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Non-destructive measurement of water and fat contents, water dynamics during drying and adulteration detection of intact small yellow croaker by low field NMR

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Abstract

Non-destructive and fast measurement and characterization of fish is highly desired during various processing treatment. In this study, water dynamics during drying process and adulteration with carrageen were detected using low field nuclear magnetic resonance (LF-NMR) technique in small yellow croaker. Prediction models of water and fat contents were established based on LF-NMR Carr–Purcell–Meiboom–Gill (CPMG) data combined with principal component regression (PCR) or partial least squares regression (PLSR). The Rcv 2 of water and fat content by PLSR model was 0.9877 and 0.9054, and the root mean square error (RMSE) of cross-validation was 9.2360 and 3.3730%, respectively. Water dynamics during hot-air drying process showed that the amount of immobile water significantly decreased, and good correlation was found between the moisture ratio and peak area by Two-term model. In addition, the adulterated small yellow croaker with carrageen or distilled water could be clearly distinguished by principal component analysis (PCA) in a fast and non-destructive manner. All the results demonstrated that the LF-NMR may have great potential in fast and non-destructive analysis of small yellow croakers during various processing treatment.

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References

  1. Z. Li, X. Shan, X. Jin, F. Dai, Fish. Res. 110, 67–74 (2011)

    Article  Google Scholar 

  2. K. Khodabux, M. Lomelette, S. Jhaumeerlaulloo, P. Ramasami, P. Rondeau, Food Chem. 102, 669–675 (2007)

    Article  CAS  Google Scholar 

  3. O.J. Torrissen, R. Nortvedt, S. Tuene, Chemometr. Intell. Lab. Syst. 42, 199–207 (1988)

    Google Scholar 

  4. K. Kappel, U. Schröder, Food Control 59, 478–486 (2016)

    Article  Google Scholar 

  5. S.M. Jepsen, H.T. Pedersen, S.B. Engelsen, J. Sci. Food Agric. 79, 1793–1802 (1999)

    Article  CAS  Google Scholar 

  6. L. Zhang, M.J. Mccarthy, Postharvest Biol. Technol. 67, 96–101 (2012)

    Article  CAS  Google Scholar 

  7. C. Li, D. Liu, G. Zhou, X. Xu, J. Qi, P. Shi, T. Xia, Meat Sci. 92, 79–83 (2012)

    Article  Google Scholar 

  8. P.M. Santos, C.C. Corrêa, L.A. Forato, R.R. Tullio, G.M. Cruz, L.A. Colnago, Food Control 38, 204–208 (2014)

    Article  CAS  Google Scholar 

  9. J. Sánchez-Valencia, I. Sánchez-Alonso, I. Martinez, M. Careche, Food Bioprocess Tech. 8, 2137–2145 (2015)

    Article  Google Scholar 

  10. E. Veliyulin, C. Van Der Zwaag, W. Burk, U. Erikson, J. Sci. Food. Agr. 85, 1299–1304 (2005)

    Article  CAS  Google Scholar 

  11. C.M. Andersen, A. Rinnan, LWT-Food Sci. Technol. 35, 687–696 (2002)

    Article  CAS  Google Scholar 

  12. F.M.V. Pereira, A.D.S. Carvalho, L.F. Cabeça, L.A. Colnago, Microchem. J. 108, 14–17 (2013)

    Article  CAS  Google Scholar 

  13. S. Nakano, J. Kousaka, K. Fujii, K. Yorozuya, M. Yoshida, Y. Mouri, M. Akizuki, R. Tetsuka, T. Ando, T. Fukutomi, Breast Cancer Res. Treat. 134, 1179–1188 (2012)

    Article  Google Scholar 

  14. S. Geng, H. Wang, X. Wang, X. Ma, S. Xiao, J. Wang, M. Tan, Anal. Methods 7, 2413–2419 (2015)

    Article  CAS  Google Scholar 

  15. X. Zheng, Y. Jin, Y. Chi, M. Ni, Energy Fuels 27, 5787–5792 (2013)

    Article  CAS  Google Scholar 

  16. B.K. Arvoh, N.O. Skeie, M. Halstensen, Sep. Purif. Technol. 107, 204–210 (2013)

    Article  CAS  Google Scholar 

  17. S. Arazuri, J. Ignacio Arana, N. Arias, L.M. Arregui, J. Gonzalez-Torralba, C. Jaren, J. Food Eng. 111, 115–121 (2012)

    Article  Google Scholar 

  18. C. Collell, P. Gou, J. Arnau, J. Comaposada, Food Chem. 129, 601–607 (2011)

    Article  CAS  Google Scholar 

  19. G. Adiletta, G. Iannone, P. Russo, G. Patimo, S.D. Pasquale, M.D. Matteo, Int. J. Food Sci. Technol. 49, 2602–2609 (2014)

    Article  CAS  Google Scholar 

  20. M. Zhang, Dry. Technol. 30, 1377–1386 (2012)

    Article  Google Scholar 

  21. S. Wold, M. Sjöström, L. Eriksson, Chemometr. Intell. Lab. Syst. 58, 109–130 (2001)

    Article  CAS  Google Scholar 

  22. G. Adiletta, P. Russo, W. Senadeera, M.D. Matteo, J. Food Eng. 172, 9–18 (2016)

    Article  CAS  Google Scholar 

  23. H.T. Pedersen, L. Munck, S.B. Engelsen, J. Am. Oil Chem. Soc. 77, 1069–1077 (2000)

    Article  CAS  Google Scholar 

  24. L. Cheng, C. Bulmer, A. Margaritis, Curr. Drug Deliv. 12, 351–357 (2015)

    Article  CAS  Google Scholar 

  25. R.V. Kulkarni, V.V. Nagathan, P.R. Biradar, A.A. Naikawadi, Int. J. Biol. Macromol. 57, 238–244 (2013)

    Article  CAS  Google Scholar 

  26. D. Wu, H. Shi, Y. He, X. Yu, Y. Bao, J. Food Eng. 119, 680–686 (2013)

    Article  CAS  Google Scholar 

  27. J. Liu, X. Zhan, J. Wan, Y. Wang, C. Wang, Carbohyd. Polym. 121, 27–36 (2015)

    Article  CAS  Google Scholar 

  28. Q. Zhang, A.S.M. Saleh, Q. Shen, Food Bioprocess Technol. 6, 2562–2570 (2013)

    Article  CAS  Google Scholar 

  29. K.D.T.D.M. Milanez, M.J.C. Pontes, Anal. Methods 7, 145–146 (2015)

    Google Scholar 

  30. R.D.O.R. Ribeiro, E.T. Mársico, C.D.S. Carneiro, M.L.G. Monteiro, C.A.C. Júnior, S. Mano, E.F.O.D. Jesus, LWT-Food Sci. Technol. 55, 90–95 (2014)

    Article  CAS  Google Scholar 

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Acknowledgements

This work was supported by the National Key Research and Development Program of China (2016YFD0400404) and the National Nature Science Foundation of China (31501561).

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Correspondence to Mingqian Tan.

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Zang, X., Lin, Z., Zhang, T. et al. Non-destructive measurement of water and fat contents, water dynamics during drying and adulteration detection of intact small yellow croaker by low field NMR. Food Measure 11, 1550–1558 (2017). https://doi.org/10.1007/s11694-017-9534-1

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  • DOI: https://doi.org/10.1007/s11694-017-9534-1

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