A hippocampus artificial breeding method and precise regulation method

Abstract

The application discloses a hippocampus artificial breeding method and a precise regulation method, belongs to the field of precise breeding, and provides the precise regulation method of the hippocampus artificial breeding, which comprises the following steps: S1, finding a safety threshold of environmental stress of hippocampus growth; and S2, controlling the difference between environmental parameters of each point in a hippocampus growth container within the safety threshold range by improving water body uniformity, so that the environmental parameters in the container are uniform and stable. The safety threshold of the environmental stress of the hippocampus growth is found, and the air separation method and the water separation method are creatively developed to improve the water body uniformity, and the precise regulation is beneficial to the survival rate and growth consistency of the hippocampus. The precise breeding method and technology can maximize the reduction of the influence of environmental stress in hippocampus breeding, improve the energy conversion rate and the growth rate, overcome the disadvantages of poor physique, slow growth and weak disease resistance of the hippocampus caused by the sensitivity of the hippocampus to the environment, and improve the hippocampus breeding success rate and breeding benefit.

Description

Technical Field

[0001] This invention relates to the field of precision aquaculture, and more specifically, to a method for artificial breeding of seahorses and a method for precise control. Background Technology

[0002] Due to immature aquaculture techniques, the survival rate of artificially bred seahorses has consistently been low, severely restricting the seahorse farming industry. The aquatic environment is one aspect of the problem; seahorses are environmentally sensitive fish, easily affected by even minor changes in their environment. Environmental stresses present in artificial breeding systems, especially those caused by small gradients in environmental factors, are often overlooked or poorly addressed in production, leading to weakened physical condition and reduced disease resistance in artificially bred seahorses. These issues result in high mortality rates and poor profitability in artificially bred seahorses. Solving these problems requires both a deeper understanding of seahorse biology and the improvement of scientific aquaculture techniques to achieve stable and high yields in artificial seahorse farming.

[0003] The stress of aquaculture environments on cultured organisms has always been a focus of attention. Numerous studies have been conducted, covering many environmental factors such as temperature, salinity, light, pH, nitrite nitrogen, ammonia nitrogen, and COD. These factors are integrated into national standards such as the "Seawater Quality Standard" and the "Fishery Water Quality Standard" to guide aquaculture production and are updated regularly. However, several problems exist. First, most indicators in these standards target only a single factor, while factors in the aquatic environment often act synergistically. Second, each factor is only given a suitable permissible range or a limit in the standards, such as a permissible pH range of 7.6-8.5, DO ≥ 4 mg / L, and ammonia nitrogen ≤ 0.05 mg / L. The former often varies due to other environmental factors, and some variations can even be more toxic. The latter makes it easy for users to overlook the homogeneity of the water in the aquaculture system, focusing only on whether the water quality in the system meets national permissible ranges, without considering the differences in water quality between different locations within the same system. In reality, within a single aquarium system, uneven water quality and variations often exist between different locations due to water movement, biological activity, container wall friction, and container materials. For example, there might be a temperature difference of several degrees Celsius or a salinity difference of several units between the corners and the center of an aquarium. This phenomenon is prevalent in aquarium systems of all sizes, forming a continuous gradient from the center to the corners. However, because the water quality values ​​at each location are within permissible ranges, their impact is often overlooked. This has little effect on some aquatic organisms that are not sensitive to gradient differences. However, for aquatic organisms like seahorses, which are extremely sensitive to even small changes in water quality gradients, swimming between water bodies with different water qualities exposes them to environmental stress caused by these subtle gradient changes, significantly increasing their chances of developing disease.

[0004] Water quality is crucial for aquaculture. Uniform water quality, with no significant differences, ensures that farmed organisms are not stressed by variations in water quality gradients. Water quality control technology is an important component of aquaculture technology, aiming to achieve two goals: first, to ensure the water quality meets national standards; and second, to maintain uniform water quality without significant differences. The latter, while receiving less attention, is a hot research topic. With the development of the aquaculture industry, numerous water quality control methods have emerged, including physical, chemical, and biological methods. These methods aim to improve water quality, ensuring it meets national standards and promoting the growth and development of farmed organisms. Many tools and products have also been invented and produced, such as aerators, water cultivators, microbial agents, and water purification equipment. However, relatively few methods, technologies, and tools exist for addressing and controlling water uniformity. The core methods and technologies currently available primarily involve aeration and water flow to promote mixing between the top and bottom layers or between the center and edges of the water. Water exchange and aeration are essential in aquaculture, crucial for maintaining water quality and frequently mentioned and applied for keeping the water homogeneous. Based on aeration and water flow methods, we conduct innovative research and refined control to address the unevenness of water in aquaculture systems. This aims to promote water homogeneity as much as possible while meeting the physiological needs of the cultured organisms, thus improving water quality control techniques. This is particularly necessary and important for aquatic organisms sensitive to environmental changes, enabling improvements in aquaculture techniques and promoting industry development. This is what precision aquaculture requires. Summary of the Invention

[0005] The problem this invention aims to solve is to overcome the shortcomings of traditional aquaculture and develop a precision aquaculture method with low environmental stress and uniform water quality.

