{"id":8090,"date":"2026-03-30T15:14:33","date_gmt":"2026-03-30T15:14:33","guid":{"rendered":"https:\/\/dev.iita.org\/?post_type=project&p=8090"},"modified":"2026-06-16T09:18:52","modified_gmt":"2026-06-16T09:18:52","slug":"image-safari-development-of-machine-learning-driven-image-based-techniques-for-quantifying-pest-damage-disease-severity-and-agronomic-traits-in-bananas","status":"publish","type":"project","link":"https:\/\/iita.org\/fr\/project\/image-safari-development-of-machine-learning-driven-image-based-techniques-for-quantifying-pest-damage-disease-severity-and-agronomic-traits-in-bananas\/","title":{"rendered":"Safari d'images : D\u00e9veloppement de techniques bas\u00e9es sur l'apprentissage automatique et l'imagerie pour quantifier les d\u00e9g\u00e2ts des ravageurs, la s\u00e9v\u00e9rit\u00e9 des maladies et les traits agronomiques chez les bananiers"},"content":{"rendered":"

Objectifs du projet<\/strong><\/p>\n\n\n\n

L'objectif du projet est de d\u00e9velopper des m\u00e9thodes d'apprentissage automatique bas\u00e9es sur l'image pour quantifier avec pr\u00e9cision la gravit\u00e9 des maladies (fl\u00e9trissement fusarien, n\u00e9matodes et Sigatoka) et les caract\u00e9ristiques agronomiques cl\u00e9s (caract\u00e9ristiques de la r\u00e9gime et couleur de la pulpe) chez les bananiers, afin d'am\u00e9liorer l'efficacit\u00e9 du ph\u00e9notypage et la pr\u00e9cision de la s\u00e9lection dans les programmes de s\u00e9lection.<\/p>\n\n\n\n

R\u00e9sultats attendus<\/strong><\/p>\n\n\n\n

    \n
  1. Identification des traits cl\u00e9s et des maladies prioritaires pour le ph\u00e9notypage \u00e0 l'aide de la vision par ordinateur.<\/li>\n\n\n\n
  2. D\u00e9ploiement de techniciens de terrain pour un engagement \u00e0 temps plein et une collaboration avec des scientifiques\/s\u00e9lectionneurs seniors.<\/li>\n\n\n\n
  3. Collecte et partage de donn\u00e9es d'images et de m\u00e9tadonn\u00e9es selon des normes de qualit\u00e9 et de quantit\u00e9.<\/li>\n\n\n\n
  4. Support expert fourni pour l'annotation d'images.<\/li>\n\n\n\n
  5. G\u00e9n\u00e9ration d'un rapport de 2 pages r\u00e9sumant les apprentissages essentiels sur les SOP, la collecte d'images, l'annotation et les recommandations pour les travaux futurs.<\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"

    Project Goals The goal of the project is to develop image-based machine learning methods for accurately quantifying disease severity (Fusarium […]<\/p>\n","protected":false},"featured_media":8097,"template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}}},"science-area":[4],"location":[27,47],"hub":[62],"project-status":[],"crop":[],"impact-areas":[73],"research-theme":[],"item-year":[],"class_list":["post-8090","project","type-project","status-publish","has-post-thumbnail","hentry","science-area-resilient-agri-food-systems","location-tanzania","location-uganda","hub-eastern-africa","impact-areas-poverty-reduction-livelihoods-and-jobs"],"_links":{"self":[{"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/project\/8090","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/project"}],"about":[{"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/types\/project"}],"version-history":[{"count":2,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/project\/8090\/revisions"}],"predecessor-version":[{"id":12493,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/project\/8090\/revisions\/12493"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/media\/8097"}],"wp:attachment":[{"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/media?parent=8090"}],"wp:term":[{"taxonomy":"science-area","embeddable":true,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/science-area?post=8090"},{"taxonomy":"location","embeddable":true,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/location?post=8090"},{"taxonomy":"hub","embeddable":true,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/hub?post=8090"},{"taxonomy":"project-status","embeddable":true,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/project-status?post=8090"},{"taxonomy":"crop","embeddable":true,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/crop?post=8090"},{"taxonomy":"impact-areas","embeddable":true,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/impact-areas?post=8090"},{"taxonomy":"research-theme","embeddable":true,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/research-theme?post=8090"},{"taxonomy":"item-year","embeddable":true,"href":"https:\/\/iita.org\/fr\/wp-json\/wp\/v2\/item-year?post=8090"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}