All Issue

2026 Vol.8, Issue 1 Preview Page

Research Article

Predicting water loss of cucumbers in maritime transport environments via heat and mass transfer modeling
Dong hyeon Kang1
,
Seongheon Kim2*
,
Jinkyung Kwon2
,
Fumina Tanaka3
,
Fumihiko Tanaka3*
1Department of Liberal Arts, Korean National University of Agriculture and Fisheries, Jeonju 54874, Republic of Korea
2Department of Agricultural Engineering, National Institute of Agricultural Sciences, Jeonju 54875, Republic of Korea
3Faculty of Agriculture, Kyushu University, Fukuoka 819-0395, Japan
*Corresponding Author
31 March 2026. pp. 56-65
PDF XML Citation
Abstract

Water loss is a primary cause of postharvest quality degradation in cucumbers, which possess high moisture content. This study developed a numerical model based on heat and mass transfer using the Finite Element Method (FEM) to predict cucumber water loss during long-distance maritime export. A 3D geometric model was constructed distinguishing the mesocarp and endocarp regions, with the stem-end scar specifically included as a critical boundary representing the primary gas exchange site. Governing equations utilized unsteady-state heat conduction and Fick’s second law of diffusion. A logistic function-based transpiration rate reduction model was integrated to account for the non-linear decrease in water loss over extended periods. The proposed model was validated against experimental data gathered during a 19.5-day maritime transport route from Fukuoka, Japan, to Singapore. Environmental conditions were monitored in both refrigerated and cooling containers. Statistical validation using independent two-sample t-tests demonstrated no significant difference (p > 0.05) between the simulated results and the observed moisture ratios across all container conditions, establishing the high reliability of the model. The results indicate that the model can function as a robust decision-support tool for real-time weight loss and shelf-life estimation in global logistics. This research provides a vital technical framework for the development of digital twins for fresh horticultural produce.

Keywords
Cucumber fruit
Finite element method (FEM)
Maritime export
Numerical analysis
References
1

Agrawal, S.G., Methekar, R.N. 2017. Mathematical model for heat and mass transfer during convective drying of pumpkin. Food and Bioproducts Processing 101: 68-73. https://doi.org/10.1016/j.fbp.2016.10.005

10.1016/j.fbp.2016.10.005
2

ASHRAE. 2006. ASHRAE Handbook: refrigeration. Atlanta, GA, USA.

3

Beck, C.B. 2010. An introduction to plant structure and development. Cambridge University Press. https://doi.org/10.1017/CBO9780511844683

10.1017/CBO9780511844683
4

Ben-Yehoshua, S. 1987. Transpiration, water, and gas exchange. Postharvest Physiology of Vegetables 24: 113-170.

5

Bird, R., Stewart, W., Lightfoot, E. 2002. Transport Phenomena (2nd ed.). John & Wiley Sons.

6

Bovi, G.G., Caleb, O.J., Linke, M., Rauh, C., Mahajan, P. V. 2016. Transpiration and moisture evolution in packaged fresh horticultural produce and the role of integrated mathematical models: A review. Biosystems Engineering 150: 24-39. https://doi.org/10.1016/j.biosystemseng.2016.07.013

10.1016/j.biosystemseng.2016.07.013
7

Castro, A.M., Mayorga, E.Y., Moreno, F.L. 2018. Mathematical modelling of convective drying of fruits: A review. Journal of Food Engineering 223: 152-167. https://doi.org/10.1016/j.jfoodeng.2017.12.012

10.1016/j.jfoodeng.2017.12.012
8

Çengel, Y. 2014. Heat and mass transfer: fundamentals and applications. New York, NY, USA: McGraw-Hill Education.

9

Chotyakul, N., Sampedro, F., Leguizamón, J.I., Rodrigo, D. 2011. Assessment of the uncertainty in thermal food processing decisions. Journal of Food Engineering 102(3): 247-256. https://doi.org/10.1016/j.jfoodeng.2010.08.027

10.1016/j.jfoodeng.2010.08.027
10

Crank, J. 1979. The mathematics of diffusion. Oxford University Press.

11

Díaz-Pérez, J.C. 2019. Transpiration. In: Postharvest Physiology and Biochemistry of Fruits and Vegetables. Woodhead Publishing.

10.1016/B978-0-12-813278-4.00008-7
12

Eboibi, O., Sanni, L.O., Kareem, S.O. 2018. Moisture-Dependent Mechanical and Textural Properties of Intact Cucumber Fruit. IJETR 8(2): 34-39.

13

Fadiji, T., Berry, T.M., Coetzee, C., Opara, U.L. 2018. The efficacy of finite element analysis (FEA) as a design tool for food packaging. Biosystems Engineering 174: 20-40. https://doi.org/10.1016/j.biosystemseng.2018.06.015

10.1016/j.biosystemseng.2018.06.015
14

Han, J.W., Zhao, C.J., Yang, X.T., Qian, J.P., Fan, B.L. 2018. Numerical modeling of forced-air cooling of palletized apple: Integral evaluation of cooling efficiency. International Journal of Refrigeration 89: 131-141. https://doi.org/10.1016/j.ijrefrig.2018.02.012

10.1016/j.ijrefrig.2018.02.012
15

James, S.J., James, C., Evans, J.A. 2006. Modelling of food transportation systems-a review. International Journal of Refrigeration 29(6): 947-957. https://doi.org/10.1016/j.ijrefrig.2006.03.017

