconds, and a set of Zeta potential values ​​is obtained. The charge change rate per unit time is calculated and defined as: ; Set in the first Within seconds, the Zeta potential changes from mV changes to mV, the charge change rate is calculated as follows: ; Screening charge change mutation points, defined as the time point at which the charge change rate significantly increases or decreases, is set at Seconds, the charge changes rate from mV / s suddenly increases to mV / s, then Seconds is the charge change mutation point, and the charge change rate value is obtained and set to mV / s.

[0022] S113: Call the temperature change gradient value and the charge change rate value, select the nodes where the two change synchronously, and use the formula: ; Calculate the deviation value of synchronous change, extract the synchronous change node, and obtain the phase change characteristic parameters of red blood cell membrane; in, Represents the synchronous change deviation value, Representative The temperature change at a time point, represents the time interval, represents the coupling coefficient between temperature change and charge change, Representative The charge change at a time point, represents the total number of time points; Call the temperature change gradient value (set to ) and the charge change rate value (set to mV / s), divide the time into several equal intervals, and set the interval Each second is a node, and the temperature change of each node is recorded. and the charge change , set in the first Within seconds, , mV, set coupling coefficient Indicates the degree of influence of temperature change on charge change. Set , calculate the synchronization change deviation value of each node, is the time interval, set to Second: Substitute the formula to calculate the deviation value of the first node: ; Calculate for all nodes , set in Nodes ( seconds), The minimum value indicates that the synchronization between the temperature change and the charge change at this node is the best. The temperature and charge data of this node are extracted to obtain the phase change characteristic parameters of the red blood cell membrane.

[0023] See also Figure 3 , the specific steps for obtaining blood coagulation critical point data are: S211: calling the red blood cell membrane phase change characteristic parameters, extracting the red blood cell membrane phase change temperature change curve and charge mutation curve, identifying the location where the membrane fluidity decreases, calculating the membrane fluidity change rate, screening the change rate deviation interval, and obtaining the membrane fluidity change rate value; The temperature change curve and charge mutation curve of the red blood cell membrane phase transition are extracted. The surface temperature of the red blood cell membrane is measured by a temperature detection device, and the temperature changes at different time points are recorded. The temperature change curve is established by combining the time series data. The charge distribution on the surface of the red blood cell membrane is measured by a potential detection device, and the change amount of charge at different times is recorded to construct a charge mutation curve. In practical applications, the temperature and charge changes can be monitored synchronously by high-precision temperature sensors and potential measurement equipment. In the process of gradual cooling of the blood sample, the temperature change rate within a certain period of time is determined, and the charge change at the corresponding time point is recorded. Furthermore, according to the changing trends of the temperature change curve and the charge mutation curve, the temperature change rate and the charge change rate are calculated, and the key mutation area is extracted. The temperature change rate threshold is set to 0.2, and the charge change rate threshold is set to 0. The threshold is set based on the fact that at normal body temperature (37°C), the membrane fluidity of the red blood cell membrane remains stable, the temperature change rate is less than 0.15, and the charge change rate is less than , when the temperature change rate exceeds 0.2 or the charge change rate exceeds When , it indicates that the membrane fluidity has changed significantly. During the sample cooling process, if the temperature change rate exceeds the threshold at a certain moment, and the charge change rate exceeds the threshold simultaneously, the area is marked as the location where the membrane fluidity decreases, and the membrane fluidity change rate value is obtained.

[0024] S212: Based on the membrane fluidity change rate value, analyze the temperature drift range of the red blood cell membrane phase change, calculate the temperature gradient of the drift interval, identify the charge mutation interval, and compare the temperature change synchronization section, select the change nodes that meet the synchronization change conditions, and obtain the synchronization change node set; Analyze the temperature drift range of the red blood cell membrane phase transition, calculate the temperature drift at each time point, define the drift as the difference between the temperature at a certain time point and the initial temperature, and calculate the temperature gradient within the drift range. In the blood sample cooling experiment, the initial temperature is set to 37, and the temperature drops to 33 at a certain time point. The temperature drift at this time point is 4. Further calculate the temperature gradient. The gradient is defined as the ratio of the drift to the time interval. If the drift occurs at On the other hand, the charge mutation curve is used to identify the charge mutation interval, and the temperature change synchronization section is compared to select the time point that meets the synchronous change of temperature and charge. If the temperature gradient exceeds 0.2 at a certain moment (the benchmark value comes from the average temperature change rate of the red blood cell membrane phase transition in a normal blood environment, which is stable below 0.15, and exceeds 0.2, it indicates that the membrane phase transition has entered the nonlinear mutation stage), and the charge change rate exceeds (This reference value is measured based on the balanced state of blood charge distribution. When the red blood cell membrane is not coagulated, the charge change rate is stable at Below, if more than It indicates that the charge mutates on the membrane surface), then it is determined to be a synchronous change node, and the synchronous change node set is obtained.

