佟 懿, 谢 晶, 肖 红, 杨胜平. 基于电子鼻的带鱼货架期预测模型[J]. 农业工程学报, 2010, 26(2): 356-360.
    引用本文: 佟 懿, 谢 晶, 肖 红, 杨胜平. 基于电子鼻的带鱼货架期预测模型[J]. 农业工程学报, 2010, 26(2): 356-360.
    Prediction model of shelf life of Trichiurus haumela using an electric nose[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(2): 356-360.
    Citation: Prediction model of shelf life of Trichiurus haumela using an electric nose[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(2): 356-360.

    基于电子鼻的带鱼货架期预测模型

    Prediction model of shelf life of Trichiurus haumela using an electric nose

    • 摘要: 为探索通过气味分析判断海产品贮藏品质的方法,利用电子鼻对带鱼在不同贮藏温度与贮藏时间下的挥发性气味变化进行了分析,对所获数据进行了主成分分析与货架期分析,并与理化品质指标值挥发性盐基氮(total volatile basic nitrogen,TVBN)相联系,建立了带鱼在273~283 K下的货架期预测模型。结果表明:电子鼻18个金属传感器能很好地将贮藏于273与283 K下的带鱼随着贮藏时间变化的气味进行区分。贮藏于不同温度条件下的带鱼的TVBN值与菌落总数值均随着贮藏时间的增加而增长,且均符合一级化学动力学模型(R2>0.9)。基于电子鼻货架期分析获得的273~283 K下的气味变化结果与该温度下理化品质指标变化具有较好的对应关系,采用Arrhenius动力学模型推导公式求得带鱼在(273~283 K)温度段内TVBN的Q10(温差为10 K的货架寿命之比)值,对照该温度段下电子鼻货架期分析获得的气味变化货架期分析值,得到带鱼在该温度段内的Q10货架期预测模型,经验证,其预测误差小于20%。可根据获得的货架期预测模型对带鱼在273~283 K条件下的货架期进行预测。

       

      Abstract: An electric nose was used to evaluate the quality of the Trichiurus haumela under different storage periods and storage temperatures. The raw data of the Trichiurus haumela of the electric nose analysis were analyzed by principal compounds analysis (PCA) and shelf life (SL). The Q10 model of the Trichiurus haumela by applying both chemical (TVBN assays) and olfactometric (e-nose) methods was developed. The results showed that the sample stored at 273 K and 283 K could be well discriminated by 18 Metal Oxide Sensors. Changes in total volatile base-nitrogen (TVBN) and total viable count (TVC) of Trichiurus haumela with respect to different storage time and temperatures conformed to the first kinetic model with highly regression coefficients(R2>0.9). Shelflife function of Alphasoft11.0 and Arrhenius kinetic model were developed to predicted the shelf life of Trichiurus haumela. It showed from the reliability assessment between predicted and observed shelf-life that relative error was within 20 % calculated by the prediction model for the shelf-life of Trichiurus haumela. The remaining shelf-life of Trichiurus haumela can be predicted at the storage temperatures from 268 to 293 K by using Q10 model.

       

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