10.1016/j.ijrefrig.2006.03.017
16

Kim, S.H., Tanaka, F., Uchino, T., Perez, J. H. 2020. Simulation of temperature profile and moisture loss of fresh cucumber fruit. Food Science and Technology Research 26(4): 459-468. https://doi.org/10.3136/fstr.26.459

10.3136/fstr.26.459
17

Kiranoudis, C.T., Maroulis, Z.B., Marinos-Kouris, D. 1995. Heat and mass transfer model building in drying with multiresponse data. IJHMT 38(3): 463-480. https://doi.org/10.1016/0017-9310(94)00166-S

10.1016/0017-9310(94)00166-S
18

Kohyama, K. Nagata, A. Tamaki, Y. Sakurai, N. 2009. Comparison of human-bite and instrument puncture tests of cucumber texture. Postharvest biology and technology 52(2): 243-246. https://doi.org/10.1016/j.postharvbio.2008.12.001

10.1016/j.postharvbio.2008.12.001
19

Labuza, T.P., Altunakar, B. 2008. Water activity prediction and moisture sorption isotherms. In: Water Activity in Foods: Fundamentals and Applications (pp. 161-206). Blackwell Publishing. https://doi.org/10.1002/9781118765982.ch7

10.1002/9781118765982.ch7
20

Lang, W., Sokhansanj, S., Rohani, S. 1994. Dynamic shrinkage and variable parameters in Bakker-Arkema’s mathematical simulations. Drying Technology 12(7): 1687-1708. https://doi.org/10.1080/07373939408962193

10.1080/07373939408962193
21

Mahiuddin, M., Khan, M.I.H., Kumar, C., Rahman, M.M., Karim, M.A. 2018. Shrinkage of food materials during drying. Comprehensive Reviews in Food Science and Food Safety 17(5): 1113-1126. https://doi.org/10.1111/1541-4337.12375

10.1111/1541-4337.12375
22

NOAA. 1976. US standard atmosphere. Washington D.C., USA: National Oceanic and Atmospheric Administration.

23

Nunes, M.C.N., Emond, J.P., Brecht, J.K. 2011. Distribution center and retail conditions affect quality of cucumbers. Postharvest Biology and Technology 59(3): 280-288. https://doi.org/10.1016/j.postharvbio.2010.10.004

10.1016/j.postharvbio.2010.10.004
24

Perez, J.H., Tanaka, F., Uchino, T. 2011. Comparative 3D simulation on water absorption and hygroscopic swelling in japonica rice grains under various isothermal soaking conditions. Food Research International 44(9): 2615-2623. https://doi.org/10.1016/j.foodres.2011.05.003

10.1016/j.foodres.2011.05.003
25

Pons, E., Yrieix, B., Heymans, L., Dubelley, F., Planes, E. 2014. Permeation of water vapor through high performance laminates for VIPs and physical characterization of sorption and diffusion phenomena. Energy and Buildings 85: 604-616. https://doi.org/10.1016/j.enbuild.2014.08.032

10.1016/j.enbuild.2014.08.032
26

Sampedro, F., Rodrigo, D., Martínez, A. 2011. Modelling the effect of pH and pectin concentration on the PEF inactivation of Salmonella enterica serovar Typhimurium by using the Monte Carlo simulation. Food Control 22(3-4): 420-425. https://doi.org/10.1016/j.foodcont.2010.09.013

10.1016/j.foodcont.2010.09.013
27

Sargent, S.A., Maynard, D.N. 2012. Cucurbits. In: Crop Post-Harvest: Science and Technology. Wiley-Blackwell. https://doi.org/10.1002/9781444354652.ch14

10.1002/9781444354652.ch14
28

Siebel, J.E. 1892. Specific heat of various products. Ice and Refrigeration 2: 256-257.

29

Smith, K.R., Fleming, H.P., Van Dyke, C.G., Lower, R.L. 1979. Scanning electron microscopy of the surface of pickling cucumber fruit. Journal of the American Society for Horticultural Science 104(4): 528-533. https://doi.org/10.21273/JASHS.104.4.528

10.21273/JASHS.104.4.528
30

Sweat, V.E. 1974. Experimental values of thermal conductivity of selected fruits and vegetables. Journal of Food Science 39(6): 1080-1083.

10.1111/j.1365-2621.1974.tb07323.x
31

Tanaka, F., Kim, S. H., Perez, J. H., Uchino, T. 2018. Observation and analysis of internal structure of cucumber fruit using X-ray CT. EAEF 11(2): 51-56. https://doi.org/10.1016/j.eaef.2017.12.004

10.1016/j.eaef.2017.12.004
Information
  • Publisher :Korean Society of Precision Agriculture
  • Publisher(Ko) :한국정밀농업학회
  • Journal Title :Precision Agriculture Science and Technology
  • Journal Title(Ko) :정밀농업과학기술
  • Volume : 8
  • No :1
  • Pages :56-65
  • Received Date : 2026-03-09
  • Revised Date : 2026-03-16
  • Accepted Date : 2026-03-17
  • DOI :https://doi.org/10.22765/pastj.20260005
Journal Informaiton Precision Agriculture Science and Technology Precision Agriculture Science and Technology
Online Submission & Review System
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • KCI 문헌 유사도 검사
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close