Sturgeon huso culture data comprehensive management method and system

Abstract

The invention discloses a sturgeon breeding data integrated management method and system, and relates to the technical field of data management, the system comprises an information collection module, a data management module and a breeding behavior module, the information collection module is used for monitoring the movement track of each sturgeon and weighing the body weight of the sturgeon, and the data management module is used for managing the body weight of the sturgeon; the data management module is used for storing and calculating various counted data and establishing an independent data portrait for each sturgeon, the breeding behavior module is used for determining sturgeon individuals needing to be caught and bred, and the information collection module comprises a PIT chip, a PIT signal reader-writer, a sonar mark, a sonar receiver and an identity confirmation module. The PIT signal reader-writer and the sonar receiver are electrically connected with the identity confirmation module, and the PIT chip is implanted into the back muscle of the sturgeon and used for marking the identity of each sturgeon.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and specifically to a comprehensive management method and system for sturgeon farming data. Background Art

[0002] Sturgeon is a large carnivorous fish, which is widely farmed after domestication. Due to the benthic characteristics of sturgeon, it usually looks for food and habitats in fixed positions, and its living space is relatively independent. Wild breeding may be affected by climate, resulting in uncertainties. During the breeding cycle, breeders usually catch individuals with breeding potential and release them into specific areas for breeding.

[0003] In the prior art, when screening for seedlings and catching sturgeon for consumption, usually larger individuals are selected for breeding and catching. However, it is difficult to screen out individuals with more delicious meat only based on body size. The factors affecting the deliciousness of sturgeon meat are highly related to its usual activity level. Individuals with a stronger predatory desire and activity level have a lower fat percentage and a denser distribution of red muscle fibers. However, it is difficult to quantify the factor of activity level. Therefore, it is necessary to design a comprehensive management method and system for sturgeon farming data for precise screening. Summary of the Invention

[0004] The purpose of the present invention is to provide a comprehensive management method and system for sturgeon farming data to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the present invention provides the following technical solution: A comprehensive management system for sturgeon farming data, including an information collection module, a data management module, and a farming behavior module. The information collection module is used to monitor the activity trajectories of individual sturgeons and weigh the weights of sturgeons. The data management module is used to store and calculate various statistically obtained data and establish a separate data profile for each sturgeon. The farming behavior module is used to determine the sturgeon individuals that need to be caught and bred.

[0006] According to the above technical solution, the information collection module includes a PIT chip, a PIT signal reader / writer, a sonar tag, a sonar receiver, and an identity confirmation module. The PIT signal reader / writer and the sonar receiver are electrically connected to the identity confirmation module. The PIT chip is implanted in the back muscle of the sturgeon to mark the identity of each sturgeon. The PIT signal reader / writer is used to read the identity identifier of the sturgeon individual during fishing. The sonar tag is implanted in the abdominal cavity of the sturgeon to confirm the position of the sturgeon by periodically sending sonar signals. The sonar receiver is used to receive sonar signals in real time. The identity confirmation module is used to correspond to the identity information of each sturgeon;

[0007] The data management module includes a data storage module, a time statistics module, a breeding time limit module, a distance statistics module, an activity calculation module, a weight weighing unit, and a weight change calculation module. The data storage module is electrically connected to the PIT signal reader / writer and the sonar receiver. The time statistics module is electrically connected to the breeding time limit module. The weight weighing unit is electrically connected to the weight change calculation module. The data storage module is used to store the identity information data, weight data, and activity data of the sturgeon. The time statistics module is used to record the current time each time data is statistically analyzed. The breeding time limit module is used to set the annual breeding cycle of the sturgeon. The distance statistics module is used to record the orientation and distance between the sonar tag in the sturgeon and the sonar receiver. The activity calculation module is used to statistically analyze the activity of the sturgeon based on the changes in the orientation and distance between the sonar tag and the sonar receiver. The weight weighing unit is used to weigh the captured sturgeon, and the weight change calculation module is used to calculate the weight change of the sturgeon;

[0008] The aquaculture behavior module includes a weight assignment module, a breeding selection module, and a fishing selection module. The weight assignment module is electrically connected to the breeding time limit module. The breeding selection module and the fishing selection module are electrically connected to the weight assignment module. The weight assignment module is used to adjust the weights of the reference weight and activity when fishing according to the interval between the current time and the breeding cycle. The breeding selection module is used to select the sturgeon individuals that need to breed, and the fishing selection module is used to select the sturgeon individuals that need to be fished.

