Pillar Industry Research Articles

Nano-Zinc Oxide Can Enhance the Tolerance of Apple Rootstock M9-T337 Seedlings to Saline Alkali Stress by Initiating a Variety of Physiological and Biochemical Pathways

Soil salinization severely restricts the growth and development of crops globally, especially in the northwest Loess Plateau, where apples constitute a pillar industry. Nanomaterials, leveraging their unique properties, can facilitate the transport of nutrients to crops, thereby enhancing plant growth and development under stress conditions. To investigate the effects of nano zinc oxide (ZnO NP) on the growth and physiological characteristics of apple self-rooted rootstock M9-T337 seedlings under saline alkali stress, one-year-old M9-T337 seedlings were used as experimental materials and ZnO NPs were used as donors for pot experiment. Six treatments were set up: CK (normal growth), SA (saline alkali stress,100 mmol/L NaCl + NaHCO3), T1 (saline alkali stress + 50 mg/L ZnO NPs), T2 (saline alkali stress + 100 mg/L ZnO NPs), T3 (saline alkali stress + 150 mg/L ZnO NPs) and T4 (saline alkali stress + 200 mg/L ZnO NPs). The results were found to show that saline alkali stress could significantly inhibit the growth and development of M9-T337 seedlings, reduce photosynthetic characteristics, and cause ion accumulation to trigger osmotic regulation system, endogenous hormone and antioxidant system imbalances. However, the biomass, plant height, stem diameter, total leaf area and leaf perimeter of M9-T337 seedlings were significantly increased after ZnO NP treatment. Specifically speaking, ZnO NPs can improve the photosynthetic capacity of M9-T337 by increasing the content of photosynthetic pigment, regulating photosynthetic intensity and chlorophyll fluorescence parameters. ZnO NPs can balance the osmotic adjustment system by increasing the contents of soluble protein (SP), soluble sugar (SS), proline (Pro) and starch, and can also enhance the activities of enzymatic (SOD, POD, and CAT) and non-enzymatic antioxidant enzymes (APX, AAO, GR, and MDHAR) to enhance the scavenging ability of reactive oxygen species (H2O2, O2•−), ultimately reducing oxidative damage; ZnO NPs promoted the growth of M9-T337 seedlings under saline alkali stress by synergistically responding to auxin (IAA), gibberellin (GA3), zeatin (ZT) and abscisic acid (ABA). Additionally, the Na+/K+ ratio was reduced by upregulating the expression of Na+ transporter genes (MdCAX5, MdCHX15, MdSOS1, and MdALT1) and downregulating the expression of K+ transporter genes (MdSKOR and MdNHX4). After comprehensive analysis of principal components and correlation, T3 (150 mg/L ZnO NPs) treatment possessed the best mitigation effect. In summary, 150 mg/L ZnO NPs(T3) can effectively maintain the hormone balance, osmotic balance and ion balance of plant cells by promoting the photosynthetic capacity of M9-T337 seedlings, and enhance the antioxidant defense mechanism, thereby improving the saline alkaline tolerance of M9-T337 seedlings.

A Comparative Study of Tourism and Advantageous Industries Between the Philippines and Thailand

The Philippines and Thailand are famous tourist countries in Southeast Asia. Against the backdrop of increasing competition in the tourism industry in Association of Southeast Asia Nations (ASEAN) countries, this article undertakes a comparative and analytical examination on the development of the Philippines and Thailand's dominant tourism industry segments, namely eco-tourism and medical tourism. Compared with Thailand, the Philippines, which has a lower international reputation as a tourist destination, can enhance the competitiveness of its tourism industry by strengthening publicity on streaming platforms and promoting rural tourism while improving infrastructure construction. The Philippines' increasingly sophisticated model of environmental eco-tourism has a long-term vision. Thailand is known worldwide for its low-cost, technologically advanced medical tourism, and offers world-renowned Thai massage to further maintain its advantages in the international market. Facing the huge tourism pressure of Thailand's ecological environment, this paper puts forward some suggestions on closing scenic spots during off-season, collecting environmental protection funds from tourists, and opening digital exhibition of national culture. The Philippines and Thailand are the representatives of island and mainland tourism countries in Southeast Asia respectively. This article has a practical reference for other countries in Southeast Asia that take tourism as the pillar industry.

