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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/56434

    Título
    An automatic non-destructive method for the classification of the ripeness stage of red delicious apples in orchards using aerial video
    Autor
    Sabzi, Sajad
    Abbaspour Gilandeh, Yousef
    García Mateos, Ginés
    Ruiz Canales, Antonio
    Molina Martínez, José Miguel
    Arribas Sánchez, Juan IgnacioAutoridad UVA Orcid
    Año del Documento
    2019
    Editorial
    MDPI
    Descripción
    Producción Científica
    Documento Fuente
    Agronomy, 2019, vol. 9, n. 2, 84
    Abstract
    The estimation of the ripening state in orchards helps improve post-harvest processes. Picking fruits based on their stage of maturity can reduce the cost of storage and increase market outcomes. Moreover, aerial images and the estimated ripeness can be used as indicators for detecting water stress and determining the water applied during irrigation. Additionally, they can also be related to the crop coefficient (Kc) of seasonal water needs. The purpose of this research is to develop a new computer vision algorithm to detect the existing fruits in aerial images of an apple cultivar (of Red Delicious variety) and estimate their ripeness stage among four possible classes: unripe, half-ripe, ripe, and overripe. The proposed method is based on a combination of the most effective color features and a classifier based on artificial neural networks optimized with genetic algorithms. The obtained results indicate an average classification accuracy of 97.88%, over a dataset of 8390 images and 27,687 apples, and values of the area under the ROC (receiver operating characteristic) curve near or above 0.99 for all classes. We believe this is a remarkable performance that allows a proper non-intrusive estimation of ripening that will help to improve harvesting strategies.
    Materias Unesco
    5312.01 Agricultura, Silvicultura, Pesca
    3325 Tecnología de las Telecomunicaciones
    Palabras Clave
    Fruit ripeness
    Frutas - Maduración
    Aerial videos
    Video aéreo
    ISSN
    2073-4395
    Revisión por pares
    SI
    DOI
    10.3390/agronomy9020084
    Patrocinador
    Iran National Science Foundation (project 96007466)
    Ministerio de Economía, Industria y Competitividad - Fondo Europeo de Desarrollo Regional (grants TIN2015-66972-C5-3-R and AGL2015-66938-C2-1-R)
    Version del Editor
    https://www.mdpi.com/2073-4395/9/2/84
    Propietario de los Derechos
    © 2019 The Authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/56434
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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    • DEP71 - Artículos de revista [358]
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