LAUSR

A novel grass carp (Ctenopharyngodon idellus) freshness rapid evaluation method using electronic nose (EN) was proposed in this paper. Total viable counts (TVC) and gas chromatography-mass spectrometry (GC–MS) were examined. EN responses to grass carp samples stored at 4 °C were continuously measured for 8 days. Microbial growth model was developed based on modified Gompertz regression. Results of TVC and GC–MS provided freshness references for EN analysis. Principal component analysis (PCA) and stochastic resonance (SR) were utilized in EN measurement data analysis. PCA qualitatively discriminated grass carp samples in different freshness. SR output signal-to-noise ratio (SNR) eigenvalues (SNRmax) quantitatively discriminated freshness for all samples. Grass carp freshness evaluation model was developed by non-linear regression between SNRmax values and storage time. Validation experiments results demonstrated that the proposed grass carp freshness rapid evaluation method presented good forecasting accuracy. The proposed method is promising in aquatic product freshness analysis.