Relying on intuition and symptomatic indicators to manage disease in crops can result in spraying too much, too often or at sub-optimal times – but automated disease surveillance heralds a step-up in both detection and management.
Airborne fungal diseases cause crop yield and quality losses in broadacre agriculture, horticulture and viticulture. The diseases they cause remain an stubborn problem because plants show no symptoms during the early stages of infection, precisely when fungicides would otherwise be most effective. Once plants show symptoms, it is often too late for effective and economic control.
Weather conditions and/or crop growth stages are currently used by growers to decide when to apply crop protectants; although they have no way of knowing whether any infectious material is actually present on farm. This means, to stay safe, growers tend to spray more than they might need. This means higher input costs and, eventually, disease resistance.
It was this agriculture-wide issue and a few chance meetings with plant pathologist colleagues that captured BioScout’s CEO Lewis Collins’ attention during his engineering doctoral studies at the University of Sydney. The issue required a solution that brought together different scientific disciplines including plant pathology, agronomy and engineering. This was the perfect fit for Lewis’ background in mechatronic engineering and biological science and his ideas for a sensor that could detect early-stage infection.
“One of the largest challenges has been taking my PhD research project to a fully commercialised product that works every day under Australian farm conditions,” Mr Collins says.
BioScout’s sensor technology actually monitors the air for disease-causing spores in near real-time. This provides growers and viticulturists with early intelligence on the presence of airborne spores, allowing a more effective use of fungicides based on actual threat.
Mr Collins says this has resulted in yield increases with fewer fungicide applications.
BioScout’s systems also help growers evaluate the effectiveness of any control measures taken, helping them to finesse their disease management strategy.
About the technology
BioScout sensors capture airborne particles such as fungal spores, pollen and dust, and monitor the air in near real-time. These particles are analysed using high-resolution imaging and artificial intelligence algorithms that have been developed to quantify particulates of interest.
The sensors also function as weather stations, providing weather data such as temperature, wind speed, wind direction, rainfall, humidity, pressure and air quality.
“This means users can access airborne particulates of interest and local weather and environmental data through a single (on screen) dashboard,” Mr Collins says.
“Although challenging, we have been able to engineer the sensors to work autonomously in remote agricultural environments, including with low connectivity.”
The software behind the sensors has also been made user-friendly.
Beyond addressing fungal disease detection, BioScout’s technology also has the ability to detect pollen and determine concentration levels. This has the potential to improve insights into crop pollination and provide a warning system for asthma sufferers. As the BioScout technology can be calibrated to detect particular particles it also has potential to detect chemicals, which the team is in the early stages of investigating.
Investment and collaboration
Mr Collins says the GrainInnovate seed investment in early 2022 allowed BioScout to evolve from a five-person team servicing trial partners to 17 person team servicing the world’s largest airborne disease sensor network.
“However, it has also taken a lot of time to create the data set required to develop machine learning algorithms,” he syas. “To do this millions of spores had to be identified and labelled by BioScout’s team over the years.
“Then, to make the data easily digestible and engaging for the growers and customers, BioScout had to develop novel software solutions.”
Mr Collins says collaborations with companies within GRDC’s network were paramount in addressing the challenges outlined above, especially addressing data shortages and developing early case studies to fine-tune the value propositions for the technology.
Case Study: BioScout provides the missing piece in pathology puzzles
Prior to joining ADAMA as the Portfolio Manager (Insecticides and AgTech) Andrew Newall gained extensive experience as a broadacre agronomist.
ADAMA has a culture of listening to growers and developing solutions to plant production challenges from paddock intelligence and Mr Newall’s experience was a fit with this.
“It was with this value proposition in mind that we were keen to work with BioScout to see how the technology could enable us to find a missing piece in fungal disease management,” Mr Newall says.
ADAMA is developing disease prediction models for significant diseases of grain crops. These models will give greater insights into disease development, allowing for improved applications of fungicides to achieve better results.
“But there was a missing piece of field intelligence that we needed,” Mr Newall says.
For us the Holy Grail has been information on spore capture and activity to know exactly when the disease spores may be present in a crop.
“This is really important to assist in more precise fungicide application to mitigate any possible resistance build-up to fungicides and ensure longevity of our products, as new products are a challenge to develop.
“If we can overlay this fungal spore information with data on the environmental conditions that are conducive to disease development, we can significantly improve fungicide applications.”
ADAMA has been test-driving BioScout’s ability to drive more informed decisions for Septoria tritici blotch management in wheat, botrytis in faba beans, net form of net blotch in barley and sclerotinia in canola.
“Working with BioScout devices in the field we can really get to know the nuances of fungi as their spores all have different features,” Mr Newall says.
“Utilising automated devices is far more efficient than using traditional manual devices. We can detect when there are periods of high risk in real-time during the season.
“If we can understand spore activity along with disease infection risk, we can then match our fungicide applications more precisely. Improving fungicide choice and application will not only ensure we are using the right product at the right time, it will also improve the sustainability of our production systems.”