CN113749030B - Fish welfare self-adaptive feeding system suitable for circulating water aquaculture mode - Google Patents
Fish welfare self-adaptive feeding system suitable for circulating water aquaculture mode Download PDFInfo
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K61/00—Culture of aquatic animals
- A01K61/80—Feeding devices
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Mining
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06T2207/10016—Video; Image sequence
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- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/80—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in fisheries management
- Y02A40/81—Aquaculture, e.g. of fish
Abstract
The invention discloses a fish welfare self-adaptive feeding system suitable for a recirculating aquaculture mode, which comprises a water treatment system, a variable-frequency feeder, an aquaculture pond, a processor, a light supplement lamp, a camera and a variable-frequency water pump, wherein the variable-frequency water pump is connected with the water treatment system; the system mainly utilizes computer vision and deep learning technology to carry out real-time analysis and quantification on the ingestion welfare of the recirculating aquaculture fishes; synchronously coupling water quality prediction information, and regulating and controlling feed feeding amount according to an 'ingestion welfare-water quality' interaction model, thereby realizing welfare self-adaptive feeding of the recirculating aquaculture fishes. The system disclosed by the invention is simple in structure, simple, convenient and effective in method, and capable of avoiding deterioration of aquaculture water quality while guaranteeing the ingestion welfare of the aquaculture fishes, thereby improving the production efficiency and maximizing the aquaculture benefit.
Description
Technical Field
The invention belongs to the technical field of fish culture feeding, relates to a fish swarm behavior analysis and recirculating aquaculture system feeding amount decision method, and particularly relates to a fish welfare self-adaptive feeding system suitable for a recirculating aquaculture mode.
Background
The circulating water aquaculture is a type of aquaculture mode which is developed vigorously since the 21 st century, belongs to an intensive aquaculture mode with high water resource utilization rate, can save 90-99% of water resources compared with the traditional aquaculture system, can realize controllable production and environmental factors, and is considered as the inevitable development trend of future fishery, and the aquaculture area can be less than 1% of that of the traditional aquaculture mode. How to realize the welfare feeding of fishes in a circulating water culture mode is not only a difficult problem in production management, but also a key technical problem to be solved urgently for realizing the welfare culture of culture objects. Although various automatic and intelligent feeding technologies are proposed at present, most of the feeding technologies only concern the food intake desire or demand of the breeding objects, ignore the problems of swimming energy consumption and water quality regulation of the breeding objects caused by feeding, and cannot completely realize the welfare feeding of the breeding objects.
The shoal behavior is a lossless and effective index reflecting the eating desire and swimming energy consumption of the cultured fishes, and by means of computer vision and related image processing technology, the high-precision quantification of the shoal behavior can be realized, so that the real-time eating desire and swimming energy consumption evaluation of the cultured fishes is realized. Therefore, the beneficial feeding of the cultured fishes can be realized by utilizing the spontaneous behavior of the fish school and synchronously coupling the water quality early warning information.
On the basis of the background, the invention provides a fish welfare feeding system suitable for a recirculating aquaculture mode, which utilizes computer vision and deep learning technology to carry out real-time analysis and quantification on the eating welfare (eating desire and swimming energy consumption) of recirculating aquaculture fishes; synchronously coupling water quality prediction information, and regulating and controlling the feed feeding amount according to the 'ingestion welfare-water quality' interaction principle, thereby realizing welfare self-adaptive feeding of the recirculating aquaculture fish. The system can ensure the ingestion welfare of the cultured fishes and simultaneously avoid the deterioration of the cultured water quality, thereby improving the production efficiency and maximizing the culture benefit.
Disclosure of Invention
The invention aims to provide a fish welfare self-adaptive feeding system suitable for a circulating water culture mode, which can complete the decision of feeding amount according to the feeding demand predicted by fish swimming behavior information and water quality prediction information and provide good technical support for welfare feeding operation of circulating water culture.
The technical scheme adopted by the invention is as follows:
a fish welfare self-adaptive feeding system suitable for a recirculating aquaculture mode firstly analyzes and quantifies the eating desire and swimming energy consumption of recirculating aquaculture fishes in real time; synchronously coupling water quality prediction information, and then regulating and controlling the feed feeding amount according to the 'ingestion welfare-water quality' interaction principle, thereby realizing welfare self-adaptive feeding of the recirculating aquaculture fishes.
