Researchers are investigating how the domesticated, flightless silkworm moth (Bombyx mori) enhances its pheromone detection abilities by flapping its wings to create airflow. In this study, they found that moths cleverly direct pheromones toward their antennae, which could lead to advancements in creating robotic systems for odor detection. This knowledge could pave the way for innovations in drone technology and inform the design of robots to effectively identify odor sources.
Researchers from Japan are examining how the domesticated, flightless silkworm moth (Bombyx mori), recognized as a key insect model in studies of smell detection, utilizes wing flapping to influence airflow, thereby improving its ability to sense distant pheromones. Their results show how moths funnel pheromones to their olfactory sensors located in their antennae and suggest potential uses for creating sophisticated robotic systems that can identify the sources of odors. This could lead to future advancements in drone design and furnish guidelines for robots to locate odor sources.
The silkworm moth (Bombyx mori) has lost its ability to fly due to domestication. Males are able to keenly detect pheromones released by females, making them ideal subjects for studying how insects locate odor sources. Although these moths cannot fly, they are known to flap their wings (referred to as fanning) when sensing pheromones. Since pheromone molecules travel through the air, the air currents generated by their wing flapping play a significant role in the detection of these odors. However, the exact quantitative effects of this wing movement remained unclear.
To explore this, a team led by Dr. Toshiyuki Nakata from the Graduate School of Engineering at Chiba University investigated how B. mori identifies pheromones. “We know that silkworm moths detect pheromones by flapping their wings to create airflows around them, but the specific influence of this flapping on the moth’s ability to locate the odor source was unknown,” stated Nakata, explaining the purpose of the research. The team included co-first author Daigo Terutsuki from Shinshu University, Chihiro Fukui from Chiba University, Ryohei Kanzaki from the University of Tokyo, and Hao Liu from Chiba University.
Their research, published on August 2, 2024, in Volume 14 of Scientific Reports, utilized high-speed photogrammetry—a method employing high-speed cameras to capture and analyze the motion and form of objects—to computationally study the aerodynamic effects of wing actions in B. mori. The researchers closely monitored the wing movements during fanning and constructed a detailed computational model of the moth and its surrounding airflow. They then analyzed simulated data to track the movement of particles that mimic pheromone molecules around the fanning silkworm moth.
A significant outcome of the study was that B. mori preferentially samples pheromones from in front of it. The moth rotates its body while fanning to scan its surroundings for pheromone sources, and this directional sampling is particularly advantageous for identifying the source of an odor, as it allows the moth to determine the path of the odor plume upon detecting the pheromone.
Importantly, the implications of this research extend beyond the sphere of insect studies. Understanding how B. mori manages airflow can advance technologies for robotic odor source localization. A team led by Dr. Daigo Terutsuki is developing drones equipped with insect-like antennae for detecting odors, which could be used in scenarios such as locating individuals in emergencies. “The results of this study stress the importance of creating directional airflow for flying robots searching for odor sources. This requires precise adjustments to the drone’s orientation and the arrangement of its propellers and sensors to enhance detection efficacy,” explained Dr. Nakata.
Moreover, the research points out the necessity for future studies to consider environmental elements like airflow disturbances and antenna designs, as these factors also impact odor detection. “At present, robots mainly depend on visual and auditory sensors for navigation. Yet, as seen with rescue dogs, the ability to smell can be extremely effective for finding people. Although the use of smell detection in robots is still developing, this research could contribute to creating robots capable of efficiently tracking odor sources in disaster situations,” Dr. Nakata remarked hopefully.
In conclusion, this study not only enhances our understanding of insect odor detection tactics but also offers essential design insights for the future generation of aerial robots specialized in detecting odors.
