1. Key Laboratory of Agricultural Information Technology in Jiangxi Province Colleges and Universities
This key laboratory was established in July 2008 with the approval of the Jiangxi Provincial Department of Education and is affiliated with the Software School of Jiangxi Agricultural University. The laboratory adheres to national strategic needs for guidance, relies on modern information technologies such as big data, artificial intelligence, Internet of Things, and blockchain, and focuses on combining the comprehensive educational advantages of Jiangxi Agricultural University with the practical development of information technology in China. It has formed four distinct research directions with clear domains and prominent characteristics:
(1) Agricultural informatization and smart agriculture: This direction uses numerical calculation, machine learning, and computer graphics technology to establish a dynamic crop growth visualization measurement system based on physiological and ecological factors. It uses computers to achieve digital cultivation of crops, providing essential technical means for agricultural modernization.
(2) Internet of Things and detection technology: This direction develops software and hardware systems for data collection, transmission, processing, and storage in product production and testing. The system serves actual agricultural production, reducing production and testing costs and improving product quality and production efficiency.
(3) Big data and computational intelligence: This direction uses extensive data analysis and computational intelligence methods and technologies to mine, analyze, and reason high-dimensional complex data, discovering potentially valuable knowledge and providing new ideas and strategies for big data analysis and processing.
(4) Artificial intelligence and pattern recognition: This direction utilizes artificial intelligence and pattern recognition technologies such as computer vision, machine learning, deep learning, and human-computer interaction for research on visual information saliency detection, image classification, object detection, image segmentation, weather prediction, visual measurement, and pest and disease feature information recognition.
Key Laboratory of Agricultural Information Technology in Jiangxi Province Colleges and Universities.
2. Master's Degree Program in "Agricultural Engineering and Information Technology"
This master's degree program adheres to a multidisciplinary approach, closely aligning with major national strategies such as smart agriculture development and rural revitalization. It is dedicated to cultivating high-quality, versatile talents that meet the development needs of specialized agricultural industries. The program aims to nurture professionals with firm ideals and beliefs, strong moral character, a spirit of cooperation, and team awareness. These individuals will possess scientific thinking abilities, proficient professional skills, and the ability to impart technical knowledge. They will have an innovative mindset, new concepts for agricultural promotion, and a deep understanding of research hotspots in modern agriculture and rural revitalization. Graduates will be capable of independently engaging in various aspects of agricultural information and engineering work, including research, development, promotion, management, and service.
The program boasts a strong faculty and implements a dual-supervisor system with internal and external advisors. The internal supervisor team comprises 38 professors and associate professors, most of whom hold doctoral degrees. Their areas of expertise cover multiple disciplines, including computer science, big data, the Internet of Things, agricultural machinery, and electronic information. Additionally, the program has invited over 20 external experts from research institutes, agriculture-related enterprises, and grassroots agricultural extension departments to serve as industry guidance teachers. This diverse faculty structure ensures depth in theoretical teaching. It strengthens the breadth of practical applications, providing a solid foundation for cultivating high-quality, versatile talents in agricultural engineering and information technology.
Hosting an IEEE international academic conference.
3. Research Project
Recently, this discipline has been approved for over 100 research projects of various types, including 24 national-level research projects. Additionally, it has received funding for 15 horizontal projects. More than 500 academic papers, including SCI and EI index 130, have been published. Over 100 patents have been granted, including over 30 national invention patents.
4. Representative Research Achievements
(1) Research on Data Mining and Knowledge Graph Construction for Rural Entrepreneurship and Innovation Subjects and Scientific and Technological Resources
This research establishes a unified data management and access mechanism to address the challenge of effectively integrating and sharing the massive, multi-source, heterogeneous scientific and technological achievement data accumulated in the agricultural science and technology field. It proposes a knowledge representation method for multi-source heterogeneous data. It utilizes deep learning technology to construct a knowledge graph for agricultural science and technology data resources. This research achievement provides a new perspective for more effective integration and organization of agricultural scientific and technological achievement data, enabling people to access valuable scientific and technological achievement information more quickly and accurately. It has essential and extensive application value for realizing precise knowledge recommendations for both the supply and demand sides of scientific and technological achievements and intelligent decision-making in agricultural production.
(2) Research on Key Blockchain Technologies for Intellectual Property Protection of Agricultural Scientific and Technological Achievements
This research focuses on blockchain-based technology for safeguarding the transformation of agricultural scientific and technological achievements and smart contract-based mechanisms for sharing rights and interests in the transformation of scientific and technological achievements, targeting issues such as the easy loss of rights and interests of agricultural scientific and technological achievements, difficulties in rights protection, inadequate protection systems, and low grassroots participation in property rights protection. This achievement can solve problems such as trusted data interaction, distributed storage of scientific and technological resource information, and high-throughput processing in the process of transforming agricultural scientific and technological achievements, forming an efficient protection scheme for intellectual property rights of agricultural scientific and technological achievements that enables rights confirmation, authorization, rights protection, and low-cost operation.
(3) Development of Blockchain Technology and IoT Devices for Trusted Quality Control of Agricultural Inputs and Products
This research focuses on blockchain-integrated "Three Products and One Standard" agricultural product certification, intelligent import systems for production information, and quality safety control technologies for agricultural inputs and products, addressing issues of agricultural product quality safety and improving the credibility of public service platforms for information traceability. It establishes a quality control management system of "one item, one code, green card on chain" for downstream agricultural inputs and upstream agricultural products in specific demonstration areas, achieving complete process visibility, entire chain trustworthiness, and full node supervision of production and transactions. This research can solve the issue of trustworthy quality control throughout the entire chain of agricultural inputs and products, encouraging producers to improve product quality while enhancing consumer confidence in agricultural product quality.
The above research achievements have been demonstrated and applied in multiple cities in Jiangxi Province, including Jinggangshan and Fengcheng, providing trusted management technologies for local agricultural intellectual property protection and agricultural product transaction services. These technologies feature full-process information sharing, full-chain trustworthiness, and full-node joint-supervision.
AI-assisted fruit tree yield analysis.
