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Study of golden pompano (Trachinotus ovatus) freshness forecasting method by utilising Vis/NIR spectroscopy combined with electronic nose

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posted on 2018-07-04, 08:14 authored by Xianfei Zhang, Huimin Zhou, Liyang Chang, Xiongwei Lou, Jian Li, Guohua Hui, Zhidong Zhao

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%.

Funding

This work is financially supported by Scientific Research Project of National Natural Science Foundation of China (No. U1709212), Zhejiang Province (Grant No. 2017C31010, GG18F030012, 2017C02044), National College Student Innovation Research Programme of China, and Student Innovation Research Programme of Zhejiang A&F University.

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