[0006] To address the above problems, the first aspect of this invention provides a method for precise control in the artificial breeding of seahorses, the precise control comprising the following steps:

[0007] S1: Determine the safe threshold for hippocampal growth without environmental stress;

[0008] S2: By improving the uniformity of the water body, the differences in environmental parameters between various points in the seahorse growth container are controlled within the above-mentioned safe threshold range, and the environmental parameters inside the container are uniform and stable.

[0009] In the first aspect of this invention, two key difficulties of the aforementioned technical problems are addressed: The first difficulty is the safety threshold, i.e., the suitable range of variation of environmental factors within which changes in environmental factors do not affect seahorse growth. Regarding the safety threshold of seahorses, this invention, taking into account the seahorse's sensitivity to environmental changes, designs experiments within a suitable range of environmental factor variations to explore the safety threshold of seahorses and obtain a water quality precision range suitable for artificial breeding and control of seahorses. The second difficulty is the issue of uniformity adjustment and control. Uneven water quality leads to a decrease in seahorse survival rate. This invention improves the uniformity of the breeding water body so that the environmental parameters at various points in the seahorse's growth environment are within the safe threshold range. With uniform and stable environmental parameters at each point, the survival rate and growth rate of seahorses can be effectively improved.

[0010] Preferably, in step S1, the safety threshold for environmental stress includes a temperature sensitivity threshold, which includes a daily temperature variation threshold and an hourly temperature change rate threshold. The daily temperature variation threshold is less than 2°C, and the hourly temperature change rate threshold is less than 0.5°C / h.

[0011] Preferably, in step S1, the safety threshold for environmental stress further includes a salinity sensitivity threshold, which includes a daily salinity variation threshold and an hourly salinity change rate threshold, wherein the daily salinity variation threshold is less than 3 and the hourly salinity change rate is less than 1‰ / h.

[0012] This invention analyzes and screens the adaptation range of the main environmental factors (temperature and salinity) of seahorses and their sensitive factors. It examines the changes in the growth, physiology and behavior of seahorses under different temperature and salinity variations and rates, compares and analyzes relevant parameters, and finds safe thresholds, laying the foundation for targeted regulation of water uniformity in step S2.

[0013] Preferably, the method for improving water uniformity includes the air distribution method, which makes the water quality in the aquaculture container uniform by changing the density and position of the air vents and the air flow rate. The air vents are distributed according to the following principle: the air vents are evenly distributed on the diagonal of the rectangular container.

[0014] Preferably, the density of vent holes is 6 to 8 per square meter.

[0015] Preferably, when artificially raising seahorse larvae, the ventilation flow rate is 90–120 mL / min;

[0016] When adult seahorses are cultured in captivity, the ventilation flow rate is 180–240 mL / min;

[0017] When raising adult seahorses in captivity, the ventilation rate is 130–160 mL / min.

[0018] Preferably, the method for improving water uniformity also includes a water distribution method, which makes the water quality in the breeding container uniform by changing the water injection position and water flow rate of the water injection pipe. The water injection position is set in the middle and lower part of the water column in the seahorse breeding container, and the angle between the water injection pipe and the container wall is 10-25°. A row of parallel water outlet slots are opened on the wall of the water injection pipe in the breeding container. The width of the water outlet slots is 3-8mm, the length is 4-6cm, and the vertical distance between adjacent water outlet slots is 1-3cm.

[0019] Preferably, the water outlet hole on the water injection pipe is opened at an angle relative to the vertical direction, and the angle between the water outlet hole and the vertical direction is 30-45°.

[0020] Preferably, when raising seahorse larvae, the water injection flow rate is 40-60 L / h;

[0021] When raising adult seahorses, the water injection flow rate is 80-120 L / h;

[0022] When raising adult seahorses, the water flow rate should be 40-60 L / h.

[0023] To address the issue of regulating and controlling water uniformity, this invention relies on both aeration and water flow. Targeting the seahorse's sensitivity to changes in environmental micro-gradients, it develops refined water quality control technologies using aeration and water flow to achieve high efficiency, convenience, and cost-effectiveness, thus forming a precise control method and technology for seahorses.

[0024] A second aspect of this invention provides a method for precise seahorse breeding, comprising the following steps:

[0025] Step A: Selection of seahorse larvae: Select seahorse larvae with a body length of 4-6cm and a weight of 0.3-0.8g for rearing;

[0026] Step B: Selection of breeding containers: Select containers with smooth walls for breeding;

[0027] Step C: Culture: The seahorses are precisely cultured according to the precise control method for artificial seahorse culture described in the first aspect. The temperature and salinity are set to ensure uniform water quality. The other culture conditions are set as follows: photoperiod L:D = (14~18):(6~10), light intensity is 900~1200 lux, feed is given once a day, and the total weight of feed is 7~10% of the weight of the seahorses.

[0028] Step D: Fishing: Fishing seahorses at night.

