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- W3126090857 abstract "The potential of two different hyperspectral imaging systems (visible near infrared spectroscopy (Vis-NIR) and NIR) was investigated to determine TVB-N contents in tilapia fillets during cold storage. With Vis-NIR and NIR data, calibration models were established between the average spectra of tilapia fillets in the hyperspectral image and their corresponding TVB-N contents and optimized with various variable selection and data fusion methods. Superior models were obtained with variable selection methods based on low-level fusion data when compared with the corresponding methods based on single data blocks. Mid-level fusion data achieved the best model based on CARS, in comparison with all others. Finally, the respective optimized models of single Vis-NIR and NIR data were employed to visualize TVB-N contents distribution in tilapia fillets. In general, the results showed the great feasibility of hyperspectral imaging in combination with data fusion analysis in the nondestructive evaluation of tilapia fillet freshness." @default.
- W3126090857 created "2021-02-01" @default.
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- W3126090857 date "2021-06-01" @default.
- W3126090857 modified "2023-10-12" @default.
- W3126090857 title "Hyperspectral imaging in combination with data fusion for rapid evaluation of tilapia fillet freshness" @default.
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- W3126090857 doi "https://doi.org/10.1016/j.foodchem.2021.129129" @default.
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