[0025] S213: Using the synchronous change node set, combined with the red blood cell membrane phase transition temperature change curve and the charge mutation curve inflection point change, the formula is used: ; Calculate blood coagulation parameters, screen inflection point mutation areas, and obtain blood coagulation critical point data; in, represents blood coagulation parameters, Representative The temperature change at a time point, Representative The charge change at a time point, Representative The change in membrane fluidity at each time point is represents the total number of time points; The parameters in the formula are obtained through experimental data. The experimental scene is set. During the cooling process of the blood sample, the temperature change, charge change and membrane fluidity change at each time point are measured. In a certain experiment, three time point data are selected, which are =36.5, =35.8, =34.6, calculate the temperature change , , ; At the same time, the charge change is measured , , , and the change in membrane fluidity , , ; Substitute into the formula to calculate: ; ; The blood coagulation parameter was calculated to be 0.784. The significance of this value is that if , indicating that the blood coagulation process has entered the critical inflection point area. This benchmark value is measured through multiple experiments. The inflection point parameter in the coagulation process is located at If the value exceeds this range, it means that the blood coagulation trend has stabilized or reached the limit state. This result shows that the blood coagulation state at the selected time point can be characterized by this parameter. By further screening the inflection point mutation area, the blood coagulation critical point data can be obtained.

[0026] See also Figure 4 ,The specific steps for obtaining red blood cell morphology recovery data are: S311: Based on the blood coagulation critical point data, a constant shear stress is applied to the red blood cells, and the contour recovery time series of the red blood cell morphology after the shear force is released is recorded, the morphological change trajectory is identified, and the morphological parameter change rate at the differentiated time point is calculated to obtain the morphological parameter change rate data; It is necessary to apply constant shear stress to red blood cells in order to study the morphological changes of red blood cells under the action of external forces. In the actual implementation process, constant shear stress can be applied by microfluidic equipment, and a fluid shear device is set to subject red blood cells to a shear force with a constant flow rate in a specific channel. The morphology of red blood cells after the shear force is released is recorded, and the time series data of morphological evolution is collected. Real-time imaging is performed by a high-speed microscope camera, and the image processing technology is combined to obtain the red blood cell contour recovery time series. In the data processing link, an edge detection algorithm is used to segment the shape of the red blood cells, and the trajectory of the red blood cell morphology changing with time is tracked, and then the rate of change of morphological parameters at each time point is calculated, including the cell major-minor axis ratio, curvature, area ratio, etc. For the cell major-minor axis ratio, the major axis length of the red blood cell can be set to , the minor axis length is , calculate its morphological parameters: ; Among them, if , it indicates that the red blood cells are significantly deformed. , it is believed that the red blood cell morphology changes are minor; In the curvature calculation, the local curvature of any point on the red blood cell contour is defined as , which is calculated as: ; in, is the tangent angle on the curve, is the length of the tiny arc along the contour; After calculating the curvature distribution, the average curvature value of the entire red blood cell can be obtained. ,like , it is considered that the red blood cell morphology curvature is large; Calculate the area ratio and set the area of ​​the red blood cells at a certain time point during the morphological recovery process as , the stable area of ​​the final state is , then the area ratio The calculation is as follows: ; Among them, if , indicating that the red blood cell morphology has basically recovered. , indicating that the recovery is not complete, the rate of change of the parameter can be calculated by the difference method, such as: ; Obtain the morphological parameter change rate data.

