Early detection of plant virus infection using multispectral imaging and spatial-spectral machine learning.

ABSTRACT: Cassava brown streak disease (CBSD) is an emerging viral disease that can greatly reduce cassava productivity, while causing only mild aerial symptoms that develop late in infection. Early detection of CBSD enables better crop management and intervention. Current techniques require laboratory equipment and are labour intensive and often inaccurate. We have developed a handheld active multispectral imaging (A-MSI) device combined with machine learning for early detection of CBSD in real-time. The principal benefits of A-MSI over passive MSI and conventional camera systems are improved spectral signal-to-noise ratio and temporal repeatability. Information fusion techniques further combine spectral and spatial information to reliably identify features that distinguish healthy cassava from pla

SUBMITTER: Peng Y 

PROVIDER: S-EPMC8873445 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature