FACULTEIT BIO-INGENIEURSWETENSCHAPPEN
An experimental and numerical study of precooling of
pome fruit in different packaging
Promotoren:
Prof. Bart Nicolaï
Dr. Ir. Pieter Verboven
Afstudeerjaar: 2014
Willem Gruyters
Introduction
It is estimated that within the next twelve years, the current world population will increase by
almost a billion. With this prediction, achieving food security will continue to be a big challenge.
Increasing food production is but one solution. Much of what is being produced may be lost before
reaching the consumer. Minimising postharvest losses is a way to increase food availability with no
additional resources and burdens on the environment. Therefore, tackling postharvest losses of
fresh produce encountered in the chain from farm-to-fork is paramount. Interruptions in the cold
chain and inferior packaging quality are known factors that contribute to the major postharvest
losses, which ultimately results in less food availability and significant financial deprivation of the
growers. By tightly controlling the temperature of fresh produce, the onset of fruit ripening and
senescence can be retarded. This temperature management (i.e. managing the cold chain) starts
right after harvest.
Precooling is the first cooling step where produce is cooled before transport to a storage facility
or into the distribution chain. It is the rapid cooling of produce from field temperature to their
optimal storage temperature, a vital step in the cold chain in preserving the end quality, prolonging
shelf life and thus reducing postharvest losses. One precooling technique that is predominantly
used in the postharvest industry is forced-air cooling (FAC). In this process, fruits placed in
bins/boxes (containers) are stacked in a specific pattern. Subsequently, cold air is forced rapidly
through the stack to remove heat from the produce. To supply uniform airflow, containers are
usually provided with vent holes. The shape, size, and location of the vent holes profoundly affect
the aerodynamic and thermodynamic performance of the container and ultimately, the fruit quality.
Optimization of a precooling process is therefore, a very complex problem. Approaching it
experimentally alone is impossible and hence, experimental and numerical approaches were
employed in this study.
The main objective of this study is to characterize the aerodynamic, thermodynamic and fruit
quality aspects of three different package designs used for transport of ‘Granny Smith’ apples. The
study evaluates the three container designs in relation to energy usage during precooling as well,
therefore also considering sustainability of the cold chain at the same time.
Materials and Methods
Experimental method
Three different containers were investigated in this study: a telescopic carton box (Mk4),
display carton box (Mk9) and a reusable plastic container (RPC). These containers were loaded with
‘Granny Smith’ apples (Malus x domestica Borkh. cv. Granny Smith) and arranged in an explicit
pattern as practically used in the industry (see Figure 1). FAC experiments were conducted on each
stack by forcing cold air at -0.5°C and at different airflow velocities. Measurements were taken to
obtain data to define the airflow characteristics of the stacks, the air and produce temperature
histories in the stacks, moisture loss experienced by the produce and fruit quality (in terms of
chilling injury). The energy use rates, the cooling performance and the produce quality of the three
container designs were compared.
Numerical method
Detailed numerical models of the experimental setups corresponding to the three container
designs were developed with Computational Fluid Dynamics (CFD). The models were based on
explicate accounting of the fruit and container geometries. However, due to computational
limitations some model simplifications were required. Out of the full stack of the Mk4 and RPC, only
a single layer was considered in the CFD model analysis. The resulting single carton layer model
geometries were individually arranged in such a way that the cooling air flows horizontally through
the vent holes. The airflow is modelled using the Reynolds-averaged Navier–Stokes equations
(called RANS equations) to which an energy balance equation is coupled to solve the heat transfer
in the cartons and fruit, considering also fruit respiration. The discretisation of the model geometry
and solving of the transport problem were performed with the ANSYS-CFX 14.5 software. The
resulting models provide detailed description of the airflow and heat transfer of the FAC process
corresponding to the three container designs. This helped in explaining the experimental
observations and design improved boxes.
