A Method to Construct Fruit Maturity Color Scales based on Support Vector Machines for Regression: Application to Olives and Grape Seeds

Color scales are a powerful tool used in agriculture for estimate maturity of fruits. Fruit maturity is an important parameter to determine the harvest time. Typically, to obtain the maturity grade, a human expert visually associates the fruit color with a color present in the scale. In this paper,...

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Autores principales: Avila, Felipe, Mora, Marco, Oyarce, Miguel, Zuñiga, Alex, Fredes, Claudio
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2017
Materias:
Ciencias Informáticas
color scales
fruit maturity
support vector regression
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/62913
http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/CAI/CAI-15.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-62913
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
color scales
fruit maturity
support vector regression
spellingShingle Ciencias Informáticas
color scales
fruit maturity
support vector regression
Avila, Felipe
Mora, Marco
Oyarce, Miguel
Zuñiga, Alex
Fredes, Claudio
A Method to Construct Fruit Maturity Color Scales based on Support Vector Machines for Regression: Application to Olives and Grape Seeds
topic_facet Ciencias Informáticas
color scales
fruit maturity
support vector regression
description Color scales are a powerful tool used in agriculture for estimate maturity of fruits. Fruit maturity is an important parameter to determine the harvest time. Typically, to obtain the maturity grade, a human expert visually associates the fruit color with a color present in the scale. In this paper, a computer-based method to create color scales is proposed. The proposed method performs a multidimensional regression based on Support Vector Regression (SVR) to generate color scales. The experimen-tation considers two color scales examples, the first one for grape seeds, the second one for olives. Grape seed data set contains 250 samples and olives data set has 200 samples. Color scales developed by SVR were validated through K-fold Cross Vali-dation method, using mean squared error as performance function. The proposed method generates scales that adequately follow the evolution of color in the fruit maturity process, provides a tool to define different phenolic pre-harvest stages, which may be of interest to the human expert.
format Objeto de conferencia
Objeto de conferencia
author Avila, Felipe
Mora, Marco
Oyarce, Miguel
Zuñiga, Alex
Fredes, Claudio
author_facet Avila, Felipe
Mora, Marco
Oyarce, Miguel
Zuñiga, Alex
Fredes, Claudio
author_sort Avila, Felipe
title A Method to Construct Fruit Maturity Color Scales based on Support Vector Machines for Regression: Application to Olives and Grape Seeds
title_short A Method to Construct Fruit Maturity Color Scales based on Support Vector Machines for Regression: Application to Olives and Grape Seeds
title_full A Method to Construct Fruit Maturity Color Scales based on Support Vector Machines for Regression: Application to Olives and Grape Seeds
title_fullStr A Method to Construct Fruit Maturity Color Scales based on Support Vector Machines for Regression: Application to Olives and Grape Seeds
title_full_unstemmed A Method to Construct Fruit Maturity Color Scales based on Support Vector Machines for Regression: Application to Olives and Grape Seeds
title_sort method to construct fruit maturity color scales based on support vector machines for regression: application to olives and grape seeds
publishDate 2017
url http://sedici.unlp.edu.ar/handle/10915/62913
http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/CAI/CAI-15.pdf
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