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Study of golden pompano (Trachinotus ovatus) freshness forecasting method by utilising Vis/NIR spectroscopy combined with electronic nose
Authors:Xianfei Zhang  Huimin Zhou  Liyang Chang  Xiongwei Lou  Jian Li
Affiliation:1. School of Electrical Information, Hangzhou Dianzi University, Hangzhou, China;2. School of Information Engineering, Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Zhejiang A &3. F University, Hangzhou, PR China;4. Renal Department, Hangzhou Hospital of Traditional Chinese Medicine, Hangzhou, PR China
Abstract:Golden pompano (Trachinotus ovatus) quality forecasting method utilising Vis/NIR spectroscopy combined with electronic nose (EN) was investigated in this article. Responses of Vis/NIR spectroscopy and EN to pompanos stored at 4°C were measured for 6 days. Physical/chemical indexes including texture, total volatile basic nitrogen, pH, total viable counts, and human sensory evaluation were synchronously examined as quality references. Chemometric methods including principal component analysis (PCA) and stochastic resonance (SR) were employed for spectroscopic and EN data analysis. Physicochemical examination demonstrated that fish quality decreased rapidly during storage. PCA qualitatively classified freshness degree of pompano samples, while SR signal-to-noise ratio (SNR) spectrum using SNR maximum quantitatively characterised quality for all samples. Golden pompano quality predictive models were developed based on spectroscopy, EN, and spectroscopy combined with EN, respectively. Results demonstrated that the model developed based on spectroscopy combined with EN presented a forecasting accuracy of 93.3%.
Keywords:Golden pompano  Quality examination  Vis/NIR spectroscopy  Electronic nose  Eigen values
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