Trends in Food Science & Technology 100 (2020) 278–291

Contents lists available at ScienceDirect

Trends in Food Science & Technology

journal homepage: www.elsevier.com/locate/tifs

Postharvest precooling of fruit and vegetables: A review T

a b c d b
Yuan Duan , Guan-Bang Wang , Olaniyi Amos Fawole , Pieter Verboven , Xin-Rong Zhang ,
Di Wua,∗, Umezuruike Linus Oparae, Bart Nicolaid, Kunsong Chena
a
College of Agriculture & Biotechnology / Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/The State Agriculture Ministry Laboratory of
Horticultural Plant Growth, Development and Quality Improvement, Zhejiang University, Zijingang Campus, Hangzhou, 310058, PR China
b
Department of Energy and Resources Engineering, College of Engineering, Peking University, Beijing, 100871, PR China
c
Department of Botany and Plant Biotechnology, University of Johannesburg, P.O. Box 524, Auckland Park, 2006, Johannesburg, South Africa
d
Flanders Centre of Postharvest Technology / BIOSYST-MeBioS, KU Leuven – University of Leuven, Willem de Croylaan 42, 3001, Leuven, Belgium
e
South African Research Chair in Postharvest Technology, Department of Horticultural Science, Stellenbosch University, Stellenbosch, 7602, South Africa

A R T I C LE I N FO A B S T R A C T

Keywords: Background: Precooling is a critical step in the postharvest cold chain. Studies of the precooling of fruit and
Precooling vegetables are based on the strong interactions between modelling, engineering, physiology and commercial
Fruit and vegetables outcomes. In recent years, new progress in precooling has been achieved. These achievements include different
Precooling technique cooling strategies, research into precooling mechanisms, and numerical simulations. This review aims to provide
Numerical simulation
the most recent information about precooling and promote its application in the fruit and vegetable industry.
Quality
Scope and approach: Different precooling strategies are evaluated with respect to the cooling rate, cooling
uniformity, and multiscale simulation. An overview of mathematical modeling approaches used to quantitatively
describe precooling processes for computer-aided designs is provided. The effect of precooling on fruit quality at
the physiological and molecular levels is outlined.
Key findings and conclusions: Numerical simulations have become widely used to improve the precooling per-
formance. Cooling homogeneity, in particular, has attracted increasing attention in recent studies because of the
substantial effects of cooling homogeneity on the precooling efficiency and produce quality. The spatial scale of
numerical simulations of the precooling process has started to become more precise and specific. Recent nu-
merical simulations have focused on the bin and package scale. Models of transport processes at multiple spatial
scales are investigated using multiscale modeling. Moreover, the effect of precooling on produce quality has
recently received increasing attention. In addition, the investigation of the effect of precooling on fruit at the
metabolomic and genomic levels has become an emerging trend and has provided deeper insights into the
molecular mechanisms underlying the effect of precooling treatments on fruit.

1. Introduction physiological and biochemical processes in fruit and vegetables during

postharvest life, and low-temperature storage is one of the most effec-
Fruit and vegetables provide people with a variety of essential vi- tive physical and green preservation methods (Mercier, Villeneuve,
tamins, antioxidants, and dietary fiber, which are beneficial for many Mondor, & Uysal, 2017). Most fruit and some vegetables are harvested
aspects of health (Prasanna, Prabha, & Tharanathan, 2007). Postharvest at relatively high temperatures and normally contain large amounts of
losses and waste in the supply chain of fruit and vegetables are as high field heat, which accelerate metabolic processes and increase the
as 13–38% before the produce even reaches the consumer (Gustafsson, growth of microorganisms (Ambaw, Mukama, & Opara, 2017; Zhu,
Cederberg, Sonesson, & Emanuelsson, 2013). The fruit and vegetable Geng, & Sun, 2019a). Furthermore, the high field heat predisposes
production industry is faced with the challenge of minimizing post- harvested fruit and vegetables to moisture loss due to continuing phy-
harvest losses (Wang, Matetić, Zhou, Zhang, & Jemrić, 2017b). Hence, siological processes (Lufu, Ambaw, & Opara, 2019; Valero,
research efforts are needed to prolong the shelf-life of fruit and vege- Mirdehghan, Sayyari, & Serrano, 2015), resulting in an accelerated loss
tables and subsequently reduce postharvest losses. of quality. The moisture loss results from transpiration and depends on
Temperature is one of the most important factors modulating the vapor pressure deficit (VPD) (Wills & Golding, 2016). The VPD

∗
Corresponding author.
E-mail address: di_wu@zju.edu.cn (D. Wu).

https://doi.org/10.1016/j.tifs.2020.04.027
Received 3 August 2019; Received in revised form 12 March 2020; Accepted 18 April 2020
Available online 24 April 2020
0924-2244/ © 2020 Elsevier Ltd. All rights reserved.
Y. Duan, et al. Trends in Food Science & Technology 100 (2020) 278–291

combines the effects of both relative humidity and temperature and is

(2018); Ozturk and Ozturk (2009)

He et al. (2013); He et al. (2013);
(2019b); Zainal et al. (2019a); de
Oliveira Alves Sena et al. (2019)

Zhu et al. (2018); Santana et al.

the difference between the saturation vapor pressure and actual air

Liang et al. (2013); Zainal et al.

