摘要
以南美白对虾为研究对象,结合感官评定和挥发性盐基氮测定,对5℃贮藏条件下的虾样品进行电子鼻测定,建立基于电子鼻技术的虾鲜度判别模型。结果显示:通过模型判别的正确率确定了数据归一化方法。通过主成分分析,提取了使得累计方差贡献率达到86.974%的前3个主成分,利用所得主成分进行fisher线性判别。得到的判别模型对建模样本数据和模型验证样本数据的判别正确率分别为98.3%和91.7%。说明运用主成分分析-fisher线性判别模型可以对虾鲜度进行判别,所建模型的判别正确率高,模型稳定。
Combined with the sensory evaluation and TVBN,the electronic nose was used to detect the Penaeus vanmamei under 5℃,and established the freshness of Penaeus vanmamei discriminant model based on the electronic nose technology. The results showed that the data normalization method is determined by the model discriminate accuracy. In principal components analysis,the first three principal components accounted for 86. 974% of total variation,which can effectively used by fisher linear discriminant analysis. Principal component analysis-fisher linear discriminant model can determine the freshness of Penaeus vanmamei with high discriminant accuracy and stability.
出处
《食品与发酵工业》
CAS
CSCD
北大核心
2013年第11期50-57,共8页
Food and Fermentation Industries
基金
"十二五"国家科技支撑计划项目(2012BAD38B01)
天津市自然科学基金资助项目(11JCZDJC17800)
关键词
南美白对虾
新鲜度
电子鼻
主成分分析
FISHER线性判别分析
Penaeus vanmamei
freshness
electronic nose
principal component analysis（PCA）
fisher linear discriminant analysis（FLDA）
