金鲳鱼货架期品质快速检测方法研究  

Investigation of Golden Pomfret Shelf-life Rapid Determination Method

作　　者：郭淼[1] 惠国华[2] 

机构地区：[1]杭州电子科技大学生命信息与仪器工程学院,杭州310018 [2]浙江农林大学信息工程学院浙江省林业智能监测与信息技术研究重点实验室,杭州311300

出　　处：《中国食品学报》2015年第12期195-202,共8页Journal of Chinese Institute Of Food Science and Technology

基　　金：浙江省公益技术应用研究项目(2011C21051;2011C23031);国家自然科学基金项目(81000645);浙江省自然科学基金项目(LY13C100003)

摘　　要：为研究金鲳鱼货架期间品质的变化,分别测定鱼肉样品的质构、挥发性盐基、p H、可见-近红外光谱、电子鼻等指标。黏度、挥发性盐基氮和p H上升以及硬度下降表明货架期间金鲳鱼的鱼肉成分及肌肉组织发生了变化。对获取的电子鼻检测数据进行主成分分析及随机共振信噪比谱分析。主成分分析表明前3个主成分构成空间可有效区分不同货架期的金鲳鱼。采用信噪比谱特征值构建金鲳鱼货架期预测模型,具有较高的拟合精度,实现了金鲳鱼货架期的定量检测。Golden pomfret shelf-life determination method was investigated in this paper. Texture properties, total volatile basic nitrogen（TVB-N）, pH, visible/NIR spectrum, and electronic nose（EN） of the samples were measured. The increase of viscosity, TVB-N, pH and the decline of hardness of the samples demonstrated that the quality of golden pomfret samples changed greatly during the shelf-life storage. Visible/NIR spectrum discriminated pofret samples of different storage time successfully. While these indexes could not determine the quality changes of pomfret samples quantitatively. Principal component analysis（PCA） and stochastic resonance （SR） analysis were conducted on electronic nose measurement data. PCA results indicated that the space constructed by the first three principal components discriminated pomfret samples successfully. Golden pomfret shelf-life determination model was built using signal-to-noise ratio （SNR） eigen values. This model presented high fitting accuracy and could determine compret shelf-life quantitatively.

关 键 词：金鲳鱼 货架期 可见/红外光谱 电子鼻 信噪比 

分 类 号：TS254.7[轻工技术与工程—水产品加工及贮藏工程]