Ambaw et al. (2017); Defraeye
Han et al. (2017a); Han et al.
(2018); Ambaw et al. (2017);
vapor pressure (Fanourakis et al., 2013). These changes may decrease
the quality and result in a limited storage and shelf-life of the produce,
adversely affecting the cross-regional and cross-border long-distance
sales of fresh produce and the economic performance of produce in the
entire cold chain (Zhao, Han, Yang, Qian, & Fan, 2016). Therefore, the

et al. (2014)
field heat must be removed from the produce after harvest.

References
Precooling aims to remove field heat from fresh horticultural pro-
duce and cool the fruit and vegetables to the optimal temperature after
harvest and before transportation to a cold storage warehouse or

temperature and air velocity to improve

● Improve energy efficiency by improving

● Improve the stack pattern and package

market (Hardenburg, Watada, & Wang, 1986). The primary purpose of

● Improve stack patterns to increase the

cooling while avoiding cold damage

designs to obtain rapid and uniform
● Explore the best combination of air

● Explore approaches to reduce cross

precooling is to slow the physiological and biochemical activities of

● Novel methods for the sustainable

cleaning and disinfection of water
fruit and vegetables and prepare for the following storage period or

● Explore approaches to expand

the design and configuration
shelf-life time by removing field heat (Kader, 2002). Furthermore,
precooling can prevent fruit and vegetables from developing physio-

applications in fruits
logical disorders, delay aging or ripening, reduce postharvest decay,
and maintain fruit quality (Kader, 2002). As the first step of tempera-

Future developments

energy efficiency
ture management for postharvest fruit and vegetables, precooling is the

cooling rate
first and most crucial line of defense in slowing biological processes to

infection
maintain the quality of fruit and vegetables (Hardenburg et al., 1986).
From a technical perspective, the removal of field heat from fruit and
vegetables by precooling helps diminish the required refrigeration ca-
pacity of the cold storage room (Albayati, Kumar, & Chauhan, 2007).

● Easily leads to microbial

Otherwise, temperature fluctuations in the cold store will occur if fruit

● Water must be cleaned

loss during application

tolerate becoming wet

● Considerable moisture
● Fruits must be able to
● Slower than vacuum
and vegetables are placed in the cold store without precooling, thus

● Costly equipment
affecting the storage of the original fruit and vegetables in the cold store

● Uneven cooling

and disinfected
contamination
(Ambaw et al., 2017).

● Not uniform
Disadvantages

● Very slow
Commonly used precooling techniques include forced air cooling,

cooling
hydrocooling, liquid ice cooling, and vacuum cooling (Hardenburg
et al., 1986). These techniques differ from a technical perspective, al-
though they all involve the fast transfer of heat from produce to a
cooling medium, such as air and water (Hardenburg et al., 1986; Wang

● Least expensive precooling method

prevent storage disorders in fruits
● Low installation and maintenance

& Sun, 2003). Based on parameters such as the characteristics of the ● High efficiency and faster than

refrigerated CaCl2 solution to

commodity and the container, rate of cooling, and further storage and

● Able to be performed with a

● Rapid and uniform cooling
Suitable fruit species, evaluation and future research challenges of different precooling technologies.

shipping conditions, the most appropriate technique depends on the

● Fast and uniform cooling

● High energy efficiency
specific circumstances (Alibas & Koksal, 2014). Many lines of research
are addressing precooling for the postharvest temperature management
● Clean and simple

● No moisture loss
of fruit and vegetables. Although the review by Brosnan and Sun (2001)
room cooling

provided detailed information about the techniques and applications of

● Hygienic
Advantages

precooling, new progress in precooling has since been achieved, in-

● Simple

costs

cluding advances in different cooling strategies, research into pre-

cooling mechanisms, and numerical simulations to improve precooling
efficiency. Consequently, this review aims to describe the state-of-the-
guava, kiwi, pineapple, grape, peach, nectarine, tomato,

art of precooling of fruit and vegetables, with greater attention to re-

search conducted since 2001. Although all the precooling technologies
Apple, cherry, litchi, pear, avocado, orange, melon
apricot, pomegranate, banana, papaya, carambola,

Leafy vegetables, mushroom, blackcurrant, melon,

Citrus, cantaloupe, apple, pear, strawberry, plum,

are equally applicable to fruit and vegetables, the literature mainly

focuses on fruit precooling. However, when appropriate, the discussion
will be extended to vegetables.