Results and discussion
From the experimentally obtained time history data of the produce temperature, cooling
curves corresponding to the three container designs were obtained. From the cooling curve the
seven-eighths cooling time (SECT) as a function of airflow rate (AFR) was evaluated at three
different locations in the layer (see Figure 2). At the lower end of the AFR, the high SECT of the
Mk9 is apparent. Evidently, increasing the AFR not only decreased the cooling time but also
improved the uniformity of the cooling process for each box design. Indeed, an increase in AFR
from a low to medium value reduced cooling time by roughly one-third for the Mk4 and RPC layer
and even by two-thirds for the Mk9 layer whereas the cooling uniformity over the layer increased
by 23.3%, 20.5% and 31.6% for the Mk4, Mk9 and RPC layer, respectively. However, a further
increase in AFR brought no noticeable improvement on the cooling rate or cooling uniformity.
The rate of moisture loss during the precooling process was about 0.05% per 24h of cooling
for all three cases, making it a negligible effect during FAC. The RPC box was shown to be prone to
chilling injury (CI). No CI was observed in the Mk4. The highly porous nature of the RPC may make
this container more prone to CI than the Mk4 or Mk9. Hence, though the RPC is relatively best in
terms of its hydrodynamic and thermodynamic performances, the relatively high proportion of CI
may make this box the least favoured.
The fan energy consumption is related to the applied pressure drop over the container, which
is inversely related to the total open area (TOA) of the side of the container perpendicular to the
airflow. Maintaining a high AFR, therefore, requires much more fan energy. The RPC has a rather
porous container design whereas the Mk4 and Mk9 are characterised by low vent hole ratios.
Distinctly, the Mk9 has no vent holes on its short sides. Therefore, it required the highest energy to
cool one kilogram of apples (see Figure 3). Using a medium AFR value required three times the
amount of fan energy when applying a low AFR value to force cold air through the RPC stack. For
the Mk9 and Mk4 stack, a factor of seven and eight was required, resp.
The main results of the experimental analysis are summarised in Table 1. From aerodynamic
point of view, the RPC design, which is the most open container, performs best. This design is
characterized by low energy usage. However, the highest loss of quality of the produce was
observed in the RPC design. The Mk9, which is with the lowest proportion of TOA, is characterized
by high energy usage but with a corresponding quality loss much lower than that observed in the
RPC. Interestingly, there is no chilling injury in the case of MK4. Reducing the cooling airflow rate
and/or increasing slightly the cooling air temperature whilst using the RPC may create a condition
that reduces the chilling injury. Adding extra vent holes on the Mk9 design may improve its energy
usage. On the other hand, extra vent holes may mean a reduction in structural integrity. Indeed,
strength and stability of containers are important factors to be considered during container design.
Table 1: Summary of the experimental results at medium airflow rate
SECT [h]
Cooling
Uniformity [%]1
# Apples
with CI2
Moisture loss
[% per day]
Energy consumption
[kJ (kg produce)-1]
0
0.0568 ± 0.002
1.49
Mk4
8
79.0
Mk9
7
80.1
17
0.0482 ± 0.001
2.41
RPC
8
78.4
106
0.0458 ± 0.002
0.16
1
2
Ratio of the average SECT of the front row and the back row in the layer
Chilling injury (CI) only observed after the experiment with the highest airflow rate
The effect of stack orientation with respect to the direction of the cooling airflow was also
experimentally evaluated. By rotating the stacks of the Mk9 and RPC boxes by 180°, the TOA of the
side at the inlet of the cooling air increased. Consequently, a reduction of 14.7% and 8.6% in
cooling time and a decrease of 26.3% and 20.9% in fan energy were achieved. However, changing
the stack orientation increased the cooling heterogeneity by 34.8% and 2% for the Mk9 and RPC
layer, respectively.
Detailed airflow profiles through individual containers loaded with fruit were obtained from the
CFD simulations. Evidently, airflow inside the Mk4 container is highly non-uniform (see Figure 4).
For this particular container, the bottom most and the top most apple layers are at low ventilation
and thus, at low cooling rates. For the Mk9, the major airflow path is the central region while the
left and right regions receive low ventilation. Therefore, the cooling uniformity of Mk9 is quite
heterogeneous with fast cooling in the centre region primarily via convection and slow cooling on
the sides mainly via conduction. The RPC, however, is characterised by its large amount of vent
holes on all sides. Accordingly, the airflow throughout this box and thus its cooling profile is the
most uniform.