Analysis and Prevention of Financial Risks of Real Estate Enterprises in China

As an important pillar industry of the national economy, the real estate industry has the characteristics of high investment, high return and high risk. In the process of rapid economic development in China, the real estate industry has developed rapidly and become one of the main driving forces of economic growth. However, while pursuing high profits, real estate enterprises are also facing huge financial risks, which are directly related to the survival and development of enterprises. As a leading real estate enterprise in China, Vanke Group's financial situation and risk management strategy have attracted much attention. In recent years, with the constant changes in the macro-control policies of the national real estate industry, the financial risk problem of Vanke Group has become increasingly prominent. This paper aims to analyze the financial risks of Vanke Group and discuss how real estate enterprises can effectively identify, evaluate and prevent financial risks in the complex and changeable economic environment.

Research on the Determinants of Real Estate Prices in China under Supply and Demand

Since the reform and opening up, the real estate industry has gradually become the pillar industry of the Chinese people, directly or indirectly promoting the development of macro-economy. However, in recent years, the continuous rise of housing prices has become the focus of attention of the government and all sectors of society, which has triggered extensive and in-depth discussion and attention on the real estate industry. Real estate prices are not only closely related to people's lives, but also related to the development of cities and the long-term stability of the country. The healthy development of the real estate industry is also related to the composition of household wealth and government revenue, as well as the stable development of the national economy. Therefore, it is of great practical significance to pay attention to the changes of housing prices. This paper mainly summarizes and reviews the relevant literature on the analysis of factors affecting house prices at home and abroad from three aspects: the supply side, the demand side and the hedonic price model of real estate. It provides basic underlying logic for academic research, policy-making, practical application and individual house purchase decision-making.

Research Progress on the Recycle and Reuse of Wasted Aluminum Substrates of CTP Plates

Recycling and reuse of wasted materials is a key topic in materials research, providing a new material recycling path for green manufacturing. As a national pillar industry, the greening and intelligent upgrading of the printing industry is an inevitable trend in the development of modern printing. To better implement the national “dual-carbon strategy” and cultivate new quality productivity, this paper presents a systematic literature review on the research progress of the recycling and reuse techniques of used aluminum substrates of CTP plates for offset printing. Analysis of existing industry data and literature shows that aluminum substrate of used CTP plates meets the recycle size and required physical and chemical characteristics, but the current research has not yet fully taken into account the integration of technical innovation in the recycling and reuse of aluminum substrate of used CTP plates. Based on material eco-cycling perspectives such as sustainable material utilization design, wasted material recycling device and multi-material fine separation process, this paper provides a unique outlook on the integrated development trend of recycling and reuse of aluminum substrates of used CTP plates, and provides greening case references for the safe management of wasted materials in the modern offset printing industry.

Analysis of Carbon Emission Driving Factors and Decoupling Effects in the Textile Industry of the Demonstration Zone of Green and Integrated Ecological Development of the Yangtze River Delta

The textile industry is one of the pillar industries in the Yangtze River Delta Region and its green and low-carbon transformation is important for supporting the high-quality development of the Yangtze River Delta. Considering the demonstration zone of green and integrated ecological development of the Yangtze River Delta as an example, this integrated study was conducted on the carbon emission inventory of the textile industry, the driving factors of carbon emissions in the industry, and decoupling effects. Based on the emission factor method, the carbon emissions of Scope 1 and 2 of the textile industry in the demonstration zone were estimated. The carbon emission efficiency of the industry was analyzed using the super efficiency slack-based measure （SBM） model with unexpected outputs. Combining the LMDI factor decomposition method and Tapio decoupling analysis, the driving factors of carbon emissions in the textile industry in the demonstration zone and the decoupling situation between emissions and economic development were identified. The results indicated： ① Between 2014 and 2021, the carbon emissions of the textile industry in the demonstration zone showed a fluctuating trend, reaching the highest value in 2019 at 9.19 million tons of CO2 equivalent. Wujiang District was the primary emission area, with electricity, heat, and coal consumption emissions being the top three emission sources. ② The overall carbon emission efficiency of the textile industry in the demonstration zone showed an upward trend； however, significant differences were present in carbon emission efficiency between regions, with Jiashan County having considerable room for improvement in carbon emission efficiency. ③ Between 2014 and 2021, the driving factors of carbon emissions in the textile industry in various regions of the demonstration zone showed significant changes, with the level of economic development being a positive driving factor affecting carbon emissions. ④ In terms of the decoupling status between carbon emissions and economic development, the overall textile industry in the demonstration zone showed a transition from negative decoupling to decoupling status between 2014 and 2016. The research results provide a scientific basis for the future balanced development of the green and low-carbon transformation of the textile industry and the high-quality development of the economy in the demonstration zone.