[0029] The second aspect of this invention is to integrate the rational grazing and precise feeding techniques of seahorses to form a precise seahorse breeding method.

[0030] The beneficial effects of this invention are as follows: This invention discloses for the first time a precision breeding technology and method for seahorses. By analyzing the safety threshold of seahorses to environmental changes, and based on this safety threshold, the uniformity of the water body in the breeding environment is controlled, and related technologies such as water separation and air separation are optimized, forming a precision breeding method and technology most suitable for seahorse growth and development. The precision breeding method and technology of this invention can minimize the impact of environmental stress in seahorse breeding, improve energy conversion rate and growth rate, overcome the shortcomings of seahorses such as poor physical condition, slow growth and weak disease resistance caused by environmental sensitivity, and improve the success rate and efficiency of seahorse breeding. Attached Figure Description

[0031] Figure 1 This is a graph showing the variation trend of seahorse feeding behavior parameters at different temperatures in Example 1 of this invention.

[0032] Figure 2 This is a graph showing the trend of enzyme activity in the hippocampus hepatopancreas at different temperatures in Example 1 of this invention.

[0033] Figure 3 This is a graph showing the expression trends of relevant functional genes in the hippocampus hepatopancreas at different temperatures in Example 1 of this invention.

[0034] Figure 4 This is a graph showing the expression trend of stress genes in the hippocampus hepatopancreas under different temperature change conditions in Example 2 of this invention.

[0035] Figure 5 This is a graph showing the expression trends of glucose and lipid metabolism genes in the hippocampus hepatopancreas under different temperature variation conditions in Example 2 of this invention.

[0036] Figure 6 This is a graph showing the expression trend of immune genes in the hippocampus hepatopancreas under different temperature variation conditions in Example 2 of this invention.

[0037] Figure 7 This is a graph showing the changing trends of seahorse feeding behavior parameters under different salinities in Example 3 of this invention.

[0038] Figure 8 This is a graph showing the trend of enzyme activity in the hepatopancreas of the hippocampus under different salinities in Example 3 of this invention.

[0039] Figure 9 This is a graph showing the expression trends of relevant functional genes in the hippocampus hepatopancreas under different salinities in Example 3 of this invention.

[0040] Figure 10This is a graph showing the expression trend of stress genes in the hippocampus hepatopancreas under different salinity variation conditions in Example 4 of this invention.

[0041] Figure 11 This is a graph showing the expression trends of glucose and lipid metabolism genes in the hippocampus hepatopancreas under different salinity variation conditions in Example 4 of this invention.

[0042] Figure 12 This is an example of the expression trend of immune genes in the hippocampal hepatopancreas under different salinity variation conditions in Example 4 of the present invention.

[0043] Figure 13 The figure shows the experimental results of stress resistance testing of the seahorse after the improvement of the gas separation method and water separation method in Example 5 of the specific embodiments of the present invention. Detailed Implementation

[0044] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described in detail below. It should be noted that the following embodiments are only used to illustrate the implementation methods and typical parameters of the present invention, and are not intended to limit the parameter range described in the present invention. Reasonable variations derived therefrom are still within the protection scope of the claims of the present invention.

[0045] It should be noted that the endpoints and any values ​​of the ranges disclosed herein are not limited to the precise ranges or values, and these ranges or values ​​should be understood to include values ​​close to these ranges or values. For numerical ranges, the endpoint values ​​of the various ranges, the endpoint values ​​of the various ranges and individual point values, and individual point values ​​can be combined with each other to obtain one or more new numerical ranges, which should be considered as specifically disclosed herein.

[0046] This invention provides a method for artificial breeding of seahorses and a method for precise control, aiming to overcome the problems caused by uneven water quality in existing breeding technologies. The aforementioned method for precise control of artificial seahorse breeding includes two steps, specifically:

[0047] S1: Identify the safe threshold for seahorse growth without environmental stress. The purpose of this step is to solve the problem of the safe threshold for seahorses. The specific implementation of this invention mainly focuses on analyzing and screening the adaptation range of the main environmental factors (temperature and salinity) of seahorses and their sensitive factors. It examines the changes in the growth, physiology and behavior of seahorses under different temperature and salinity variations and rates, compares and analyzes relevant parameters, and identifies the safe threshold. Among them, the temperature sensitivity threshold includes the daily temperature variation threshold and the hourly temperature change rate threshold. The daily temperature variation threshold is less than 2℃, and the hourly temperature change rate threshold is less than 0.5℃ / h. The salinity sensitivity threshold includes the daily salinity variation threshold and the hourly salinity change rate threshold. The daily salinity variation threshold is less than 3, and the hourly salinity change rate is less than 1‰ / h.

