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ridgetail white prawn (exopalaemon carinicauda) k value predicting method by using electronic nose combined with non-linear data analysis model
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نویسنده
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shao chenning ,zheng haonan ,zhou zhixin ,li jian ,lou xiongwei ,hui guohua ,zhao zhidong
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منبع
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food analytical methods - 2018 - دوره : 11 - شماره : 11 - صفحه:3121 -3129
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چکیده
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In this paper, ridgetail white prawn (exopalaemon carinicauda) k value predicting model by electronic nose (en) was studied. human sensory evaluation (hse), weight loss, color, total viable counts (tvc), gc-ms, and k value were examined to provide quality references for en detection. en responses to prawns were recorded and processed by principal component analysis (pca) and stochastic resonance (sr). results indicated that prawn k value rapidly increased due to microbiology propagation. the volatile gases emitted by prawns increased with the increase of storage time based on gc-ms results. pca method could not discriminate the prawns in different qualities, and sr signal-to-noise ratio (snr) maximum (snrmax) values successfully discriminated all samples. k value predicting model was developed by linear fitting regression between k values and snrmaxvalues (r2 = 0.97). the proposed method will promote the applications of en in aquatic product quality rapid determination.
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کلیدواژه
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white prawn ,k value ,forecasting model ,electronic nose ,signal-to-noise ratio
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آدرس
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zhejiang a & f university, school of information engineering, key laboratory of forestry intelligent monitoring and information technology of zhejiang province, people’s republic of china, zhejiang a & f university, school of information engineering, key laboratory of forestry intelligent monitoring and information technology of zhejiang province, people’s republic of china, zhejiang a & f university, school of information engineering, key laboratory of forestry intelligent monitoring and information technology of zhejiang province, people’s republic of china, zhejiang a & f university, school of information engineering, key laboratory of forestry intelligent monitoring and information technology of zhejiang province, people’s republic of china, zhejiang a & f university, school of information engineering, key laboratory of forestry intelligent monitoring and information technology of zhejiang province, people’s republic of china, zhejiang a & f university, school of information engineering, key laboratory of forestry intelligent monitoring and information technology of zhejiang province, people’s republic of china, hangzhou dianzi university, hangdian smart city research center of zhejiang province, college of electronics and information, people’s republic of china
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Authors
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