Research on factors influencing total carbon emissions of construction based on structural equation modeling: A case study from China

As a pillar industry in China, the construction sector plays a crucial role in advancing the country's carbon emission (CE) reduction initiatives. The factors influencing CE in the construction industry (CI) are numerous and complex. This paper analyzes the influencing factors of CE in the CI based on structural equation modeling. Firstly, by combining the relevant literature and actual situation of CE in the CI, 38 common influencing factors corresponding to the building, economic, social, technological and energy levels are initially selected, and the data corresponding to each influencing factor in each province and city in China for 10 years are collected and then processed without dimension. Secondlyd, 12 hypothetical relationships between building, economic, social, technological and energy and CE from the CI are established based on the actual situation, and the initial CE in the CI structural equation model is established after the data set is tested for normal distribution, reliability and validity. Thirdly, the model is evaluated for path significance and model fit, and the modified structural equation model of CE from the CI is obtained after the initial model is modified, and the modified model is evaluated again. Finally, based on the modified model, the influence degree and effect of CE influencing factors in the CI are analyzed. It is concluded that economy, technology, and energy are the main factors successively affecting the total CE of buildings.

Research on the Path of Digital Economy Empowering the Green Transformation and Upgrading of Jiangsu’s Manufacturing Industry

In the era of digital economy, digital technology has become an important force in promoting industrial upgrading. As a pillar industry in Jiangsu, manufacturing plays an important role in promoting Jiangsu's economic development. With the proposal of the "dual carbon" goal, how to enable the digital economy to empower the green transformation and upgrading of Jiangsu's manufacturing industry has become a common concern in the industry. In view of a series of problems currently existing in Jiangsu's manufacturing industry, including the imbalance of regional digital economic development, low integration of digital economy and manufacturing, and "stuck" key core technologies, it is proposed to increase financial investment support, enhance digital innovation, and Strengthening the research and development of key core technologies will be the path to comprehensively enhance the green manufacturing capabilities of Jiangsu's manufacturing industry and deepen digital technology empowerment.

A Study on the Relationship between Civil Automobile Consumption and Real Estate in China

Since the reform and opening up, China’s economy has been booming, especially the real estate industry and the automobile industry, which have become the first and second pillar industries of China’s economy in recent years. Different scholars have studied the impact of the real estate, residential and automotive sectors on other consumption and have different attitudes. However, few studies have analyzed the relationship between the two, and it is impossible to know the specific relationship between them. Therefore, this paper first puts forward a new theoretical hypothesis for the interaction between the two, then uses Eviews7.2 as the main data processing tool, and uses the cointegration test and the Granger causality test to conduct an empirical analysis of the annual number of new registered civil vehicles and the annual real estate and residential development investment amount in China from 2002 to 2022. The results show a long-term and stable equilibrium relationship between civil automobile consumption and the real estate and residential industry and that civil automobile consumption is a one-way Granger reason for the development of the real estate and residential industry, which is in line with one of the hypotheses. Finally, based on the conclusion, this paper proposes policy suggestions to promote real estate development through automobile consumption.

Research on Dynamic Flexible Performance Evaluation System of Geely Automobile under the Background of Digital Transformation

As a pillar industry of the country, the automobile manufacturing industry implements the digital transformation strategy in the era of intelligent innovation, which is not only an objective requirement for the development of the digital economy in the era of big data, but also an internal driving force for diversified consumer demand and improving the core competitiveness of products, reducing costs and increasing efficiency and improving the operating efficiency of enterprises. Under the premise of analyzing the necessity and feasibility of the construction of Geely Automobile's dynamic flexible performance evaluation system under the background of digital transformation, this paper constructs Geely Automobile's dynamic flexible performance evaluation system from four aspects: target layer, criterion layer, scheme layer and influence layer, based on the principles of dynamic flexibility and reflecting key success factors. The empirical results show that the Geely Automobile dynamic flexible performance evaluation system constructed in this paper has relevance, stability and explanatory ability.