[0048] S2: By improving water homogeneity, the differences in environmental parameters between various locations in the seahorse's growth environment are kept within a safe threshold range, ensuring uniform and stable environmental parameters at each location. In a specific embodiment of this invention, the methods for improving water homogeneity include air separation and water separation. Air separation, in particular, achieves water homogeneity by changing the position and aeration rate of the ventilation holes. The distribution of ventilation holes follows these principles: ventilation holes are evenly distributed along the diagonal of a rectangular container, with a density of 6-8 holes per square meter. When artificially raising seahorse juveniles, the gas flow rate through the ventilation holes is 90-120 mL / min; when artificially raising adult seahorses, the gas flow rate through the ventilation holes is 180-240 mL / min; when artificially raising parent seahorses, the gas flow rate through the ventilation holes... The injection rate is 130–160 mL / min. The water distribution method ensures uniform water quality by changing the injection position and flow rate. The injection position is located in the lower middle part of the water surface in the seahorse rearing tank. A row of parallel outlet slots is opened on the wall of the injection pipe located in the lower middle part of the rearing container. The width of the outlet slots is 3–8 mm, the length is 4–6 cm, and the vertical spacing between adjacent outlet slots is 1–3 cm. The angle between the side of the injection pipe with the slots and the rearing tank wall is 10–25°, and the angle between the outlet slots and the vertical direction is 30–45°. When rearing seahorse juveniles, the injection flow rate is 40–60 L / h; when rearing adult seahorses, the injection flow rate is 80–120 L / h; and when rearing parent seahorses, the injection flow rate is 40–60 L / h.

[0049] The precise control method for artificial breeding of seahorses provided by the specific embodiments of the present invention can effectively improve the survival rate, growth rate and stress resistance of seahorses.

[0050] Example 1

[0051] To calculate the temperature sensitivity threshold for hippocampal growth, the following experiment was designed in this embodiment:

[0052] Three hundred and fifty seahorse larvae (weight 0.2759 ± 0.0309 g, body length 4.96 ± 0.34 cm) were selected and subjected to the following temperature treatments: the larvae were rapidly transferred from a water temperature of 25℃ (25T) to low-temperature stress groups (23℃ (23T), 21℃ (21T), 19℃ (19T), 17℃ (17T)) and high-temperature stress groups (27℃ (27T), 29℃ (29T), 31℃ (31T) seawater with a salinity of 25. The 25T group served as a control group. After 24 hours under these conditions, feeding behavior was observed, enzyme activity was measured, and liver tissue was collected for gene expression analysis.

[0053] Enzyme activity indicators: Hippocampal tissue was used to determine ① antioxidant-related indicators: the activities of superoxide dismutase (SOD) and catalase (CAT), and the contents of glutathione (GSH) and malondialdehyde (MDA); ② digestive enzymes: the activities of α-amylase (AMS) and lipase (LPS); ③ immune enzymes: the activities of alkaline phosphatase (AKP) and acid phosphatase (ACP).

[0054] Behavioral indicators: The feeding behavior of seahorses was photographed and recorded in situ in each group. The following three feeding behavior parameters were analyzed, including: ① Feeding response time (s): the time from when the brine shrimp enters the water to when they are first preyed upon; ② Feeding rate (ind / min): the average rate at which seahorse larvae consume brine shrimp larvae within 10 minutes from 6 min to 15 min; ③ Feeding amount (ind / time): the total number of brine shrimp larvae consumed by seahorse larvae during the entire feeding period.

[0055] Functional gene indicators include the expression of Fas, Sod, Hsp70, Pdha1, Cyp51, Fadsd6, Gst, Bcl2, Mdh1, Idh3b, G6pd, Gadd45α, Pyy, Mtor, Hsp90, P53, Casp9, Casp3, Cpt1, B2m, etc.

[0056] The changes in the above indicators under each treatment were compared and analyzed to identify relevant indicators or combinations of indicators sensitive to temperature changes. Correlation analysis was performed between in vivo (enzyme and gene indicators) and in vitro (behavioral indicators) results to identify sensitive indicators linking in vivo and in vitro processes for use in the next experimental step.

[0057] Figure 1 This indicates the changing trends of seahorse feeding behavior parameters under different temperatures, among which, Figure 1 In this context, 'a' represents the trend of hippocampal feeding response time under different temperatures; Figure 1 In this context, 'b' represents the trend of the feeding rate of the seahorse under different temperatures; Figure 1 In this context, 'c' represents the trend of seahorse food intake at different temperatures.

[0058] Figure 2 This indicates the changing trends of enzyme activity in the hippocampus, hepatopancreas, and liver at different temperatures. Figure 2 In this context, 'a' represents the changing trend of malondialdehyde (MDA) content in the hippocampus under different temperatures. Figure 2 In this context, 'b' represents the trend of α-amylase activity in the hippocampus under different temperatures. Figure 2 In this context, 'c' represents the trend of pancreatic enzyme activity in the hippocampus at different temperatures. Figure 2 In this context, d represents the trend of lipase activity in the hippocampus at different temperatures. Figure 2 In this context, 'e' represents the trend of superoxide dismutase activity in the hippocampus at different temperatures. Figure 2 In this context, f represents the trend of catalase activity in the hippocampus at different temperatures; Figure 2 In this context, 'g' represents the trend of alkaline phosphatase activity in the hippocampus at different temperatures. Figure 2 In the figure, h represents the trend of acid phosphatase activity in the hippocampus at different temperatures.