[0009] A comprehensive management method for sturgeon aquaculture data includes the following steps:

[0010] S1. When the sturgeon seedlings grow to a certain stage, implant a PIT chip and a sonar tag into their bodies, establish an independent identity for each sturgeon individual, place a sonar receiver at a specific location in the aquaculture area, and receive the position signals of each sturgeon at fixed intervals to obtain their activity data;

[0011] S2. Catch the sturgeon at regular intervals for weighing, statistically analyze the weight change, predict the future weight, and correct the predicted weight value according to the weight of the sturgeon statistically analyzed during weighing;

[0012] S3. When fishing and breeding are required, determine the fishing targets and breeding targets according to the interval between the current time and the breeding cycle, combined with the predicted weight and historical activity of the sturgeon;

[0013] S4. After selecting the targets, carry out fishing and breeding selection. The sturgeon selected for breeding are put into a specific area for breeding after being caught until the breeding cycle ends, and then the sturgeon are put back into the aquaculture area.

[0014] According to the above technical solution, in the said S1, the method for obtaining the activity data is as follows:

[0015] S1-1: Taking the sonar receiver as the origin of the coordinate system, establishing a three-dimensional rectangular coordinate system, statistically recording the positions of each individual sturgeon at fixed time intervals, obtaining the xyz-axis coordinate values, and forming a coordinate set {(x1y1z1), (x2y2z2), …, (x n y n z n ), where n is the number of sturgeons, calculating the spatial distance of the sturgeon coordinates between the previous and the next statistical times {l1, l2, …, l i}, where i + 1 is the number of statistical times;

[0016] S1-2: The activity data of the sturgeon is the result of weighted operations on the spatial distances of coordinates statistically recorded at different times, that is, the activity Q = ∑a i l i , the weight coefficients of each spatial distance of coordinates are different, and all the weight coefficients form an arithmetic sequence {a1, a2, … a i}, the closer to the last statistical time, the greater the weight coefficient of the spatial distance of coordinates, the value of a i is constant, and the smaller the difference between the front and back terms in the arithmetic sequence with the increase of the number of statistical times. The advantage of this kind of statistics is that the closer to the time of the last fishing and breeding, the more it can reflect the current physical condition of the sturgeon, and it is not possible to only count the activity of the sturgeon recently, because there may be single statistical deviations, and it can objectively reflect the overall activity of the sturgeon.

[0017] According to the above technical solution, in the said S2, the specific method for predicting the future weight is as follows:

[0018] S2-1: Statistically recording the data of the weight change of all sturgeons in the system history from the growth and development stage to the mature stage over time, obtaining the weight growth curves of sturgeon seedlings with different initial weights over time, corresponding the current sturgeon seedlings to the weight growth curves that match their initial weights, and obtaining the weight prediction function f(t), and the value of f(t) is the weight prediction value;

[0019] S2-2. With each capture, the weight is statistically measured to obtain the deviation value k between the measured weight value and the predicted value of this sturgeon. If the measured value is greater than the predicted value, k is positive; otherwise, k is negative. The weight prediction value f(t) is modified to f(t) + μkΔt, where μ is the correction amplitude coefficient and Δt is the time elapsed from the last time the weight of this sturgeon was statistically measured to the current time. Δt no longer increases after the current time reaches the mature stage of the sturgeon. As the number of times of weight statistics increases, μ decreases linearly. The advantage of this is that it is possible to predict the weights of all sturgeons when preparing for fishing, and then select the appropriate ones for fishing, without having to measure each sturgeon after fishing all of them, reducing the number of fishing times. As the number of statistics increases, the weight growth area of the sturgeon becomes stable, and the adjustment amplitude decreases, which can avoid the situation of excessive deviation from the actual value caused by excessive adjustment.

[0020] According to the above technical solution, in S3, the specific method for determining the fishing target and the breeding target is as follows:

[0021] S3-1. When fishing, the predicted weight value and activity level of the sturgeon are used as the selection criteria. Outside the annual breeding cycle, more emphasis is placed on selecting sturgeons with a large activity level for fishing. Inside the annual breeding cycle, more emphasis is placed on selecting sturgeons with a large predicted weight value for fishing.

