Effect of ultrasonic energy density on moisture transfer during ultrasound enhanced vacuum drying of honey

  • Sijia Liu
  • Wenxue ZhuEmail author
  • Xiting Bai
  • Taifei You
  • Jingming Yan
Original Paper


The purpose of this work is to explore the water content, distribution and stage changes of honey during ultrasound enhanced vacuum drying process. Ultrasound enhanced vacuum drying of honey was carried out at ultrasonic energy density levels of 0, 0.4, 0.8, 1.2, 1.6 W/g, respectively, and the drying kinetics model was established. The transverse relaxation time T2 inversion spectra of honey at different ultrasonic energy densities during drying process were measured and the changing characteristics of internal moisture state were analyzed by using the low-field nuclear magnetic resonance (LF-NMR). The results showed that the process of honey during ultrasound enhanced vacuum drying could mainly be divided into two periods, namely accelerating rate period and falling rate period. The range of effective moisture diffusion coefficient (Deff) was from 0.7879 × 10−7 to 2.1850 × 10−7 m2/s and the Deff values increased with the rise of ultrasonic energy density. According to the nonlinear fitting based on 9 dynamic models, two-term exponential model was determined by the optimal model, and the values of R2, χ2 and RMSE were 0.9991, 0.001 and 0.0091, respectively. The LF-NMR results showed that immobilized water was the main moisture in honey, which was 96.47%. As the drying proceeded, the relaxation time of immobilized water (T22) and free water (T23) decreased, which indicated that their mobility reduced gradually. The relaxation time of bound water (T21) showed little changes. The amplitude of immobilized water (A22) and free water (A23) decreased significantly at the initial stage of drying, and the amplitude of bound water (A21) decreased significantly at the last stage. Magnetic resonance imaging results revealed that the moisture distribution in honey was uneven and the brightness of images started to darken with the increase of drying time. Therefore, the results of this work demonstrate that NMR is a promising method to measure and quantify residual water content, water distribution and state of water of honey in real time during the drying process.


Ultrasound Vacuum drying Low-field nuclear magnetic resonance (LF-NMR) Drying characteristics Moisture transfer Honey 



The authors express their sincere appreciation to the Support Plan of the College Scientific and technological Innovation team of Henan province (project 17IRTSTHN016) and the College Scientific and Technological Innovation Talents Program of Henan province (project 19HASTIT013) for support this study financially.


