Fish growth and development monitoring test method under temperature control gradient

Abstract

The invention discloses a monitoring test method for fish growth and development under a temperature control gradient, which comprises the following steps: constructing a water temperature gradient application model in a target fish growth and development test process, a gradient water temperature application period being a theoretical period of target fish growing from fry to adult fish; the water temperature gradient comprises a low-temperature stage, a proper-temperature stage and a high-temperature stage; regulating and controlling the water temperature according to the water temperature gradient applying model, regularly collecting images of the target fish, obtaining body type parameters of the target fish in different growth periods under different water temperature gradients, the body type parameters including width data and length data, and calculating growth speed coefficients of the target fish in different growth periods and different water temperature gradients; and calculating an average value of the growth speed coefficients of the target fish under the same water temperature gradient by using the growth speed coefficients of the target fish under different growth periods and different water temperature gradients, and evaluating whether the target fish is suitable for growing under the corresponding water temperature gradients in different growth periods by using the average value of the growth speed coefficients.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of fish biology research, and particularly relates to a monitoring test method for fish growth and development under temperature gradient control. BACKGROUND

[0002] The growth of fish in natural environment is affected by the water temperature of the growth environment, and the growth speed of different fish under different water temperature conditions is quite different. Due to the change of water environment and climate change, the water temperature of the habitat of fish will also change, which will seriously affect the breeding and growth of fish population. For the fish population which is greatly reduced or about to be extinct, it is very important to research and find new habitats, and it is the most important to find the water temperature environment suitable for the growth of fish, and it is the current research topic to find the water temperature environment suitable for the growth of target fish in different growth periods. Therefore, the present application provides a monitoring test method for fish growth and development under temperature gradient control to study the temperature gradient most suitable for the growth of target fish in different growth periods. SUMMARY

[0003] In view of the above problems of the prior art, the present application provides a monitoring test method for fish growth and development under temperature gradient control, which studies and analyzes the water temperature most suitable for the growth of target fish based on the water temperature of the current natural growth environment of target fish under experimental conditions.

[0004] To achieve the above-mentioned application purposes, the technical solution adopted by the present application is as follows: The present application provides a monitoring test method for fish growth and development under temperature gradient control, which includes the following steps: S1: constructing a water temperature gradient application model of the growth and development test process of target fish, the gradient water temperature application period is the theoretical period from the growth of fry to the growth of adult fish of target fish; the water temperature gradient includes a low temperature stage, a suitable temperature stage and a high temperature stage; S2: adjusting the water temperature of target fish in different growth and development periods from the growth of fry to the growth of adult fish according to the water temperature gradient application model, and collecting images of target fish at regular time intervals to obtain body shape parameters of target fish in different growth periods under different water temperature gradients, the body shape parameters including width data and length data, and calculating the growth speed coefficient of target fish in different growth periods and different water temperature gradients; t S3: calculating the average value of the growth speed coefficient of target fish under the same water temperature gradient by using the growth speed coefficient of target fish in different growth periods and different water temperature gradients, and evaluating whether target fish is suitable for growth under the corresponding water temperature gradient in different growth periods by using the average value of the growth speed coefficient.

[0005] Further, the water temperature gradient application model in step S1 is specifically as follows: ;​ in, The minimum and maximum water temperatures required for the target fish species to survive in their natural environment. To set the water temperature from the lowest water temperature Raise to the optimal water temperature The time point, t The growth and development time of the target fish. The timing for placing the fish fry into the experimental rearing tank. To adjust the water temperature from the optimal water temperature Rise to maximum water temperature The time point, This is the time point at which the theoretical cycle ends. a This is the coefficient for the rate of water temperature rise. b For the nonlinear coefficients in the low-temperature stage, A The set diurnal fluctuation amplitude of water temperature These represent the angular frequency and phase shift of the diurnal fluctuation of water temperature, respectively. c This is the water temperature stability coefficient. d The water temperature attenuation coefficient is... e The coefficient representing the rate of decrease in water temperature. f This represents the nonlinear coefficient during the high-temperature stage.