The system can comprise a water treatment system, a variable-frequency feeder, a culture pond, a processor, a light supplement lamp, a camera and a variable-frequency water pump; the camera is arranged right above the culture pond and is connected with the processor; and the output end of the processor is respectively connected with the variable-frequency feeder, the light supplementing lamp and the variable-frequency water pump.
The self-adaptive feeding system can be used for carrying out a welfare feeding decision in the circulating water culture by analyzing the ingestion desire, swimming energy consumption and water quality prediction conditions of the culture object, and specifically comprises the following steps:
before feeding:
(1) the DSP triggers the high-definition camera to read real-time pictures, then the DSP quantizes the overall motion characteristics of the fish school within 30s before feeding by utilizing the improved kinetic energy model, and the improved kinetic energy model is expressed as follows: E-CE×v2In which C isEThe degree of irregularity of the fish school movement is represented as v, and the average movement speed of the fish school (namely the average movement speed of pixel points representing the fish school) is represented as v; then, linear fitting is carried out on the kinetic energy value E obtained from the time sequence, and the absolute value | k | of the slope k is solved;
(2) meanwhile, the fish school foreground is segmented by utilizing a segmentation algorithm, and the average swing frequency (f) and the average swing amplitude of the tail of the fish school are calculated based on the obtained fish school foreground(a, taking the fish body length as a unit), and then calculating the fish swimming energy consumption, wherein the fish swimming energy consumption is expressed as
Wherein U is the current average flow velocity of the water body (taking the length of the fish body as a unit), and N is the number of individuals in the fish school; int is a rounding function. The segmentation algorithm preferably employs a deep learning instance segmentation algorithm.
In the feeding process (firstly, based on a single-round multiple feeding strategy, the feeding time length of each time is T, and the feeding interval time of each time is 3T):
(1) the fish school movement characteristics in each feeding process are quantified by utilizing an improved kinetic energy model, and the time point (recorded as t) of the maximum kinetic energy value in the process is determinedmax) (ii) a Then feeding is started at the time point t0To a time point tmaxLinear fitting is carried out on the kinetic energy value, and an absolute value | k ' | of the slope k ' of the linear fitting is obtained, namely the larger | k ' | is, the stronger is the fish herd eating desire;
(2) synchronously, calculating the average swimming energy consumption of the fish school in the 2T-3T time period after each feeding trigger (marked as E)s’)；
(3) Meanwhile, ammonia nitrogen discharge amount within 3 hours after each feeding of the fish school is predicted by using a water quality prediction model, and the predicted discharge amount is expressed as Q1.21 × log2(Qf×Qp×QN×tx) Wherein Q isfFor the current total feed (in kg), QpAnd QNIs the percentage of protein and nitrogen content in the feed, txIs a time number (taking every 10 minutes as a timing unit), t is more than or equal to 0x≤18。
(4) When | k ' | is more than or equal to 1.4| k | and | E |, the method can be used for solving the problem that the absolute value of | k ' | is larger than or equal to 1.4| k |, and | E |, the method can not be used for solving the problem that the absolute value of | k ' | is larger than or equal to 1.4| k | and | ES'|≤1.25|ESIs |, and Q is not more than QratedTime (Q)ratedThe maximum ammonia nitrogen treatment capacity in unit time of a biological filter in a recirculating aquaculture system), feeding the next time, wherein the feeding amount is 90% of the current feeding amount;
(5) when | k' | is ≧ 1.4| k | and | ES'|＞1.25|ESIs |, and Q is not more than QratedWhen the system is used, the system automatically aligns to the current water bodyThe flow rate U ' is adjusted to ensure that U ' is more than or equal to 0.83U and less than or equal to U ', and the next feeding is carried out, wherein the feeding amount is the current feeding amount
(6) When | k' | < 1.4| k | or Q > QratedOr stopping feeding when the average fish length is less than or equal to 0.5 time.
The invention has the beneficial effects that;
the fish welfare self-adaptive feeding system applicable to the circulating water culture mode is simple in structure and accurate and effective in method, the feeding quantity decision is based on an interaction model of 'food intake welfare (food intake desire and swimming energy consumption) -water quality' of cultured fishes, the food intake welfare of the cultured fishes is emphasized, the excessive dependence on the artificial experience in the feeding quantity decision process is eliminated, the development trend of the aquaculture welfare is met, and the production efficiency of the circulating water culture is effectively improved while the energy supply required by the growth of cultured fish groups is met.
Drawings
FIG. 1 is a structural diagram of a fish welfare self-adaptive feeding system suitable for a circulating water culture mode.