[0022] S3-2. Inside the annual breeding cycle, more emphasis is placed on selecting sturgeons with a large activity level for breeding and selection, so that the offspring of the selected sturgeons have a stronger predation desire and activity level.

[0023] According to the above technical solution, in S3-1, the fishing priority value is calculated, that is, the fishing priority value E of the sturgeon = αQ + βf(t), and the fishing priority values E of each sturgeon are sorted, and several sturgeons with the largest E are selected for fishing, where α is the activity level weight coefficient and β is the weight weight coefficient. When the fishing time is outside the breeding cycle, the number of days m between the fishing day and the breeding cycle is calculated, where When the fishing time is inside the breeding cycle, where τ is the breeding cycle adjustment coefficient and m0 is the minimum set value of the activity level weight ratio. The advantage of this setting is that the most active individuals are not fished during the breeding cycle, and the currently most active and most fertile individuals can be selected for breeding to improve the breeding rate. The activity level during other non-breeding times has less reference value for breeding, and individuals with a large activity level during this period are more likely to have more delicious meat.

[0024] According to the above technical solution, in S3-2, inside the annual breeding cycle, after setting the lower limit f of the breeding weight min all sturgeons with predicted weight values within f minSort the sturgeon according to the activity level Q, and select several sturgeons with the largest predicted weight value f(t) for capture and breeding according to the selected number of sturgeons to be bred.

[0025] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: In the present invention, the PIT chip is combined with the sonar marking technology to track the activity trajectories of individual sturgeons, obtain their activity data, and count the weights of the captured sturgeons. According to the breeding cycle of the sturgeons, the fishing and breeding targets are screened. Individuals with a greater activity level are selected for breeding during the time period close to the breeding cycle, while individuals with a larger body size are focused on for fishing. Individuals with a greater activity level are selected for fishing during the time period far from the breeding cycle. On the premise of ensuring that the sturgeon population becomes increasingly high-quality in terms of meat quality with artificial breeding iteration, consumers can enjoy individuals with fresher meat to the greatest extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0027] Figure 1 is a schematic diagram of the overall module structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0029] Please refer to Figure 1 , the present invention provides a technical solution: A comprehensive management system for sturgeon breeding data, including an information collection module, a data management module, and a breeding behavior module. The information collection module is used to monitor the activity trajectories of individual sturgeons and weigh the weights of the sturgeons. The data management module is used to store and calculate various statistical data and establish a separate data profile for each sturgeon. The breeding behavior module is used to determine the individual sturgeons that need to be captured and bred;

[0030] The information collection module includes a PIT chip, a PIT signal reader / writer, a sonar tag, a sonar receiver, and an identity confirmation module. The PIT signal reader / writer and the sonar receiver are electrically connected to the identity confirmation module. The PIT chip is implanted in the dorsal muscle of the sturgeon for marking the identity of each sturgeon. The PIT signal reader / writer is used to read the identity identifier of the sturgeon individual during fishing. The sonar tag is implanted in the abdominal cavity of the sturgeon to confirm the position of the sturgeon by periodically sending sonar signals. The sonar receiver is used to receive sonar signals in real time. The identity confirmation module is used to correspond to the identity information of each sturgeon;

[0031] The data management module includes a data storage module, a time statistics module, a breeding time limit module, a distance statistics module, an activity calculation module, a weight weighing unit, and a weight change calculation module. The data storage module is electrically connected to the PIT signal reader / writer and the sonar receiver. The time statistics module is electrically connected to the breeding time limit module. The weight weighing unit is electrically connected to the weight change calculation module. The data storage module is used to store the identity information data, weight data, and activity data of the sturgeon. The time statistics module is used to record the current time each time data is statistically analyzed. The breeding time limit module is used to set the annual breeding cycle of the sturgeon. The distance statistics module is used to record the orientation and distance between the sonar tag in the sturgeon and the sonar receiver. The activity calculation module is used to statistically analyze the activity of the sturgeon based on the changes in the orientation and distance between the sonar tag and the sonar receiver. The weight weighing unit is used to weigh the captured sturgeon, and the weight change calculation module is used to calculate the weight change of the sturgeon;

[0032] The aquaculture behavior module includes a weight assignment module, a breeding selection module, and a fishing selection module. The weight assignment module is electrically connected to the breeding time limit module. The breeding selection module and the fishing selection module are electrically connected to the weight assignment module. The weight assignment module is used to adjust the weights of the reference weight and activity during fishing according to the interval between the current time and the breeding cycle. The breeding selection module is used to select the sturgeon individuals that need to breed. The fishing selection module is used to select the sturgeon individuals that need to be fished;

