CN-120782279-B - Multi-level screening and evaluating method for deep open sea suitable fish

CN120782279BCN 120782279 BCN120782279 BCN 120782279BCN-120782279-B

Abstract

The invention discloses a multi-level screening and evaluating method for deep-open sea suitable fish, which comprises the following steps of establishing a first-level environment analysis model based on sea condition parameters, hydrologic conditions and substrate parameters of a target sea area, matching deep-open sea culture facility types and matched equipment parameters according to a first-level analysis result to generate a second-level facility type selection scheme, integrating biological characteristics, economic values and industrial current situation data of the local fish of the target sea area, constructing a third-level local fish database, screening suitable fish adapting to the target sea area and facilities through a weighted allocation method based on comprehensive data of the first three levels, and forming a fourth-level evaluation result. The invention systematically integrates multidimensional data such as sea conditions, hydrology, substrates, biological characteristics, economic values and the like by constructing a five-layer framework, dynamically matches sea area environment and fish characteristics by a weighted score method (core indexes such as biological suitability, economic values and the like), and remarkably improves adaptability of suitable varieties.

Inventors

XU YONGJIANG
JIANG YAN
LIU XINFU
CUI AIJUN
ZHENG JICHANG
CAI XIN
WANG BIN

Assignees

中国水产科学研究院黄海水产研究所

Dates

Publication Date: 20260508
Application Date: 20250626

Claims (5)

1. The multi-level screening and evaluating method for the deep open sea suitable fish is characterized by comprising the following steps of: s1, establishing a first-level environment analysis model based on sea condition parameters, hydrologic conditions and substrate parameters of a target sea area; S2, matching the type of the deep-sea culture facility and the matched equipment parameters according to the first-level analysis result to generate a second-level facility model selection scheme; S3, integrating biological characteristics, economic value and current industrial state data of the native fishes in the target sea area, and constructing a third-level native fish database; S4, screening adaptive fishes adapting to the target sea area and facilities through a weighted score method based on the comprehensive data of the first three layers to form a fourth-layer evaluation result; S5, designing land-sea relay culture technology and an intelligent management scheme aiming at the screened suitable fish to generate fifth-level culture decisions; in the second-level facility selection scheme, the deep-open sea culture facility type comprises at least one of a wind and wave resistant gravity type net cage, a deep sea bottom-sitting intelligent net cage, a submerged truss net cage and a culture engineering ship, and the matched equipment comprises a bait feeding system, an environment monitoring device, climate monitoring equipment and relay transportation equipment; In the third-level native fish database, the biological characteristics comprise growth speed, flow resistance and feed protein demand, the economic value comprises market price, market demand and export potential, the industrial current situation comprises main-production-area distribution, cultivation mode and annual output data, and the data are dynamically updated and trend predicted through a machine learning algorithm; the weighting and grading method of the fourth-level evaluation result comprises the steps of setting four core indexes of biological suitability, economic value, industrialization feasibility and processing suitability, distributing dynamic weight coefficients for each index, calculating comprehensive scores through linear weighting, and screening fish with scores higher than a preset threshold value; In the fifth-level cultivation decision, the land-sea relay cultivation technology process comprises connection parameters of a land-based cultivation stage and a deep-open sea cultivation stage, specifically comprises a water temperature transition gradient, a transportation duration control and environment adaptability training scheme, and the intelligent management scheme comprises a remote environment monitoring module, a risk early warning system and a cultivation expert decision support module.
2. The multi-level screening and evaluating method for deep open sea suitable fish farming according to claim 1, wherein the sea condition parameters comprise wave height, ocean current speed and storm occurrence frequency, the hydrologic conditions comprise water temperature, salinity, dissolved oxygen and illumination intensity, the substrate parameters comprise geological structure type and mud layer thickness, and multidimensional data fusion and visual display are realized through a geographic information system.
3. The multi-level screening and evaluating method for deep open sea suitable fish farming according to claim 1, wherein the biological suitability index is further refined into three sub-parameters of hypoxia tolerance, disease resistance and storm resistance, and the weight coefficient of each sub-parameter is dynamically adjusted according to the environmental characteristics of the target sea area.
4. The multi-level screening and evaluating method for deep open sea suitable fish farming according to claim 1, wherein the method further comprises a culture data storage module based on a blockchain technology, wherein the culture data storage module is used for encrypting and storing each level screening process, evaluation result and decision basis, so as to ensure the non-falsifiability and whole-course traceability of data.
5. The multi-level screening and evaluating method for the deep open sea suitable fish farming of claim 1, wherein the intelligent management scheme is characterized in that the intelligent management scheme collects farming environment data in real time through Internet of things equipment, a virtual farming scene is constructed by utilizing a digital twin technology, fish growth states under different farming conditions are simulated, and bait feeding strategies and disaster emergency response schemes are optimized.

