This project plans to engage a third-party institution tocarry out research on the construction andapplicationof an aquaculture standardization system based on integrated aerial, terrestrial, and aquaticsensing.

REOI

Country: The People's Republic of China
Project Name: IBRD Guangdong Agricultural Product Quality Safety Improvement (Demonstration) Project

Loan No.: 9213-CN

Assignment Name: Research on AI-Based Digital Standardized Aquaculture Technology Model

Contract No.: GDCS-020

Bidding No.0733-26083765

The Government of the People's Republic of China has received a loan from the International Bank for Reconstruction and Development to improve food safety management at the national and sub-national levels and to reduce food safety risks in selected value chains. The project is being implemented by the State Administration for Market Regulation, the Ministry of Agriculture and Rural Affairs, Guangdong Province, and Shandong Province (Yantai City).

As part of this project, this study proposes to conduct research on the AI-Based Digital Standardized Aquaculture Technology Model. Building upon existing development advantages and targeting the modernization of aquaculture, the study will dynamically monitor the growth status of aquatic products and implement timely interventions. This will continuously enhance quality and safety throughout the production process, ultimately establishing a standardized aquaculture system.

Under this Contract, World Bank loan funds shall be utilized to procure the services of a consulting advisor (hereinafter referred to as the "Consultant") for the sub-project on Research on AI-Based Digital Standardized Aquaculture Technology Model. The Consultant shall research and develop a standardized aquaculture system based on big data, integrate multi-source data, and comprehensively analyze aquaculture growth processes, feeding records, and early warnings for growth status, thereby achieving the digitalization of the aquaculture process. Meanwhile, based on time-series analysis and observation, the system will monitor aquaculture quality in real-time and implement timely interventions, continuously enhancing product quality and safety throughout the production process, and ultimately establishing a standardized aquaculture system.

The implementation period of this Contract is 12 months, with an estimated total input of 36 person-months. The anticipated start date for the assignment is September 2026. Please refer to the Attachment for the detailed Terms of Reference.

Guangdong Provincial Center of Agro-product Safety and Quality (Guangdong Green Food Development Center) hereby invites qualified and interested Consultants to submit proposals for consulting services. Please refer to the Terms of Reference for the main scope of work.

Selection Criteria for the Consultants' Shortlist:

1.Capability to independently bear civil liability (Must provide a copy of the Business License or the Certificate of Legal Person for Public Institutions);

2.Sound financial accounting system (Must provide audited financial reports for the past 3 years);

3.Possess the equipment and professional technical capabilities necessary for the performance of the contract (A commitment letter providing the supporting inspection drones and essential testing equipment [as specified in ] must be submitted);

4.Good record of tax and social security payment in accordance with the law (Must provide proof of tax payment and social security contribution for the past 3 months);

5.Good business credit and sound business performance (Must provide a statement certifying no major illegal or irregular business activities in the past 3 years, and that the applicant is not listed on the "Credit China" website as a "person subject to enforcement for dishonesty," "major tax violation entity," or "entity with serious illegal acts in government procurement").

6.Track Record: Within the past five years (from January 1, 2021, up to the deadline for submitting the Letter of Intent for this project, subject to the contract signing date), the Consultant shall have signed no less than one similar performance contract. A similar performance contract refers to a technical consulting service contract involving the application of drones, remote sensing imagery, or AI intelligent recognition in agricultural research, or a service contract for research on intelligent and standardized aquatic product production technology. (Applicants must submit copies of the corresponding supporting documents [as specified in ], including key pages of the contract that clearly indicate the contract title, service content, signing date, and the signatures and seals of both contracting parties).

Please note that the Consultant must provide all the supporting materials stipulated in the above "Selection Criteria for the Consultants' Shortlist," along with detailed contact information (including contact person, address, telephone number, email address, etc.). The Consultant shall solely bear the relevant responsibilities and consequences for any issues arising from incomplete submission or failure to meet the requirements.

Interested Consultants are advised to refer to the provisions regarding Conflict of Interest policy in Sections 3.14, 3.16, and 3.17, and the provisions regarding Eligibility in Sections 3.21, 3.22, 3.23, and 3.24 of the "World Bank Procurement Regulations for IPF Borrowers" (November 2020).

Consulting firms may form an association with other firms, but it must be clearly indicated whether the arrangement is in the form of a Joint Venture or Subcontracting. If the Joint Venture form is chosen, each member of the Joint Venture shall be jointly and severally liable for the entire Contract. Please note that every member of the Joint Venture must meet the requirements of the above "Selection Criteria for the Consultants' Shortlist".

