Skip to main content
Log in

Online determination of quality parameters of dried soybean protein–lipid films (Fuzhu) by NIR spectroscopy combined with chemometrics

  • Original Paper
  • Published:
Journal of Food Measurement and Characterization Aims and scope Submit manuscript

Abstract

Fuzhu, a protein–lipid film, is formed during the heating of soymilk. Protein, lipid and moisture contents are key quality parameters, which also affect commercial pricing in the Fuzhu industry. Near-infrared (NIR) technology was investigated for the online determination of Fuzhu quality parameters. The spectra (1000–2499 nm) of intact Fuzhu collected from four production lines during a complete production cycle were recorded on a NIR spectrometer using diffused reflectance mode. A hybrid approach combining wavelet transform with derivative calculation and multiplicative scatter correction optimally enhanced the spectral characteristic signals. Random frog (RF) and successive projections algorithm (SPA) were used for determination of key variables for PLS and MLR modeling. Comparing to the routine PLS and MLR models, the performances of RF-PLS and SPA-MLR models showed higher residual predictive deviations of 2.89 and 2.91 for protein, 3.03 and 2.97 for lipid, and 3.61 and 3.45 for moisture, respectively. An external sample set from another production line was used to assess the performances of developed RF-PLS models of protein, lipid and moisture, which yielded lower root mean squared error of prediction of 0.675, 0.554 and 0.136%, respectively, and lower absolute error value range of 1.57–1.42, 1.08–0.98 and 0.29–0.23%, respectively. Based on the predicted values obtained with RF-PLS models, a satisfactory classification of Fuzhu grades was also obtained with a total accuracy rate of 91.8%. The above results indicate that NIR coupled with chemometrics shall be a promising tool for online determination of the quality parameters of Fuzhu.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. R. Bressani, J. Am. Oil Chem. Soc. 58, 392–400 (1981)

    Article  CAS  Google Scholar 

  2. L. Wu, R. Bates, J. Food Sci. 37, 36–39 (1972)

    Article  CAS  Google Scholar 

  3. D. Martínez-Valdivieso, R. Font, P. Gómez, T. Blanco-Díaz, M. Del Río-Celestino, J. Sci. Food. Agric. 94, 3171–3180 (2014)

    Article  CAS  PubMed  Google Scholar 

  4. J. Wang, J. Wang, Z. Chen, D. Han, Postharvest Biol. Technol. 129, 143–151 (2017)

    Article  Google Scholar 

  5. M.B. Buyukcan, I. Kavdir, J. Food Meas. Charact. 11, 651–659 (2017)

    Article  Google Scholar 

  6. D.S. Ferreira, O.F. Galão, J.A.L. Pallone, R.J. Poppi, Food Control 35, 227–232 (2014)

    Article  CAS  Google Scholar 

  7. P.C. Williams, K.H. Norris, in Near Infrared Technology in the Agricultural and Food Industries, ed. by P.C. Williams, K.H. Norris (American Association of Cereal Chemists, St. Paul, 1987), pp. 241–246

    Google Scholar 

  8. L.P. Brás, S.A. Bernardino, J.A. Lopes, J.C. Menezes, Chemometr. Intell. Lab. Syst. 75, 91–99 (2005)

    Article  CAS  Google Scholar 

  9. N. Li, S.G. Min, F.L. Qin, M.X. Zhang, S.F. Ye, Spectrosc. Spect. Anal. 24, 45–49 (2004)

    Google Scholar 

  10. I.V. Kovalenko, G.R. Rippke, C.R. Hurburgh, J. Am. Oil Chem. Soc. 83, 421–427 (2006)

    Article  CAS  Google Scholar 

  11. C. Lu, D. Han, J. Near Infrared. Spectrosc. 13, 139–145 (2005)

    Article  CAS  Google Scholar 

  12. M. Casale, R. Simonetti, J. Near Infrared Spectrosc. 22, 59–80 (2014)

    Article  CAS  Google Scholar 

  13. J.U. Porep, D.R. Kammerer, R. Carle, Trends Food Sci. Technol. 46, 211–230 (2015)

    Article  CAS  Google Scholar 

  14. J. Beltrán Ortega, M. Gila, M. Diego, D. Aguilera Puerto, J. Gámez García, J. Gómez Ortega, J. Sci. Food Agric. 96, 4644–4662 (2016)

