Adapting human medical technology to predict plant diseases
Not only do agricultural producers have to contend with unpredictable weather patterns, changing economic circumstances, and a dynamic and diverse population of pests bent on devouring their crops — they also face the perennial issue of plant diseases. The diseases are spread by a wide range of pathogens — including fungi, bacteria, nematodes and viruses — and the potential damage is alarming.
For instance, a 2000 outbreak of fire blight carved a wide swath through Michigan’s orchards, resulting in an estimated $42 million in losses and destroying between 350,000 and 450,000 apple and cherry trees. The disease broke out and spread rapidly. Growers spent much of the following years replanting and restoring their orchards. Last year an outbreak of white mold in Michigan soybeans destroyed approximately $50 million worth of crops.
Developing technology to ensure that growers have the capability to fight the next such epidemic has been the subject of ongoing research at Michigan State University (MSU) and in agriculture and natural resources programs around the country. Now, MSU researchers from human medicine, plant genetics and plant pathology have joined forces to adapt the latest technology for tracking and predicting the next major plant epidemic.
Martin Chilvers and Brad Day, MSU AgBioResearch plant pathologists, are leading the multidisciplinary team.
“We aim to provide point-of-contact plant disease diagnosis, which will facilitate rapid disease management decisions to minimize crop losses and improve grower profitability,” said Chilvers, assistant professor in the MSU Department of Plant, Soil and Microbial Sciences. “The data we collect will also aid in longer term management solutions. For the general public and globally, this will translate into increased food security.”
To diagnose plant diseases, however, the team needed an expert who could identify the genetic markers of plant disease. Day has spent his entire career combing plant genomes in an effort to understand how plants resist pathogens. His work has generated an enormous amount of tertiary data that has led to new potential uses.
“I looked at this huge amount of collateral data we had on all these different species and asked, ‘Are there any alternative uses for this?’” said Day, associate professor and associate department chair for research in the MSU Department of Plant, Soil and Microbial Sciences. “Plant pathogens cause about $60 billion in losses each year in the U.S. alone. Being able to understand where they come from and how they spread would be a major accomplishment.”
Day, whose work is primarily focused on fundamental lab research, needs help to deploy that data in the field. Evangelyn Alocilja, professor in the MSU Department of Biosystems and Agricultural Engineering, developed a biosensor for detecting pathogens in humans. After conversations with Day, however, the two researchers realized that the potential for her technology could reach beyond human medicine. By adjusting the sensor’s probes, Alocilja was able to use Day’s genomic data to reconfigure the device to target specific plant pathogens.
“The biosensor could allow early and quick screening of plants in the field, which would warn growers about impending outbreaks,” Alocilja said. “Early recognition of pathogens would give them time to implement disease control methods before the pathogens reach epidemic proportions.”
Though the biosensor can detect pathogens, putting that data into a larger geographical context requires an additional tool. That tool, dubbed PhotosynQ, is in the final stages of development by David Kramer, MSU Hannah distinguished professor in photosynthesis and bioenergetics. The PhotosynQ system is composed of two equally important components: A handheld device, called MultispeQ, that allows the user to collect data on plant and soil health.
PhotosynQ proper, a web-based database where users from all over the world can upload the information scanned with their MultispeQ devices.
“PhotosynQ can collect information that people are taking globally, and we can use that to see where incidences of plant diseaseare occurring,” Day explained. “Sitting here in East Lansing, we can look at data being uploaded by a farmer in Malawi and maybe see the first signs of an epidemic. From there, we can do fundamental research on the ground to try to stop it before it becomes a serious problem.”
The more people using PhotosynQ around the world, the better the chances of spotting an epidemic before it truly begins. Kramer plans to produce the device in large quantities and distribute it to growers at a minimal cost.
“If we can get thousands of devices to people and have them collect data on plant variety, environmental conditions, management techniques, etc., we can generate a massive data set,” Kramer said. “The more data we have, the better the picture of global plant conditions that emerges from it. That’s what we’re trying to do with PhotosynQ — lower the barriers to getting the instruments and
the data out there to people.”
By combining research from plant pathology, plant genetics and human medicine with cutting-edge technology, the MSU team is pushing the boundaries of what is possible in plant epidemiology. Predicting the next plant epidemic could have far-reaching benefits across agriculture.
“Here at MSU, we’re working on deploying next-generation nanotechnology for the detection of plant pathogens. That’s really cool,” Day said. “This is a way to not only combat disease but to make our data accessible regardless of geography. It’s a great opportunity.”
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