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Development of a Botrytis specific immunosensor : towards using PCR species identificationBinder, Michael January 2014 (has links)
Botrytis species affect over 300 host plants in all climate areas of the world, at both pre and post-harvest stages, leading to significant losses in agricultural produce. Therefore, the development of a rapid, sensitive and reliable method to assess the pathogen load of infected crops can help to prescribe an effective curing regime. Growers would then have the ability to predict and manage the full storage potential of their crops and thus provide an effective disease control and reduce post-harvest losses. A highly sensitive electrochemical immunosensor based on a screen-printed gold electrode (SPGE) with onboard carbon counter and silver / silver chloride (Ag/AgCl) pseudo-reference electrode was developed in this work for the detection and quantification of Botrytis species. The sensor utilised a direct sandwich enzyme-linked immunosorbent assay (ELISA) format with a monoclonal antibody against Botrytis immobilised on the gold working electrode. Two immobilisation strategies were investigated for the capture antibody, and these included adsorption and covalent immobilisation after self-assembled monolayer formation with 3-dithiodipropionic acid (DTDPA). A polyclonal antibody conjugated to the electroactive enzyme horseradish peroxidase (HRP) was then applied for signal generation. Electrochemical measurements were conducted using 3,3’, 5,5’-tetramethylbenzidine dihydrochloride / hydrogen peroxide (TMB/H2O2) as the enzyme substrate system at a potential of -200 mV. The developed biosensor was capable of detecting latent Botrytis infections 24 h post inoculation with a linear range from 150 to 0.05 μg fungal mycelium ml-1 and a limit of detection (LOD) as low as 16 ng ml-1 for covalent immobilisation and 58 ng ml-1 for adsorption, respectively. Benchmarked against the commercially available Botrytis ELISA kits, the optimised immuno-electrochemical biosensor showed strong correlation of the quantified samples (R2=0.998).
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Development of a Botrytis specific immunosensor: towards using PCR species identificationBinder, Michael 01 1900 (has links)
Botrytis species affect over 300 host plants in all climate areas of the world, at both pre
and post-harvest stages, leading to significant losses in agricultural produce. Therefore,
the development of a rapid, sensitive and reliable method to assess the pathogen load of
infected crops can help to prescribe an effective curing regime. Growers would then
have the ability to predict and manage the full storage potential of their crops and thus
provide an effective disease control and reduce post-harvest losses.
A highly sensitive electrochemical immunosensor based on a screen-printed gold
electrode (SPGE) with onboard carbon counter and silver / silver chloride (Ag/AgCl)
pseudo-reference electrode was developed in this work for the detection and
quantification of Botrytis species. The sensor utilised a direct sandwich enzyme-linked
immunosorbent assay (ELISA) format with a monoclonal antibody against Botrytis
immobilised on the gold working electrode. Two immobilisation strategies were
investigated for the capture antibody, and these included adsorption and covalent
immobilisation after self-assembled monolayer formation with 3-dithiodipropionic acid
(DTDPA). A polyclonal antibody conjugated to the electroactive enzyme horseradish
peroxidase (HRP) was then applied for signal generation. Electrochemical
measurements were conducted using 3,3’, 5,5’-tetramethylbenzidine dihydrochloride /
hydrogen peroxide (TMB/H2O2) as the enzyme substrate system at a potential
of -200 mV. The developed biosensor was capable of detecting latent Botrytis infections
24 h post inoculation with a linear range from 150 to 0.05 μg fungal mycelium ml-1 and
a limit of detection (LOD) as low as 16 ng ml-1 for covalent immobilisation and
58 ng ml-1 for adsorption, respectively. Benchmarked against the commercially
available Botrytis ELISA kits, the optimised immuno-electrochemical biosensor showed
strong correlation of the quantified samples (R2=0.998) ... [cont.].
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