2. Precooling techniques and strategies

2.1. Precooling techniques

blueberry, blackberry
Suitable fruit species

2.1.1. Room cooling and forced air cooling

strawberry; cherry

Room cooling is achieved by placing the bulk or containerized

commodity in a refrigerated room for several hours or days, and the
Most fruits

cooling room provides temporary storage for produce after precooling

(Prusky, 2011). Although room cooling is suitable for most fruit and
vegetables, room cooling is a slower process than other cooling systems
(Ambaw et al., 2017) (Table 1). A significant improvement in the
Forced air cooling

Vacuum cooling

cooling efficiency is achieved by establishing higher airflow rates

Room cooling

Hydrocooling

through the produce, thus increasing the local surface heat transfer
techniques
Precooling

coefficient (Ambaw et al., 2017). This principle led to the development

Table 1

of forced air or pressure cooling, which is a rapid air-cooling substitute

for room cooling (Ambaw et al., 2017). Forced air cooling is a technique

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Y. Duan, et al. Trends in Food Science & Technology 100 (2020) 278–291

Fig. 1. Schematics of a tunnel-type forced air cooler (a), a serpentine forced air cooler (b) and a cold-wall forced air cooler (c).

of cooling packed produce by forcing cold air to quickly flow through and vegetables that are subjected to hydrocooling must be tolerant of
containers, and it is the most widely used commercial cooling technique water and not sensitive to the sanitizing chemicals that are added to the
for bulk produce and palletized produce (Dehghannya, Ngadi, & cold water (Prusky, 2011), such as apple, litchi and cherry (Table 1).
Vigneault, 2010; Thompson, Mitchell, & Rumsay, 2008) (Table 1).
Three major types of forced air cooling arrangements for fruit pre- 2.1.3. Vacuum cooling
cooling have been described (Gopala Rao, 2015a). These arrangements The principle of vacuum cooling is based on a rapid decrease in the
include the circulation of air at a high velocity in refrigerated rooms, temperature of the produce through the evaporation of moisture from
forcing cold air through bulk or stacked produce as they continuously the produce surface and within the produce (Zhu et al., 2019a). A va-
move through a cooling tunnel on a conveyor, and forcing air through cuum cooling system generally consists of a vacuum chamber, a va-
produce packed in containers using the pressure differential technique. cuum pump, and a vapor condenser (Fig. 3). Several requirements have
The third arrangement is most commonly used and is typically achieved been established for produce to be suitable for vacuum cooling (Sun &
using three types of airflow systems, namely, tunnel-type cooling, Zheng, 2006). First, free water is needed in the produce to be vacuum
forced air serpentine cooling, and cold wall forced air cooling (Fig. 1) cooled. Second, the produce should have a porous structure to ensure
(Gopala Rao, 2015a). that the vapor generated through evaporation will diffuse into the
The air velocity and air temperature are critical factors for forced air surrounding environments. Third, the amount of moisture loss during
cooling (Cortbaoui et al., 2006; Lrde, Vigneault, & Lab, 2005). A greater vacuum cooling should not cause significant deterioration that affects
air flow rate requires a higher static pressure, which not only leads to an the quality of the produce (Sun & Zheng, 2006; Wang & Sun, 2001;
increase in total energy consumption but also may result in the Zheng & Sun, 2004). Water is sometimes sprayed on the produce before
shrinkage, wilting, and chilling injury (CI) of fruit (Cortbaoui et al., it is placed in the vacuum chamber to reduce moisture loss (Zhu et al.,
2006; Lrde et al., 2005). Excessive air flow and excessively low air 2019a).
temperatures should be avoided to minimize water loss from the pro- Vacuum cooling is efficient for mushrooms (Zhang, Pu, & Sun,
duce and the possibility of CI during cooling (Delele et al., 2013). 2018) and leafy vegetables such as lettuce (Kongwong, Boonyakiat, &
Poonlarp, 2019; Ozturk & Ozturk, 2009), spinach (Garrido, Tudela, &
2.1.2. Hydrocooling Gil, 2015), broccoli (Santana et al., 2018) and cabbage (Zhu et al.,
Hydrocooling is an older and effective cooling technique because of 2018). Due to the large surface to mass ratio, leafy vegetables are
the high heat transfer coefficient of water; this process involves usually able to be cooled within 30 min, which is beneficial to minimize
spraying cold water on fruit and vegetables with a shower system postharvest quality losses (Zhu et al., 2019a). According to Kongwong
(Fig. 2a) or by immersing fruit and vegetables directly in an agitated et al. (2019), vacuum cooling achieved a longer shelf-life of baby cos
bath of cold water or ice water mixture (Fig. 2b) (Becker & Fricke, lettuce than room cooling and forced air cooling. A potential explana-
2002; Liang, Wongmetha, Wu, & Ke, 2013). Shower coolers usually cool tion is that the integrity of cells and chloroplasts of vacuum-cooled
fruit and vegetables more rapidly than immersion coolers because of samples was maintained, resulting in delayed cell senescence in baby
the higher water flow rate and subsequently increased surface heat cos lettuce (Kongwong et al., 2019). Root vegetables and most fruit are
transfer coefficient (Gopala Rao, 2015b). Moreover, hydrocooling is not usually not suitable for vacuum cooling due to the presence of a dense
suitable for all types of fruit and vegetables, as some fruit and vege- peel, which reduces transpiration (Zhu et al., 2019a). However, some
tables are easily damaged during or after being soaked in water, such as positive effects on maintaining the good quality of certain fruit, such as
strawberries (Emond, Mercier, Sadfa, Bourre, & Gakwaya, 1996). Fruit cherry and mulberry, have been observed during storage (Han, Gao,

280
Y. Duan, et al. Trends in Food Science & Technology 100 (2020) 278–291

Fig. 2. Schematics of a shower cooler (a) and an immersion cooler (b).

