Fluorescence-based immunoassay for the detection of Xanthomonas oryzae pv. oryzae in rice leaf

Abstract

The identification of rice bacterial leaf blight disease requires a simple, rapid, highly sensitive, and quantitative approach that can be applied as an early detection monitoring tool in rice health. This paper highlights the development of a turn-off fluorescence-based immunoassay for the early detection of Xanthomonas oryzae pv. oryzae (Xoo), a gram-negative bacterium that causes rice bacterial leaf blight disease. Antibodies against Xoo bacterial cells were produced as specific biorecognition molecules and the conjugation of these antibodies with graphene quantum dots and gold nanoparticles was performed and characterized, respectively. The combination of both these bio-probes as a fluorescent donor and metal quencher led to changes in the fluorescence signal. The immunoreaction between AntiXoo-GQDs, Xoo cells, and AntiXoo-AuNPs in the immunoaggregation complex led to the energy transfer in the turn-off fluorescence-based quenching system. The change in fluorescence intensity was proportional to the logarithm of Xoo cells in the range of 100-105 CFU mL−1. The limit of detection was achieved at 22 CFU mL−1 and the specificity test against other plant disease pathogens showed high specificity towards Xoo. The detection of Xoo in real plant samples was also performed in this study and demonstrated satisfactory results.

Current and emerging nanotechnology for sustainable development of agriculture: Implementation design strategy and application

“… Nanomaterials Analytes (pathogens or biomarkers) Sensing systems LOD Ref AuNPs MeSA Biomarker SERS 0.608 ppm [ 102 ] AuNPs Botrytis cinerea , Pseudomonas syrin gae, Fusarium oxysporum SERS-RPA (recombinase polymerase amplification) 2 copies of pathogen genomic DNA [ 103 ] AuNPs Potato virus Y LFIA 5.4 ng/mL [ 104 ] AuNPs, MWCNTs, and CTSNPs Ganoderma boninense Electrochemical 7.87–18.54 ppb [ 105 ] SWCNT Candidatus Liberibacter Chemoresistive biosensor 5 nM [ 106 ] GQDs and AuNPs Xanthomonas oryzae pv. oryzae Fluorescence-based immunoassay 22 CFU/mL [ 107 ] AuNPs Pseudomonas syringae Colorimetry 15 ng/μL [ 108 ] CdSe QDs Banana bunchy top virus Electrochemical ELISA N/A [ 109 ] ZnO Grapevine virus A-type proteins Luminescence 1 pg/ml to 10 ng/ml [ 110 …”

Hyperspectral Imaging Combined With Deep Transfer Learning for Rice Disease Detection

“…To ensure the growth of rice, it is crucial to develop rapid and accurate detection methods. For the past decades, numerous rice disease detection methods have been proposed based on the inner and external changes in infected rice leaves (Awaludin et al, 2020 ; Lin et al, 2020 ; Shrivastava and Pradhan, 2020 ). Hyperspectral imaging (HSI) is one of the most studied detection approaches and is sensitive enough to capture the inner chemical difference between a healthy plant and an infected one (Abdulridha et al, 2020 ; Gao et al, 2020 ).…”