Spectroscopy Opens Potential for Ultra-Early Pest Detection in Crops
By Leslie Mertz, Ph.D.
Doctors try to catch illnesses early because they’re usually much easier to treat. The same holds true for farmers seeking the upper hand in fighting plant diseases and pest infestations, including population spikes in insects, such as the western corn rootworm (Diabrotica virgifera virgifera), that develop resistance to previously effective pest-control measures and can do considerable damage if not caught quickly. To that end, researchers at Purdue University are developing a way to spot problems in plants before any visible symptoms appear, and they’re doing it with a modern twist on the age-old technique of spectroscopy.
The Purdue researchers are using the standard spectroscopy approach: shine a light on a plant and break down the reflected light into its component wavelengths—collectively known as a spectral profile—which correspond to different molecules in the plant. Instead of looking for minerals in rocks, which is how spectroscopy has been used traditionally, the researchers are looking for certain compounds or combinations of compounds that the plant begins producing as soon as it faces an insect attack, infection with a virus, or some other stressor, such as drought, according to Purdue graduate student Raquel Peron, who has been developing applications for the technique in the research group of John Couture, Ph.D., assistant professor of entomology. Peron presented the work at the annual meeting of the Entomological Society of America’s North Central Branch in March.
“The concept is that anything affecting the physiology will affect the spectral profile of the plants, so this technique has the potential to predict multiple types of stress the plants are under,” Peron says.
Shining a Light on Plants
To do their work, the researchers meticulously gather spectral data from healthy and unhealthy plants and from the same plants before and after an insect or other stressor arrives. They then incorporate machine-learning algorithms and multivariate statistics to help figure out which collections of the compounds are related to which response. Peron is currently developing and validating the models to match spectral data to plant responses.
As the modeling work continues, Couture and his research group are taking on the challenge of mounting a spectral camera on a drone (also called an unmanned aerial vehicle, or UAV) so they can fly it over a field, quickly capture spectral profiles, and report to farmers about the state of their crops. It’s a rather tricky proposition, however, because only parts of the plants are visible from the air, and atmospheric water and other conditions can interfere with spectral collections. “The benefit of being at Purdue, however, is we have an excellent engineering program and an aviation program, so we have those partnerships available,” Couture says.
A Wealth of Applications
They have also begun corresponding spectral data to desirable traits, which would be useful in breeding programs. An example of a desirable trait might be a crop plant that produces just as much yield when it is water-stressed as it does when it is well watered. “The physiological functions that drive such yield stability are not really well-known, so if we can develop a rapid method of screening hundreds or even thousands of plant samples to find those with spectral data related to yield stability, we can start to breed for it,” Couture says.
Couture also sees spectral profiles as a means to reduce pesticide use in fighting insect and other infestations. “Once you can visually see symptoms, such as lesions, there are definitely management approaches you can take to mitigate further spread, and that includes pesticides and other chemicals. But if you can identify an issue before you see lesions, you have that much more of an opportunity to implement what are frequently less-harsh management strategies,” he says. “So, not only are we looking at enhancing the ability of growers and farm managers to manage more efficiently, but we’re also looking at decreasing chemical inputs as well.”
In addition, he says, spectral profiles could alert farmers that certain insects have developed resistance to a pest-control method. An example is the western corn rootworm, which farmers often control by planting Bt corn, or corn that has been genetically modified with a toxin produced from a bacterium that inhibits the rootworms from feeding. Rootworms, however, can develop resistance to the toxins. If growers are aware that this has happened, they can switch to other pest-management tactics. “Spectral profiling really needs to be a part of a larger integrated pest management strategy. It’s a tool that can provide detection, but it’s the management decisions that follow that are going to be important,” he says.
To help ensure that spectral profiling eventually reaches farmers, Couture is beginning to reach out to the agricultural industry to develop products for farmers to use in the field, and Peron is doing an internship this summer with an agricultural technology company to explore that avenue.
Thinking about spectral profiling overall, Couture says that its ability to detect problems early has the potential to lead to more efficient pest and disease management, promptly detect pest resistance, reduce chemical use, encourage non-chemical integrated pest management practices, and assist in breeding plants with desirable traits. He says, “It’s really food security in almost a holistic sense.”
Leslie Mertz, Ph.D., teaches summer field-biology courses, writes about science, and runs an educational insect-identification website, www.knowyourinsects.org. She resides in northern Michigan.