Chen, Fang, & Wu, 2017b; He, Zhang, Yu, Li, & Yang, 2013). 2009; Lurie & Crisosto, 2005; Nunes, Brecht, Morais, & Sargent, 1995).
Delayed cooling generally reduces quality and the storage life of fruit
2.2. Precooling strategies and vegetables, such as plums (Guerra & Casquero, 2009), and straw-
berries (Hiroaki, Tatsuo, Nobutaka, & Satoru, 2013; Nunes et al., 1995).
2.2.1. Prompt precooling Nevertheless, a certain extent of cooling delay may be beneficial to
Prompt precooling is a conventional practice used to rapidly cool maintain the quality of some fruit and vegetables, such as cherry
fruit and vegetables immediately after harvest (Thompson et al., 2008). (Bernalte, Sabio, Hernández, & Gervasini, 2003), peach, nectarine
Commercially important fruit and vegetables that must be precooled (Lurie & Crisosto, 2005) and apple (Luo et al., 2018).
promptly include asparagus, cauliflower, broccoli, carrots, snap beans,
snow peas, sweet corn, summer squash, globe artichokes, radishes, 2.2.3. Gradual cooling
brussel sprouts, leafy vegetables, avocados, nectarines, apricots, plums, Gradual cooling is a strategy accomplished by lowering the tem-
cherries, and tropical and subtropical fruit, such as papayas, guavas, perature of fruit and vegetables only a certain number of degrees over
pineapples, and mangos (ASHRAE, 2014). Some varieties of fruit and an interval of hours or days (Woolf, Cox, White, & Ferguson, 2003;
vegetables, such as pumpkins, sweet potatoes, white potatoes, winter Yang et al., 2012; Zhang et al., 2017). Gradual cooling, including low
squash, citrus, apple, and pears have long postharvest lives, but prompt temperature conditioning (LTC), induces the cold tolerance of chilling-
cooling is still essential for them to maintain a high quality during the sensitive fruit and vegetables, such as mango (Zhang et al., 2017),
holding period (ASHRAE, 2014). avocado (Woolf et al., 2003), grape (Chaudhary, Jayaprakasha, Porat, &
Patil, 2014), loquat (Jin et al., 2015), and kiwifruit (Yang et al., 2012).
2.2.2. Delayed cooling In addition, the duration and temperatures for effective gradual cooling
Delayed cooling is a treatment that results in a lag between the may vary depending on the species, maturity, or ripening stage of the
harvest and precooling of fruit and vegetables (Guerra & Casquero, fruit and vegetables, as well as the storage conditions (Zhang et al.,

Fig. 3. Layout of the vacuum cooling system (Sun & Zheng, 2006).

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Y. Duan, et al. Trends in Food Science & Technology 100 (2020) 278–291

2017). 2019b). In addition, the evaporative heat transfer is typically only

significant for vacuum cooling due to the much lower pressure (Brosnan
3. Evaluation of precooling & Sun, 2001). Therefore, this ratio is meaningless for conventional
cooling processes performed under atmospheric pressure with insig-
3.1. Factors influencing the precooling process nificant evaporative heat transfer, such as room cooling and forced air
cooling.
Many factors affect the precooling process of fruit and vegetables,
among which the characteristics of fruit and vegetables (e.g., shape, 3.2.2. Uniformity of precooling
size, surface to volume ratio, porosity, internal structure, density, Numerical and experimental studies have been conducted to eval-
thermal properties, and respiratory heat generation rate) are the most uate the uniformity of precooling by comparing the temperature history
important (Pathare, Opara, Vigneault, Delele, & Al-Said, 2012). The and cooling time of fruit and air velocity at different locations inside the
temperature and velocity of the cooling medium and relative humidity fruit stack (Ambaw et al., 2017; Wu & Defraeye, 2018; Wu, Häller,
of the ambient environment are other main factors that potentially Cronjé, & Defraeye, 2018).
influence the effectiveness of precooling (Pathare et al., 2012). Flow heterogeneity is the main cause of heterogeneous cooling
performance, particularly when air is used as the cooling medium
3.2. Metrics for evaluating the effect of precooling (Alvarez & Flick, 1999). The local mean age of air (MAA), which de-
scribes the mean time required to transport air from the inlet to an
3.2.1. Cooling rate arbitrary point (Desta et al., 2005), may be used to quantify the effec-
The cooling rate is a crucial parameter determining the duration of tiveness of ventilation (Simons & Waters, 2002). Typically, the local
the operation and directly affects the postharvest life of fruit and ve- MAA is calculated with either the step-up injection method using
getables (Defraeye et al., 2015; Lrde et al., 2005). The total produce Equation (1) (Sandberg & Sjöberg, 1983),
throughput and operational costs are related to the cooling rate
(Defraeye et al., 2015). Different precooling techniques have different τi = ∫0
∞
⎛1 − Ci (t ) ⎞ dt
⎜ ⎟

