In this article, we present the Pico electronic nose, an artificial olfactory system based on thin-film semiconductor sensors, and two applications: food-quality control (coffee analysis) and environmental monitoring (odors at a landfill site). For both applications, the electronic nose data correlated with that of panels of trained judges. For the coffee, a global index (called the hedonic index) characterizing the sensorial appeal could be predicted with the electronic nose, and for the landfill site, the intensity of odors could be quantified. In this article, we stress the importance of stable and sensitive sensors, such as metal oxide thin films produced by sputtering, and of multivariate data analysis for extracting knowledge (e.g., gaining selectivity) from the data.
