Organisms perceive odorants in the environment through the use of a large number of olfactory receptors. Various odor biosensors have been researched and developed in order to mimic this olfactory mechanism. This study examines the quantification of odorant concentrations through the use of a sensor array comprised of several types of cell-based odor sensors expressing insect olfactory receptors with nonlinear characteristics. The sensor system utilized an active sensing method in order to compare the responses of a target odorant and a prepared odorant in determining the relative concentration of the target odorant. By combining an active sensing method with a real-time reference method in which the target odorant was measured every time the prepared odorant was measured, the relative concentrations were successfully determined even when the response fluctuation was large or odorant sensor cell responses varied as measurement time increased. For proof of concept purposes, the study primarily focused on quantifying odorant concentrations composed of one or two odorant components. It was confirmed that an algorithm to find the optimal relative odorant concentration among a limited number of odorant concentrations is achievable. Though this study is still in the initial stage of the developing odor sensors and has many challenges, it can provide insight into paving the way towards a new type of odor biosensor with active sensing.

Various types of odor sensor systems have been developed for discrimination and quantification of odorants. Although the use of biological components may improve sensitivity, few studies have reported on the use of an array of biological elements for odor discrimination. In this study, odorants were discriminated using an odor biosensor system with cells expressing different types of olfactory receptors. A cell’s response to an odorant was acquired as a fluorescent image followed by an image processing technique based on circle Hough transform. Principal component analysis and linear discriminant analysis demonstrated the ability to discriminate between two odorants at different concentrations. The result suggests that the combination of a biosensor and image processing technique have potential to discriminate between different odorants even if cells are placed at random.

The extensive diversity of volatile organic compounds, along with their minor structural variations, presents significant challenges in the development of chemosensory-based biosensors. Previously, we generated sensor cells expressing insect odorant receptors (ORs) in Sf21 cells, demonstrating their potential as cell-based odorant sensor elements. However, it remains unclear whether the selectivity of cells expressing ORs in vitro for diverse compounds aligns with the receptor’s in vivo performance, aside from the response to target compounds. To address this, we assessed the ligand responses of sensor cells expressing ORs from Drosophila melanogaster using a high-throughput calcium imaging system. Our results demonstrate that in vitro receptor responses exhibit ligand selectivity comparable to in vivo conditions across different chemical categories. Broadly tuned OR-expressing sensor cells (Or13a, Or47a, and Or98a) displayed differential affinities, whereas the narrowly tuned Or56a-expressing sensor cells selectively responded to geosmin. Moreover, cell responses varied with subtle differences in chemical structure, including carbon chain length and functional group positioning. These findings provide valuable insights into insect OR–ligand interactions in vitro, demonstrating that receptor selectivity in sensor cells closely mirrors in vivo conditions. In addition to this consistency, our results highlight the subtle ligand differentiation capabilities of sensor cells enabling fluorescence-based visualization of receptor–ligand interactions.