[0033] A comprehensive management method for sturgeon aquaculture data includes the following steps:

[0034] S1. When the sturgeon seedlings grow to a certain stage, implant a PIT chip and a sonar tag into their bodies to establish an independent identity identifier for each sturgeon individual. Place a sonar receiver at a specific position in the aquaculture area to receive the position signals of each sturgeon at fixed intervals to obtain their activity data;

[0035] S2. Catch sturgeons at regular intervals for weighing, statistically analyze the weight changes, predict the future weight, and correct the predicted weight value according to the weight of the sturgeon statistically analyzed during weighing;

[0036] S3. When fishing and breeding are required, determine the fishing targets and breeding targets according to the interval between the current time and the breeding cycle, in combination with the predicted weight and historical activity level of the Huso dauricus.

[0037] S4. After selecting the targets, carry out fishing and breeding selection. The Huso dauricus selected for breeding is released into a specific area for breeding after being captured until the end of the breeding cycle, and then the Huso dauricus is put back into the breeding area again.

[0038] In S1, the method for obtaining the activity level data is as follows:

[0039] S1-1. Taking the sonar receiver as the origin of the coordinate system, establish a three-dimensional rectangular coordinate system, and count the positions of each Huso dauricus individual at fixed time intervals to obtain the coordinate values of the x, y, and z axes, forming a coordinate set {(x1y1z1), (x2y2z2), …, (x n y n z n ), where n is the number of Huso dauricus, and calculate the spatial distance of the Huso dauricus coordinates between the two statistical times {l1, l2, …, l i}, where i + 1 is the number of statistical times;

[0040] S1-2. The activity level data of the Huso dauricus is the result of weighted operations on the spatial distances of coordinates statistically obtained at different times, that is, the activity level Q = ∑a i l i , and the weight coefficients of each spatial distance of coordinates are different. All the weight coefficients form an arithmetic sequence {a1, a2, … a i}. The closer to the last statistical time, the greater the weight coefficient of the spatial distance of coordinates. The value of a i is constant, and the smaller the difference between the two adjacent terms in the arithmetic sequence with the increase of the number of statistical times. The advantage of this kind of statistics is that the closer to the time of the last fishing and breeding, the more it can reflect the current physical condition of the Huso dauricus, and it is not possible to only count the activity level of the Huso dauricus recently, because there may be single statistical deviations, which can objectively reflect the overall activity level of the Huso dauricus;

[0041] In S2, the specific method for predicting the future weight is as follows:

[0042] S2-1. Statistically analyze the data of the weight change of all Huso dauricus in the system history from the growth and development stage to the mature stage over time, obtain the weight growth curves of Huso dauricus seedlings with different initial weights over time, map the current Huso dauricus seedlings to the weight growth curves corresponding to their initial weights, and obtain the predicted function f(t) of the weight over time. The value of f(t) is the weight prediction value;

[0043] S2-2. With each capture, the weight is statistically measured to obtain the deviation value k between the actual measured weight and the predicted weight of this sturgeon. If the actual measured value is greater than the predicted value, k is positive; otherwise, k is negative. The weight prediction value f(t) is modified to f(t) + μkΔt, where μ is the correction amplitude coefficient and Δt is the time elapsed from the last time this sturgeon's weight was statistically measured to the current time. Δt no longer increases after the current time reaches the mature stage of the sturgeon. As the number of times of statistically measuring the weight increases, μ decreases linearly. The advantage of this is that it is possible to predict the weights of all sturgeons when preparing for fishing, and then select the appropriate ones for fishing, without having to measure each sturgeon after fishing all of them, reducing the number of fishing times. As the number of statistical times increases, the weight growth area of the sturgeon becomes stable and the adjustment amplitude decreases, which can avoid the situation of excessive deviation from the actual value caused by excessive adjustment;

[0044] In S3, the specific method for determining the fishing targets and breeding targets is as follows:

[0045] S3-1. When fishing, the predicted weight and activity level of the sturgeon are used as selection criteria. Outside the annual breeding cycle, more emphasis is placed on selecting sturgeons with high activity levels for fishing. Inside the annual breeding cycle, more emphasis is placed on selecting sturgeons with large predicted weights for fishing;