    Article  CAS  PubMed  Google Scholar 

  15. L. Wang, D.W. Sun, H. Pu, J.H. Cheng, Crit. Rev. Food Sci. 57, 1524–1538 (2017)

    Article  CAS  Google Scholar 

  16. J.A. Guthrie, K.B. Walsh, Aust. J. Exp. Agric. 39, 73–80 (1999)

    Article  Google Scholar 

  17. J. Cai, Q. Chen, X. Wan, J. Zhao, Food Chem. 126, 1354–1360 (2011)

    Article  CAS  Google Scholar 

  18. S. Tripathi, H.N. Mishra, Food Control 20, 840–846 (2009)

    Article  CAS  Google Scholar 

  19. L. Xu, Y.P. Zhou, L.J. Tang, H.L. Wu, J.H. Jiang, G.L. Shen, R.Q. Yu, Anal. Chim. Acta 616, 138–143 (2008)

    Article  CAS  PubMed  Google Scholar 

  20. H. Ma, J. Wang, Y. Chen, Z. Lai, Food Chem. 215, 108–115 (2017)

    Article  CAS  PubMed  Google Scholar 

  21. B.A.J.G. Jacobs, B.E. Verlinden, E. Bobelyn, A. Decombel, P. Bleyaert, J.V. Lommel, I. Vandevelde, W. Saeys, B.M. Nicolai, Postharvest Biol. Technol. 113, 95–105 (2016)

    Article  CAS  Google Scholar 

  22. C. Zhang, H. Ye, F. Liu, Y. He, W. Kong, K. Sheng, Sensors 16, 244 (2016)

    Article  CAS  PubMed  Google Scholar 

  23. X. Li, C. Sun, L. Luo, Y. He, Comput. Electron. Agric. 112, 28–35 (2015)

    Article  Google Scholar 

  24. X. Sun, X. Dong, J. Food Meas. Charact. 9, 95–103 (2015)

    Article  Google Scholar 

  25. C.M. Andersen, R. Bro, J Chemometr. 24, 728–737 (2010)

    Article  CAS  Google Scholar 

  26. AOAC, in Official methods of analysis of AOAC International, ed. by W. Horwitz, G.W. Latimer (AOAC International, Gaithersbrug, 2006)

    Google Scholar 

  27. X. Shao, C. Pang, Q. Su, Fresen. J. Anal. Chem. 367, 525–529 (2000)

    Article  CAS  Google Scholar 

  28. H.D. Li, Q.S. Xu, Y.Z. Liang, Anal. Chim. Acta. 740, 20–26 (2012)

    Article  CAS  PubMed  Google Scholar 

  29. M.C.U. Araújo, T.C.B. Saldanha, R.K.H. Galvão, T. Yoneyama, H.C. Chame, V. Visani, Chemometr. Intell. Lab. Syst. 57, 65–73 (2001)

    Article  Google Scholar 

  30. R.K.H. Galvão, M.C.U. Araújo, W.D. Fragoso, E.C. Silva, G.E. José, S.F.C. Soares, H.M.A. Paiva, Chemometr. Intell. Lab. Syst. 92, 83–91 (2008)

    Article  CAS  Google Scholar 

  31. libPLS: An Integrated Library for Partial Least Squares Regression and Discriminant Analysis (2017). http://www.libpls.net/download.php. Accessed 27 Feb 2017

  32. The Successive Projections Algorithm (SPA) Homepage (2016). http://www.ele.ita.br/~kawakami/spa/. Accessed 27 Feb 2016

  33. P.C. Williams, in Near-Infrared Technology in the Agricultural and Food Industries, ed. by P.C. Williams, K.H. Norris (American Association of Cereal Chemists, St. Paul, 2001), pp. 145–171

    Google Scholar 

  34. S.A. Haughey, S.F. Graham, E. Cancouët, C.T. Elliott, Food Chem. 136, 1–15 (2013)

    Article  CAS  Google Scholar 

  35. M.S. Dhanoa, S.J. Lister, R. Sanderson, R.J. Barnes, J. Near Infrared Spectrosc. 2, 43–47 (1994)

    Article  CAS  Google Scholar 

  36. J. Workman Jr., L. Weyer, Practical Guide to Interpretive Near-Infrared Spectroscopy (CRC Press, New York, 2008), pp. 239–287

    Google Scholar 

  37. W. Saeys, A.M. Mouazen, H. Ramon, Biosyst. Eng. 91, 393–402 (2005)

    Article  Google Scholar 

  38. M.W. Davey, W. Saeys, E. Hof, H. Ramon, R.L. Swennen, J. Keulemans, J. Agric. Food Chem. 57, 1742–1751 (2009)

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (31401579), China Scholarship Council (CSC) and Programs for Science and Technology Development of Henan Province of China (122102210247).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Jiahua Wang or Zhenya Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, J., Zhang, X., Sun, S. et al. Online determination of quality parameters of dried soybean protein–lipid films (Fuzhu) by NIR spectroscopy combined with chemometrics. Food Measure 12, 1473–1484 (2018). https://doi.org/10.1007/s11694-018-9762-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11694-018-9762-z

Keywords

Navigation