Bidirectional dynamic interaction model of seed traceability based on location analysis and its implementation

FANG Yu1 ZHU Jingbo1 XU Xue2 QIN Ruiying2 GUO Shupu1 ZHANG Liping1

(1.Institute of Agricultural Economy and Information, Anhui Academy of Agricultural Sciences, Hefei, Anhui Province, China 230031)
(2.Institute of Rice Research, Anhui Academy of Agricultural Sciences, Hefei, Anhui Province, China 230031)
【Knowledge Link】data stream/data flow

【Abstract】Agricultural product safety concerns the national economy and the people’s livelihood. From the starting point of agriculture production, the quality and safety of seeds are crucial and need to be traced. To realize the traceability of crop seeds and help the production enterprise to analyze the operation status and realize the interactive marketing, in this paper, we construct a bidirectional dynamic model of seed traceability based on location analysis. Through the seed electronic code of seeds, the model divides the traditional logistics information chain data into different sets of geographic codes, which are nested according to the geographical location of the distribution. The commodity seed from the factory to the user will experience a lot of path node, the distributor of each node dealer is required to writes its own geographic code. The geographic code contains the company information of the distributors at all levels and the geographic name information of the sale’s area. In the pre-sale stage of the seed, the geographic code set information is independent of each other. When the end user queries the seed electronic code, the flag is activated and the model starts to dynamically analyze the location of the user. By converting the user’s latitude and longitude, this model receives the detailed address, starts to match the geographical code set of information from low to high levels, and ultimately finds the distributor information or returns warning information. The query action of the user connects the geographical code sets of all levels, and the whole traceability data chain provides the traceability result to both the enterprise and the user at this time. The enterprise-side model consisted of a collection layer, a data sharing analysis layer, and an application presentation layer. When the enterprise obtains the traceability information, it can communicate with users, collecting user’s behavior data and pushing enterprise marketing information. The enterprise-side model can be combined with the supply chain data for data analysis to help improve and guide production. Through the correlation analysis of the data of sales and feedback of Huacheng 3366 wheat in ten counties, the goodness-of-fit is 0.997 8, which shows that the feedback from the code scanning can promote the sales. The model adds the bidirectional interactive data link on the traditional traceability model, so that the enterprise can interact with the user when scanning and obtain the user behavior data and push the marketing information. The model’s commissioning of the geocode location conversion rate, the number of days, the site safe operation and other technical indicators can effectively help companies master the actual operation, effectively prevent the occurrence of the transregional behavior, and optimize the enterprise distribution channels. It also provides a more reliable means of information for the regulatory department to manage the seed market.

【Keywords】 seed; crops; models; seed traceability; location analysis; geographic code set; seed electronic code;


【Funds】 Science and Technology Major Project of the Ministry of Science and Technology of Anhui Province (15czz03117) Presidential Youth Innovation Foundation of Anhui Academy of Agricultural Sciences, China (15B1424)

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(Translated by LIU T)


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This Article


CN: 11-2047/S

Vol 33, No. 24, Pages 207-214

December 2017


Article Outline



  • 0 Introduction
  • 1 Establishment of the bidirectional dynamic interaction model
  • 2 Implementation of bidirectional dynamic interaction model of seed traceability
  • 3 Analysis and comparison of bidirectional dynamic interaction model of seed traceability and traditional traceability model
  • 4 Discussion
  • 5 Conclusions
  • References