The Consultant will be selected through the Consultant Qualification Selection (CQS) method as specified in the Procurement Regulations.

This Request for Expressions of Interest (REOI) is published on the "World Bank Section of China Tendering and Bidding Public Service Platform" (https://bulletin.cebpubservice.com/bank/index.html) and "China Tendering and Bidding Network" (https://www.chinabidding.cn/).

For further information, please contact the Procurement Agent during working hours from September 2nd, 2026, to September 22nd, 2026, between 9:00-11:30 AM and 1:00-5:00 PM (Beijing Time).

The number of hard copies of the Expression of Interest (including: specified supporting materials, a brief introduction of the company's basic information and business scope, and any other materials the Consultant deems necessary) shall be: one original and four copies in Chinese. Each copy must be perfect bound. In addition, the Consultant shall submit an electronic version separately on a USB flash drive at the same time as the submission of the Expression of Interest. The USB flash drive must be labeled with the Contract Number and the full name of the Consultant. The USB flash drive shall be sealed together with the original Expression of Interest.

Deadline and Address for Submission of Expressions of Interest:

Deadline for submission: 10:00 AM (Beijing Time) on September 23rd, 2026;

Address: Bid Opening Room, 6th Floor, Guangren Building, No. 1 Guangren Road, Yuexiu District, Guangzhou, Guangdong Province.

Client: Guangdong Provincial Center of Agro-product Safety and Quality (Guangdong Green Food Development Center)
Contact Person: Ms. Wu
Address: No. 135, Xianlie East Road, Tianhe District, Guangzhou, Guangdong Province
Postal Code: 510230

Tel: +86-20-87590235
E-mail: mailto:nynct_ncpzx_zhangsh@gd.gov.cn

Procurement Agent: CITIC International Tendering Co., Ltd.
Contact Person: Ms. Guo, Mr. Zhang
Address: Room 1811, 18/F, Tower 59, No. 59 Dongsanhuan Middle Road, Chaoyang District, Beijing
Postal Code: 100022
Tel: +86-10-87945198-503/504
E-mail: mailto:guoying@ck.citic.com; mailto:zhangfan@ck.citic.com

Attachment: TOR for the Consulting Advisor's Work on Research of AI-Based Digital Standardized Aquaculture Technology Model (Contract No.: GDCS-020) under the IBRD Guangdong Agricultural Product Quality Safety Improvement (Demonstration) Project

TOR for the Consulting Advisor's Work on Research of AI-Based Digital Standardized Aquaculture Technology Model (Contract No.: GDCS-020) under the IBRD Guangdong Agricultural Product Quality Safety Improvement (Demonstration) Project

To facilitate the organization and implementation of the agricultural product quality and safety research under the IBRD Guangdong Agricultural Product Quality Safety Improvement (Demonstration) Project (hereinafter referred to as the "World Bank Loan Project"), and to ensure the successful completion of the project in accordance with its objectives and schedule, the Guangdong Center for Agricultural Product Quality and Safety (Guangdong Green Food Development Center) intends to hire a consulting advisor to conduct research on the AI-based digital standardized aquaculture technology model.

I.Background

As a vital component of China's agricultural economy, the aquaculture industry is a key sector for ensuring food security and optimizing dietary structures. With the continuous upgrading of consumer demands for aquatic product quality and increasingly stringent ecological and environmental protection policies, the traditional extensive aquaculture model can no longer meet the requirements of high-quality development. Particularly in terms of quality and safety supervision, aquaculture still faces prominent challenges, such as opaque production processes, delayed risk early warnings, and difficulties in tracing key indicators.

Due to its unique industrial characteristics, aquaculture still exhibits significant shortcomings in digital supervision practices. On the one hand, the dynamic and ever-changing aquatic environment involves multi-dimensional spatial interactions across the upper atmosphere, surface water bodies, and underwater ecosystems, making it difficult for traditional single monitoring methods to achieve full-scenario coverage. On the other hand, aquatic activities are characterized by concealment and suddenness. Traditional monitoring methods suffer from limited scope, untimely information acquisition, difficulty in identifying hidden behaviors, insufficient data accuracy, and high labor costs. These issues make the establishment of a standardized aquaculture system an urgent priority.

