Hyperspectral image analysis for classification of multiple infections in wheat.

ABSTRACT: Plant diseases can cause heavy yield losses in arable crops resulting in major economic losses. Effective early disease recognition is paramount for modern large-scale farming. Since plants can be infected with multiple concurrent pathogens, it is important to be able to distinguish and identify each disease to ensure appropriate treatments can be applied. Hyperspectral imaging is a state-of-the art computer vision approach, which can improve plant disease classification, by capturing a wide range of wavelengths before symptoms become visible to the naked eye. Whilst a lot of work has been done applying the technique to identifying single infections, to our knowledge, it has not been used to analyse multiple concurrent infections which presents both practical and scientific challenges. In

SUBMITTER: Chossegros M 

PROVIDER: S-EPMC12595906 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature