Pershore College. Semi-automated on-site quantification of airborne pathogen inoculum to predict the strawberry fruit rot risks. Mologic Ltd – Innovate Project 76061-503699
April 2017 – March 2020
This Innovate funded project, led Mologic Ltd, will develop semiautomatic spore trapping devices for monitoring fungal pathogens responsible for fruit rotting and provide growers with aligned technologies to use these devices. Specifically, there will be the development of a low cost, reliable device to be used on-site and giving real time results for sampling and quantifying airborne inoculum of multiple pathogens, initially with a focus on pathogens causing strawberry rots. Additionally there will be the development of predictive models to relate estimated inoculum levels and microclimate conditions to rot risks for each pathogen. The generation of practical guidance to combine the data gained to enable growers to make informed decisions on the need for, type and timeframe of control measures to implement depending on the relative prevalence of the pathogens will form an outcome of the project.
The project uses immune-chromatographic based devices for the present project; this methodology does not require pre-extraction or DNA amplification and can provide a low-cost, simpler approach in real time. In order that quantitative data relating to inoculum concentration can be derived, it is necessary to measure the intensity of immune-chromatographic response (as opposed to simply observing the presence or absence of a response). Mologic has developed a low-cost (<£300) highly portable optical reader that can analyse multiple test lines and a control line simultaneously on a single multiplex device (lateral flow device format) to produce quantitate data relating to test line intensity and therefore, via a simple calibration routine, inoculum concentration(s). The optical reader can output the data directly onto an in-built LCD screen for immediate use or it can be transferred to other devices (e.g. phone, tablet) via either a wired or wireless connection for storage (either locally or Cloud-based) and post-processing. This allows the inoculum concentration data to be integrated with other data sets.
To fully utilise the device in decision making, the project will develop predictive models to relate estimated inoculum levels and microclimate conditions to rot risks for each pathogen. Using the models, growers can then make informed decisions on the need for control and, if so, what control measures to implement.
For further information please contact Professor Roy Kennedy: firstname.lastname@example.org