The core of this research lies in utilizing modern information technologies to achieve intelligent management of agricultural product quality and safety. Traditional production monitoring methods still face issues such as incomplete information collection and delayed responses to risk early warnings. To better address these challenges and further promote the digitalization of agricultural product quality and safety supervision, there is an urgent need to rely on modern information technologies—including AI, big data, IoT sensors, and cloud computing—to continuously improve the regulatory system. This is particularly crucial for process supervision and quality traceability in aquaculture, aiming to achieve full-chain safety management from production to distribution. This will not only help enhance the market competitiveness of agricultural products but also lay a solid foundation for the sustainable development of agricultural product quality and safety.

II.Objectives and Tasks

(I) Objectives

To address the current issues in aquaculture, including restricted information collection, delayed acquisition of key indicators, and the difficulty of tracing growth processes that lead to insufficient quality and safety, this project proposes to carry out the Development of an AI-Based Standardized Aquaculture System. Building upon existing development advantages and targeting the modernization of aquaculture, the project will dynamically monitor the growth status of aquatic products and implement timely interventions. This will continuously enhance product quality and safety throughout the production process, ultimately establishing a standardized aquaculture system.

(II) Specific Tasks

This research utilizes integrated space-air-ground intelligent technology, combined with remote sensing meteorological inversion, to accurately forecast key meteorological factors for the next 7 to 15 days, providing data support for large-scale cowpea planting management. By leveraging deep visual technology and crop growth prediction models, the study forecasts cowpea growth trends and establishes a pest and disease risk early-warning system. This enables precise fertilizer and pesticide application, promoting green and precision pest control. Furthermore, demonstration sites will be set up to host technical observation and training sessions, ultimately driving the safe, green, and sustainable development of cowpea production.

1.SWOT Analysis 

Summarize the current application status and existing challenges of new technologies, including satellite remote sensing, UAV remote sensing, ground sensors, and AI, in aquaculture production. Taking into account the actual conditions of the aquaculture production areas in the project pilot city, and considering multiple factors such as policy, economy, society, and technology, identify specific areas for investigation and evaluation. Examples include cost-benefit analysis, user acceptance surveys, and technical reliability testing. Meanwhile, ensure that the analysis provides a solid basis for subsequent strategy formulation.

2.Development of Intelligent Recognition Algorithms for Aquaculture Status Based on Low-Altitude Sensing Technology

Utilize drones to capture high-definition images or videos near automatic feeders. Combined with deep learning technology, accurately analyze aquatic product density, feeding behavior, health status, and pathological characteristics. The study will precisely extract the intrinsic correlations between image features and aquaculture status, effectively addressing the issues of untimely and imprecise perception in traditional monitoring methods. This will significantly enhance the timeliness and accuracy of aquaculture status monitoring, providing robust algorithmic support for the intelligent management of aquaculture.

3. Development of a Big Data-Driven Standardized Digital Aquaculture Management System

Integrate multi-source data to comprehensively analyze aquaculture growth processes, feeding records, and growth status early warnings, thereby achieving the digitalization of the aquaculture process. Meanwhile, based on time-series analysis and observation, monitor aquatic product quality in real-time and implement timely interventions to continuously provide quality and safety recommendations throughout the production process. Comprehensively map the complex relationships among the water environment, meteorological conditions, biological status, and aquaculture farming operations to establish a standardized digital aquaculture system. This will realize full-process digital and information-based management of aquaculture, thoroughly resolving industry pain points such as unsmooth information flow and untimely farming operations. Ultimately, it will ensure the quality and safety of aquatic products across the entire chain from source to terminal, driving the high-quality development of the aquaculture industry.

4.Exploration and Screening of New Technologies

Develop aquaculture status recognition algorithms that integrate remote sensing with low-altitude sensing. The remote sensing analysis will utilize drones to dynamically and automatically capture high-definition images or videos near automatic feeders. Combined with remote sensing technologies for aquaculture environment analysis, the system will accurately analyze aquatic product density, feeding behavior, health status, and pathological characteristics, thereby achieving refined aquaculture status recognition.

Screening Criteria: Focusing on core indicators such as technological maturity, cost-effectiveness, and environmental adaptability, the optimal technology portfolio will be determined through laboratory simulations and pilot validations.

5.Development of an Integrated "Space-Air-Ground-Water" Technical System

Hardware Layer: Deploy a satellite remote sensing monitoring network, UAV inspection systems, and IoT water quality sensors to achieve full-dimensional dynamic tracking and identification of aquatic product status and the environment in the production areas.

Platform Layer: Utilize an aquaculture big data cloud platform to integrate a multi-source data fusion engine, AI analysis modules (such as density recognition and disease prediction), and a visual decision-making dashboard, supporting synchronized access via both PC and mobile clients.

