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Internet-based Farm Animal "Adoption" Management Model Research

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DOI: 10.23977/agrfem.2023.060304 | Downloads: 39 | Views: 409

Author(s)

Deqiao Zheng 1, Jiaxi Luo 1, Xuetong Liu 1, Nanyan Yu 1, Xiaolong Hu 1

Affiliation(s)

1 Shenyang Institute of Technology, Shenyang, China

Corresponding Author

Jiaxi Luo

ABSTRACT

With the advent of the new era of the Internet, it has become a trend to apply cloud computing and big data technologies to farming and livestock production. In order to solve the problem of marketing the excellent farming and livestock products in South China, and in response to the National 14th Five-Year Plan, technology is used to achieve real poverty alleviation in the sense of science and technology, and to develop a smart farming and livestock industry. Therefore, this project plans to design an Internet-based farm animal "adoption" system. Under this model, agricultural and livestock product producers sell their products on the internet and consumers can purchase the products directly and claim the products they have purchased through the internet. After claiming, consumers can use information means such as the traceability code or QR code provided by the producer to achieve traceability of information such as product quality, safety and production links. The system is developed using popular technologies such as the MINA framework, the front-end interface is designed using a combination of WXML + WXSS + JavaScript, and the system uses a B/S model with a Spring Boot back-end system for data exchange. At the same time, manufacturers can also use the recognition system to keep abreast of consumer feedback and opinions on their products, providing useful information for the management and improvement of the production process.

KEYWORDS

Agricultural and livestock products; Traceability codes; B/S model; MINA framework; Spring Boot Back office systems

CITE THIS PAPER

Deqiao Zheng, Jiaxi Luo, Xuetong Liu, Nanyan Yu, Xiaolong Hu, Internet-based Farm Animal "Adoption" Management Model Research. Agricultural & Forestry Economics and Management (2023) Vol. 6: 22-29. DOI: http://dx.doi.org/10.23977/agrfem.2023.060304.

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