High throughput field phenotyping (HTFP) of wheat and weed cover in field experiments using RGB images: assessment of crop-weed competition with a simple ecophysiological model - Institut Agro Dijon Accéder directement au contenu
Chapitre D'ouvrage Année : 2021

High throughput field phenotyping (HTFP) of wheat and weed cover in field experiments using RGB images: assessment of crop-weed competition with a simple ecophysiological model

Résumé

The early stages of growth for two winter wheat cultivars, Apache and Rubisko, were studied in field experiments based on destructive measurements and visible images. They cover the period from the three-leaf stage to tillering at four sampling dates. Maps of fractional vegetation cover (FVC) were established for both the crops and weeds. FVC was automatically determined from the images with an SVM-RBF classifier, using Bag of Visual Words vectors as inputs. The heterogeneity in populations and crop-weed competition were studied using descriptive and inferential statistics. The impact of weeds on crops was evaluated by comparing the results with simulations under unstressed conditions.
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hal-03275337 , version 1 (30-04-2024)

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Christelle Gée, Victor Mignon, Laurence Dujourdy, Emmanuel Denimal. High throughput field phenotyping (HTFP) of wheat and weed cover in field experiments using RGB images: assessment of crop-weed competition with a simple ecophysiological model. Precision agriculture ’21. WeedElec: a robotic research platform for individual weed detection and selective electrical weeding, John V. Stafford, pp.225 - 232, 2021, Proceedings "13th European Conference on Precision Agriculture ECPA2021". Budapest, Hongrie, 19-22 Juillet 2021, 978-90-8686-363-1. ⟨10.3920/978-90-8686-916-9_26⟩. ⟨hal-03275337⟩
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