Hire a third-partyinstitution to conduct research on thequality and safety of cowpeas.

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-Empowered Green Pest Control Technology for Cowpea

Contract No.: GDCS-019

Bidding No.0733-26083763

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 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.

 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-Empowered Green Pest Control Technology for Cowpea. The Consultant shall research and develop an integrated agricultural cultivation and management service model for cowpea production, covering pre-risk early warning, in-process risk control, and post-risk resolution, thereby standardizing the full-chain safe production management process "from farm to table." Based on the actual requirements for the sustainable development of cowpea production, cultivation management processes, and product standards, the Consultant shall establish a green pest control technology model that is adaptable to practical production and suitable for widespread promotion.

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 cowpea 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 21st, 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 22nd, 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-Empowered Green Pest Control Technology for Cowpea (Contract No.: GDCS-019) under the IBRD Guangdong Agricultural Product Quality Safety Improvement (Demonstration) Project

TOR for the Consulting Advisor's Work on Research of AI-Empowered Green Pest Control Technology for Cowpea (Contract No.: GDCS-019) 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 AI-empowered green pest control technology for cowpea.

I.Background

Cowpea is a major vegetable crop; however, pests such as thrips are particularly difficult to control during its cultivation. These pests can cause severe damage, including blackened heads and tails, insect holes, pod wrapping, and pod rot. Unscientific and non-standard pest control measures can easily lead to safety hazards, making cowpea pesticide residue a key focus of monitoring.

Traditional control methods for thrips heavily rely on pesticide spraying. However, the outer layer of cowpea flowers is tightly closed, while the inner layer is pouch-like, providing a natural "shelter" for thrips. No matter how the pesticides are sprayed, it is difficult to completely eliminate the pests hidden inside the flowers, failing to achieve ideal control results. Furthermore, irregular use of pesticides increases the risk of residue. Thrips are most active at temperatures of around 25°C, with peak activity typically occurring between 10:00 AM and 12:00 PM. Their population dynamics and occurrence across different cowpea growth stages are closely related to climatic conditions.

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—such as AI, drones, IoT sensors, and cloud computing—to monitor the cowpea cultivation process and enable quality traceability, thereby achieving full-chain safety management from production to distribution.

II.Objectives and Tasks

(I) Objectives

1.Guided by the goal of enhancing food safety, accurately predict key meteorological factors and other variables during the cowpea cultivation process to provide data support for large-scale cowpea planting management, thereby effectively boosting the efficiency of high-quality agricultural development.

2.Research and develop an integrated agricultural cultivation and management service model for cowpea production that covers pre-risk early warning, in-process risk control, and post-risk resolution, standardizing the full-chain safe production management process "from farm to table." Based on the actual requirements for the sustainable development of cowpea production, cultivation management processes, and product standards, establish a green pest control technology model that is adaptable to practical production and suitable for widespread promotion.

(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 in cowpea production, including satellite remote sensing, UAV remote sensing, ground sensors, and AI. Taking into account the actual conditions of domestic cowpea-producing regions, 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 a "Low-Altitude + Meteorological + Sensor" Early Warning Model for Cowpea Growth and Pest/Disease Risks

Develop an information model for cowpea growth anomalies by modeling the nonlinear relationships between various meteorological factors and crop growth status across different growth stages. Based on high-resolution agricultural meteorological data from satellite remote sensing, and combined with ground sensor data monitoring temperature, humidity, light, rainfall, and soil moisture, quantitatively analyze and predict the risks to cowpea growth caused by abnormal climatic conditions—such as drought, low temperatures, and high temperatures—over large-scale planting areas for the next 7 to 15 days.

Furthermore, as thrips are currently the primary pest threatening cowpeas, with an optimal activity temperature of approximately 25°C and specific occurrence patterns across different growth stages, a quantitative database for crop pest and disease risks will be established. This involves modeling the risk probability of pest and disease proliferation based on different cowpea phenotypes under varying meteorological conditions. Integrated with large-scale crop growth stage estimation technology, this system will analyze the occurrence probability of major pests and diseases, such as thrips, thereby enabling proactive prevention.

3. Research and Application of Intelligent Crop Monitoring and Precision Fertilizer & Pesticide Management Technologies for Cowpea Cultivation

Based on the application research of systems including precision agricultural meteorological forecasts, crop growth estimation models, and risk early-warning models, this task aims to develop and demonstrate a precision pesticide application technology system integrating pest monitoring with fertigation (water and fertilizer integration). The study will apply efficient UAV-based pest monitoring technology to achieve early detection of pests and diseases, and conduct research on adjusting water and fertilizer agronomic practices and pesticide management based on the risk early-warning models. Demonstration bases will be established to continuously track and monitor the effectiveness of pest control and eradication through technology integration. The study will evaluate the pesticide reduction effects and cowpea compliance rates, and formulate standard operating procedures (SOPs) for precision management in cowpea production.