cooling rates. With room cooling, fruit placed in cold storage cool ⎝ Ci (∞) ⎠ (1)
slowly, and the cooling time will be even longer if fruit and vegetables
or using Equation (2) (Rouaud & Havet, 2005),
are packed with materials such as paper wraps or bags that restrict
airflow (Ambaw et al., 2017). The cooling time for forced air cooling is 1 ∞

usually 75–90% shorter than for conventional room cooling because

τi =
Ci (t0)
∫t
0
Ci (t )dt
(2)
cold air is pulled through individual produce containers by a fan rather
where τi is the local MAA (s), Ci is the location concentration of the
than flowing around the container unit during room cooling (Cortbaoui
tracer gas at position i and t is time (s). Furthermore, computational
et al., 2006). As shown in the studies by Han et al. (2017a) and Han,
fluid dynamics (CFD) simulations combined with an additional con-
Zhao, Qian, Ruiz-Garcia, and Zhang (2018), the cooling rate of apple is
vection-diffusion equation have also been employed to calculate the
increased considerably by increasing the airflow velocity. Any further
local MAA and to visualize airflow heterogeneity in forced-ventilation
increase in the airflow velocity was considered a waste of energy be-
food plants (Chanteloup & Mirade, 2009).
cause it did not lead to an obvious increase in the cooling rate and heat
The difference in temperature between individual fruit at different
transfer fluxes across the surface of the fruit (Han et al., 2017a, 2018).
positions is described by the relative standard deviation (Han, Zhao,
Water is a better heat transfer medium than air, particularly when the
Yang, Qian, & Fan, 2015):
water is refrigerated (Thompson et al., 2008). Cooling fruit and vege-
tables through hydrocooling with a specific volume of water removes 1 1
m

field heat at a higher rate than forced air cooling with the same volume HI =
T‾ m−1
∑ (Tn − T‾)2
of air at the same temperature (Thompson et al., 2008). Consequently, n=1 (3)
fruit and vegetables are cooled through hydrocooling in a reasonably where Tn is the temperature at a specific location,‾T is the average
short time. According to Silva, Goyette, Bourgeois, and Vigneault temperature, and m is the number of positions. Recently, Olatunji, Love,
(2006), the hydrocooling of apple results in cooling that is twice as fast Shim, Ferrua, and East (2017) described the shortcomings of the het-
as forced air cooling under comparable conditions. Fruit with small erogeneity index (HI) described above, namely, HI is only applicable at
diameters, such as cherries, can be hydrocooled within 15 min in well- single time points and becomes mathematically unstable as it ap-
designed shower coolers (Manganaris, Ilias, Vasilakakis, & Mignani, proaches infinity or becomes negative when refrigeration temperatures
2007). Nevertheless, the cooling rate with air is theoretically compar- are near zero or below zero. Then, these authors further proposed a new
able to hydrocooling when the produce is subjected to specific condi- metric called the overall heterogeneity index (OHI):
tions, such as a very high volume airflow rate, but the high cost may not
1 TSTART
be justified (ASHRAE, 2014) and fruit will suffer from substantial
moisture loss. Therefore, the airflow rate should not increase without
OHI = ∫ ∫ ΔY dTdF (ΔY )
0 TEND (4)
limits to pursuit the same cooling rate as hydrocooling under practical
conditions. Furthermore, vacuum cooling is much faster than conven- where Y is the cooling ratio at a specific location, |ΔY| is the absolute
tional cooling under the same conditions due to the small ratio of difference between the cooling ratio at a specific location and the
conductive heat transfer through the laminar boundary layer to eva- average cooling ratio, F(ΔY) is the cumulative distribution function
porative heat transfer, which is less than 1:16 (Sun & Zheng, 2006). and T is the process progression index. Compared with the standard
This ratio is used to evaluate the relative magnitude of different heat deviation, this new metric enables a cumulative heterogeneity evalua-
transfer mechanisms during vacuum cooling (Sun & Zheng, 2006). As tion throughout the process and is more suitable for a refrigeration
the evaporative heat transfer coefficient is much higher than the con- temperature of approximately zero (Olatunji et al., 2017). Additionally,
vective heat transfer coefficient, a greater amount of evaporative heat the cooling ratio can be substituted with the fractional unaccomplished
transfer results in faster cooling (Rao, 2015). However, the ratio should quantity change, and then the heterogeneities in terms of the partial
not be as low as possible. A very small ratio will lead to a large amount pressure of water vapor and enthalpy are further obtained (Olatunji
of moisture loss of the produce (Zhu et al., 2019a). Consequently, a et al., 2017).
trade-off exists between conductive heat transfer through the laminar Flow field uniformity is an important factor affecting the effec-
boundary layer and evaporative heat transfer (Zhu, Li, Sun, & Wang, tiveness and energy consumption of forced air cooling (Lrde et al.,

