Skip to Main content Skip to Navigation
Journal articles

An automatic non-invasive classification for plant phenotyping by MRI images: An application for quality control on cauliflower at primary meristem stage

Abstract : During the past few years, milder autumn and winter seasons have caused severe problems to cauliflower harvest of Brittany region in France, mainly due to curd deformation. Consequently, cauliflower breeders are working on breeding new varieties that are more robust to climate change to stabilize the quality of cauliflower production. The aim of this study was to identify at which stage of the curd formation, significant difference can be detected between healthy and stressed cauliflower. A non-invasive classification based on Magnetic Resonance Imaging (MRI) images for cauliflower phenotyping was proposed. Plants exposed to vernalization stress were sampled at different times around primary meristem stage, then both MRI imaged and apex dissected. A work flow was developped to extract features from MRI images. A classification on phenotype was learned by LDA, QDA, PLSDA and CNN binary classification between two groups: healthy and stressed cauliflower. Promising F1 score and MCC up to 95% were achieved. Curd deformation is the main cause for cauliflower’s later physiological disorders when reaching maturity. Therefore, the cauliflowers with deformation could be removed at the earliest, e.g., screening for plant breeding. At the same time, the healthy cauliflowers are not destroyed and continue their life cycle
Document type :
Journal articles
Complete list of metadata

https://hal.inrae.fr/hal-03347927
Contributor : Anne-Sophie Grenier Connect in order to contact the contributor
Submitted on : Friday, September 17, 2021 - 3:54:30 PM
Last modification on : Thursday, October 28, 2021 - 2:21:41 PM

Identifiers

Citation

Yifan Zhou, Raphaël Maître, Mélanie Hupel, Gwenn Trotoux, Damien Penguilly, et al.. An automatic non-invasive classification for plant phenotyping by MRI images: An application for quality control on cauliflower at primary meristem stage. Computers and Electronics in Agriculture, Elsevier, 2021, 187, pp.106303. ⟨10.1016/j.compag.2021.106303⟩. ⟨hal-03347927⟩

Share

Metrics

Record views

23