Litchi freshness rapid non-destructive evaluating method using electronic nose and non-linear dynamics stochastic resonance model.
In this paper, litchi freshness rapid non-destructive evaluating method using electronic nose (e-nose) and non-linear stochastic resonance (SR) was proposed. EN responses to litchi samples were continuously detected for 6 d Principal component analysis (PCA) and non-linear stochastic resonance (SR) methods were utilized to analyze EN detection data. PCA method could not totally discriminate litchi samples, while SR signal-to-noise ratio (SNR) eigen spectrum successfully discriminated all litchi samples. Litchi freshness predictive model developed using SNR eigen values shows high predictive accuracy with regression coefficients R(2) = 0 .99396.
a School of Information Engineering; Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province; Zhejiang A & F University ; Linan , China.
Xiaoguo
X
Ying
Wei
W
Liu
Guohua
G
Hui
D015374:Biosensing Techniques / Q000295:instrumentation* / Q000379:methods; D062609:Electronic Nose; D005504:Food Analysis / Q000295:instrumentation* / Q000379:methods; D005638:Fruit / Q000737:chemistry*; D006801:Humans; D032125:Litchi / Q000737:chemistry*; D017711:Nonlinear Dynamics; D025341:Principal Component Analysis; D059629:Signal-To-Noise Ratio; D013269:Stochastic Processes
electronic nose; litchi freshness; non-destructive evaluation; signal-to-noise ratio; stochastic resonance