Evaluations on classified selection of dense vectors for vegetable geographical origin identification system using trace elements

  • Authors:
  • Nobuyoshi Sato;Minoru Uehara;Koichiro Shimomura;Hirobumi Yamamoto;Kenichi Kamijo

  • Affiliations:
  • Faculty of Software and Information Science, Iwate Prefectural University, Iwate, Japan;Depertment of Information and Computer Sciences, Toyo University, Saitama, Japan;Plant Regulation Research Center, Toyo University, Gunma, Japan;Plant Regulation Research Center, Toyo University, Gunma, Japan;Plant Regulation Research Center, Toyo University, Gunma, Japan

  • Venue:
  • NBiS'07 Proceedings of the 1st international conference on Network-based information systems
  • Year:
  • 2007

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Abstract

Recently, in Japan, some farming districts established their locality as brands, and prices of agricultural products differs from their grown places. This induced some agricultural food origin forgery cases. Food traceability systems are introduced and some are now in operation to solve this problem. However, food traceability systems have vulnerabilities in their nature because they traces only artificially attached IDs. So there are possibility to forge ID and packages, and switching the vegetables in packages. So, we developed a geographical origin identification system for vegetables by using their trace element compositions. Trace element means very small quantities of elements. This system gathers trace element data of vegetables when shipping from farms, and stores them into databases located in farming districts. In case of a vegetable which has doubtful geographical origin is found in markets, their trace element compositions are measured and compared with data in databases to find its actual geographical origin. Our system judges geographical origin by whether correlation coefficient. This requires calculating correlation coefficients for identifying one and all stored data. However, this is not scalable for the number of data. In this paper, we describe a method to limit the number of data to be used to calculate correlation coefficients before calculating them, and realize scalability.