In the figure: 1-a circulating water treatment system; 2-frequency conversion feeder; 3-a culture pond; 4, a DSP processor; 5-LED light supplement lamp; 6-high definition camera; 7-frequency conversion water pump.
Detailed Description
The invention is further described with reference to the following figures and specific examples.
Referring to fig. 1, a concrete structure example of the fish welfare self-adaptive feeding system suitable for the circulating water aquaculture mode comprises a water treatment system 1, a variable frequency feeding machine 2, a culture pond 3, a DSP processor 4, an LED light supplement lamp 5, a high definition camera 6 and a variable frequency water pump 7; the high-definition camera 6 is arranged right above the culture pond 3 and is connected with the DSP 4; meanwhile, the output end of the DSP 4 is respectively connected with the variable-frequency feeder 2, the LED light supplement lamp 5 and the variable-frequency water pump 7.
The device is applied to the circulating water culture system welfare self-adaptive feeding decision, and the decision method comprises the following steps:
before feeding:
(1) DSP triggers high definition camera to read the real-time picture, DSP then utilizes the improvement kinetic energy model to quantize the fish school global motion characteristic in 30s before throwing something and feeding, and the improvement kinetic energy model expression is: e ═ CE×v2In which C isEV is the average movement speed of the fish school (namely the average movement speed of pixel points representing the fish school) (the model can be specifically found in the literature, research on evaluation method of feeding activity intensity of swimming fish in recirculating aquaculture, report of agricultural machinery, 2016,8: 288-; then, linear fitting is carried out on the dynamic value E obtained from the time sequence, and the absolute value | k | of the slope k of the linear value E is obtained;
(2) meanwhile, the fish school foreground is segmented by utilizing a segmentation algorithm, the average swing frequency (f) and the average swing amplitude (a; the fish body length is taken as a unit) of the tail of the fish school are calculated based on the obtained fish school foreground, and then the fish school swimming energy consumption is calculated, wherein the fish school swimming energy consumption is expressed as
Wherein U is the current average flow velocity of the water body (taking the length of the fish body as a unit), and N is the number of individuals in the fish school; int is a rounding function.
In the feeding process (firstly, based on a single-round multiple feeding strategy, the feeding time length of each time is T, and the feeding interval time of each time is 3T):
(1) quantizing the fish school motion characteristics in each feeding process by utilizing an improved kinetic energy model, determining the time point of the maximum value of the kinetic energy in the process, and recording as tmax(ii) a Then feeding is started at the time point t0To a time point tmaxLinear fitting is carried out on the kinetic energy value, and an absolute value | k ' | of the slope k ' of the linear fitting is obtained, namely the larger | k ' | is, the stronger is the fish herd eating desire;
(2) synchronously, calculating the average swimming energy consumption of the fish school in the 2T-3T time period after each feeding trigger, and recording as Es’；
(3) Meanwhile, ammonia nitrogen in 3 hours after each feeding of the fish school is predicted by using a water quality prediction modelThe emission was predicted, and the predicted emission was expressed as Q1.21 × log2(Qf×Qp×QN×tx) Wherein Q isfFor the current total feed (in kg), QpAnd QNThe contents of protein and nitrogen in the feed are percent, txIs a time sequence number (taking every 10 minutes as a timing unit), t is more than or equal to 0x≤18。
(4) When | k ' | is more than or equal to 1.4| k | and | E |, the method can be used for solving the problem that the absolute value of | k ' | is larger than or equal to 1.4| k |, and | E |, the method can not be used for solving the problem that the absolute value of | k ' | is larger than or equal to 1.4| k | and | ES'|≤1.25|ESIs |, and Q is not more than QratedTime (Q)ratedThe maximum ammonia nitrogen treatment capacity in unit time of a biological filter in a recirculating aquaculture system), feeding the next time, wherein the feeding amount is 90% of the current feeding amount;
(5) when | k ' | is more than or equal to 1.4| k | and | E |, the method can be used for solving the problem that the absolute value of | k ' | is larger than or equal to 1.4| k |, and | E |, the method can not be used for solving the problem that the absolute value of | k ' | is larger than or equal to 1.4| k | and | ES'|＞1.25|ESI and Q is less than or equal to QratedWhen the system is used, the current water flow rate U 'is automatically adjusted by the system, so that the current water flow rate U' is more than or equal to 0.83U 'and less than or equal to U', and the next feeding is carried out simultaneously, wherein the feeding amount is the current feeding amount
(6) When | k' | < 1.4| k | or Q > QratedOr stopping feeding when the average fish length is less than or equal to 0.5 time.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention.