Research on Jiangxi Cultural Wisdom Tourism Industry Strategy Based on OHDSI General Data Model and Digital Art Empowerment

With the rapid development and wide application of a new round of information technologies, such as the global Internet of Things, the new generation of mobile Internet, cloud computing, etc., informatization has opened a new stage of smart tourism (ST), and ST has become the main trend of tourism development in China at present and for a long time to come. Tourism industry has become one of the important pillar industries in Jiangxi, and it plays an increasingly prominent role in stimulating and supporting economic and social development. Wisdom tourism is an important means to improve tourism service, tourism management and tourism marketing, and an important starting point to promote the upgrading of tourism industry in Jiangxi Province, and to achieve carry-over and leapfrog development and overtaking at corners. This paper is constantly improving and updating on the basis of data warehouse integration mechanism. Under the data warehouse mechanism, through the effective integration of spatial data, virtual reality data and dynamic data, a comprehensive data warehouse oriented to tourism promotion, scenic spot management and department management is formed. It aims to promote the rapid implementation of ST, bring tourists a comfortable tourism experience, save costs and improve efficiency for tourism service providers.

An Introduction to the Development and Protection of Tourism Resources in China

Introduction: Tourism resources provide great potential for tourism development, but at the same time, they also face problems such as over-exploitation and environmental damage, so it is crucial to achieve a balance between development and conservation. This study explores the development and protection of tourism resources in China. Background: Since the reform and opening up of China more than 30 years ago, China's tourism industry has rapidly developed into one of the important pillar industries of the national economy. At the same time, the destruction of tourism resources has also become more and more prominent, therefore, we must correctly deal with the relationship between the development and protection of tourism resources, to ensure the economic benefits while achieving the sustainable development of tourism resources. Novelty: Many studies in China currently focus on either tourism development or conservation, but this study endeavours to consider the relationship between the two in an integrated manner, providing a comprehensive approach to effectively develop and conserve China's rich tourism resources, while at the same time obtaining economic benefits. Research Methods: This study adopts the methods of literature review and qualitative analysis to review the research results on the development and protection of China's tourism resources by collecting relevant literature and summarising and analysing the ideas in the literature to conclude the development and protection of China's tourism resources. Finally, corresponding management suggestions and policy measures are proposed based on the conclusions. Results:To promote the sustainable use and protection of tourism resources, and to ensure the long-term stability and sustainability of the resources Conclusions: To solve this problem, this study puts forward the following suggestions: (1) to formulate strict laws and regulations; (2) to raise the overall awareness of environmental protection; (3) to promote the corresponding scientific research and technological support; (4) to strengthen tourism planning and management. (5) Establishment of funds for the protection of tourism resources; (6) Strengthening of cooperation and exchanges.

Quantitative simulation and validation of energy carbon emission efficiency changes in Chinese urban agglomerations

In the context of the global energy dilemma, enhancing energy efficiency has inevitably become a pivotal strategy for mitigating energy waste and promoting sustainable development. Urban agglomerations, as growth poles leading high-quality regional economic development, play a significant role in this process. Within these urban agglomerations, the aggregation of various factors and the substitution of energy resources substantially influence the energy carbon emission efficiency (ECEE) of surrounding cities during their development and maturation phases. This study initially employs a three-stage Data Envelopment Analysis (DEA) to quantitatively analyze the ECEE values of 19 urban agglomerations from 2006 to 2020. It then establishes a methodology for calculating the joint intensity (JI) and joint threshold (JT) of ECEE within these urban agglomerations. Finally, a validation process is executed using MATLAB simulation and verification methodology to fit and authenticate the evolutionary patterns of ECEE in Chinese urban agglomerations. The primary objective of this research is to model the evolution of ECEE, thereby exploring the sustainable development pathways for urban agglomerations in China. The research findings indicate that: (1) The results from the three-stage DEA demonstrate that, after removing the influences of external environmental factors and random errors, the comprehensive technical efficiency (TE) of energy carbon emissions for the 19 urban agglomerations in China experienced a wave-like increase, rising from 0.410 to 0.506 between 2006 and 2020. (2) The calculation results of the constructed JI model indicate that the JT values of ECEE for national-level, regional-level, and local-level urban agglomerations are 1006.92, 226.60, and 160.14, respectively. The national-level urban agglomerations have significantly higher JT values and JI than the other two levels of urban agglomerations. (3) The results of the Matlab simulation verification show that 16 urban agglomerations fit well with the wave-like ascending evolutionary pattern. However, four urban agglomerations exhibit an opposite fitting effect due to the influence of their pillar industries or the small number of cities within these accumulations, making them unrepresentative. Consequently, the evolutionary curve of ECEE in Chinese urban agglomerations generally exhibits a wave-like upward trend over time.