[0059] Figure 3 The expression trends of relevant functional genes in the hippocampus hepatopancreas at different temperatures are shown. * indicates a significant difference between the experimental groups and the control group at 25T (P<0.05). Figure 3 In this context, 'a' represents the expression trend of the Sod gene at different temperatures; Figure 3 In this context, 'b' represents the expression trends of Hsp70, Hsp90, and Gst genes at different temperatures. Figure 3 In this context, 'c' represents the expression trends of Pdha1 and Mdh1 genes at different temperatures. Figure 3 In this context, d represents the expression trends of the Idh3b and G6pd genes at different temperatures.

[0060] Table 1 shows the correlation analysis of gene expression under temperature stress. * indicates a significant correlation at the 0.05 level, and ** indicates a significant correlation at the 0.01 level.

[0061] Table 1. Correlation analysis of gene expression under temperature stress.

[0062]

[0063] Table 2 shows the correlation analysis between internal and external indicators under temperature stress. * indicates a significant correlation at the 0.05 level, and ** indicates a significant correlation at the 0.01 level.

[0064] Table 2 Correlation analysis between internal and external indicators under temperature stress

[0065]

[0066]

[0067] Thus, we obtained the sensitivity index of the hippocampus to temperature gradient changes, with a daily temperature variation threshold of less than 2℃.

[0068] Example 2

[0069] Using the experimental results from Example 1, a safety threshold analysis of the hippocampus's rate of temperature change per hour was conducted. The experiment was designed with two temperature amplitude gradients and three rate gradients. See Table 3 for details.

[0070] Table 3 Temperature Variation and Speed ​​Gradient Settings

[0071]

[0072] Under the above conditions, 360 juvenile seahorses (weight 0.6±0.1g, body length 5.0±1.0cm) were selected and reared in each of the above treatments for 30 days. The environmental conditions for rearing were: salinity 25, photoperiod L:D 16:8, and light intensity 1000 lux. Feeding was set to two hours after the lights were turned on, once a day, with each feeding amount being approximately 8% of the total weight of the seahorses in the group. On days 4 and 7, seahorse liver tissue was collected for expression analysis of relevant target functional genes, including stress genes (Sod1 and Hsp70), energy metabolism genes (Idha, Mdh1, Cpt1, and Fasn), and immune-related genes (P53 and Casp3).

[0073] Figure 4 This indicates the expression trends of stress genes in the hippocampus, hepatopancreas, under different temperature variation conditions. Figure 4 In this context, 'a' represents the expression trend of the sod1 gene at different cooling rates after 12 hours and 96 hours. Figure 4 In this context, 'b' represents the expression trend of the sod1 gene at different heating rates after 12 hours and 96 hours. Figure 4 In the figure, 'c' represents the expression trend of the hsp70 gene at different cooling rates after 12 hours and 96 hours. Figure 4 In the figure, d represents the expression trend of the hsp70 gene after 12 hours and 96 hours under different heating rates.

[0074] Figure 5 This indicates the expression trends of glucose and lipid metabolism genes in the hippocampus hepatopancreas under different temperature variation conditions. Figure 5 In this context, 'a' represents the expression trend of the ldha gene at different cooling rates after 12 hours and 96 hours. Figure 5 In the figure, 'b' represents the expression trend of the ldha gene at different heating rates after 12 hours and 96 hours. Figure 5In this context, 'c' represents the expression trend of the mdh1 gene at different cooling rates after 12 hours and 96 hours. Figure 5 In the figure, d represents the expression trend of the mdh1 gene after 12 hours and 96 hours under different heating rates.

[0075] Figure 6 This indicates the expression trends of immune genes in the hippocampus, hepatopancreas, under different temperature variation conditions. Figure 6 In this context, 'a' represents the expression trend of the p53 gene at different cooling rates after 12 hours and 96 hours. Figure 6 In the figure, 'b' represents the expression trend of the p53 gene at different heating rates after 12 hours and 96 hours. Figure 6 In the figure, 'c' represents the expression trend of the casp3 gene at different cooling rates after 12 hours and 96 hours. Figure 6 In the figure, d represents the expression trend of the casp3 gene at different heating rates after 12 hours and 96 hours.

[0076] Based on the experimental results in this embodiment, the safe threshold for temperature change rate of the hippocampus is: the threshold for hourly temperature change rate is 0.5℃ / h, and the maximum hourly temperature change rate should be less than 1℃ / h.

[0077] Example 3

[0078] To calculate the salinity sensitivity threshold for seahorse growth, the following experiment was designed in this embodiment:

[0079] Three hundred and fifty seahorse larvae (weight 0.2759 ± 0.0309 g, body length 4.96 ± 0.34 cm) were selected and subjected to the following salinity treatments: the larvae were rapidly transferred from seawater with a salinity of 25 (25S) to low-salinity stress groups (salinity 23 (23S), 21 (21S), 19 (19S), 17 (17S)) and high-salinity stress groups (salinity 27 (27S), 29 (29S), 31 (31S)) at a temperature of 25℃. The 25S group served as a control. After 24 hours under these conditions, feeding behavior was observed, enzyme activity was measured, and liver tissue was collected for gene expression analysis.

