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Investigating the Effects of Table Grape Package Components and Stacking on Airflow, Heat and Mass Transfer Using 3-D CFD Modelling

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Abstract

The flow phenomenon during cooling and handling of packed table grapes was studied using a computational fluid dynamic (CFD) model and validated using experimental results. The effects of the packaging components (bunch carry bag and plastic liners) and box stacking on airflow, heat and mass transfer were analysed. The carton box was explicitly modelled, grape bunch with the carry bag was treated as a porous medium and perforated plastic liners were taken as a porous jump. Pressure loss coefficients of grape bunch with the carry bag and perforated plastic liners were determined using wind tunnel experiments. Compared with the cooling of bulk grape bunch, the presence of the carry bag increased the half and seven eighth cooling time by 61.09 and 97.34 %, respectively. The addition of plastic liners over the bunch carry bag increased the half and seven eighth cooling time by up to 168.90 and 185.22 %, respectively. Non-perforated liners were most effective in preventing moisture loss but also generated the highest condensation of water vapour inside the package. For perforated plastic liners, cooling with a high relative humidity (RH) air minimised fruit moisture loss. Partial cooling of the grape bunch inside the carry bag before covering it with a non-perforated plastic liner maintained the required high RH inside the package without condensation. The stacking of packages over the pallet affected the airflow pattern, the cooling rate and moisture transfer. There was a good agreement between measured and predicted results. The result demonstrated clearly the applicability of CFD models to determine optimum table grape packaging and cooling procedures.

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Abbreviations

A c :

Cooler surface area (m2)

a p :

Specific fruit area (m−1)

Bi:

Biot number

C p :

Specific heat capacity (J kg−1 °C−1)

D :

Diffusion coefficient (m2 s−1)

D c :

Collar diameter of heat exchanger tube (m)

D e :

Effective diffusivity (m2 s−1)

D P :

Fruit diameter (m)

g :

Gravitational acceleration (m s−2)

h h :

Heat transfer coefficient (W m−2 °C−1)

h m :

Mass transfer coefficient (m s−1)

K :

Darcy permeability (m2)

k :

Turbulence kinetic energy (m2 s−2)

L :

Latent heat (J kg−1)

p :

Pressure (Pa)

Pr:

Prandtl number

p sat :

Saturated vapour pressure (Pa)

p v :

Vapour pressure (Pa)

Re :

Reynolds number

Sc:

Schmidt number

S e :

Heat source term (W m−3)

S m :

Mass source term (kg m−3 s−1)

St:

Stanton number

t :

Time (s)

T :

Temperature (°C)

T′ :

Fluctuating temperature (°C)

u i , u j :

Mean velocity components in X, Y, and Z directions (m s−1)

u i ′, u j ′:

Fluctuating velocity components (m s−1)

V :

Volume (m−3)

x i , x j :

Cartesian coordinates (m)

X v :

Moisture content (kg/kg)

Y v :

Vapour mass fraction

β :

Forchheimer drag coefficient (m−1)

ε :

Dissipation rate of turbulence kinetic energy (m2 s−3)

μ :

Dynamic viscosity (kg m−1 s−1)

λ :

Thermal conductivity (W m−1 °C−1)

ω :

Specific dissipation rate (s−1)

ρ :

Density (kg m−3)

ϕ :

Porosity

α :

Thermal expansion coefficient (°C−1)

a :

Air phase

c :

Cooler

o :

Reference condition

p :

Product

t :

Turbulence

i, j :

Cartesian coordinate index

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Acknowledgements

This work is based upon research supported by the South African Research Chairs Initiative of the Department of Science and Technology and National Research Foundation. The financial support of the South African Postharvest Innovation Programme through the award of research grant on ‘Packaging of the Future’ project is acknowledged. The authors are grateful to Mr. Cobus Zietsman for his technical support with the wind tunnel experiment and to Ms. Nazneen Ebrahim for support in the postharvest technology laboratory. We thank the anonymous reviewers for their valuable comments and feedback.

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Delele, M.A., Ngcobo, M.E.K., Opara, U.L. et al. Investigating the Effects of Table Grape Package Components and Stacking on Airflow, Heat and Mass Transfer Using 3-D CFD Modelling. Food Bioprocess Technol 6, 2571–2585 (2013). https://doi.org/10.1007/s11947-012-0895-5

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