Olive oil density characterization through microfluidic detection using acoustic signatures (MIDAS)

Abstract

The fraudulent business derived from olive oil adulteration fuels a multi-million dollar underground economy. Current methods to identify adulteration in olive oils, although very sensitive, are costly and time consuming. We propose a miniaturized platform, which we call MIDAS – microfluidic detection using acoustic signatures – that determines the density of an unknown solution by measuring the time delay of an ultrasound wave traveling within the solution. By post-processing the data using a custom Matlab script that implements a matched filter and an ad hoc pre-filter, we show a sensitivity of 0.36% or 3.2 kg m⁻³. MIDAS could be used to determine the density of a wide variety of samples, including biological fluids for health monitoring.