Application Layer: Implement an intelligent decision-making system. Based on inversion models and growth prediction algorithms, it will automatically generate agronomic recommendations such as feeding amounts and water replacement cycles, and push them to farmers via mobile apps or mini-programs.

6. Effectiveness Evaluation and Promotion & Application

Multi-dimensional Evaluation: Quantify evaluation indicators such as the water quality compliance rate and disease incidence rate. Select two typical aquaculture demonstration sites in the Pearl River Delta to conduct application demonstrations. Verify the technological effectiveness through comparative trials, thereby providing a complete technical solution for the Guangdong Aquatic Product Quality and Safety Enhancement initiative. This will strongly drive the digital transformation and high-quality development of the aquaculture industry, demonstrating robust competitiveness and development potential in the era of the digital economy.

Basic Requirements for Aquaculture Demonstration Bases: The pond aquaculture area must be no less than 200 mu. Bases must establish an agricultural product quality and safety management system in accordance with the law, produce in compliance with relevant agricultural product quality and safety standards, and maintain digitalized production records for agricultural products.

III.Qualification Requirements for the Consultant

1.Capability to independently bear civil liability (Must provide a copy of the Business License or the Certificate of Legal Person for Public Institutions);

2.Sound financial accounting system (Must provide audited financial reports for the past 3 years);

3.Possess the equipment and professional technical capabilities necessary for the performance of the contract (A commitment letter providing the supporting inspection drones and essential testing equipment [as specified in ] must be submitted);

4.Good record of tax and social security payment in accordance with the law (Must provide proof of tax payment and social security contribution for the past 3 months);

5.Good business credit and sound business performance (Must provide a statement certifying no major illegal or irregular business activities in the past 3 years, and that the applicant is not listed on the "Credit China" website as a "person subject to enforcement for dishonesty," "major tax violation entity," or "entity with serious illegal acts in government procurement").

6.Track Record: Within the past five years (from January 1, 2021, up to the deadline for submitting the Letter of Intent for this project, subject to the contract signing date), the Consultant shall have signed no less than one similar performance contract. A similar performance contract refers to a technical consulting service contract involving the application of drones, remote sensing imagery, or AI intelligent recognition in agricultural research, or a service contract for research on intelligent and standardized aquatic product production technology. (Applicants must submit copies of the corresponding supporting documents [as specified in ], including key pages of the contract that clearly indicate the contract title, service content, signing date, and the signatures and seals of both contracting parties).

V.Staffing Requirements

The Consultant shall ensure that the personnel nominated in the technical proposal are available to undertake and complete the assigned tasks. No changes to the personnel shall be made without the prior written approval of the Provincial Project Office.

V.Deliverables, Timeline, and Management

1. Deliverables:

(1)One (1) copy of the Project SWOT Analysis Report;

(2)One (1) complete set of Intelligent Recognition Algorithms for Aquaculture Status Based on Low-Altitude Sensing Technology, including related algorithm design documentation (such as the sensing technical solution, data preprocessing workflow, core algorithm architecture, and performance evaluation metrics), technical validation reports, and outcome demonstrations.

(3) One (1) complete set of Digital Aquaculture Management Protocols. Based on the summarization and refinement of research outcomes, a scientific, standardized, and practical protocol for digital aquaculture management will be formulated.

(4) Conduct application demonstrations at two typical aquaculture demonstration sites in the Pearl River Delta.

(5)One copy of the Project Effectiveness Evaluation and Economic Cost Analysis Report.

Reporting and Intellectual Property Requirements:

All research reports shall be provided in both Chinese and English, with 6 printed copies of each language, as well as electronic versions. All reports must not contain any sensitive information.

The ownership of data, reports, and related intellectual property rights generated from the fulfillment of this consulting assignment shall belong to Guangdong DARA. Other outcomes (e.g., papers, monographs, patents, software copyrights) must explicitly acknowledge support from this project.

2.Duration

The estimated implementation period for this consulting assignment is 12 months.

3.Supervision and Management

The consultant shall report to, and be subject to the supervision of, the Provincial Project Management Office (PPMO) and the Provincial Agricultural Safety Center.

VI. Support Provided by the PPMO

1.The PPMO and project implementation units at all levels will work closely with the consultant, designate dedicated liaison personnel, and provide necessary support, including relevant materials;

2.The consultant is expected to collaborate closely with other relevant stakeholders involved in this project.