As aforementioned, the pressure drop is inversely related to the TOA of the side perpendicular
to the airflow. With the RPC having the largest TOA and the Mk4 the lowest, the pressure drop and
thus the required energy is highest for the Mk4 and lowest for the RPC. The pressure drop of the
Mk9 could not be directly compared to the other two designs since the airflow in this study was
perpendicular to its long side. In general, it can be postulated that all three containers cool more
uniform at higher AFRs but that the RPC performed best, followed by the Mk9 and the Mk4. Also,
the presence of apple-supporting trays apparently block cross-circulation of cold air between the
different apple layers leading to a very heterogeneous cooling behaviour. By adding holes on the
trays, cross-ventilation between layers can be facilitated. Consequently, a faster and more uniform
cooling can be obtained, a favourable situation that is also less energy consuming.
After carefully investigating the cooling behaviour of the individual containers, a discrete CFD
model of a palletized Mk4 and RPC layer was developed. The CFD model adequately captured the
experimental results. Inside the Mk4 layer, a highly heterogeneous airflow distribution was
observed. The presence of apple supporting trays and the arrangement of the containers, with
respect to the cooling airflow direction, significantly influenced the cooling uniformity of this
container design. The CFD model of the RPC layer, as dictated by the experiment, showed a more
uniform airflow distribution concomitant with a rather uniform cooling profile. The regions of high
and low cooling regions in both stacks were clearly identified (see Figure 5). Since the TOA of the
RPC layer is almost four-fold higher than the Mk4, a much lower pressure gradient was required by
the RPC at the same AFR. However, the experiments showed that cooling with the RPC had the
highest susceptibility to chilling injury. Hence, further analysis of this box is recommended before
taking advantage of the more uniform cooling rate and the lower pressure drop characteristics.
Adjusting the cooling air temperature and flow rate to some appropriate value may be needed to
guaranty an acceptable degree of chilling injury.
Conclusions
The precooling characteristics of three container designs were examined experimentally and
numerically. The CFD models agree well with the measured values and provide a detailed
description on the airflow and temperature distributions, which would be hard to achieve
experimentally alone. Both the experimental and numerical studies show noticeable differences
between the three designs. It is evident that design of trays (used to support fruit inside a
container), pattern of fruit arrangement on tray and arrangement of the loaded containers in the
FAC system affect the cooling performance. These and similar aspects of the precooling process can
be further investigated with the help of the CFD model. The CFD models developed in this study will
help the search of an optimum package design for fresh produce and eventually, lead to the
optimisation of the cold chain and the reduction of postharvest losses.
Explanation words
Shelf life: the length of time for which a product remains usable, fit for consumption or saleable
Telescopic box: telescopic implies that the top part of the box slides over the bottom part
Computational Fluid Dynamics (CFD): A mathematical tool that can efficiently be used to simulate
the spatial and temporal distribution of fluid and calculate pressure, temperature, velocity and
other scalar quantities within for example containers but even commercial cold stores.
Seven-eighths cooling time (SECT): this parameter indicates the time required to cool the produce
down to a temperature that is seven-eighths of the initial produce-coolant temperature difference.
The SECT is of particular interest in commercial cooling operations because it depicts the moment
in time when the temperature of the produce lies reasonably close to the required storage
temperature. Once the SECT is reached, the produce can be placed inside conventional storage
facilities where the remaining heat can be removed with less energy costs.
Fan energy consumption: This value is obtained by multiplying the required fan power (Pw) with
the time needed to maintain this airflow (i.e. the SECT). An estimation of the power Pw [W]
required to force cold air through a stack of packaging during FAC can be calculated as the product
of the pressure drop ΔP [Pa] over the stack and the flow rate (Qair [m3⋅s-1]).
Figures
Figure 1: The photo of the empty fruit-boxes and their corresponding stacking pattern in the cold
store. The external dimensions are in millimetres.
Figure 2: Average seven-eighths cooling time (h) for the three different containers at three
different depths in the layer
Figure 3: Energy requirement to maintain a certain flow rate through the stack of containers
Figure 4: Horizontal velocity distribution around apples positioned on a tray inside an Mk4
container at three different superficial air velocities indicating that the airflow distribution is highly
non-uniform.
Figure 5: Spatiotemporal temperature profile of apples placed in one Mk4 layer and in apple placed
in Tray2 of the middle layer of an RPC layer at three different superficial air velocities (m⋅s-1)