Integrating a high-energy activation method for the sustainable treatment of iron smelting slag, phosphogypsum, and arsenic-contaminated water

Metallurgy is one of the pillar industries in China, but metallurgy inevitably produces a large amount of industrial solid waste and heavy metal pollution. Phosphogypsum (PG) is a by-product of the production of wet-process phosphoric acid, and after the preliminary fieldwork, there is a very small amount of arsenic [As(V)] in some of the phosphorus ores, and there is a risk of heavy metal pollution. In the present study, the preparation of arsenic adsorbent (PG/IS) by doping iron smelting slag (IS) with PG as a base material was proposed and the preparation conditions were optimized by Response Surface Methodology. PG/IS was systematically characterized and its adsorption properties were investigated with respect to a variety of factors. PG/IS exhibits spontaneous endothermic chemical adsorption characteristics for As(V)，its adsorption process is more consistent with the pseudo-second-order kinetic model. Coordination complexation and chemical precipitation are the primary mechanisms by which PG/IS removes As(V). This study provides a new approach for phosphorus chemical enterprises to achieve green development and reduce industrial solid waste and As(V) emissions.

Problems And Solutions of Real Estate Industry in China

Since real estate industry is one of the national pillar industries in China, therefore, it has great contributions to China’s economy and society. for example, promoting the Chinese economic growth in the long-run, and it provide financial support to government and benefits for cities development. Secondly, real estate also helping the development of relevant business, creating large amount of job opportunities to society, for residents, they can enjoy higher living standard. However, at same time of rapid development of real estate industry and economic boost, they exist series of problems that harmful to society like real estate bubble, unfinished buildings and cooperates financing difficulties. aiming at these problems, this paper suggest that government can through promulgate some new policies, laws, and establish the compete financing channel mechanism to solve these kinds of problems. The target of this study is to help real estate industry in China keep healthy development.

Do corporate managers glean information from their stock prices? New evidence from China's strategic emerging industries

Strategic emerging industries (SEIs) have become the pillar industries in China. However, prior studies argue that the Chinese stock market fails to adequately support the development of SEIs by primarily considering its financing function while ignoring its market feedback role. Based on data from 2007 to 2020, our study fills this gap by examining whether managers of Chinese SEI firms glean information from stock prices to guide their investment decisions. We find a significantly positive relationship between stock price informativeness (proxied by the volume-synchronized probability of informed trading) and investment-to-price sensitivity in the SEI firms only, indicating that managers of the SEI firms exhibit prominent learning behaviors. We further reveal that high growth prospects and high sensitivity of corporate fundamentals to macroeconomic factors contribute to the learning behaviors in China's SEIs. Our study sheds light on the role of the Chinese stock market in supporting the SEIs' evolution.

The Integration of Artificial Intelligence in Architectural Visualization Enhances Augmented Realism and Interactivity

The construction industry is an important part of the national economic market of various countries; since 2013, the construction industry's added value in the gross domestic product has been more than 6%, reaching 6.89% in 2022, and is a pillar industry of the national economy. Intelligent construction is the realistic demand to promote the high-quality development of China's construction industry. It is the key focus of transforming and upgrading the traditional construction industry to information, digital, and intelligent. As a new production factor, construction robots have become the key to promoting intelligent construction. Under the guidance of various national and industry policies, thanks to China's huge construction market volume and rich application scenarios, many innovative and entrepreneurial entities have entered the field of construction robots. Architectural visualization is a crucial aspect of architectural design and communication. With the development of science and technology, artificial intelligence (AI) technology is increasingly becoming an essential tool for architectural visualization and communication. The emergence of AI technology has provided architects with more flexible and creative ways to present design ideas. All along, designers who love architecture have been passionate about exploring better solutions for architecture, but there is never an optimal solution for architectural design; AI is the fire of the future era; it brings us more opportunities but also forces us to face new challenges from the future.

