Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/25884

Title: A Smart Approach to Harvest Date Forecasting
Authors: Charneca, Beatriz
Santos, Vanda
Crespo, Ana
Vicente, Henrique
Chaves, Humberto
Ribeiro, Jorge
Alves, Victor
Neves, José
Editors: Gonçalves, Paulo
Calado, João
Keywords: Analysis of the Must
Date of the Harvest
Knowledge Discovery in Databases
Data Mining
Decision Trees
Issue Date: 2019
Publisher: Eurosis – ETI Publication
Citation: Charneca, B., Santos, V., Crespo, A., Vicente, H., Chaves, H., Ribeiro, J., Alves V. & Neves, J., A Smart Approach to Harvest Date Forecasting. In P.J.S. Gonçalves & J.M.F. Calado Eds., ISC'2019, pp. 19–25, Eurosis – ETI Publication, Ghent, Belgium, 2019.
Abstract: The concept of grape ripeness depends not only on the degree of enrichment of the chemical compounds in the grape and the volume of the berries, but also on the possible production purposes. The different types of maturation in individual cases are not sufficient for the decision on the harvest date. Taken together, however, they define oenological maturation times and help to harvest them. However, there are no consistent studies that correlate the chemical parameters obtained from must analysis and oenological maturation due to the nonlinearity of these two types of variables. Therefore, this work seeks to create a self-explanatory model that allows for the prediction of ideal harvest time, based on eneological parameters related to practices in new developments in knowledge acquisition and management in relational databases.
URI: https://www.eurosis.org/cms/files/proceedings/ISC/ISC2019contents.pdf
http://hdl.handle.net/10174/25884
ISBN: 978-94-92859-0-75
Type: bookPart
Appears in Collections:QUI - Publicações - Capítulos de Livros

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