Title :
Simultaneous regional traceability assessments based on Artificial Neural Networks
Author :
Mirela Praisler;Simona Constantin Ghinita;Atanasia Stoica Mandru;Luminita Dumitriu
Author_Institution :
Department of Chemistry, Physics and Environment, "Dunarea de Jos" University of Galati, Galati, Romania
Abstract :
We are presenting an Artificial Neural Networks (ANN) application designed to perform detailed (regional) authenticity and traceability assessments in the case of herbal spices. Its capacity to correctly assign the class (regional) identity when the properties of a new sample are compared simultaneously with models built for several regions of origin has been evaluated. A case study performed for dill (Anethum graveolens) indicates that ANN is very fit for the purpose, the system providing efficient and cost-effective simultaneous regional traceability assessments.
Keywords :
"Artificial neural networks","Training","Chemicals","Europe","Knowledge based systems","Data models","Moisture"
Conference_Titel :
E-Health and Bioengineering Conference (EHB), 2015
Print_ISBN :
978-1-4673-7544-3
DOI :
10.1109/EHB.2015.7391557