Dichotomous classification tree; Fusarium Head Blight; Near Infrared Hyperspectral Imaging; PLS-DA; Winter wheat; Analytical Chemistry; Spectroscopy
Abstract :
[en] The scope of this article is to present a laboratory-based method for the assessment of Fusarium Head Blight (FHB) on ears of winter wheat using Near Infrared Hyperspectral Imaging (NIR-HSI) in the spectral range 900–1700 nm. Inoculated and non-inoculated winter wheat ears were collected from a trial field in Belgium and analysed in the laboratory. Using a dichotomous classification tree framework, Partial Least Squares Discriminant Analysis (PLS-DA) models were developed and applied at pixel level to discriminate the different parts of the ears, namely the awns, the stem and the healthy and infected parts of the ears. This study proposes the use of spectral information at pixel level instead of averaging the spectral signature of the ear. This approach allows using the spatial information of the data in order to provide a quantitative assessment of the severity of the infection on the ear. The results presented in this work confirm that wavelengths related to water and nitrogen are important for the detection of FHB. The validation of the models indicates a good performance for the detection of FHB infection at pixel level with a sensitivity of 96 % and a specificity of 100 %. Furthermore, the validation of the method at ear level shows good performance for the detection of FHB-infected ears with a sensitivity of 99.4 % and a specificity of 91.9 %. The literature reports similar performances, but using equipment with a broader spectral range (400–2500 nm). The present study thus indicates that good discrimination performance can be achieved using a much narrower spectral range. In addition, the obtained results suggest that the method can discriminate three classes of FHB severity, which enables a semi-quantitative assessment of the FHB infection.
Disciplines :
Agriculture & agronomy
Author, co-author :
Vincke, Damien ; Université de Liège - ULiège > TERRA Research Centre
Eylenbosch, Damien; Walloon Agricultural Research Centre (CRA-W), Productions in Agriculture Department, Crop Production Unit, Gembloux, Belgium
Jacquemin, Guillaume; Walloon Agricultural Research Centre (CRA-W), Life Sciences Department, Biodiversity and Plant and Forest Improvement Unit, Gembloux, Belgium
Chandelier, Anne; Walloon Agricultural Research Centre (CRA-W), Life Sciences Department, Crops and Forest Health Unit, Gembloux, Belgium
Fernández Pierna, Juan Antonio; Walloon Agricultural Research Centre (CRA-W), Knowledge and Valorization of Agricultural Products Department, Quality and Authentication of Agricultural Products Unit, Gembloux, Belgium
Stevens, François; Walloon Agricultural Research Centre (CRA-W), Knowledge and Valorization of Agricultural Products Department, Quality and Authentication of Agricultural Products Unit, Gembloux, Belgium
Baeten, Vincent; Walloon Agricultural Research Centre (CRA-W), Knowledge and Valorization of Agricultural Products Department, Quality and Authentication of Agricultural Products Unit, Gembloux, Belgium
Mercatoris, Benoît ; Université de Liège - ULiège > TERRA Research Centre > Biosystems Dynamics and Exchanges (BIODYNE)
Vermeulen, Philippe; Walloon Agricultural Research Centre (CRA-W), Knowledge and Valorization of Agricultural Products Department, Quality and Authentication of Agricultural Products Unit, Gembloux, Belgium
Language :
English
Title :
Near infrared hyperspectral imaging method to assess Fusarium Head Blight infection on winter wheat ears
SPW - Service Public de Wallonie [BE] EU - European Union [BE] SPW DG03-DGARNE - Service Public de Wallonie. Direction Générale Opérationnelle Agriculture, Ressources naturelles et Environnement [BE] EC - European Commission [BE]
Funding text :
This work was performed by the PhenWheat project funded by the Walloon Region, Service Public de Wallonie (SPW), Direction Générale Agriculture Ressources Naturelles Environnement (DGO3 - DGARNE), Direction Recherche et Développement, project number D31-1385/S1 . This study has also contributed as preliminary work for the INVITE project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 817970 . The authors are grateful to the team from the Crop Production Unit of the CRA-W for managing the field trials. They are also grateful to Lisa Plasman, Benoît Scaut, Nicaise Kayoka Mukendi and the technical staff of all CRA-W research teams involved.This work was performed by the PhenWheat project funded by the Walloon Region, Service Public de Wallonie (SPW), Direction Générale Agriculture Ressources Naturelles Environnement (DGO3 - DGARNE), Direction Recherche et Développement, project number D31-1385/S1. This study has also contributed as preliminary work for the INVITE project funded by the European Union's Horizon 2020 research and innovation programme under grant agreement N° 817970. The authors are grateful to the team from the Crop Production Unit of the CRA-W for managing the field trials. They are also grateful to Lisa Plasman, Benoît Scaut, Nicaise Kayoka Mukendi and the technical staff of all CRA-W research teams involved.
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