[0080] Enzyme activity indicators: Hippocampal tissue was used to determine ① antioxidant-related indicators: the activities of superoxide dismutase (SOD) and catalase (CAT), and the contents of glutathione (GSH) and malondialdehyde (MDA); ② digestive enzymes: the activities of α-amylase (AMS) and lipase (LPS); ③ immune enzymes: the activities of alkaline phosphatase (AKP) and acid phosphatase (ACP).

[0081] Behavioral indicators: The feeding behavior of seahorses was photographed and recorded in situ in each group. The following three feeding behavior parameters were analyzed, including: ① Feeding response time (s): the time from when the brine shrimp enters the water to when they are first preyed upon; ② Feeding rate (ind / min): the average rate at which seahorse larvae consume brine shrimp larvae within 10 minutes from 6 min to 15 min; ③ Feeding amount (ind / time): the total number of brine shrimp larvae consumed by seahorse larvae during the entire feeding period.

[0082] Functional gene indicators include the expression of Fas, Sod, Hsp70, Pdha1, Cyp51, Fadsd6, Gst, Bcl2, Mdh1, Idh3b, G6pd, Gadd45α, Pyy, Mtor, Hsp90, P53, Casp9, Casp3, Cpt1, B2m, etc.

[0083] The changes in the above indicators under each treatment were compared and analyzed to identify relevant indicators or combinations of indicators sensitive to salinity changes. Correlation analysis was performed between in vivo (enzyme and gene indicators) and in vitro (behavioral indicators) results to identify sensitive indicators linking in vivo and in vitro processes for use in the next experimental step.

[0084] Figure 7 This indicates the changing trends of seahorse feeding behavior parameters under different salinity levels, among which, Figure 7 In this context, 'a' represents the trend of changes in the feeding response time of seahorses under different salinity levels. Figure 7 In this context, 'b' represents the trend of the feeding rate of seahorses under different salinity levels. Figure 7 In this context, 'c' represents the trend of seahorse food intake under different salinity levels.

[0085] Figure 8 This indicates the changing trends of enzyme activity in the hepatopancreas of the hippocampus under different salinity levels, among which... Figure 8 In this context, 'a' represents the changing trend of malondialdehyde (MDA) content in the seahorse under different salinities. Figure 8 In this context, 'b' represents the trend of α-amylase activity in the hippocampus under different salinities. Figure 8 In this context, 'c' represents the trend of pancreatic enzyme activity in the hippocampus under different salinity levels. Figure 8 In this context, 'd' represents the trend of lipase activity in the hippocampus under different salinity levels. Figure 8 The 'e' in the text represents the trend of superoxide dismutase activity in the hippocampus under different salinity levels. Figure 8 In this context, f represents the trend of catalase activity in the hippocampus under different salinity levels. Figure 8 In this context, 'g' represents the trend of alkaline phosphatase activity in the hippocampus under different salinity levels. Figure 8 In this context, 'h' represents the trend of acid phosphatase activity in the hippocampus under different salinity levels.

[0086] Figure 9 The expression trends of relevant functional genes in the hippocampus hepatopancreas under different salinity levels are shown. * indicates a significant difference between the experimental groups and the control group at 25S (P<0.05). Figure 9 In this context, 'a' represents the expression trend of the Sod gene under different salinity levels. Figure 9 In this context, 'b' represents the expression trends of Hsp70, Hsp90, and Gst genes under different salinity levels. Figure 9 In this context, 'c' represents the expression trends of Pdha1 and Mdh1 genes under different salinity levels. Figure 9 In the figure, d represents the expression trend of Idh3b and G6pd genes under different salinity.

[0087] Table 4 shows the correlation analysis of gene expression under salinity stress. * indicates a significant correlation at the 0.05 level, and ** indicates a significant correlation at the 0.01 level.

[0088] Table 4. Correlation analysis of gene expression under salinity stress.

[0089]

[0090]

[0091] Table 5 shows the correlation analysis between internal and external indicators under salinity stress. * indicates a significant correlation at the 0.05 level, and ** indicates a significant correlation at the 0.01 level.

[0092] Table 5. Correlation analysis between internal and external indicators under salinity stress.

[0093]

[0094] Thus, a sensitivity index of the seahorse to changes in salinity gradient was obtained, with a daily salinity variation threshold of less than 3.

[0095] Example 4

[0096] Using the experimental results from Example 3, a safety threshold analysis of the hourly rate of change of salinity in the seahorse was conducted. Two salinity amplitude gradients and three rate gradients were designed for the experiment. See Table 6 for details.

