| Autor: |
Han, Lin, Jinghao, Jiang, Feixiang, Zheng, Guohua, Hui |
| Zdroj: |
Journal of Food Measurement & Characterization; Dec2015, Vol. 9 Issue 4, p541-549, 9p |
| Abstrakt: |
In this paper, hairtail ( Trichiurus haumela) freshness determination method using electronic nose (EN) technology is discussed. Hairtail samples under different storage time are measured by EN. At the same time, physical/chemical indexes of hairtail samples, such as total volatile based nitrogen, total aerobic counts, pH, and texture characteristics, are also examined. The relationship between EN responses and physical/chemical indexes of the samples is discussed. Results indicate that principal component analysis method discriminates hairtail samples successfully. Stochastic resonance signal-to-noise ratio (SNR) eigen values qualitatively and quantitatively discriminate hairtail samples of different freshness. Hairtail freshness predicting model is developed using SNR eigen value non-linear fitting regression. The developed model forecasts freshness of hairtail samples with an accuracy of 90.48 %. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
Full text from SpringerLink