Grape maturity estimation based on seed images and neural networks

Zuniga, A; Mora M.; Oyarce, M; Fredes, C.

Abstract

The grape phenolic maturity is one of the most important parameters to determine the optimal time for harvest. In this paper we propose an innovative methodology for the problem of how this task is performed today. In particular, the method consists in analyzing seed images using pattern recognition methodology, and classifying them in immature, mature and over mature states through a supervised learning neural network. The methodology presented gives objective information about maturity, which is useful for deciding the moment when the harvest should be performed. (C) 2014 Elsevier Ltd. All rights reserved.

Más información

Título según WOS: Grape maturity estimation based on seed images and neural networks
Título según SCOPUS: Grape maturity estimation based on seed images and neural networks
Título de la Revista: ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volumen: 35
Editorial: PERGAMON-ELSEVIER SCIENCE LTD
Fecha de publicación: 2014
Página de inicio: 95
Página final: 104
Idioma: English
DOI:

10.1016/j.engappai.2014.06.007

Notas: ISI, SCOPUS