Articles
Hairy root disease: digitized images based method to monitor the hairy root development on eggplants growing on soilless substrate in greenhouse
Article number
1296_41
Pages
313 – 322
Language
English
Abstract
In greenhouses, Agrobacterium rhizogenes is a bacterium responsible for hairy root disease (HRD) that mainly affects tomatoes grown on substrate.
Contaminated plants produce excessive roots in and on the slabs surface.
In the framework of the C-IPM project C-RootControl, one of the objectives of which is to reduce the symptoms created by the disease, a method for easy and accurate monitoring of the root contamination development of was needed.
The usual method was to score from 1 (low) to 5 (high) root development by visual estimation.
This method is subject to approximations depending on the operators who carry out the controls in the greenhouse and is time consuming.
The proposed method is based on photos of the slabs taken at regular time intervals.
The method was applied to 3,600 and 5,184 photos shot in 2017 and 2018, respectively.
An automation of the digitalization of photos has been implemented using a transformation of the RGB raw images into binary images.
Processing of binarized images allowed a fast estimation of the percentage of slab occupied by roots.
This method, tested on more than 8,000 images, has been validated considering: 1) the reference method based on visual estimation of slab occupied by roots (R=0.94), 2) manually analysed images to estimate the slab occupied by roots (R=0.90), and 3) the effect of operators (R=0.91). Finally, the new method allowed to distinguish the plants infested by Agrobacterium rhizogenes from non-infested plants over the 2 years of trials 2017 and 2018. These results were as good as those obtained with the visual method but a lot of time was saved and approximation due to operators was avoided.
Such a new method opens perspective to work on Agrobacterium rhizogenes at a larger scale compared to actual studies by analysing thousands of samples and reach more consistent and significant results.
Contaminated plants produce excessive roots in and on the slabs surface.
In the framework of the C-IPM project C-RootControl, one of the objectives of which is to reduce the symptoms created by the disease, a method for easy and accurate monitoring of the root contamination development of was needed.
The usual method was to score from 1 (low) to 5 (high) root development by visual estimation.
This method is subject to approximations depending on the operators who carry out the controls in the greenhouse and is time consuming.
The proposed method is based on photos of the slabs taken at regular time intervals.
The method was applied to 3,600 and 5,184 photos shot in 2017 and 2018, respectively.
An automation of the digitalization of photos has been implemented using a transformation of the RGB raw images into binary images.
Processing of binarized images allowed a fast estimation of the percentage of slab occupied by roots.
This method, tested on more than 8,000 images, has been validated considering: 1) the reference method based on visual estimation of slab occupied by roots (R=0.94), 2) manually analysed images to estimate the slab occupied by roots (R=0.90), and 3) the effect of operators (R=0.91). Finally, the new method allowed to distinguish the plants infested by Agrobacterium rhizogenes from non-infested plants over the 2 years of trials 2017 and 2018. These results were as good as those obtained with the visual method but a lot of time was saved and approximation due to operators was avoided.
Such a new method opens perspective to work on Agrobacterium rhizogenes at a larger scale compared to actual studies by analysing thousands of samples and reach more consistent and significant results.
Publication
Authors
S. Eberle, C. Gilli, Y. Fleury, C. Camps
Keywords
image analysis, eggplant, rockwool, root disease, Agrobacterium rhizogenes
Groups involved
- Division Precision Horticulture and Engineering
- Division Greenhouse and Indoor Production Horticulture
- Working Group Organic Greenhouse Horticulture
- Working Group Protected Cultivation, Nettings and Screens for Mild Climates
- Working Group Light in Horticulture
- Working Group Vegetable Grafting
- Working Group Computational Fluid Dynamics in Agriculture
- Working Group Mechanization, Digitization, Sensing and Robotics
- Working Group Modelling Plant Growth, Environmental Control, Greenhouse Environment
- Working Group Greenhouse Environment and Climate Control
- Working Group Design and Automation in Integrated Indoor Production Systems
- Commission Agroecology and Organic Farming Systems
- Division Landscape and Urban Horticulture
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