[0097] Table 6. Salinity Variation and Velocity Gradient Settings

[0098]

[0099] Under the above conditions, 360 juvenile seahorses (weight 0.6±0.1g, body length 5.0±1.0cm) were selected and reared in each of the above treatments for 30 days. The environmental conditions were: temperature 25℃, photoperiod L:D 16:8, and light intensity 1000 lux. Feeding was scheduled two hours after the lights were turned on, once a day, with each feeding amount being approximately 8% of the total weight of the seahorses in the group. On days 4 and 7, seahorse liver tissue was collected for expression analysis of relevant target functional genes, including stress genes (Sod1 and Hsp70), energy metabolism genes (Idha, Mdh1, Cpt1, and Fasn), and immune-related genes (P53 and Casp3).

[0100] Figure 10 This indicates the expression trends of stress genes in the hippocampus hepatopancreas under different salinity variation conditions. Figure 10 In this context, 'a' represents the expression trend of the sod1 gene at different salinity decrease rates at 12 hours and 96 hours. Figure 10 In this context, 'b' represents the expression trend of the sod1 gene at different salinity rise rates after 12 hours and 96 hours. Figure 10 In the figure, 'c' represents the expression trend of the hsp70 gene at different salinity decrease rates at 12 hours and 96 hours. Figure 10 In the figure, d represents the expression trend of the hsp70 gene at different salinity rise rates at 12 hours and 96 hours.

[0101] Figure 11 This indicates the expression trends of glucose and lipid metabolism genes in the hippocampus hepatopancreas under different salinity variation conditions. Figure 11 In this context, 'a' represents the expression trend of the ldha gene at different salinity decrease rates at 12 hours and 96 hours. Figure 11 In the figure, 'b' represents the expression trend of the ldha gene at different rates of salinity increase, after 12 hours and 96 hours. Figure 11 In the figure, 'c' represents the expression trend of the mdh1 gene at different salinity decrease rates at 12 hours and 96 hours. Figure 11 In the figure, d represents the expression trend of the mdh1 gene at different salinity rise rates at 12 hours and 96 hours.

[0102] Figure 12 This indicates the expression trends of immune genes in the hippocampus hepatopancreas under different salinity variation conditions. Figure 12 In this context, 'a' represents the expression trend of the p53 gene at different salinity decrease rates after 12 hours and 96 hours. Figure 12 In the figure, 'b' represents the expression trend of the p53 gene at different rates of salinity increase after 12 hours and 96 hours. Figure 12In the figure, 'c' represents the expression trend of the casp3 gene at different salinity decrease rates at 12 hours and 96 hours. Figure 12 In the figure, d represents the expression trend of the casp3 gene at different salinity rise rates at 12 hours and 96 hours.

[0103] Based on the experimental results in this embodiment, the safe threshold for the rate of change of salinity in the seahorse is as follows: the threshold for the hourly rate of change of temperature is 1‰ / h, and the maximum hourly rate of change of temperature should be less than 2‰ / h.

[0104] Example 5

[0105] A study on precise microenvironment control technology was conducted using the air separation and water separation methods. First, the heterogeneity of the water in the aquaculture container was verified. A rectangular glass aquarium (50cm×27cm×25cm) was used, filled with 20cm of distilled water. A spherical air stone was fixed at the center of the bottom of the tank, connected to an air pump, and the aeration rate was adjusted to 200mL / min. The airflow field inside the tank was captured using a high-speed camera, and water samples were taken from various points within the tank for water quality parameter analysis. The results are shown in Table 7. In Table 7, different lowercase letters represent significant differences in the same area across different weeks (P<0.05); different uppercase letters represent significant differences in different areas within the same week (P<0.05). It is evident that before the improvement, there were significant differences in water quality at various locations within the tank. Furthermore, the water quality at the same locations also varied greatly at different time periods, indicating extreme instability.

[0106] Table 7 Water quality in different sampling areas

[0107]

[0108] The aeration method was used, with ICEM CFD software to mesh different types of aeration stones and rectangular tanks. Fluent 2020 software was used to simulate the flow field generated by the type, quantity, and placement of the aeration stones under different aeration modes, and the water quality uniformity coverage area was compared. The results showed that the four disc-shaped aeration stones placed in a four-part division mode had the most uniform flow velocity distribution, the largest water flow coverage area, and the best water quality uniformity. With the center point of the aquarium as the origin (0, 0, 0), the three-dimensional coordinates of the four disc-shaped aeration stones were: (-12.5, 6.25, 0), (12.5, 6.25, 0), (-12.5, -6.25, 0), and (12.5, -6.25, 0). The optimal mixing effect of the water in the container was achieved. The water mixing degree stabilized within 6 hours with a single aeration stone (93.4%) and then within 2 hours (98.7%).

[0109] The water separation method employed ICEM CFD software to mesh different inlet and outlet water types and a rectangular tank. Fluent 2020 software was used to simulate the flow field generated by the inlet position, angle, and outlet position under dynamic inlet and outlet water modes, comparing the coverage areas for water quality uniformity. Results showed that using a single row of obliquely spaced slots on a cylindrical injection pipe (elongated slots at a 45-degree angle to the vertical, 5mm x 5cm, 20cm in total length), with the injection pipe at a 15-degree angle to the tank wall, resulted in a flow velocity distribution that was higher at the bottom and lower at the top under outlet water mode. This velocities drove the flow of water at the bottom of the tank, gradually covering the entire container and achieving the best water quality uniformity. Under these conditions, the optimal water mixing effect was achieved, increasing the water mixing rate from 87.6% with straight pipe inlet water to 95.5%.