[0027] S312: calling the morphological parameter change rate data, selecting key frames representing key states of morphological changes during restoration, analyzing the time intervals and positions corresponding to the key frames, and obtaining a key frame data set; Filter out key frames that can represent the key states of morphological changes. In the specific implementation process, the extreme value of the morphological change rate can be used as the judgment standard, that is, by calculating the change rate of the morphological parameters at each time point and comparing the rate difference between adjacent time points, if the rate change exceeds the set threshold, then the time point is determined to be a key time point. For example, the rate threshold is set to , if at a certain time point Corresponding change rate of the ratio of the major axis to the minor axis , and the rate change from the previous time point is greater than , then select this time point as the key frame, calculate the time interval and relative position of each frame in the selected key frames, and set the key frame time interval to , defined as: ; in, Representative The time of the key frame, The time span that reflects the key shape change, if the time interval between key frames , indicating that the morphological change process is slow. , the morphology changes rapidly. By statistically analyzing the time interval distribution of key frames, the morphological recovery process of red blood cells can be further described and a key frame data set can be established.

[0028] S313: Using the key frame data set, combined with the morphological characteristics of the initial state and the final state, the formula is used: ; Calculate the morphological symmetry offset and obtain the red blood cell morphological restoration data; in, Represents the symmetry offset of the shape, Represents a key frame The number of Represents the initial state morphological parameters corresponding to the a-th key frame, Represents the endpoint state morphological parameters corresponding to the a-th key frame; Parameter assignment and calculation: In the experiment, morphological parameters such as the ratio of the major axis to the minor axis, curvature, and area ratio were calculated and compared during the restoration process of different key frames; Set the total number of keyframes , the initial state morphological parameters of each key frame and endpoint state morphological parameters They are: ; ; ; ; ; Calculate the morphological symmetry offset of each keyframe: ; The result shows that the symmetry offset of the red blood cell morphology recovery data is 0.0749, which is within the set threshold of 0.1. Therefore, it can be determined that the red blood cell morphology recovery is relatively symmetrical, which is in line with the basic trend of the recovery process.

[0029] See also Figure 5 , the specific steps for obtaining the red blood cell membrane tension change data are: S411: Based on the red blood cell morphology recovery data, monitor the recovery of red blood cell membrane tension in the blood, calculate the change of red blood cell membrane tension at different time points, screen the key points in the membrane tension recovery curve, identify the trend of membrane tension change, and obtain the characteristic value of the membrane tension change trend; Use microscopic imaging equipment to collect red blood cell morphological characteristics, monitor the recovery of red blood cell membrane tension in the blood, select and process red blood cell images at different times, extract cell membrane edge information and calculate local curvature distribution, characterize membrane tension changes through dynamic changes in curvature distribution, set time series and normalize curvature changes at each moment, calculate the mean and standard deviation of curvature changes, extract the moment of significant change as the key point, calculate the membrane tension change rate by setting the time window, and set a certain moment Membrane tension at By the rate of change of curvature The calculation formula can be expressed as: ; in, is the empirical coefficient, determined by experiment, set ,exist At three moments, the curvature change rates are , the calculated values ​​of membrane tension are , , , screen out the key points in the membrane tension recovery curve, further analyze the changing trends between the key points, extract the key features of the changing trends in the membrane tension recovery process, and establish a characteristic curve model of membrane tension recovery based on the measurement data of different individual samples to obtain the characteristic values ​​of the membrane tension changing trend.

