Literature DB >> 25920547

Litchi freshness rapid non-destructive evaluating method using electronic nose and non-linear dynamics stochastic resonance model.

Xiaoguo Ying1, Wei Liu, Guohua Hui.   

Abstract

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.

Entities:  

Keywords:  electronic nose; litchi freshness; non-destructive evaluation; signal-to-noise ratio; stochastic resonance

Mesh:

Year:  2015        PMID: 25920547      PMCID: PMC4601198          DOI: 10.1080/21655979.2015.1011032

Source DB:  PubMed          Journal:  Bioengineered        ISSN: 2165-5979            Impact factor:   3.269


  5 in total

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Journal:  Food Chem       Date:  2013-09-05       Impact factor: 7.514

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Journal:  Food Chem       Date:  2013-06-25       Impact factor: 7.514

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Journal:  Food Chem       Date:  2013-03-22       Impact factor: 7.514

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Journal:  J Plant Physiol       Date:  2013-03-15       Impact factor: 3.549

5.  Control of post-harvest pericarp browning of litchi (Litchi chinensis Sonn).

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  5 in total
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2.  A Micro-Damage Detection Method of Litchi Fruit Using Hyperspectral Imaging Technology.

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Journal:  Sensors (Basel)       Date:  2018-02-26       Impact factor: 3.576

3.  Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics.

Authors:  Zhiming Guo; Chuang Guo; Quansheng Chen; Qin Ouyang; Jiyong Shi; Hesham R El-Seedi; Xiaobo Zou
Journal:  Sensors (Basel)       Date:  2020-04-09       Impact factor: 3.576

  3 in total

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