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

设为首页

收藏本站

网站地图 | English | 公务邮箱

About the library

Background
History
Leadership
Organization

Readers' Guide

Opening Hours
Collections
Help Via Email

Publications

Electronic Information Resources

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

详细信息查看全文

作者：M. Garbez^a ; ^{mgarbez@agrocampus-ouest.fr" class="auth_mail" title="E-mail the corresponding author} ; Y. Ché ; né ; ^b ; É ; . Belin^b ; M. Sigogne^c ; J.-M. Labatte^d ; G. Hunault^e ; R. Symoneaux^f ; D. Rousseau^g ; G. Galopin^a
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

•: 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.