[0006] Further, step S2 includes: S21: Adjusting different growth and development times of target fish from fry to adult fish based on a water temperature gradient application model. t The water temperature was monitored, and images of the experimental rearing tank were taken at regular intervals to obtain images of the target fish at different growth stages; S22: Convert the image of the target fish to grayscale to obtain a grayscale image, and set the standard grayscale value of the boundary pixels of the target fish in the image. And calculate the grayscale value of each pixel in the grayscale image. Compared with standard gray values The difference , These are pixel coordinates; S23: Set the pixel grayscale value difference threshold ,like Then determine the pixel If it is a boundary pixel, then determine the pixel. Not a boundary pixel; S24: Mark all boundary pixels in the grayscale image. And calculate each boundary pixel The difference in grayscale value between adjacent pixels If the boundary pixels The difference in grayscale value between each adjacent pixel satisfies If the boundary pixel is isolated, then the boundary pixel is isolated If the boundary pixel is not isolated, then the boundary pixel is continuous ; S25: Replace all isolated boundary pixels in the gray-scale image with the average of the gray-scale values of the pixels adjacent to the isolated boundary pixels , w is the number of isolated boundary pixels, v is the number of pixels adjacent to the isolated boundary pixel w , V is the number of pixels adjacent to the isolated boundary pixel w ; S26: Repeat steps S24-S25 until there are no isolated boundary pixels in the gray-scale image, and output the gray-scale image with the interference of isolated boundary pixels eliminated S27: Draw evenly N vertical reference lines in the gray-scale image with the interference of isolated boundary pixels eliminated, obtain the boundary pixels on each reference line, and extract the pixel coordinates of the two boundary pixels farthest apart on each reference line, and calculate the vertical distance between the two boundary pixels farthest apart ; ; wherein, n is the number of vertical reference lines, are the pixel coordinates of the two boundary pixels farthest apart on the vertical reference line, respectively, are the numbers of the two boundary pixels farthest apart on the vertical reference line, respectively; S28: Obtain one vertical distance for each vertical reference line N , and select the maximum value from the vertical distance values as the width data of the target fish at the current growth period , a is the number of the target fish; S29: Repeat steps S27-S28, draw evenly M horizontal reference lines in the gray-scale image with the interference of isolated boundary pixels eliminated, calculate M horizontal distances, and select the maximum value from the horizontal distances as the length data of the target fish at the current growth period M ; S210: According to the number of target fish in the test aquaculture tank , calculate the growth speed coefficient of the current growth period compared to the previous growth period A , ​​The growth cycle number is used to calculate the growth rate coefficient; ; in, These are the width and length data of the target fish in the previous growth cycle, respectively. The time interval between two adjacent growth cycles. The weights for the influence of the width and length of the target fish on the growth rate coefficient are respectively. S211: Obtain the growth rate coefficient of the target fish under different growth cycles and different water temperature gradients.

[0007] Further, step S3 includes: S31: Calculate the average growth rate coefficient of the target fish under the same water temperature gradient using the growth rate coefficients at different growth stages and under different water temperature gradients. ; ; in, This refers to the number of times the growth rate coefficient is calculated under the same water temperature gradient.

[0008] S32: The average growth rate coefficient of the target fish at different water temperature gradients and different growth cycles. Threshold of growth rate coefficient Compare; like Then it is determined that the target fish is in the corresponding growth cycle. It is suitable for growth under this water temperature gradient; like Then it is determined that the target fish is in the corresponding growth cycle. It is not suitable for growth under this water temperature gradient.

[0009] The beneficial effects of this invention are as follows: This invention is used to study the suitable temperature gradients and ranges for target fish at different growth stages under laboratory conditions, providing effective data support for fish to find new habitats or for artificial fish farming. A dynamic, cyclical water temperature environment is applied to the experimental rearing tank using a water temperature gradient application model, and dynamic body shape parameters are obtained through image recognition and processing. This allows for the evaluation of the growth rate of target fish at different growth stages and temperature gradients, thereby screening out the optimal water temperature growth environment for different growth stages. It is applicable to the study of growth patterns, optimization of aquaculture environments, and seedling cultivation of various fish species, including freshwater fish, saltwater fish, and plateau fish. Attached Figure Description

[0010] Figure 1 This is a flowchart of an experimental method for monitoring fish growth and development under a temperature-controlled gradient.

[0011] Figure 2 Drawing in grayscale image N A schematic diagram of a vertical reference line. Detailed Implementation

