NDLI: Hierarchical Cluster Analysis: A reliable tool allowing more detailed (regional) traceability investigations

Content Provider	IEEE Xplore Digital Library
Author	Praisler, M. Ghinita, S.C. Stoica, A. Dumitriu, L.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. & Inf. Technol., “Dunarea de Jos” Univ. of Galati, Galati, Romania (Stoica, A.; Dumitriu, L.) \|\| Dept. of Chem., “Dunarea de Jos” Univ. of Galati, Galati, Romania (Praisler, M.; Ghinita, S.C.)
Abstract	We are presenting an artificial intelligence application designed to perform a reliable recognition of the geographical origin of horticultural products. The system allows more detailed traceability investigations than those required by the present general and specific standards imposed by the European Community legislation. The classification is performed by using an unsupervised pattern recognition technique, i.e. Hierarchical Cluster Analysis. The efficiency of the system is illustrated for dill (Anethum gruveoles), which is one of the most popular spice in Europe. Dill is also used for its digestive, antispasmodic, anti-inflammatory, diuretic and antioxidant properties. The knowledge base includes physico-chemical information about dill samples originating from four neighboring regions of Romania and of the Republic of Moldova. The inference engine assigns the class identity (region of origin) based on agglomerative clustering. The results show that the system is a remarkably reliable tool for in-depth traceability investigations. It clearly discriminates dill samples originating from closely located regions, which are characterized by quite similar pedo-climatic conditions. The human-machine interface is user-friendly, allowing the system to be easily used even by non-specialists. The sensitivity of selectivity of the system is discussed in comparison with those obtained by using Principal Component Analysis.
Starting Page	157
Ending Page	161
File Size	429938
Page Count	5
File Format	PDF
e-ISBN	9781479984817
DOI	10.1109/ICSTCC.2015.7321286
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-14
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hierarchical Cluster Analysis Knowledge based systems Dill (Anethum gruveoles) Europe Geographical origin Pattern recognition Reliability Standards Principal component analysis Classification tree analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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