Detection of Pork Freshness using a Novel Wirless Electronic Nose
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Abstract:
The detecting possibility of a novel wineless electronic nose were explored for 5 different freshness pork samples, which was designed with the STM32 and CC2430. Data processing included extracting the steady-state response after smoothing, and using principal component analysis and probabilistic neural network to establish model for freshness recognition. The results showed that contribution rate of the first two principal components total reached 92.79%. Classification effect is obvious and the identification rate of probabilistic neural network model achieved 100%.