282
Y. Duan, et al. Trends in Food Science & Technology 100 (2020) 278–291

2005). In studies of the forced air cooling of horticultural produce Goswami, 2007). Tanaka, Konishi, Kuroki, Hamanaka, and Uchino
(Alvarez, Bournet, & Flick, 2003; Alvarez & Flick, 1999), the tem- (2012) numerically studied the cooling performance of a partially
perature of fruit and vegetables contained in bins or bulk stacked on loaded cold room with different loading patterns of produce containers.
pallets was far from homogeneous during the cooling process. Mercier, The best temperature uniformity and fastest cooling rate were obtained
Brecht, and Uysal (2019) investigated the temperature distribution of for flat loading with air gaps. In all these investigations, a porous
strawberries in pallets during commercial forced air cooling and ob- medium approach was followed, in which the stack of fruit was mod-
served temperature variations of up to 7 °C at the end of precooling. eled as a porous material with apparent transport properties that must
Fruit and vegetables located behind blind walls were not sufficiently be obtained experimentally, e.g., through wind tunnel studies. Hoang
cooled, while other fruit and vegetables exposed to higher velocities et al. (2015) conducted a numerical study on airflow and heat transfer
were already frosted, thus generating freezing, chilling, or drying da- for the room cooling of apples in boxes stacked on pallets. The apple
mage (Pathare et al., 2012). Undercooling or overcooling spots within pallets were either modeled with a porous medium approach or as
the package consequently caused losses in the quality of fruit and ve- stacks of boxes in which the apple shape was considered. Several tur-
getables during the storage period (O'Sullivan et al., 2017). During bulence models, including standard k-ε, Renormalization Group (RNG)
forced air precooling, the occurrence of heat transfer heterogeneity is k-ε, realizable k-ε, and Shear Stress Transport (SST) k-ω models, were
probably attributed to the flow heterogeneity, which is directly related investigated (Hoang et al., 2015). Based on validation studies, the solid-
to frictional loss as the air flows through containers and packages and block approach was able to better predict the evolution of the produce
passes by fruit during the precooling process (Wu & Defraeye, 2018). temperature, while acceptable results were also obtained using the
However, hydrocooling still offers a more homogeneous and faster porous-medium approach with a smaller mesh density (Hoang et al.,
cooling process than precooling by air, both for individual produce and 2015). The SST k-ω turbulence model provided the best results (Hoang
the whole batch of produce, because of the high thermal conductivity, et al., 2015).
volumetric heat capacity and heat transfer coefficient of water and the As forced air cooling is commonly used for postharvest fruit cooling
more uniform contact between cold water and the produce, particularly because of the efficient ventilation with less bypass airflow, recent CFD
when fruit and vegetables are packed in containers (Elansari, 2008; simulations have focused on the bin and package scale (Defraeye et al.,
Liang et al., 2013). Likewise, for vacuum cooling, Sun and Zheng 2015). A package design based on the numerical modeling of flow and
(2006) indicated that the temperature of produce was reduced at the heat transfer has been investigated for vented boxes with models in
same rate, regardless of whether the fruit and vegetables were on the which the fruit was explicitly modeled (Defraeye et al., 2014). The
top, at the bottom or in the center of a pile, because a reduction in the authors revealed the feasibility of using CFD to design packages with an
produce temperature is achieved through water evaporation both inside improved cooling rate and uniformity and reduced energy consumption
and outside the produce, resulting in a relatively uniform temperature (Defraeye et al., 2014). Han et al. (2015) modeled a box filled with
distribution (Sun & Zheng, 2006). spheres representing fruit for package design purposes, and they con-
siderably improved cooling performance by optimizing the package
3.3. Evaluation using computational fluid dynamics design. More recently, numerical studies on this scale combined models
of the package and pallet. Ferrua and Singh (2011) proposed a new
Numerical simulations have been used to visualize the distribution packaging system for the forced air cooling of strawberries based on the
of important variables of the cooling process, such as temperature, air improved airflow pattern suggested by numerical results. This new
velocity, and relative humidity, which supplements the limited ex- design examined pallets, trays, and clamshells for more uniform and
perimental data (Ambaw et al., 2013). Complex mechanisms of energy energy-efficient cooling. O'Sullivan et al. (2017) used a 3D CFD model
and mass transport are involved in the precooling process and are de- of palletized polylined kiwifruit packages to obtain the optimal oper-
scribed by conservation laws of mass, momentum, and energy (Zhao ating conditions for forced air cooling. Based on the evaluation of the
et al., 2016). The corresponding transport equations are numerically cooling rate, uniformity, energy consumption and productivity, an op-
solved using CFD. This procedure is complicated because of the pre- timal operating condition with 100 Pa (0.25 L kg−1 s−1) and alter-
sence of different spatial scales, including the room, pallet, package, native package design were determined. The airflow and heat transfer
individual produce, tissue, and even the cell (Ho et al., 2013), and within a refrigerated shipping container filled with apple pallets were
because the high air velocities at the exit of a typical fan-evaporator investigated to study the evolution of the temperature field inside the
assembly induce turbulence in the flow. shipping container by considering the packaging design and related
Room-scale models are necessary to understand the airflow and heat flow resistance (Getahun, Ambaw, Delele, Meyer, & Opara, 2017a,b).
exchange between air and produce inside the cold room, particularly The absence of vent holes on the bottom face of the packaging box
when a bypass airflow exists for room cooling (Hoang, Duret, Flick, & caused non-uniform airflow and a highly heterogeneous cooling
Laguerre, 2015). During precooling, the amount of field heat that must (Getahun et al., 2017a,b). Wu and Defraeye (2018) computed the
be removed is much larger than the respiratory heat generated, and temperature-time history of a pallet with 80 cartons containing 5120
thus the latter is typically neglected in CFD studies (Wu & Defraeye, individual fruit using an explicit CFD model incorporating discrete
2018). Nahor, Hoang, Verboven, Baelmans, and Nicolaï (2005) devel- spheres representing the fruit and predicted the evolution of fruit
oped a transient 3D numerical model to study the distribution of the quality using kinetic rate law models. Based on the simulations, the
flow, temperature and moisture fields in both an empty room and a blockage of vent holes considerably increased the thermal hetero-
room filled with pears. Despite an error of approximately 20% for the geneity (Wu & Defraeye, 2018). Gruyters et al. (2019) studied the
velocity prediction, this model provided acceptable results for the cooling performance of two types of packing boxes by evaluating the
cooling rate and weight loss, which were helpful for the practical design temperature uniformity, cooling rate, energy consumption and fruit
of cold rooms. Using a similar CFD model, Chourasia and Goswami quality. Trade-offs between energy consumption and cooling rates were
(2007) studied the effects of operation and produce parameters, such as captured using a computational analysis. In addition, experiments were
heat generation by respiration, bulk porosity, produce size and relative conducted under similar conditions, and the CFD simulations were
humidity, on heat and mass transfer within stacked bags of potato. All consistent with the experimental cooling characteristics and success-
parameters affected the produce temperature and moisture loss, and, fully the verified computations.
hence, the cooling time. The average difference in temperature between Research at the scale of the individual fruit has also been conducted
the experimental and simulated data was 1.2 °C. Large variations in to study heat and mass transfer at the fruit surface or inside the fruit. A
moisture loss were observed if the characteristics of the produce and single apple fruit placed in a wind tunnel with a sphere as a reference
storage conditions varied from the prescribed conditions (Chourasia & was numerically studied with CFD using an SST k-ω turbulence model