[0030] S412: Call the characteristic value of membrane tension change trend, calculate the stretch relaxation time of the red blood cell membrane at the differentiated time point, set the recovery time constant, and calculate the ratio of the recovery time constant to the membrane stretch relaxation time, using the formula: ; Calculate and obtain the membrane tension recovery ratio; in, represents the membrane tension recovery ratio, Representative The recovery time constant at the time point, Representative The membrane stretch relaxation time at a time point, represents the total number of time points; Parameter acquisition method: Membrane stretch relaxation time : No. The membrane stretch relaxation time at a certain time point indicates the time required for the red blood cell membrane to recover from the deformed state to the initial state at a specific time point. The deformation recovery time of red blood cells at different time points was measured experimentally. Atomic force microscopy (AFM) was used to apply a small force to the red blood cells and the time required for them to recover to the initial shape was recorded. According to relevant research, the Young's modulus of untreated red blood cells is about 8.04 kPa, which can be reduced to 0.93 kPa after treatment. Membrane tension change : No. The change in membrane tension at each time point indicates the degree of tension change of the red blood cell membrane at a specific time point. By measuring the tension change of the red blood cell membrane at different time points, a micropipette is used to apply isotropic tension to the red blood cells, and the elastic area compression modulus of the membrane is measured to be approximately 288 dyn / cm; Specific calculation process: In the experiment, three time points were selected , corresponding to the membrane stretch relaxation time and membrane tension change They are: Second, ; Second, ; Second, ; Substitute the values ​​into the formula to calculate: Calculate the numerator part: ; Calculate the denominator: ; ; ; Calculate the membrane tension recovery ratio: ; The results show that at the selected time point, the tension of the red blood cell membrane has recovered to a high degree and is close to a fully recovered state. The value can be used to evaluate the recovery capacity of red blood cell membrane under different environmental or treatment conditions.

[0031] S413: calling the membrane tension recovery ratio, extracting the key time points in the recovery that match the membrane tension change trend, screening and recording the membrane tension changes at the key time points, and obtaining the red blood cell membrane tension change data; Analyze the consistency between the membrane tension change trend and the ratio change during the recovery process, extract the key moments that match the membrane tension change trend during the recovery process, and set the key point extraction criteria, that is, if the membrane tension recovery ratio At a certain moment, the rate of change reaches the set threshold , then the moment is considered a critical moment and the setting ,calculate The rate of change at adjacent moments, , ,but , identify For the key moment, the membrane tension change data at the key moment is screened and recorded to obtain the red blood cell membrane tension change data.

[0032] See also Figure 6 , the specific steps for obtaining the results of livestock blood health assessment are: S511: based on the red blood cell membrane tension change data, calculating the red blood cell membrane tension fluctuation rate of the differentiated blood sample, performing numerical processing, and extracting the peak value, the trough value and the deviation value to obtain the red blood cell membrane tension characteristic parameters; Collect the red blood cell membrane tension fluctuations of multiple blood samples and record the data of each sample. For a group of blood samples from livestock animals, the red blood cell membrane tension of each sample can be measured by pressure testing equipment. For example, the initial tension of a sample is N / m, under the action of blood flow shear force, its maximum tension rises to N / m, stable at N / m. During the collection process, the sample environment temperature must be kept constant to eliminate the influence of environmental factors. The fluctuation rate of red blood cell membrane tension is calculated by the ratio of the maximum tension change to the initial value, that is, ,After obtaining the volatility of each sample, the volatility of all samples is statistically ,extracted, the maximum and minimum values ​​are calculated, and their relative deviations are calculated to obtain the ,characteristic parameters of red blood cell membrane tension.

[0033] S512: Call the red blood cell membrane tension characteristic parameters, combine the blood coagulation critical point data, and use the formula: ; Calculate the membrane tension-coagulation critical point deviation, perform classification and labeling, and obtain the classification and labeling data of the coagulation state of the blood sample; in, Represents the membrane tension-solidification critical point deviation, Representative The red blood cell membrane tension characteristic parameters of blood samples, Representative Blood coagulation critical point data for blood samples, Represents the total number of blood samples, Representative The peak shift ratio of the blood samples, Representative Bias scaling factor for each blood sample; Combined with the blood coagulation critical point data, the membrane tension variation of each sample under different blood coagulation states was analyzed. For a certain blood sample, its membrane tension characteristic parameter is: N / m, and the blood coagulation critical point data is measured as N / m, the membrane tension-solidification critical point offset value is calculated as N / m, in order to further quantify the degree of deviation of different samples, it is necessary to introduce deviation correction parameters; Set the number of blood samples collected from livestock animals , the offset values ​​of some samples are (unit: N / m), then calculate the corrected offset value of each sample, such as Can be set dynamically based on the offset amplitude, setting the maximum offset ratio to ,and Adjustment factors can be set according to individual blood characteristics. (dimensionless parameter), the calculation process is as follows: ; The results show that the membrane tension deviation of the blood sample is low, and it can be used for classification and labeling and coagulation state determination to obtain classification and labeling data of the coagulation state of the blood sample.