4.Exploring Adaptable Technologies and Establishing Screening Mechanisms Centered on Core Green Pest Control Issues for Cowpea

Intelligent Pest Monitoring Technology: Develop an intelligent pest monitoring system combining trapping with AI image recognition. This system is based on a deep vision pest identification system and integrates trapping data from yellow and blue sticky boards and sex pheromone lures with meteorological models. It will dynamically predict pest population density and optimize pesticide application windows.

Multi-source Integrated Pest Management (IPM): Screen for highly efficient natural enemy resources and establish a synergistic pest control model integrating "physical + chemical + biological" methods. Dynamically trigger differentiated, balanced pest control prescriptions to build an optimal closed-loop control model for pest and disease monitoring.

Screening of Precision Fertilizer and Pesticide Control Technologies: Establish a screening mechanism based on the criteria of environmental friendliness, economic feasibility, and operational convenience. Combined with the adjustment of water and fertilizer agronomic practices and pesticide management based on risk early-warning models, this will quantitatively evaluate the pesticide reduction effects and cowpea compliance rates.

5.Development of an Integrated Technical Scheme for "Monitoring - Early Warning - Control - Feedback"

Perception Layer: Utilizing a three-dimensional monitoring network composed of satellite remote sensing data analysis, UAV inspection data collection, and IoT sensors, the system will push real-time pest control recommendations via mobile apps or mini-programs.

Decision-Making Layer: Output dynamic pest control thresholds through a multi-factor coupled early-warning model integrating "cowpea growth stages, meteorology, and pests/diseases." Build an agronomic decision-making engine driven by an expert knowledge base to automatically generate parameterized solutions, such as pesticide mixing concentrations and UAV flight altitudes.

Interactive Feedback Layer: Through a mobile mini-program, provide three core functions: risk early-warning push notifications, an AI diagnostic assistant, and blockchain-based authentication for agricultural operation records.

6. Effectiveness Evaluation and Economic Cost Analysis

(1) Multi-dimensional Effectiveness Evaluation

Ecological Benefits: Monitor the reduction rate of chemical pesticides, the survival rate of natural enemy insects, and changes in soil organic matter content.

Quality and Safety: Compare the pesticide residue compliance rate, commercial fruit rate, and traceability information completeness between demonstration fields and conventional planting areas.

Economic Benefits: Calculate the per-mu income increase (premium for high-quality fruits + savings on agricultural inputs) and the reduction in labor costs.

Technical Adaptability: Conduct regional verification in major producing areas to analyze the technological adaptability across different climatic zones.

(2) Economic Cost Analysis of New Technologies in Cowpea Production and Quality Safety. Conduct a comparative analysis between cowpea planting plots within or near the demonstration bases that utilize the new technology and conventional plots that do not.

7. Promotion and Application

Technology Validation Phase: Establish two core demonstration bases in the main cowpea-producing areas of the project pilot city. These bases will be equipped with UAVs, IoT sensors, and intelligent pest monitoring and forecasting equipment. Comparative trials of "AI-based Pest Control vs. Traditional Pest Control" will be conducted. Additionally, an AI Technology Operation Manual for Green Pest Control in Cowpea will be compiled, and training courses covering scenarios such as pest identification and equipment operation will be developed.

Basic Requirements for Cowpea Planting Demonstration Bases: The open-field planting area must be no less than 10 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.

Model Replication Phase: Utilize a mini-program to integrate functions such as meteorological early warning, a technical video library, and agricultural e-commerce. In collaboration with agricultural cooperatives, promote the "Technology Entrustment" service model, where professional teams provide full-process AI monitoring and pest control execution.

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 cowpea 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 proposed in the Technical Proposal are available to participate in and complete the assigned tasks. Should it be necessary to replace any personnel, the Consultant must submit a written request at least thirty (30) days in advance. Personnel replacement may only be made upon the prior written approval of the Provincial Project Management Office (PPMO). The qualifications of the proposed replacement personnel shall be no less than those of the originally proposed personnel.

V.Deliverables, Timeline, and Management

1. Deliverables:

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

(2)One (1) copy of the AI Technology Operation Manual for Green Pest Control in Cowpea;

(3) One (1) complete set of Early Warning Models for Cowpea Growth and Pest/Disease Risks, including related technical documentation (detailing the model's structure, algorithms, data sources, and processing methods), user manuals, testing reports, technical validation reports, and outcome demonstrations;

(4) One complete set of Digital and Ecological Cultivation Management Protocols for Cowpea. Based on the summarization and refinement of research outcomes, a scientific, standardized, and practical protocol will be formulated to promote the enhancement of cowpea quality and safety. This protocol shall cover phenotypic information collection, pest and disease control, and quality control;

(5)Application Demonstration: Select at least two cowpea planting demonstration bases in the main cowpea-producing areas of the project's pilot city for in-depth application. This aims to verify the feasibility and effectiveness of the digital cultivation and management technology for cowpea, and to provide practical recommendations for subsequent promotion and application;

(6) 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.