[0046] S3-2. Inside the annual breeding cycle, more emphasis is placed on selecting sturgeons with high activity levels for breeding and selection, so that the offspring of the selected sturgeons have stronger predatory desires and activity levels;

[0047] In S3-1, the fishing priority value is calculated, that is, the fishing priority value E of the sturgeon = αQ + βf(t), and the fishing priority values E of each sturgeon are sorted, and several sturgeons with the largest E are selected for fishing, where α is the activity level weight coefficient and β is the weight weight coefficient. When the fishing time is outside the breeding cycle, calculate the number of days m between the fishing day and the breeding cycle, where When the fishing time is inside the breeding cycle, where τ is the breeding cycle adjustment coefficient and m0 is the minimum set value of the activity level weight ratio. The advantage of this setting is that the most active individuals are not fished during the breeding cycle, and the currently most active and most fertile individuals can be selected for breeding to improve the breeding rate. The activity levels during other non-breeding times have less reference value for breeding, and individuals with high activity levels during this time are more likely to have more delicious meat;

[0048] In S3-2, inside the annual breeding cycle, after setting the lower limit f of the breeding weight min After that, for all predicted weights within f minSort the sturgeon according to the activity level Q, and select several sturgeons with the largest predicted weight value f(t) for capture and breeding according to the selected number of sturgeons to be bred.

[0049] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device.

[0050] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A comprehensive management system for sturgeon farming data, characterized in that: It includes an information collection module, a data management module, and a farming behavior module. The information collection module is used to monitor the activity trajectories of individual sturgeon and weigh the sturgeon. The data management module is used to store and calculate various statistical data and create a separate data profile for each sturgeon. The farming behavior module is used to determine the individual sturgeon that need to be fished and reproduced.

2. The integrated management system for sturgeon farming data according to claim 1, wherein: The information collection module includes a PIT chip, a PIT signal reader / writer, a sonar tag, a sonar receiver, and an identity confirmation module. The PIT signal reader / writer and the sonar receiver are electrically connected to the identity confirmation module. The PIT chip is implanted in the dorsal muscle of the sturgeon to mark the identity of each sturgeon. The PIT signal reader / writer is used to read the identity identifier of the sturgeon individual during fishing. The sonar tag is implanted in the abdominal cavity of the sturgeon to confirm the position of the sturgeon by periodically sending sonar signals. The sonar receiver is used to receive sonar signals in real time. The identity confirmation module is used to correspond to the identity information of each sturgeon. The data management module includes a data storage module, a time statistics module, a reproduction time limit module, a distance statistics module, an activity calculation module, a weight weighing unit, and a weight change calculation module. The data storage module is electrically connected to the PIT signal reader / writer and the sonar receiver. The time statistics module is electrically connected to the reproduction time limit module. The weight weighing unit is electrically connected to the weight change calculation module. The data storage module is used to store the identity information data, weight data, and activity data of the sturgeon. The time statistics module is used to record the current time each time data is statistically analyzed. The reproduction time limit module is used to set the annual reproduction cycle of the sturgeon. The distance statistics module is used to record the orientation and distance between the sonar tag in the sturgeon and the sonar receiver. The activity calculation module is used to statistically analyze the activity of the sturgeon based on the changes in the orientation and distance between the sonar tag and the sonar receiver. The weight weighing unit is used to weigh the captured sturgeon. The weight change calculation module is used to calculate the weight change of the sturgeon. The farming behavior module includes a weight allocation module, a reproduction selection module, and a fishing selection module. The weight allocation module is electrically connected to the reproduction time limit module. The reproduction selection module and the fishing selection module are electrically connected to the weight allocation module. The weight allocation module is used to adjust the weights of the reference weight and activity during fishing according to the interval between the current time and the reproduction cycle. The reproduction selection module is used to select the individual sturgeon that need to be reproduced. The fishing selection module is used to select the individual sturgeon that need to be fished.

