Article Dans Une Revue (Data Paper) Data in Brief Année : 2025

Early detection of Zymoseptoria tritici infection on wheat leaves using hyperspectral imaging data

Résumé

This article presents a hyperspectral imaging (HSI) database of healthy leaves and leaves infected with Zymoseptoria tritici fungal pathogen responsible for leaf blotch (Lb) disease. Leaves of two durum wheat genotypes were studied under controlled conditions to track the evolution of Lb disease and capture significant spectral and spatial differences until the onset of symptoms. Hyperspectral image acquisitions were purchased with two cameras in visible-near infrared (VNIR) and short-wave infrared (SWIR) spectral ranges on eighteen dates between one day before inoculation and twenty days after inoculation. For each wavelength range studied, a total of 1175 images provided information on 3326 leaves measured throughout the experiment. These data are valuable since they can be used as a basis to monitor disease's development over time, to build leaf classification models according to their infection status per genotype per day, to develop prediction models related to symptoms' appearance, or to test imaging and spectral analysis methods.

Fichier principal
Vignette du fichier
1-s2.0-S2352340925001362-main.pdf (1.73 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Licence
Recherche Data Gouv

Cite 10.57745/WVP0FJ Jeu de données LATCHOUMANE, Lorraine, 2024, "Early detection of septoria infection on wheat leaves using hyperspectral imaging data", https://doi.org/10.57745/WVP0FJ, Recherche Data Gouv, V1

Dates et versions

hal-04959064 , version 1 (11-03-2025)

Licence

Identifiants

Citer

Lorraine Latchoumane, Martin Ecarnot, Ryad Bendoula, Jean-Michel J. -M. Roger, Sílvia Mas Garcia, et al.. Early detection of Zymoseptoria tritici infection on wheat leaves using hyperspectral imaging data. Data in Brief, 2025, 59, pp.111404. ⟨10.1016/j.dib.2025.111404⟩. ⟨hal-04959064⟩
520 Consultations
253 Téléchargements

Altmetric

Partager

  • More