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(Defraeye, Herremans, Verboven, Carmeliet, & Nicolai, 2012). The loss during room or forced air cooling depends on both the VPD, the air
authors found that sources of moisture loss, such as stomata or lenticels, velocity and uniformity, and the transpiration properties of the fruit
discretely distributed on the surface resulted in convective transfer that (Veraverbeke, Verboven, Van Oostveldt, & Nicolaï, 2003). The air ve-
depended on the coverage ratio, the Reynolds number, and the source locity also affects moisture loss, as the surface moisture transfer coef-
size. Furthermore, simulations of this convective transfer with different ficient is related to the surface heat transfer coefficient, according to the
boundary layer and turbulence models were compared (Defraeye, Lewis analogy (Holman & Holman, 1976). Thus, an increase in the air
Verboven, & Nicolai, 2013). The most accurate results were obtained velocity to facilitate heat transfer inherently increases moisture loss,
with the SST k-ω turbulence model in combination with low-Reynolds again stressing the importance of humidifying the air (Siddiqui & Ali,
number modeling of the boundary layer at the expense of a higher 2017). The transpiration coefficient mainly depends on skin properties,
computational load. Han et al. (2017a) used CFD simulations to study such as the thickness of the cuticle and epicuticular wax layer, cracks in
the airflow and heat transfer of a single apple subjected to forced air the latter, and the presence of stomata and lenticels (Veraverbeke et al.,
cooling in a wind tunnel. Different air inflow velocities were tested, and 2003). Fruit such as citrus with a thick rind are less susceptible to water
an optimal airflow velocity of 2.5 m/s was proposed after a con- loss (Hardenburg et al., 1986). Vacuum cooling may also cause
sideration of the trade-off between the increase in cooling rate and moisture loss: a temperature reduction from 25 °C to 1 °C typically
energy requirements. causes a weight loss of 4% (Sun & Zheng, 2006). Moisture loss has been
A novel approach for modeling transport processes during pre- reduced by prewetting the produce prior to forced air cooling or va-
cooling at multiple spatial scales is multiscale modeling (Ho et al., cuum cooling (Zhu et al., 2019a). Packing the produce in bags or
2013; Zhang, 2017). Multiscale modeling is used to obtain models that wrapping it in plastic may also reduce moisture loss at the expense of
are essentially submodels with a hierarchical structure. Multiscale longer cooling times (Hardenburg et al., 1986). Fruit that are hydro-
modeling interconnects submodels by describing the behavior of ma- cooled do not suffer from moisture loss (Kader, 2002). According to
terials at different spatial scales (Ho et al., 2013). The advantage of this Liang et al. (2013), after 30 min of hydrocooling and 1 h of drying, the
approach is that it incorporates the effects of, for example, shapes of the weight of litchi fruit was greater than the initial weight and the weight
produce on the macroscopic heat and mass transfer at the scale of the of the control group (without hydrocooling).
entire cool store without explicitly modeling them, thus considerably Firmness constitutes a fundamental attribute of the sensory quality
reducing the required computational resources (Ho et al., 2013). Delele and exerts a significant effect on fruit handling, conditioning, and
et al. (2008) created a random stack of spheres representing apples transportation (Alique, Martínez, & Alonso, 2006). The activity of en-
using a discrete element method and calculated the apparent properties zymes related to a loss of firmness, including polygalacturonases, β-
of the stack using a CFD model to obtain a pressure-flow rate char- galactosidases, pectin methyl esterases, pectin lyases, and others, are
acteristic. These properties were then used in a porous medium model highly temperature-dependent, and removal of the field heat through
of an entire cool room. Gruyters et al. (2018) extended this approach precooling is therefore essential, particularly for highly perishable
and created variable 3D apple and pear models using a geometric model produce, such as cherries and strawberries (Wills, McGlasson, Graham,
generator based on X-ray computed tomography images. The fruit was & Joyce, 1998). The turgor pressure is related to the water status of the
randomly stacked into a geometrical model of a corrugated fiberboard cells and is highly sensitive even to small moisture losses (Nobel, 2005).
box using the discrete element method. A forced air cooling process was For this reason, small fruit with a large surface-to-volume ratio should
simulated for three different apple filling patterns using CFD, and the preferably be precooled using methods that minimize moisture loss,
results showed substantial differences in flow behavior when re- such as hydrocooling. As shown in the study by de Oliveira Alves Sena
presenting fruit such as pears with equivalent spheres (Fig. 4). et al. (2019), hydrocooling delays cashew apples softening and slows
weight and vitamin C losses, but no further analysis of the reason for
the maintenance of firmness was provided. Zainal, Ding, Ismail, and
4. Effect of precooling on fruit quality
Saari (2019b) reported a higher pulp firmness and turgor pressure of
the rind of rock melon hydrocooled with 1/2 the cooling time, sug-
4.1. Effects of cooling and different cooling techniques on fruit quality
gesting that hydrocooling maintains the cell wall integrity of rock
melon fruit and preserve quality during cold storage.
The use of precooling and the corresponding cooling techniques
In addition to weight loss and firmness, other essential indexes of
affect fruit quality. Weight loss, which is mainly caused by the loss of
fruit quality attributes have been measured after precooling. Han et al.
moisture, is the main quality parameter and exerts a direct effect on the
(2017b) observed a delay in the loss of TSS and TA after a precooling
financial return because fruit is typically sold based on weight, but
treatment and the maintenance of the color of mulberry fruit during
indirect negative effects have also been observed as fruit become shri-
subsequent cold storage, which might be related to the respiratory rates
veled and withered (Kozos, Ochmian, & Chełpiński, 2014). Moisture

