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

Abstract

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.

Plant phenotyping relevance

コムギ葉の病害状態をハイパースペクトル画像で取得したデータベースを構築し、感染状態分類・症状出現予測や画像解析手法の評価基盤として提供しており、表現型取得法が中心である。

Code and data availability

The paper is a Data in Brief article describing a public hyperspectral imaging dataset of healthy and Zymoseptoria tritici-infected durum wheat leaves, deposited on Data INRAE with DOI 10.57745/WVP0FJ. This is the paper's own plant-phenotyping measurement data (VNIR/SWIR hyperspectral images, pixel coordinates, and CSV