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
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- 作者：M. Garbeza ; mgarbez@agrocampus-ouest.fr" class="auth_mail" title="E-mail the corresponding author ; Y. Ché ; né ; b ; É ; . Belinb ; M. Sigognec ; J.-M. Labatted ; G. Hunaulte ; R. Symoneauxf ; D. Rousseaug ; G. Galopina
- 关键词：CV ; cross-validation ; MD ; morphometrical descriptor ; OLS ; ordinary least squares regression ; PBI ; plant binarized image ; PCI ; plant convex hull image ; PCR ; principal component regression ; PFI ; plant filled image ; PLSR ; partial least squares regression ; RMSEP ; root mean square error of prediction ; SA ; sensory attribute ; VRB ; virtual rose bush
- 刊名：Computers and Electronics in Agriculture
- 出版年：2016
- 出版时间：February 2016
- 年：2016
- 卷：121
- 期：Complete
- 页码：331-346
- 全文大小：1633 K
文摘
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A method to construct morphometrical descriptors from rotating plants is proposed.
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Rotating virtual plants stimuli are appropriate for sensory profile experiments.
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Sensory attributes and morphometrical descriptors present strong relationships.
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Sensory attributes are efficiently predicted with few morphometrical descriptors.