Description

Multi-level screening and evaluating method for deep open sea suitable fish Technical Field The invention relates to the technical field of deep sea cultivation, in particular to a multi-level screening and evaluating method for deep and open sea suitable fish. Background The great development of deep and open sea cultivation has become an important strategic direction for the transformation and upgrading of marine fishery and the high-quality development of China. Deep-sea large facilities such as deep-sea net cages, large fences, aquaculture boats and the like develop rapidly, and the mariculture is continuously pushed to develop in deeper and more distant sea areas. The key of successful deep-open sea cultivation is 'safety facility + intelligent equipment + fine variety + technical process'. However, the development of deep and open sea cultivation in China faces the embarrassment of few suitable cultivation varieties and insufficient support of cultivation technology, and an excellent suitable cultivation variety screening and cultivation technology system is urgently needed to be established to support the high-quality development of deep and open sea cultivation. According to the current variety and technical requirements of deep-open sea cultivation, a multi-level screening and evaluating method for the suitable-for-sea fish is established, and a suitable-for-cultivation variety screening and evaluating and suitable-for-cultivation variety land-sea relay cultivation technical support is provided for deep-open sea cultivation facilities in different sea areas. Disclosure of Invention The technical problem to be solved by the invention is to overcome the technical defects and provide a multi-level screening and evaluating method for deep open sea suitable fish culture. In order to solve the problems, the technical scheme of the invention is that the multi-level screening and evaluating method for the deep-open sea suitable fish culture comprises the following steps: s1, establishing a first-level environment analysis model based on sea condition parameters, hydrologic conditions and substrate parameters of a target sea area; s2, matching the type of the deep-sea culture facility and the matched equipment parameters according to the first-level analysis result to generate a second-level facility model selection scheme; S3, integrating biological characteristics, economic value and current industrial state data of the native fishes in the target sea area, and constructing a third-level native fish database; S4, screening adaptive fishes adapting to the target sea area and facilities through a weighted score method based on the comprehensive data of the first three layers to form a fourth-layer evaluation result; S5, designing land-sea relay culture technology and an intelligent management scheme aiming at the screened suitable fish, and generating a fifth-level culture decision. Further, in the second-level facility model selection scheme, the deep-open sea culture facility type comprises at least one of a wind and wave resistant gravity type net cage, a deep sea bottom-mounted intelligent net cage, a submerged truss net cage and a culture engineering ship, and the matched equipment parameters comprise a bait feeding system, an environment monitoring device, climate monitoring equipment, netting automatic cleaning equipment and sea-land relay transfer equipment. Further, the weighting and grading method of the fourth-level evaluation result comprises the steps of setting four core indexes of biological suitability, economic value, industrialization feasibility and processing suitability, distributing dynamic weight coefficients for each index, calculating comprehensive scores through linear weighting, and screening fish with scores higher than a preset threshold value. Further, the biological suitability index is further refined into three sub-parameters of hypoxia tolerance, disease resistance and storm resistance adaptability, and the weight coefficient of each sub-parameter is dynamically adjusted according to the environmental characteristics of the target sea area. Further, the intelligent management scheme collects the breeding environment data in real time through the Internet of things equipment, a virtual breeding scene is constructed by utilizing a digital twin technology, the growth state of fishes under deep sea breeding conditions is monitored and calculated, and the bait feeding strategy and emergency response scheme of emergency are optimized. Further, the sea condition parameters comprise wave height, ocean current speed and storm occurrence frequency, the hydrologic conditions comprise water temperature, salinity, dissolved oxygen, pH, illumination intensity and the like, the substrate parameters comprise geological structure type and mud layer thickness, and multidimensional data fusion and visual display are realized through a geographic information system. Further, in the third-level