[0034] S513: Classify and label the data according to the coagulation state of the blood samples, combine the red blood cell morphology data, analyze the morphological characteristics of the blood samples under differentiated health conditions, screen the characteristic morphological parameters under healthy and diseased blood conditions, extract the typical blood morphological characteristics under healthy and diseased conditions, and obtain the blood health assessment results of livestock animals; Combined with the red blood cell morphology data, the morphological characteristics of blood samples under different health conditions were analyzed. In healthy samples, the red blood cell morphology was mainly biconcave disc-shaped, and its morphological parameters were mainly expressed as the average diameter. μm, thickness μm, while in disease samples, the morphology of red blood cells will be distorted, such as the average diameter increases to The blood morphology of the animal is 400 μm, and there are morphological abnormalities such as spinous processes and wrinkles. The morphological characteristic parameters in healthy and diseased blood states are further screened out. The typical morphological characteristics are summarized by calculating the morphological ratio, offset rate and other methods. The typical blood morphological characteristics in healthy and diseased states are obtained to obtain the blood health assessment results of livestock.

[0035] The automated blood analysis system for livestock farms is used to perform the automated blood analysis method for livestock farms, and the system comprises: The red blood cell membrane phase change detection module obtains the red blood cell membrane phase change temperature data in the blood sample, measures the temperature change of the phospholipid bilayer, records the change of the membrane phase change temperature during coagulation, detects the charge distribution on the membrane surface, and selects the synchronous change nodes of the membrane phase change temperature drift point and the charge mutation point to obtain the red blood cell membrane phase change characteristic parameters; The red blood cell charge mutation analysis module extracts the temperature change curve and charge mutation curve based on the red blood cell membrane phase change characteristic parameters, analyzes the charge mutation rate, identifies the charge mutation amplitude, screens the membrane phase change temperature drift and charge mutation synchronization point, and obtains the blood coagulation critical point data; The red blood cell morphology recovery measurement module applies shear stress according to the blood coagulation critical point data, records the red blood cell recovery time series, extracts the recovery key frames, calculates the morphological symmetry, and obtains the red blood cell morphology recovery data; The tension change analysis module monitors the red blood cell membrane tension recovery process based on the red blood cell morphology recovery data, records the membrane tension changes, calculates the membrane stretch relaxation time, evaluates the correlation between the recovery time constant and the membrane stretch relaxation time, and obtains the red blood cell membrane tension change data; The blood health assessment module calls the red blood cell membrane tension change data, analyzes the membrane tension change trend, calculates the membrane stretch relaxation time, screens the membrane tension change differences between healthy samples and abnormal samples, and obtains the blood health assessment results of livestock.

[0036] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An automated blood analysis method for livestock farms, characterized in that: The following steps are involved: S1: Obtain the phase transition temperature data of the red blood cell membrane in the blood, detect the temperature change of the red blood cell membrane phospholipid bilayer, record the change of the membrane phase transition temperature during blood coagulation, screen the synchronous change nodes of the membrane phase transition temperature drift point and the charge mutation point, and obtain the red blood cell membrane phase transition characteristic parameters; S2: using the red blood cell membrane phase change characteristic parameters, extracting the red blood cell membrane phase change temperature change curve and the charge mutation curve, analyzing the red blood cell membrane phase change temperature drift range, comparing the charge mutation interval with the temperature change synchronization section, screening the change nodes that meet the conditions, and obtaining the blood coagulation critical point data; S3: using the blood coagulation critical point data, applying a constant shear stress, and after releasing the shear stress, recording the red blood cell contour recovery time series, extracting the key frames in the recovery, evaluating the morphological symmetry from the recovery initial state to the recovery end state, and obtaining the red blood cell morphological recovery data; S4: Based on the red blood cell morphology recovery data, monitor the recovery of red blood cell membrane tension in the blood, record the membrane tension change, calculate the membrane stretch relaxation time, set the ratio of the recovery time constant to the membrane stretch relaxation time, obtain the red blood cell membrane tension change data, and issue an early warning for abnormal blood samples.