  1. 1.
    I.D. Thorat, D. Mohapatra, R.F. Sutar, S.S. Kapdi, D.D. Jagtap, Mathematical modeling and experimental study on thin-layer vacuum drying of ginger (Zingiber officinale R.) slices. Food Bioprocess Technol. 5(4), 1379–1383 (2012)CrossRefGoogle Scholar
  2. 2.
    Z.W. Cui, S.Y. Xu, D.W. Sun, Microwave–vacuum drying kinetics of carrot slices. J. Food Eng. 65(2), 157–164 (2004)CrossRefGoogle Scholar
  3. 3.
    A. Arévalo-Pinedo, F.E.X. Murr, Influence of pre-treatments on the drying kinetics during vacuum drying of carrot and pumpkin. J. Food Eng. 80(1), 152–156 (2007)CrossRefGoogle Scholar
  4. 4.
    F.A.N. Fernandes, F.I.P. Oliveira, S. Rodrigues, Use of ultrasound for dehydration of papayas. Food Bioprocess Technol. 1(4), 339–345 (2008)CrossRefGoogle Scholar
  5. 5.
    Z. Yang, X. Li, Z.C. Tao, N. Luo, F. Yu, Ultrasound-assisted heat pump drying of pea seed. Drying Technol. 5, 1–12 (2018)CrossRefGoogle Scholar
  6. 6.
    Y.H. Liu, Y. Sun, S. Miao, F. Li, D.L. Luo, Drying characteristics of ultrasound assisted hot air drying of flos lonicerae. J. Food Sci. Technol. 52(8), 4955–4964 (2015)CrossRefGoogle Scholar
  7. 7.
    J.A. Cárcel, J.V. Garcia-Perez, E. Riera, A. Mulet, Improvement of convective drying of carrot by applying power ultrasound—influence of mass load density. Dry. Technol. 29(2), 174–182 (2011)CrossRefGoogle Scholar
  8. 8.
    Y. Deng, Y.Y. Zhao, Effect of pulsed vacuum and ultrasound osmopretreatments on glass transition temperature, texture, microstructure and calcium penetration of dried apples (Fuji). LWT Food Sci. Technol. 41(9), 1575–1585 (2008)CrossRefGoogle Scholar
  9. 9.
    H.U. Hebbar, N.K. Rastogi, R. Subramanian, Properties of dried and intermediate moisture honey products: a review. Int. J. Food Prop. 11(4), 804–819 (2008)CrossRefGoogle Scholar
  10. 10.
    K. Samborska, M. Czelejewska, The influence of thermal treatment and spray drying on the physicochemical properties of polish honeys. J. Food Process. Preserv. 38(1), 413–419 (2014)CrossRefGoogle Scholar
  11. 11.
    M.Y. Troutman, I.V. Mastikhin, B.J. Balcom, T.M. Eads, G.R. Ziegler, Moisture migration in soft-panned confections during engrossing and aging as observed by magnetic resonance imaging. J. Food Eng. 48(3), 257–267 (2001)CrossRefGoogle Scholar
  12. 12.
    H. Todt, G. Guthausen, W. Burk, D. Schmalbein, A. Kamlowski, Water/moisture and fat analysis by time-domain NMR. Food Chem. 96(3), 436–440 (2006)CrossRefGoogle Scholar
  13. 13.
    S.S. Cheng, Y.Q. Tang, T. Zhang, Y.K. Song, X.H. Wang, H.H. Wang, H.T. Wang, M.Q. Tan, An approach for monitoring the dynamic states of water in shrimp during drying process with LF-NMR and MRI. Dry. Technol. 36(7), 841–848 (2017)CrossRefGoogle Scholar
  14. 14.
    W.Q. Lv, M. Zhang, Y.C. Wang, B. Adhikari, Online measurement of moisture content, moisture distribution, and state of water in corn kernels during microwave vacuum drying using novel smart NMR/MRI detection system. Dry. Technol. 36(13), 1592–1602 (2018)CrossRefGoogle Scholar
  15. 15.
    S.S. Cheng, T. Zhang, L. Yao, X.H. Wang, Y.K. Song, H.H. Wang, H.T. Wang, M.Q. Tan, Use of Low Field-NMR and MRI to characterize water mobility and distribution in pacific oyster (Crassostrea gigas) during drying process. Dry. Technol. 36(5), 630–636 (2018)CrossRefGoogle Scholar
  16. 16.
    AOAC, Official methods of analysis, 15th edn. (Association of Official Analytical Chemists, Washington, D.C., 1990)Google Scholar
  17. 17.
    Y. Ma, W. Zhu et al., Drying characteristics and kinetics model of liquid whole egg during ultrasound reinforced vacuum drying. J. Food Sci. 39(3), 142–149 (2018)Google Scholar
  18. 18.
    A.R. Celma, F. López-Rodríguez, F.C. Blázquez, Experimental modelling of infrared drying of industrial grape by-products. Food Bioprod. Process 87(4), 247–253 (2009)CrossRefGoogle Scholar
  19. 19.
    I.T. Togrul, D. Pehlivan, Modelling of thin layer drying kinetics of some fruits under open-air sun drying process. J. Food Eng. 65(3), 413–425 (2004)CrossRefGoogle Scholar
  20. 20.
    A. Kaleta, K. Górnicki, Evaluation of drying models of apple (var. McIntosh) dried in a convective dryer. Int. J. Food Sci. Technol. 45(5), 891–898 (2010)CrossRefGoogle Scholar
  21. 21.
    İ Doymaz, Drying kinetics of white mulberry. J. Food Eng. 61(3), 341–346 (2004)CrossRefGoogle Scholar
  22. 22.
    E.K. Akpinar, Y. Bicer, Modelling of the drying of eggplants in thin-layers. Int. J. Food Sci. Technol. 40(3), 273–281 (2010)CrossRefGoogle Scholar
  23. 23.
    A. Taherigaravand, S. Rafiee, A. Keyhani, Study on effective moisture diffusivity, activation energy and mathematical modeling of thin layer drying kinetics of bell pepper. Aust. J. Crop Sci. 5(2), 128–131 (2011)Google Scholar