Claims (3)
1. A fish welfare feeding system suitable for a recirculating aquaculture mode is characterized in that the fish eating desire and swimming energy consumption of the recirculating aquaculture fish are analyzed and quantified in real time; synchronously coupling water quality prediction information, and regulating and controlling the feed feeding amount according to the 'ingestion welfare-water quality' interaction principle, thereby realizing welfare self-adaptive feeding of the circulating water aquaculture fish; the system carries out welfare feeding decision in the circulating water aquaculture by analyzing the feeding desire, swimming energy consumption and water quality prediction condition of the cultured fishes, and the following operations are carried out before feeding:
(1) the processor triggers the camera to read a real-time picture, then the processor quantifies the overall motion characteristics of the fish school within 30s before feeding by using an improved kinetic energy model, and the improved kinetic energy model is expressed as follows: e ═ CE×v2In which C isEThe degree of irregularity of the fish school movement is represented as v, and the average movement speed of the fish school is represented as v, namely the average movement speed of pixel points representing the fish school; then, linear fitting is carried out on the kinetic energy value E obtained from the time sequence, and the absolute value | k | of the slope k is solved;
(2) utilizing a segmentation algorithm to segment the fish school foreground, calculating the average swing frequency f and the average swing amplitude a of the tail of the fish school based on the obtained fish school foreground, and then calculating the fish school swimming energy consumption which is expressed as
Wherein U is the current average flow velocity of the water body, and N is the number of individuals in the fish school; int is a rounding function;
the system is based on a single-round multi-feeding strategy, the feeding time is T every time, the feeding interval time of every two times is 3T, and then the following operations are carried out in the feeding process:
(1) quantizing the fish school motion characteristics in each feeding process by utilizing an improved kinetic energy model, determining the time point of the maximum value of the kinetic energy in the process, and recording as tmax(ii) a Then feeding is started at the time point t0To a time point tmaxLinear fitting is carried out on the kinetic energy value, and the absolute value | k ' | of the slope k ' of the linear fitting is obtained, namely the current ingestion desire of the fish school is stronger if | k ' | is larger;
(2) synchronously, calculating the average swimming energy consumption of the fish school in the 2T-3T time period after each feeding trigger, and recording as Es’；
(3) Meanwhile, ammonia nitrogen discharge amount within 3 hours after each feeding of the fish school is predicted by using a water quality prediction model, and the predicted discharge amount is expressed as Q1.21 × log2(Qf×Qp×QN×tx) Wherein Q isfFor the current total feeding amount, QpAnd QNAre respectively asPercentage of protein and nitrogen content in the feed, txIs a time sequence number, takes every 10 minutes as a timing unit, and t is more than or equal to 0x≤18；
(4) When | k ' | is more than or equal to 1.4| k | and | E |, the method can be used for solving the problem that the absolute value of | k ' | is larger than or equal to 1.4| k |, and | E |, the method can not be used for solving the problem that the absolute value of | k ' | is larger than or equal to 1.4| k | and | ES'|≤1.25|ESIs |, and Q is not more than QratedIn which Q isratedFeeding the next time for the maximum ammonia nitrogen treatment capacity in unit time of a biological filter in a recirculating aquaculture system, wherein the feeding amount is 90% of the current feeding amount;
(5) when | k' | is ≧ 1.4| k | and | ES'|＞1.25|ESIs |, and Q is not more than QratedWhen the system is used, the current water flow rate U 'is automatically adjusted by the system, so that the current water flow rate U' is more than or equal to 0.83U 'and less than or equal to U', and the next feeding is carried out, wherein the feeding amount is the current feeding amount
(6) When | k' | < 1.4| k | or Q > QratedOr stopping feeding when the average fish length is less than or equal to 0.5 time.
2. The fish welfare feeding system suitable for the recirculating aquaculture mode of claim 1, wherein the system comprises a water treatment system, a variable frequency feeding machine, an aquaculture pond, a processor, a light supplement lamp, a camera and a variable frequency water pump; the camera is arranged right above the culture pond and is connected with the processor; and the output end of the processor is respectively connected with the variable-frequency feeder, the light supplementing lamp and the variable-frequency water pump.
3. The fish welfare feeding system for the recirculating aquaculture mode of claim 1, wherein the segmentation algorithm is a deep learning instance segmentation algorithm.
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