3. A comprehensive management method for sturgeon breeding data, characterized in that: It includes the following steps: S1. When the sturgeon seedlings grow to a certain stage, implant a PIT chip and a sonar tag into their bodies to establish an independent identity identifier for each sturgeon individual. Place a sonar receiver at a specific location in the farming area and receive the position signals of each sturgeon at fixed intervals to obtain their activity data. S2. Catch the sturgeon and huso sturgeon at regular intervals for weighing, count the weight changes, predict the future weight, and correct the predicted weight value according to the weight of the sturgeon and huso sturgeon counted during weighing; S3. When fishing and breeding are required, determine the fishing targets and breeding targets according to the interval between the current time and the breeding cycle, combined with the predicted weight and historical activity of the sturgeon and huso sturgeon; S4. After selecting the targets, carry out fishing and breeding selection. The sturgeon and huso sturgeon selected for breeding are released into a specific area for breeding after being caught until the end of the breeding cycle, and then the sturgeon and huso sturgeon are put back into the breeding area.

4. The comprehensive management method for sturgeon farming data according to claim 3, characterized in that: In S1, the method for obtaining the activity data is as follows: S1-1. With the sonar receiver as the origin of the coordinate system, a three-dimensional rectangular coordinate system is established. The positions of each individual sturgeon are statistically counted at fixed time intervals to obtain the xyz-axis coordinate values, forming a coordinate set {(x1y1z1), (x2y2z2), …, (x n y n z n )}, where n is the number of sturgeons. Calculate the spatial distance of the sturgeon coordinates between the previous and the next statistical times {l1, l2, …, l i}, where i + 1 is the number of statistical times; S1-2. The activity data of sturgeon is the result of weighted operation of coordinate space distances statistically at different times, that is, the activity Q = ∑a i l i , and the weight coefficients of each coordinate space distance are different. All the weight coefficients form an arithmetic progression Pa1, a2,... a i}, the closer to the last statistical time, the greater the weight coefficient of the coordinate space distance. The value of a i is constant, and the smaller the difference between the two adjacent terms in the arithmetic progression is with the increase of the number of statistics.

5. The comprehensive management method for sturgeon breeding data according to claim 4, characterized in that: In S2, the specific method for predicting the future weight is as follows: S2-1. Count the weight change data of all sturgeon and huso sturgeon in the system history from the growth and development stage to the mature stage over time, obtain the weight growth curves of sturgeon and huso sturgeon seedlings with different initial weights over time, map the current sturgeon and huso sturgeon seedlings to the weight growth curve that matches their initial weights, and obtain the predicted function f(t) of weight over time. The value of f(t) is the predicted weight value; S2-2. With each catch and weight statistic, obtain the deviation value k between the measured weight value and the predicted value of this sturgeon and huso sturgeon. If the measured value is greater than the predicted value, k is positive, otherwise k is negative. The weight predicted value f(t) is modified to f(t)+μkΔt, where μ is the correction amplitude coefficient and Δt is the time elapsed since the last weight statistic of this sturgeon and huso sturgeon. Δt no longer increases after the current time reaches the mature stage of the sturgeon and huso sturgeon. As the number of weight statistics increases, μ decreases linearly.

6. The comprehensive management method for sturgeon breeding data according to claim 5, wherein: In S3, the specific method for determining the fishing targets and breeding targets is as follows: S3-1. When fishing, use the predicted weight value and activity of the sturgeon and huso sturgeon as the selection criteria. Outside the annual breeding cycle, focus more on selecting sturgeon and huso sturgeon with large activity for fishing. Inside the annual breeding cycle, focus more on selecting sturgeon and huso sturgeon with large predicted weight values for fishing; S3-2. Inside the annual breeding cycle, focus more on selecting sturgeon and huso sturgeon with large activity for breeding selection, so that the offspring of the selected sturgeon and huso sturgeon have stronger predation desire and activity.

7. A comprehensive management method for sturgeon farming data according to claim 6, characterized in that: In S3-1, the fishing priority value is calculated, that is, the fishing priority value E of the sturgeon is E = αQ + βf(t), and the fishing priority values E of each sturgeon are sorted, and several sturgeons with the largest E are selected for fishing, where α is the activity weight coefficient and β is the body weight weight coefficient. When the fishing time is outside the breeding cycle, the number of days m between the fishing day and the breeding cycle is calculated, where When the fishing time is within the breeding cycle, where τ is the breeding cycle adjustment coefficient and m0 is the minimum set value of the activity weight ratio.

8. A comprehensive management method for sturgeon farming data according to claim 7, characterized in that: In S3-2, within each annual breeding cycle, after setting the lower limit f of the breeding weight min , for all sturgeon with weight prediction values above f min , sort them according to the activity level Q, and select several sturgeon with the largest weight prediction values f(t) for capture and breeding according to the selected number of sturgeon to be bred.

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