  24. 24.
    C. Ertekin, O. Yaldiz, Drying of eggplant and selection of a suitable thin layer drying model. J. Food Eng. 63(3), 349–359 (2004)CrossRefGoogle Scholar
  25. 25.
    I.T. Togrul, D. Pehlivan, Mathematical modelling of solar drying of apricots in thin layers. J. Food Eng. 55(3), 209–216 (2002)CrossRefGoogle Scholar
  26. 26.
    C. Chen, P.C. Wu, Thin-layer drying model for rough rice with high moisture content. J. Agric. Eng. Res. 80(1), 45–52 (2001)CrossRefGoogle Scholar
  27. 27.
    L.M. Diamante, P.A. Munro, Mathematical modelling of hot air drying of sweet potato slices. Int. J. Food Sci. Technol. 26(1), 99–109 (1991)CrossRefGoogle Scholar
  28. 28.
    Z.Q. Guan, X.Z. Wang, M. Li, X.Q. Jiang, J. Xie, Mathematical modeling of hot air drying of thin layer litchi flesh. Trans. CSAM 43(2), 151–158 (2012)Google Scholar
  29. 29.
    P.M. Azoubel, M.D.A.M. Baima, M.D.R. Amorim, S.S.B. Oliveira, Effect of ultrasound on banana cv pacovan drying kinetics. J. Food Eng. 97(2), 194–198 (2010)CrossRefGoogle Scholar
  30. 30.
    K.J. Mothibe, M. Zhang, J. Nsor-atindana, Y.C. Wang, Use of ultrasound pretreatment in drying of fruits: drying rates, quality attributes, and shelf life extension. Dry. Technol. 29(14), 1611–1621 (2011)CrossRefGoogle Scholar
  31. 31.
    F. Zhao, D.L. Cheng, Z.Q. Chen, Effect of ultrasonic treatment on hot air drying process of sludge. Trans. CSAE 31(4), 272–276 (2015)Google Scholar
  32. 32.
    O. Rodríguez, J.V. Santacatalina, S. Simal, J.V. Garcia-Perez, A. Femenia, C. Rosselló, Influence of power ultrasound application on drying kinetics of apple and its antioxidant and microstructural properties. J. Food Eng. 129(1), 21–29 (2014)CrossRefGoogle Scholar
  33. 33.
    H.T. Sabarez, J.A. Gallego-Juarez, E. Riera, Ultrasonic-assisted convective drying of apple slices. Drying Technol. 30(9), 989–997 (2012)CrossRefGoogle Scholar
  34. 34.
    A. Wiktor, M. Sledz, M. Nowacka, K. Rybak, D. Witrowa-Rajchert, The influence of immersion and contact ultrasound treatment on selected properties of the apple tissue. Appl. Acoustics 103, 136–142 (2016)CrossRefGoogle Scholar
  35. 35.
    P. Udomkun, D. Argyropoulos, M. Nagle, B. Mahayothee, S. Janjai, J. Müller, Single layer drying kinetics of papaya amidst vertical and horizontal airflow. LWT Food Sci. Technol. 64(1), 67–73 (2015)CrossRefGoogle Scholar
  36. 36.
    Y.H. Liu, Y. Sun, H.C. Yu, Y. Yin, X. Li, X. Duan, Hot air drying of purple-fleshed sweet potato with contact ultrasound assistance. Dry. Technol. 35(5), 564–576 (2016)CrossRefGoogle Scholar
  37. 37.
    J.V. Garcia-Perez, J.A. Carcel, E. Riera, C. Rosselló, A. Mulet, Intensification of low-temperature drying by using ultrasound. Dry. Technol. 30(11–12), 1199–1208 (2012)CrossRefGoogle Scholar
  38. 38.
    M.Y. Li, H.B. Wang, G.M. Zhao, M.W. Qiao, M. Li, L.X. Sun, X.P. Gao, J.W. Zhang, Determining the drying degree and quality of chicken jerky by LF-NMR. J. Food Eng. 139(139), 43–49 (2014)CrossRefGoogle Scholar
  39. 39.
    S. Faal, T. Tavakoli, B. Ghobadian, Mathematical modelling of thin layer hot air drying of apricot with combined heat and power dryer. J. Food Sci. Technol. 52(5), 2950–2957 (2015)CrossRefGoogle Scholar
  40. 40.
    J.G. Xu, S.W. Zhang, G. Xu, Z. Gu, H.D. Li, Thin-layer hot air drying characteristics and moisture diffusivity of lotus seeds. Trans. CSAE 32(13), 303–309 (2016)Google Scholar
  41. 41.
    S. Wei, B.Q. Tian, H.F. Jia, H.Y. Zhang, F. He, Z.P. Song, Investigation on water distribution and state in tobacco leaves with stalks during curing by LF-NMR and MRI. Dry. Technol. 36(12), 1515–1522 (2018)CrossRefGoogle Scholar
  42. 42.
    Y.H. Liu, Y. Sun, L. Wang, S. Miao, D.L. Luo, L. Luo, Drying characteristics of pear slices during ultrasound-assisted hot air drying. J. Food Sci. 36(9), 1–6 (2015)Google Scholar
  43. 43.
    J.V. García-Pérez, J.A. Cárcel, J. Benedito, A. Mulet, Power ultrasound mass transfer enhancement in food drying. Food Bioprod. Process 85(3), 247–254 (2007)CrossRefGoogle Scholar
  44. 44.
    C. Borompichaichartkul, G. Moran, G. Srzednicki, W.S. Price, Nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) studies of corn at subzero temperatures. J. Food Eng. 69(2), 199–205 (2005)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Sijia Liu
    • 1
  • Wenxue Zhu
    • 1
    Email author
  • Xiting Bai
    • 1
  • Taifei You
    • 1
  • Jingming Yan
    • 1
  1. 1.College of Food and BioengineeringHenan University of Science and TechnologyLuoyangChina

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