Response time based output of metal oxide gas sensors applied to evaluation of meat freshness with neural signal analysis

The resistance response to a steep change of the composition in air is investigated for gas sensors based on metal oxide thin films after the target odour was injected from the chicken meat into the atmosphere of clean air. The change of the response is described using an exponential decrease with few time constants for the slope. The time constants are considered as an output data of the gas sensors. The output data are collected for chicken meat from an array of the sensors. Meat freshness is evaluated basing on the smell when the output data of the gas sensors are processed with a neural network. If the time constants are used for the output, the target smell is recognised even with a single sensor.