摘要
通过自制的可视嗅觉指纹技术系统跟踪了不同储藏时间下的对虾、梭子蟹和小黄鱼的挥发性气体成分变化。通过色敏传感器阵列对不同水产品的挥发性气体进行了整体表征,并通过主成分分析(principal component analysis,PCA)呈现水产品储藏过程的气味变化趋势;然后通过线性判别分析(linear discriminant analysis,LDA)定性识别了对虾、梭子蟹和小黄鱼的新鲜度。结果表明,新鲜对虾的识别率为94. 44%,腐败对虾的识别率为93. 75%,新鲜小黄鱼的识别率为95%,腐败小黄鱼的识别率为100%,新鲜梭子蟹的识别率为100%,腐败梭子蟹的识别率为92. 31%;利用该技术结合误差反向传播人工神经网络(back propagation artificial neural network,BP-ANN)模型来定量预测水产品中的挥发性盐基氮(total volatile basic nitrogen,TVBN)含量,该模型与半微量定氮法测定对虾、梭子蟹和小黄鱼中TVBN含量的相关系数分别为0. 988 4、0. 995 4、0. 983 8,结果表明,该技术可用于水产品新鲜度的快速表征。
Colorimetric sensor array system was employed to characterize changes in volatile organic compounds (VOC) in aquatic products (prawn, small yellow croaker, shuttle crab) with different storage time. Firstly, the VOC of different aquatic products were characterized by colorimetric sensor array system, and the trends of VOC changes during storage were analyzed by principal component analysis (PCA). Linear discriminant analysis (LDA) qualitatively identified the freshness of prawn, shuttle crab, and small yellow croaker. The results showed that the recognition rates of fresh prawn, stale prawn, fresh small yellow croaker, stale small yellow croaker, fresh shuttle crab, and stale shuttle crab were 94.44%, 93.75%, 95%, 100%, 100%, and 92.31%, respectively. The technique was then combined with the back propagation artificial neural network (BP-ANN) model to quantitatively predict the amount of TVB-N in these products. It was found that the correlation coefficient values between this model and semimicro-kjeldahl determination to determine TVB-N levels in prawn, shuttle crab, and small yellow croaker were 0.9884,0.9954, and 0.9838, respectively. These results showed that colorimetric sensor array can be used to characterize the freshness of aquatic products rapidly.
作者
管彬彬
陈彬
GUAN Binbin;CHEN Bin(Nantong Food and Drug Supervision and Inspection Center, Nantong 226006,China)
出处
《食品与发酵工业》
CAS
CSCD
北大核心
2019年第9期171-175,共5页
Food and Fermentation Industries
基金
南通市科技局项目(MS12017018-1)
江苏省食品药品监督管理局项目(20170224)
关键词
水产品
可视嗅觉指纹技术
新鲜度
表征
误差反向传播人工神经网络
aquatic products
colorimetric sensor array
freshness
characterization
back propagation artificial neural network
