Detection of mosaic virus disease in cassava plants by sunlight-induced fluorescence imaging: a pilot study for proximal sensing

Abstract

Cassava mosaic disease (CMD) is a prominent virus infection that causes considerable crop damage and yield reduction. Early detection of crop damage by remote sensing could be a useful tool for initiating remedial measures to reduce further crop damage. This article presents a non-destructive method for detection and classification of CMD infection, based on the red:far-red chlorophyll (chl) fluorescence image ratio. This pilot study was carried out in 14 varieties of potted cassava plants (Manihot esculenta Crantz) with a multispectral imaging system (MSIS) consisting of an electron multiplying charge coupled device (EMCCD) camera. Sunlight-induced chl fluorescence (SICF) images of plant leaves were recorded using the MSIS at the Fraunhofer lines of O 2 -B at 687 nm and O 2 -A at 759.5 nm and their off-lines at 684 and 757.5 nm. The recorded images were analysed using the Fraunhofer line discrimination (FLD) technique to extract the SICF from the solar reflectance in the recorded images. The chl fluorescence image ratio (red:far-red, F 687 :F 760 ) was computed and correlated with the laser-induced chl fluorescence (LICF) ratio (F 685 :F 735 ) determined by point monitoring, chl content variation, and the net photosynthetic rate (P n ). The scatter plot of the F 687 :F 760 image ratio showed good discrimination between different levels of CMD infection as evidenced by the high sensitivity and specificity values. It is observed that the fluorescence image ratio (F 687 : F 760 ) has a good correlation with P n (coefficient of determination (R 2 ) = 0.85), chl content (R 2 = 0.82), and the LICF ratio (F 685 :F 735 ) (R 2 = 0.80), thereby highlighting the potential of the SICF image ratio in the discrimination of CMD infection. The results clearly indicate that changes in the red:far-red fluorescence image ratio due to CMD stress can easily be detected at an early stage and the technique has great potential for monitoring the health of crops and vegetation from proximal sensing platforms.

Phenotyping Plant Responses to Biotic Stress by Chlorophyll Fluorescence Imaging

“…Their results lead to the conclusion that their model could make possible to map SiF for single-tree assessment of forest physiological condition offering the possibility of early disease detection. Raji et al (2015) analyzed the infection of cassava plants by the Cassava mosaic virus by the FLD method, finding that the fluorescence ratio F687/F760 showed a good correlation with net photosynthesis rate, the Chl content, and the laser-induced Chl-F (LICF) ratio F685/F735 and that this parameter could be a good marker of early stress detection in crops and vegetation.…”

Deriving diurnal variations in sun-induced chlorophyll-a fluorescence in winter wheat canopies and maize leaves from ground-based hyperspectral measurements

“…Furthermore, a study provided by Lee et al (2013) could provide additional insights into the effect of drought on productivity in Amazonian forests using GOSAT (Greenhouse Gases Observing Satellite) based measurements of SIF. Apart from water stress detection, promising results have been shown by using SIF information for nitrogen stress discrimination between different plants (Corp et al, "Solar Induced Fluorescence," 2006;Middleton, Corp, and Campbell 2008) or most recently for the detection of mosaic virus disease in cassava plants (Raji et al 2015).…”

Research on Polarized Multi-Spectral System and Fusion Algorithm for Remote Sensing of Vegetation Status at Night

“…Under stress, the decrease of the NDVI ratio was related to the decrease of the SPAD content, and this proportional relationship could be explained by the optical characteristics of leaves. Compared with healthy leaves, those under stress had lower chlorophyll con-tents [71], and the reduced chlorophyll content led to a decreased chlorophyll absorption and enhanced reflectance at F680 nm. Moreover, the reflectance at F760 nm was reduced.…”