Prediction of new housing prices in Changsha urban area based on multiple machine learning algorithms: A comparative analysis

<p>As China’s pillar industry, the property market has suffered a considerable impact in recent years, with a decline in turnover and many developers at risk of bankruptcy. As one of the most concerned factors for stakeholders, housing prices need to be predicted more objectively and accurately to minimize decision-making errors by developers and consumers. Many prediction models in recent years have been unfriendly to consumers due to technical difficulties, high data demand, and varying factors affecting house prices in different regions. A uniform model across the country cannot capture local differences accurately, so this study compares and analyses the fitting effects of multiple machine learning models using February 2024 new building data in Changsha as an example, aiming to provide consumers with a simple and practical reference for prediction methods. The modeling exploration applies several regression techniques based on machine learning algorithms, such as Stepwise regression, Robust regression, Lasso regression, Ridge regression, Ordinary Least Squares (OLS) regression, Extreme Gradient Boosted regression (XGBoost), and Random Forest (RF) regression. These algorithms are used to construct forecasting models, and the best-performing model is selected by conducting a comparative analysis of the forecasting errors obtained between these models. The research found that machine learning is a practical approach to property price prediction, with least squares regression and Lasso regression providing relatively more convincing results.</p>

The impact of two-way FDI on the upgrading of China’s industrial structure: Based on the research in Chongqing

The improvement in the economic environment and the implementation of the “bring in and go global” strategy have had an impact on China's economic development and the optimization of its economic structure. The decline of Chongqing's traditional pillar industries has made the promotion of economic structure upgrading a key to economic development. The purpose of this paper is to study the role of two-way foreign direct investment (FDI) in industrial structure upgrading. This paper is designed to study the effect of outward foreign direct investment (OFDI) and inward foreign direct investment (IFDI) on the industrial structure upgrading from both theoretical and empirical perspectives. This study selects data from Chongqing from 1987 to 2022 and uses Stata 17.0 software for empirical analysis, based on Chenery’s “standard structure” industrial change model. The research findings show that OFDI and IFDI have a significant positive impact on the intensification and servicification of Chongqing's industrial structure and are significant at the 0.01 level. OFDI and IFDI have a significant positive impact on the rationalization of Chongqing's industrial structure and are significant at the 0.05 level. This means that two-way FDI has a positive effect on the optimization of industrial structure. The practical implication of this study is that it provides a realistic basis for Chongqing to fully leverage the advantages of international direct investment and promote the optimization and upgrading of the industrial structure, which also has enlightening significance for China’s economic structure reform.

WBi-YOLOSF: improved feature pyramid network for aquatic real-time target detection under the artificial rabbits optimization

As the pillar industry of coastal areas, aquaculture needs artificial intelligence technology to promote economic development. To realize the automation of the aquaculture industry, this paper proposes a new underwater object detection network: WBi-YOLOSF. It realizes the automatic classification and detection of aquatic products, improves the production efficiency of the aquaculture industry, and promotes its economic development. This paper creates an image dataset containing 15 aquatic products to lay the data foundation for model training. In the data preprocessing part, an underwater image enhancement algorithm is proposed to improve the quality of the data set effectively. Aiming at the problem of high false detection rate and missed detection rate of underwater dense small targets, a new data enhancement method was proposed to improve the training set’s data quality comprehensively. Inspired by the weighted bidirectional feature pyramid network, this paper proposes a new feature extraction network: AU-BiFPN, which solves the gradient problem caused by the network hierarchy’s deepening on enhancing the network’s multi-scale feature fusion. The AU-BiFPN network structure is embedded into the YOLO series network framework, significantly improving the basic network’s feature extraction and feature fusion ability and dramatically improving the prediction accuracy without affecting the network inference speed. Here, the swarm intelligence algorithm is introduced to optimize the model hyperparameters, accelerating the convergence speed of model training and significantly reducing the computational cost. At the same time, the model’s accuracy is improved by a cliff. In addition, the Funnel Activation is introduced in the network’s backbone, and the simple, parameter-free attention module is integrated, effectively improving the accuracy and speed of the model prediction. Ablation and comparison experiments show the effectiveness and superiority of the proposed model. Verified by the mean average precision and frame rate evaluation indicators, the experimental results of the WBi-YOLOSF target detection network can reach 0.982 and 203 frames per second, which are 1.4% and five frames per second higher than the network with the second score. In summary, this method can quickly and accurately identify aquatic products, realize real-time target detection of aquatic products, and lay the foundation for developing an aquaculture automation system.