Predicting sensorial attribute scores of ornamental plants assessed in 3D through rotation on video by image analysis: A study on the morphology of virtual rose bushes

Autor: G. Galopin, Yann Chéné, Etienne Belin, J.-M. Labatte, M. Sigogne, M. Garbez, R. Symoneaux, David Rousseau, Gilles Hunault
Přispěvatelé: Institut de Recherche en Horticulture et Semences (IRHS), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA)-Université d'Angers (UA), Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d'Angers (UA), Hémodynamique, Interaction Fibrose et Invasivité tumorales Hépatiques (HIFIH), Unité de Recherche GRAPPE, SFR 4207 QUASAV, Ecole supérieure d'Agricultures d'Angers (ESA), Université Sciences et Technologies - Bordeaux 1, Université d'Angers (UA)-Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Pays de la Loire Regional council
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Zdroj: Computers and Electronics in Agriculture
Computers and Electronics in Agriculture, Elsevier, 2016, 121, pp.331-346. ⟨10.1016/j.compag.2016.01.001⟩
ISSN: 0168-1699
Popis: A method to construct morphometrical descriptors from rotating plants is proposed.Rotating virtual plants stimuli are appropriate for sensory profile experiments.Sensory attributes and morphometrical descriptors present strong relationships.Sensory attributes are efficiently predicted with few morphometrical descriptors. The visual appearance of a plant is tightly linked to its 3D architecture, and can be characterized by means of sensorial experiments. Providing a method to manage image features to predict objective visual traits of real or in silico ornamental plants seen and assessed in rotation, could be a valuable tool to take into account the 3D of the plants in order to reach faster, more faithful and more reproducible hedonic-free characterizations. The present study aims to present a simple approach to manage image data from rotating plant videos in order to predict some visual characteristics as beforehand determined through a non-hedonic sensory evaluation. It is proposed to implement plant morphometrical descriptors using common descriptive statistics computed from 2D features measured along the plant rotation with the aim to integrate the plant 3D. As a preliminary study to evaluate the potential of the proposed approach, the present experiment used virtual plants. First, a sensory profile on 20 virtual rose bushes videos for which 12 plant morphology-related sensory attributes were developed is presented. In parallel, 2D features from the video frames have been extracted considering an 8?-rotation interval and their discriminant power have been checked. Results showed that each sensory attributes presented at least one strong and significant linear relationship with a specific morphometrical descriptor (Pearson's correlation coefficient ?0.8, p-values
Databáze: OpenAIRE
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