[0012] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0013] like Figure 1 As shown, a method for monitoring fish growth and development under a temperature-controlled gradient includes the following steps: S1: Construct a water temperature gradient application model for the growth and development of the target fish species. The gradient water temperature application period is the theoretical period from fry to adult fish. The water temperature gradient includes a low-temperature phase, a suitable-temperature phase, and a high-temperature phase. ; in, The minimum and maximum water temperatures required for the target fish species to survive in their natural environment. To set the water temperature from the lowest water temperature Raise to the optimal water temperature The time point, t The growth and development time of the target fish. The timing for placing the fish fry into the experimental rearing tank. To adjust the water temperature from the optimal water temperature Rise to maximum water temperature The time point, This is the time point at which the theoretical cycle ends. a This is the coefficient for the rate of water temperature rise. b For the nonlinear coefficients in the low-temperature stage, A The set diurnal fluctuation amplitude of water temperature These represent the angular frequency and phase shift of the diurnal fluctuation of water temperature, respectively. c This is the water temperature stability coefficient. d The water temperature attenuation coefficient is... e The coefficient representing the rate of decrease in water temperature. f For the nonlinear coefficients in the high-temperature stage; In this embodiment, the lowest water temperature , maximum water temperature Optimal water temperature The optimal water temperature for the target fish species is determined based on the ambient water temperature of their natural habitat. For example, for the Qinghai Lake naked carp, the minimum water temperature is 6℃, the maximum water temperature is 22.3℃, and the optimal water temperature is 10℃. The optimal water temperature is the average annual water temperature of the Qinghai Lake naked carp's natural habitat. The temperature gradient includes the low-temperature stage. Suitable temperature stage and high temperature stage Nonlinear coefficients in the low-temperature stage b The increasing characteristic of the rate of temperature rise is characterized by a value of 1.2 to 1.5 in this embodiment, representing the water temperature stability coefficient. c Used to control water temperature around the optimal water temperature. The fluctuation range is taken as 0.5~1.0 in this embodiment, and the water temperature attenuation coefficient is... d Allow the water temperature to gradually approach the optimal water temperature. In this embodiment, the value is taken as 0.005~0.01, which is the nonlinear coefficient in the high-temperature stage. f The decreasing rate of water temperature decrease is characterized by a value of 1.1 to 1.3 in this embodiment, representing the diurnal fluctuation amplitude of water temperature. A Set to 1~3℃, the angular frequency of water temperature fluctuation between day and night. It adapts to the 24-hour day-night cycle.

[0014] S2: Based on the water temperature gradient, the model is applied to regulate different growth and development times of the target fish from fry to adult. t The water temperature is monitored, and images of the target fish are collected periodically to obtain the body size parameters of the target fish at different growth cycles under different water temperature gradients. The growth rate coefficient of the target fish at different growth cycles and different water temperature gradients is calculated.

[0015] This embodiment uses a transparent experimental rearing tank to raise the target fish, such as the Qinghai Lake naked carp. A set number (5 fish) of Qinghai Lake naked carp fry are placed in a water-filled experimental rearing tank for cultivation. The number of fry should not be too large to avoid overlapping during image acquisition. Each time an image of the target fish is acquired, it is optimal to select an image where each fish is fully displayed. Images with overlapping fish need to be re-acquired to allow for natural growth. The experimental rearing tank is equipped with a water temperature control system. The controller of the water temperature control system adjusts the water temperature at different stages based on a water temperature gradient application model. Body size parameters are identified and calculated using the acquired images of the Qinghai Lake naked carp. During the experiment, the rearing water is changed regularly to ensure cleanliness and prevent water quality from affecting the accuracy of the experiment. If any fish die unexpectedly, fish of the same size need to be added back to the experimental rearing tank.

[0016] Step S2 specifically includes: S21: Adjusting different growth and development times of target fish from fry to adult fish based on a water temperature gradient application model. tThe water temperature was monitored, and images of the experimental rearing tank were taken at regular intervals to obtain images of the target fish at different growth stages; S22: Convert the image of the target fish to grayscale to obtain a grayscale image, and set the standard grayscale value of the boundary pixels of the target fish in the image. And calculate the grayscale value of each pixel in the grayscale image. Compared with standard gray values The difference , These are pixel coordinates; S23: Set the pixel grayscale value difference threshold ,like Then determine the pixel If it is a boundary pixel, then determine the pixel. Not a boundary pixel; S24: Mark all boundary pixels in the grayscale image. And calculate each boundary pixel The difference in grayscale value between adjacent pixels If the boundary pixels The difference in grayscale value between each adjacent pixel satisfies Then determine the boundary pixels. If it is an isolated boundary pixel, then determine the boundary pixel. For continuous boundary pixels; S25: Replace all isolated boundary pixels in the grayscale image with the average grayscale value of its neighboring pixels. , w For isolated boundary pixels, v For isolated boundary pixels w Adjacent pixel numbers, V For isolated boundary pixels w Number of adjacent pixels; S26: Repeat steps S24-S25 until there are no isolated boundary pixels in the grayscale image, and output a grayscale image with isolated boundary pixel interference eliminated; S27: Draw uniformly in a grayscale image to eliminate interference from isolated boundary pixels. N A vertical reference line, such as Figure 2 As shown, the boundary pixels on each reference line are obtained, and the pixel coordinates of the two farthest boundary pixels on each reference line are extracted. The vertical distance between the two farthest boundary pixels is then calculated. ; ; in, n Number the vertical reference lines. These are the pixel coordinates of the two boundary pixels furthest apart on the vertical reference line. These are the numbers of the two boundary pixels furthest apart on the vertical reference line; S28: A vertical distance is obtained on each vertical reference line. ,from N vertical distance Filter the maximum value from the values This serves as the width data for the target fish during its current growth cycle. , a The target fish species is designated by its identification number. S29: Repeat steps S27-S28 to uniformly draw on the grayscale image after eliminating interference from isolated boundary pixels. M Horizontal reference line, calculation M A horizontal distance, and from M Select the maximum value from the horizontal distances, as... Length data of this target fish in its current growth cycle ; S210: Based on the number of target fish in the experimental rearing tank A Calculate the growth rate coefficient of the current growth cycle compared to the previous growth cycle. , The growth cycle number is used to calculate the growth rate coefficient; ; in, These are the width and length data of the target fish in the previous growth cycle, respectively. The time interval between two adjacent growth cycles. These represent the weights of the width and length of the target fish's growth on the growth rate coefficient, respectively. In this embodiment, we take... ; In this embodiment, the growth length and width of all fish in the comprehensive experimental breeding tank are used to calculate the growth rate coefficient, eliminating the error caused by individual differences. The growth rate coefficient of all target fish is calculated to characterize the comprehensive growth rate of target fish under different water temperature gradients. The larger the growth rate value, the faster the target fish grows under that water temperature gradient, and the more suitable it is for breeding under that water temperature gradient.

