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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/23303
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Title: | Olive Oil Screening |
Authors: | Vicente, Henrique Martins, M. Rosário Barrucho, Inês Santos, Miguel Fernandes, Rafaela Costa, João Ribeiro, Jorge Neves, José |
Editors: | Machado, José Abelha, António Gomes, Luís M. Guerra, Hélia |
Keywords: | Artificial Intelligence Olive Oil Screening Sensorial Analysis Artificial Neural Networks Incomplete Information |
Issue Date: | 2018 |
Publisher: | Eurosis – ETI Publication |
Citation: | Vicente, H., Martins, M.R., Barrucho, I., Santos, M., Fernandes, R., Costa, J., Ribeiro, J. & Neves, J., Olive Oil Screening. In J. Machado, A. Abelha, L.M. Gomes & H. Guerra Eds., ISC'2018, pp. 41–46, Eurosis – ETI Publication, Ghent, Belgium, 2018. |
Abstract: | On the one hand, the olive oils’ quality is fixed by the region in which it is produced, the olive variety, the year of production, the degree of maturation, the extraction and the preservation processes, i.e., the olive oils` quality is assessed by two types of analyzes, the organoleptic and the biochemical ones. On the other hand, there are no studies linking analytical parameters to sensory data due to the nonlinearity that exists between these two types of variables. The present study aims to provide an answer to these problems by modeling the causal processes used at different types of olive and olive oil production. To this end, we called at an Artificial Neural Network approach to problem solving once it provides a way to handle the various stages of ripeness of the olives and olive oil production, by allowing one to deal with incomplete, unknown or even self-contradictory information or knowledge. |
URI: | https://www.eurosis.org/cms/files/proceedings/ISC/ISC2018contents.pdf http://hdl.handle.net/10174/23303 |
ISBN: | 978-94-92859-03-7 |
Type: | bookPart |
Appears in Collections: | HERCULES - Publicações - Capítulos de Livros CQE - Publicações - Capítulos de Livros QUI - Publicações - Capítulos de Livros
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