Scientists have used artificial intelligence to track down the scent signal that lets female lily moths call males, and the method could open the door to finding similar signals in other pests. The work comes from a team at INRAE, working with researchers at Université Côte d’Azur and Nanjing Agricultural University in China. Their results appear in BMC Biology.
The lily moth, whose caterpillars feed on lilies, is a pest found in Asia and Oceania. Its adult form produces a chemical signal that attracts mates, and that signal had never been identified before. The new AI approach changed that, and the findings are part of the EXPLOR’AE program.
What the AI did
The team used an AI-based method to hunt for the sex pheromone of the lily moth. Pheromones are chemicals that insects release to communicate with each other, and they play a huge role in crop protection strategies.
The method also turned up the olfactory receptors linked to that signal. Those receptors are the proteins in the insect’s body that detect the pheromone once it reaches them. Finding both together is the whole package.
Why this matters for crops
Pheromones are central to certain biocontrol strategies used to protect crops, especially in France. By tracking down the signal that brings male and female lily moths together, researchers can target that signal directly.
The EXPLOR’AE program is designed to explore new ways of understanding biological systems, and this result fits that goal. The BMC Biology publication means the work has been published in a major journal.
How the signal was found
The AI approach is what made the discovery possible. Rather than relying on traditional lab tests, the team fed data through machine learning algorithms to pinpoint the molecule.
The exact steps of the process are not detailed in the brief report, but the setup is clear enough to understand the scale of the achievement.
What this opens up
The method is not limited to the lily moth. The same approach can be applied to other pests, and the team’s publication suggests they are already thinking about that next step.
That is the whole point of EXPLOR’AE. The program aims to produce new knowledge about biological systems, and this pheromone work is a direct example of that mission in action.
The practical payoff
Crop protection strategies that rely on pheromones are already in use, and the French market is one of the main ones. Identifying the signal that drives mating behavior gives farmers a clearer target.
For farmers, the promise is clearer targeting of pest behavior. For science, the promise is faster identification of signals across entire families of insects.
The lily moth’s secret was outed by an algorithm, and the rest of nature is probably full of similar secrets waiting for the right code to crack them open.
| Pest | Known pheromone | New pheromone |
|---|---|---|
| Lily moth | Not previously identified | Now identified via AI |
The EXPLOR’AE program is built around exploring biological systems, and this pheromone work shows what that exploration can look like in practice. The method itself is portable across many other pests.
The French crop protection industry already relies heavily on pheromones, and this work strengthens that foundation. For farmers, the promise is clearer targeting of pest behavior. For science, the promise is faster identification of signals across entire families of insects.
The lily moth’s secret was outed by an algorithm, and the rest of nature is probably full of similar secrets waiting for the right code to crack them open.
Source material: “Crop protection: A new method for understanding insect sexual communication,” Phys.org.
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