The project was a fusion of engineering, IT, electronics, molecular biology, aerobiology and field biology, which aimed to produce an automated air sampling device, able to use a DNA-based method to detect spores of key pathogens or genetic traits such as fungicide insensitivity, and text the result, along with met data, to a web-based information portal to alert growers and advisers. The system was designed for multiple devices to operate as a network to enhance information quality and IT systems were also designed to augment currently available infection models with the information on airborne spore presence to produce a disease risk alert in time for application of crop protection products. The devices are powered by mains electricity so each one can be placed in a secure location on a farm, close to crops, ready to detect and report the first signs of spore release long before crop infection. This was found to be preferred by consulted end-users over placing a battery-powered device in a remote field site, due to security concerns and previous data from high volume samplers suggests that airborne inoculum affecting broad-acre crops in the proximity of the farm scale can be detected easily in this way (West et al, 2017).
The mains-powered automated air sampler was designed and built by the Burkard Manufacturing Co. Ltd., comprising a high-volume air sampler, which samples air at 300L/minute and can collect spores at least as small as 4 µm (aerodynamic diameter) with excellent efficiency (>90%). Each device is programmed by the user to sample for a set period each day. The collected sample is then processed mechanically in liquid to burst all spore types, releasing DNA, and a sub-sample of the disrupted spore suspension is transferred to a reaction tube where an isothermal DNA-based assay takes place inside the sampler. Two types of DNA-based assay can be used, LAMP assays or RPA assays, which differ in the reagents used and the temperature at which the reaction takes place, around 65-72 or 37-40 ֯C, respectively. The result of the assay is measured by fluorescence and results are sent wirelessly by an internal 4G router as a text message to a server. This can be repeated, currently for up to three different target pathogens to be tested from the same sample each day. Weather data, collected continuously by an on-board met station, is also sent by text every 10 minutes. The resulting data is automatically processed, collated and graphed for display on a web-portal. Simple rules applied to the data allow an automated calculation of the spore detection result, indicating zero, low or high numbers of spores present and an estimation of occurrence of infection conditions can currently be made for yellow rust and Sclerotinia. Hence, the system can provide information in near real-time on the presence of airborne spores and the weather conditions necessary for infection. Each device requires weekly attendance by the user to replenish consumables (reagents and various tubes) and to perform simple maintenance. In future, additional new assays will be added and additional weather-based infection models will be integrated.
The project suffered a major and unforeseen technical problem concerning translating effective lab-based assays using freshly prepared wet reagents into stable, dried formats with long shelf-life and good reliability that could be used in the autoDNA-sampler. Solutions to the problem involved different drying processes, addition of stabilising chemicals and testing of different reagents. A completely dry format was successfully developed for one assay as part of a related project but unfortunately this did not work reliably for arable crop pathogen assays when validated against freshly-made wet reagents in a lab. Instead, the best working development by the end of the project was a compromise method involving some dried reagents and some separately-stored liquid reagents that have a moderate shelf life (several weeks at room temperature) and can be added successfully to additional dried reagents along with the spore sample with good sensitivity and specificity of results.
Despite the technical problem, this ambitious project has developed new LAMP assays for lab-based use to detect the following pathogens: Pyrenopeziza brassicae (King et al, 2017), and publications are in preparation for the following: Sclerotinia sclerotiorum, Zymoseptoria tritici, Rhynchosporium sp, Oculimacula yallundae & O. acuformis (joint assay), Alternaria solani, and for fungicide insensitivity in Zymoseptoria tritici (assays for reduced DMI sensitivity and separately an assay for multidrug resistance including reduced DMI and SDHI sensitivity). These new assays are themselves of great use for research purposes and also for practical use by extension workers and growers with the correct portable equipment to perform in-field diagnostic tests. In addition, some existing assays, published by other researchers, were assessed for sensitivity and specificity to UK pathogens (Phytophthora infestans, Puccinia striiformis and Fusarium graminearum). The new lab-based assays will be available for use by diagnostic providers and for research in crop protection. The automated air sampling device will continue development under other funding and is expected to be available for commercial use to improve spray timing and fungicide selection from 2019 onwards.
The novel device will lead to a new approach in precision agriculture by providing information on exactly when and where growers should protect crops against disease, hence informing smart spray recommendations. The technology will in time, with use of appropriate reagents (DNA primers), be translated to improve disease control in other AHDB sectors and could be available for fungicide resistance monitoring in addition to disease forecasting. The technology, through detection of Fusarium graminearum, will assist in control of mycotoxins and will optimise agrochemical performance as part of integrated crop management. Further research is recommended to enable assessment of the system, further validate it against results from conventional air samplers for new target pathogens and to improve interpretation of results and to optimise sampler location when used for detection of specific pathogens. An additional improvement might be to add a component of forecast weather for up to three days ahead of current time whenever the device has detected airborne spores or to add economics models based on crop growth stage and value of the expected yield to assist with spray decisions.