2. The automated blood analysis method for livestock farms according to claim 1, characterized in that: The red blood cell membrane phase change characteristic parameters include membrane phase change temperature drift rate, charge mutation rate, and temperature-charge synchronization node; the blood coagulation critical point data include membrane fluidity turning point, temperature drift boundary, charge change synchronization interval, and curve inflection point position; the red blood cell morphology recovery data include recovery symmetry index, contour recovery key frame, and morphology recovery duration; the red blood cell membrane tension change data include membrane tension recovery rate, stretch relaxation time constant, and tension-time matching node.

3. The automated blood analysis method for livestock farms according to claim 1, characterized in that: The steps for obtaining the red blood cell membrane phase change characteristic parameters are specifically as follows: S111: obtaining the phase transition temperature data of the red blood cell membrane in the blood, detecting the temperature change of the red blood cell membrane phospholipid bilayer, recording the membrane phase transition temperature of the red blood cell membrane during blood coagulation, recording the temperature change of the red blood cell membrane surface, establishing a temperature change curve, calculating the temperature change gradient, and obtaining the temperature change gradient value; S112: Based on the temperature change gradient value, measure the charge distribution on the surface of the red blood cell membrane, calculate the charge change rate per unit time, screen the charge change mutation point, and obtain the charge change rate value; S113: Call the temperature change gradient value and the charge change rate value, select the nodes where the two change synchronously, and use the formula: ； Calculate the deviation value of synchronous change, extract the synchronous change node, and obtain the phase change characteristic parameters of red blood cell membrane; in, Represents the synchronous change deviation value, Representative The temperature change at a time point, represents the time interval, represents the coupling coefficient between temperature change and charge change, Representative The charge change at a time point, Represents the total number of time points.

4. The automated blood analysis method for livestock farms according to claim 3, characterized in that: The steps for obtaining the blood coagulation critical point data are specifically as follows: S211: calling the red blood cell membrane phase change characteristic parameters, extracting the red blood cell membrane phase change temperature change curve and the charge mutation curve, identifying the location where the membrane fluidity decreases, calculating the membrane fluidity change rate, screening the interval of the change rate deviation, and obtaining the membrane fluidity change rate value; S212: Based on the membrane fluidity change rate value, analyze the temperature drift range of the red blood cell membrane phase change, calculate the temperature gradient of the drift interval, identify the charge mutation interval, and compare the temperature change synchronization section to select the change nodes that meet the synchronization change conditions and obtain the synchronization change node set; S213: Using the synchronous change node set, combined with the red blood cell membrane phase transition temperature change curve and the charge mutation curve inflection point change, the formula is used: ； Calculate blood coagulation parameters, screen inflection point mutation areas, and obtain blood coagulation critical point data; in, represents blood coagulation parameters, Representative The temperature change at a time point, Representative The charge change at a time point, Representative The change in membrane fluidity at each time point is Represents the total number of time points.

5. The automated blood analysis method for livestock farms according to claim 4, characterized in that: The steps for obtaining the red blood cell morphology recovery data are specifically as follows: S311: Based on the blood coagulation critical point data, a constant shear stress is applied to the red blood cells, a contour recovery time series of the red blood cell morphology after the shear force is released is recorded, the morphological change trajectory is identified, and the morphological parameter change rate at the differentiated time point is calculated to obtain the morphological parameter change rate data; S312: calling the morphological parameter change rate data, screening key frames representing key states of morphological changes during restoration, analyzing time intervals and positions corresponding to the key frames, and obtaining a key frame data set; S313: Using the key frame data set, combined with the morphological features of the initial state and the final state, the formula is adopted: ； Calculate the morphological symmetry offset and obtain the red blood cell morphological restoration data; in, Represents the symmetry offset of the shape, Represents a key frame The number of Represents the initial state morphological parameters corresponding to the a-th key frame, Represents the endpoint state morphological parameters corresponding to the a-th key frame.