[0017] This invention uses the exp function to calculate the growth rate coefficient. The exp function is a monotonically increasing curve. As the difference between the width and length data increases, the exp function increases at a faster rate, thereby amplifying the growth rate coefficient and making the suitable water temperature gradient more prominent.

[0018] S211: Obtain the growth rate coefficient of the target fish under different growth cycles and different water temperature gradients.

[0019] S3: Calculate the average growth rate coefficient of the target fish under the same water temperature gradient using the growth rate coefficients at different growth stages and under different water temperature gradients. Use the average growth rate coefficient to assess whether the target fish is suitable for growth under the corresponding water temperature gradient at different growth stages. Step S3 specifically includes: S31: Calculate the average growth rate coefficient of the target fish under the same water temperature gradient using the growth rate coefficients at different growth stages and under different water temperature gradients. ; ; in, This refers to the number of times the growth rate coefficient is calculated under the same water temperature gradient.

[0020] S32: The average growth rate coefficient of the target fish at different water temperature gradients and different growth cycles. Threshold of growth rate coefficient Compare; like Then it is determined that the target fish is in the corresponding growth cycle. It is suitable for growth under this water temperature gradient; like Then it is determined that the target fish is in the corresponding growth cycle. It is not suitable for growth under this water temperature gradient.

[0021] This embodiment can further improve the screening accuracy of the optimal temperature gradient by conducting multiple experiments and applying different temperature gradients to different target fish growth cycles.

[0022] This invention is used to study the suitable temperature gradients and ranges for target fish at different growth stages under laboratory conditions, providing effective data support for fish to find new habitats or for artificial fish farming. A dynamic, cyclical water temperature environment is applied to experimental rearing tanks using a water temperature gradient application model, and dynamic body shape parameters are obtained through image recognition and processing. This allows for the evaluation of the growth rate of target fish at different growth stages and temperature gradients, thereby identifying the optimal water temperature growth environment for different growth stages. It is applicable to the study of growth patterns, optimization of aquaculture environments, and seedling cultivation of various fish species, including freshwater fish, saltwater fish, and plateau fish.

Claims

1. A method for monitoring fish growth and development under a temperature-controlled gradient, characterized in that, Includes the following steps: S1: Construct a water temperature gradient application model for the growth and development of the target fish species. The water temperature gradient application period is the theoretical period from fry to adult fish. The water temperature gradient includes a low temperature stage, a suitable temperature stage, and a high temperature stage. S2: Based on the water temperature gradient, the model is applied to regulate different growth and development times of the target fish from fry to adult. t The water temperature is monitored, and images of the target fish are collected periodically to obtain the body shape parameters of the target fish at different growth stages under different water temperature gradients. The body shape parameters include width data and length data. The growth rate coefficient of the target fish at different growth stages and different water temperature gradients is calculated. S3: Calculate the average growth rate coefficient of the target fish under the same water temperature gradient using the growth rate coefficient under different growth cycles and different water temperature gradients. Use the average growth rate coefficient to evaluate whether the target fish is suitable for growth under the corresponding water temperature gradient at different growth cycles.