[0110] Table 8 shows the water quality tracking and observation table during seahorse farming after precise regulation. It can be seen that the water quality in each area is roughly the same, which means that the microenvironment is roughly the same and the water quality is uniform.

[0111] Table 8 Water Quality Tracking Survey Form

[0112]

[0113] After the uniformity of the aquaculture water was improved, the growth of the cultured organisms also improved significantly (see Table 9); their resistance to adverse conditions was significantly enhanced (see Table 9). Figure 13 .

[0114] Table 9. Record of Seahorse Growth Consistency

[0115]

[0116] Unless otherwise defined, all terms, symbols, and other scientific terms used herein are intended to have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. In some instances, terms having a conventional meaning are defined herein for clarification or ease of reference, and such definitions should not be construed as indicating a significant difference from conventional understanding in the art. The technical methods described or referenced herein are generally well understood by those skilled in the art and employed by conventional methods. Unless otherwise stated, the use of commercially available kits, reagents, and instruments shall be performed according to the manufacturer's instructions and parameters.

[0117] While the disclosure is as stated above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of this disclosure, and all such changes and modifications will fall within the protection scope of this invention.

Claims

1. A method for precise control in the artificial breeding of seahorses, characterized in that, The precise regulation includes the following steps: S1: Determine the safe threshold for hippocampal growth without environmental stress; S2: By improving water homogeneity, the differences in environmental parameters between points in the seahorse growth container are controlled within the aforementioned safe threshold range, resulting in uniform and stable environmental parameters within the container. The methods for improving water homogeneity include gas separation and water separation. The air distribution method makes the water quality in the aquaculture container uniform by changing the density and position of the air vents and the air flow rate. The distribution of the air vents follows the following principle: the air vents are evenly distributed on the diagonal of the rectangular container. The water distribution method ensures uniform water quality within the aquaculture container by altering the water injection position and flow rate. The water injection position is located in the lower middle part of the water column within the seahorse aquaculture container, with an angle of 10-25° between the water injection pipe and the container wall. A row of parallel water outlet slots is formed on the wall of the water injection pipe within the aquaculture container. The width of each water outlet slot is 3-8 mm, its length is 4-6 cm, and the vertical spacing between adjacent water outlet slots is 1-3 cm.

2. The precise control method for artificial breeding of seahorses as described in claim 1, characterized in that, In step S1, the safety threshold for environmental stress includes a temperature sensitivity threshold, which includes a daily temperature variation threshold and an hourly temperature change rate threshold. The daily temperature variation threshold is less than 2 ℃, and the hourly temperature change rate threshold is less than 0.5 ℃ / h.

3. The precise control method for artificial breeding of seahorses as described in claim 1, characterized in that, In step S1, the safety threshold for environmental stress also includes a salinity sensitivity threshold, which includes a daily salinity variation threshold and an hourly salinity change rate threshold. The daily salinity variation threshold is less than 3, and the hourly salinity change rate is less than 1‰ / h.

4. The precise control method for artificial breeding of seahorses as described in claim 1, characterized in that, When using the air distribution method, the density of the air vents is 6 to 8 per square meter.

5. The method for precise control in artificial seahorse breeding as described in claim 1, characterized in that, When using the gas separation method, the ventilation flow rate is 90~120 mL / min when artificially raising seahorse larvae; When adult seahorses are cultured in captivity, the ventilation rate is 180~240 mL / min; When raising adult seahorses in captivity, the ventilation rate is 130-160 mL / min.

6. The method for precise control in artificial seahorse breeding as described in claim 1, characterized in that, When using the water distribution method, the water outlet hole is opened at an angle relative to the vertical direction, and the angle between the water outlet hole and the vertical direction is 30~45°.

7. The method for precise control in artificial seahorse breeding as described in claim 1, characterized in that, When using the water separation method, the water injection flow rate is 40~60 L / h when raising seahorse larvae; When raising adult seahorses, the water injection flow rate is 80~120 L / h; When raising adult seahorses, the water flow rate should be 40-60 L / h.

8. A method for precise seahorse breeding, characterized in that, Includes the following steps: Step A: Selection of seahorse larvae: Select seahorse larvae with a body length of 4-6 cm and a weight of 0.3-0.8 g for rearing; Step B: Selection of breeding containers: Select containers with smooth walls for breeding; Step C: Culture: The seahorse is precisely cultured using the precise control method for artificial culture of seahorses according to any one of claims 1 to 7. Temperature and salinity are set to ensure uniform water quality. Other culture conditions are set as follows: photoperiod L:D = (14~18):(6~10), light intensity is 900~1200 lux, and the seahorses are fed once a day. The total weight of the feed is 7~10% of the weight of the seahorse. Step D: Fishing: Fishing seahorses at night.

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