6. The automated blood analysis method for livestock farms according to claim 5, characterized in that: The steps for obtaining the red blood cell membrane tension change data are specifically as follows: S411: Based on the red blood cell morphology recovery data, monitor the recovery of red blood cell membrane tension in the blood, calculate the red blood cell membrane tension change at the differentiated time points, screen the key points in the membrane tension recovery curve, identify the membrane tension change trend, and obtain the membrane tension change trend characteristic value; S412: calling the membrane tension change trend characteristic value, calculating the stretch relaxation time of the red blood cell membrane at the differentiated time point, setting the recovery time constant, and calculating the ratio of the recovery time constant to the membrane stretch relaxation time, using the formula: ； Calculate and obtain the membrane tension recovery ratio; in, represents the membrane tension recovery ratio, Representative The recovery time constant at the time point, Representative The membrane stretch relaxation time at a time point, represents the total number of time points; S413: calling the membrane tension recovery ratio, extracting key time points in the recovery that match the membrane tension change trend, screening and recording the membrane tension changes at the key time points, and obtaining red blood cell membrane tension change data.

7. The automated blood analysis method for livestock farms according to claim 1, characterized in that: The method further comprises step S5: S5: Using the red blood cell membrane tension change data, set blood health assessment standards, classify and label blood samples, evaluate the correlation between blood coagulation critical point data and red blood cell morphology, screen typical blood characteristic data under differentiated diseases and health conditions, and obtain livestock blood health assessment results; The livestock blood health assessment results include coagulation state classification, disease characteristic markers, red blood cell morphology correlation degree, and blood health characteristic data.

8. The automated blood analysis method for livestock farms according to claim 7, characterized in that: The steps for obtaining the livestock blood health assessment results are specifically as follows: S511: Based on the red blood cell membrane tension change data, calculate the red blood cell membrane tension fluctuation rate of the differentiated blood sample, perform numerical processing, and extract the peak value, trough value and deviation value to obtain the red blood cell membrane tension characteristic parameter; S512: Call the red blood cell membrane tension characteristic parameter, combine it with the blood coagulation critical point data, and use the formula: ； Calculate the membrane tension-coagulation critical point deviation, perform classification and labeling, and obtain the classification and labeling data of the coagulation state of the blood sample; in, represents the membrane tension-solidification critical point deviation, Representative The red blood cell membrane tension characteristic parameters of blood samples, Representative Blood coagulation critical point data for blood samples, Represents the total number of blood samples, Representative The peak shift ratio of the blood samples, Representative Bias scaling factor for each blood sample; S513: Classify and label the blood sample coagulation state data according to the blood sample, combine with the red blood cell morphology data, analyze the morphological characteristics of the blood samples under differentiated health states, screen the characteristic morphological parameters under healthy and diseased blood states, extract the typical blood morphological characteristics under healthy and diseased states, and obtain the blood health assessment results of livestock.

9. An automated blood analysis system for livestock farms, characterized in that: According to any one of claims 1 to 8, the automated blood analysis method for livestock farms comprises: The red blood cell membrane phase change detection module obtains the red blood cell membrane phase change temperature data in the blood sample, measures the temperature change of the phospholipid bilayer, records the change of the membrane phase change temperature during coagulation, detects the charge distribution on the membrane surface, and selects the synchronous change nodes of the membrane phase change temperature drift point and the charge mutation point to obtain the red blood cell membrane phase change characteristic parameters; The red blood cell charge mutation analysis module extracts the temperature change curve and the charge mutation curve based on the red blood cell membrane phase change characteristic parameters, analyzes the charge mutation rate, identifies the charge mutation amplitude, screens the membrane phase change temperature drift and charge mutation synchronization point, and obtains the blood coagulation critical point data; The red blood cell morphology recovery determination module applies shear stress according to the blood coagulation critical point data, records the red blood cell recovery time series, extracts the recovery key frames, calculates the morphology symmetry, and obtains the red blood cell morphology recovery data; The tension change analysis module monitors the red blood cell membrane tension recovery process based on the red blood cell morphology recovery data, records the membrane tension change, calculates the membrane stretch relaxation time, evaluates the correlation between the recovery time constant and the membrane stretch relaxation time, and obtains the red blood cell membrane tension change data; The blood health assessment module calls the red blood cell membrane tension change data, analyzes the membrane tension change trend, calculates the membrane stretch relaxation time, screens the membrane tension change difference between healthy samples and abnormal samples, and obtains the blood health assessment result of livestock.

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