2. The method for monitoring fish growth and development under a temperature-controlled gradient according to claim 1, characterized in that, The water temperature gradient application model in step S1 is specifically as follows: ； in, The minimum and maximum water temperatures required for the target fish species to survive in their natural environment. To set the water temperature from the lowest water temperature Raise to the optimal water temperature The time point, t The growth and development time of the target fish. The timing for placing the fish fry into the experimental rearing tank. To adjust the water temperature from the optimal water temperature Rise to maximum water temperature The time point, This is the time point at which the theoretical cycle ends. a This is the coefficient for the rate of water temperature rise. b For the nonlinear coefficients in the low-temperature stage, A The set diurnal fluctuation amplitude of water temperature These represent the angular frequency and phase shift of the diurnal fluctuation of water temperature, respectively. c This is the water temperature stability coefficient. d The water temperature attenuation coefficient is... e The coefficient representing the rate of decrease in water temperature. f This represents the nonlinear coefficient during the high-temperature stage.

3. The method for monitoring fish growth and development under a temperature-controlled gradient according to claim 2, characterized in that, Step S2 includes: S21: Adjusting different growth and development times of target fish from fry to adult fish based on a water temperature gradient application model. t The water temperature was monitored, and images of the experimental rearing tank were taken at regular intervals to obtain images of the target fish at different growth stages; S22: Convert the image of the target fish to grayscale to obtain a grayscale image, and set the standard grayscale value of the boundary pixels of the target fish in the image. And calculate the grayscale value of each pixel in the grayscale image. Compared with standard gray values The difference , These are pixel coordinates; S23: Set the pixel grayscale value difference threshold ,like Then determine the pixel If it is a boundary pixel, then determine the pixel. Not a boundary pixel; S24: Mark all boundary pixels in the grayscale image. And calculate each boundary pixel The difference in grayscale value between adjacent pixels If the boundary pixels The difference in grayscale value between each adjacent pixel satisfies Then determine the boundary pixels. If it is an isolated boundary pixel, then determine the boundary pixel. For continuous boundary pixels; S25: Replace all isolated boundary pixels in the grayscale image with the average grayscale value of its neighboring pixels. , w For isolated boundary pixels, v For isolated boundary pixels w Adjacent pixel numbers, V For isolated boundary pixels w Number of adjacent pixels; S26: Repeat steps S24-S25 until there are no isolated boundary pixels in the grayscale image, and output a grayscale image with isolated boundary pixel interference eliminated; S27: Draw uniformly in a grayscale image to eliminate interference from isolated boundary pixels. N We use vertical reference lines to obtain the boundary pixels on each reference line, extract the pixel coordinates of the two farthest boundary pixels on each reference line, and calculate the vertical distance between the two farthest boundary pixels. ; ； in, n Number the vertical reference lines. These are the pixel coordinates of the two boundary pixels furthest apart on the vertical reference line. These are the numbers of the two boundary pixels furthest apart on the vertical reference line; S28: A vertical distance is obtained on each vertical reference line. ,from N vertical distance Filter the maximum value from the values This serves as the width data for the target fish during its current growth cycle. , a The target fish species is designated by its identification number. S29: Repeat steps S27-S28 to uniformly draw on the grayscale image after eliminating interference from isolated boundary pixels. M Horizontal reference line, calculation M A horizontal distance, and from M Select the maximum value from the horizontal distances, as... Length data of this target fish in its current growth cycle ; S210: Based on the number of target fish in the experimental rearing tank A Calculate the growth rate coefficient of the current growth cycle compared to the previous growth cycle. , The growth cycle number is used to calculate the growth rate coefficient; ； in, These are the width and length data of the target fish in the previous growth cycle, respectively. The time interval between two adjacent growth cycles. The weights for the influence of the width and length of the target fish on the growth rate coefficient are respectively. S211: Obtain the growth rate coefficient of the target fish under different growth cycles and different water temperature gradients.

4. The method for monitoring fish growth and development under a temperature-controlled gradient according to claim 3, characterized in that, Step S3 includes: S31: Calculate the average growth rate coefficient of the target fish under the same water temperature gradient using the growth rate coefficients at different growth stages and under different water temperature gradients. ; ； in, This refers to the number of times the growth rate coefficient is calculated under the same water temperature gradient. S32: The average growth rate coefficient of the target fish at different water temperature gradients and different growth cycles. Threshold of growth rate coefficient Compare; like Then it is determined that the target fish is in the corresponding growth cycle. It is suitable for growth under this water temperature gradient; like Then it is determined that the target fish is in the corresponding growth cycle. It is not suitable for growth under this water temperature gradient.

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