Fig. 4. Contour plot of the convective heat transfer

coefficients (h [W m−2 K−1]) at the interface be-
tween the air and the apples (left panel)/equivalent
spheres (middle)/pears (right panel) filling the
Supervent box at a medium flow rate. The air enters
the computational domain from the right side. The
heat transfer coefficients are overestimated by ap-
proximating the fruit shape using spheres.
Substantial differences in flow behavior are ob-
served when representing fruit such as pears with
equivalent spheres (Gruyters et al., 2018).

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and metabolic activity of mulberry fruit. Zainal, Ding, Ismail, and Saari peaches and nectarines (Lurie & Crisosto, 2005; Zhou et al., 2000).
(2019a) indicated the effective preservation of beta-carotene in rock- Zhou et al. (2000) found that delayed cooling at 20 °C for 48 h reduced
melon pulp after the application of hydrocooling. This result might be the woolliness of nectarines during 7 days of ripening after cold storage.
associated with less significant effect of the low environmental tem- Delayed cooling resulted in higher polygalacturonase (PG) activity and
perature during hydrocooling on carotenoid degradation in hydro- lower pectin esterase activity than in control fruits, but no differences in
cooled fruit compared with non-hydrocooled fruit (Zainal et al., 2019a). the levels of the PG and pectin esterase mRNAs were observed between
control and delayed cooling fruits.
4.2. Effects of different precooling strategies on fruit quality
4.2.3. Gradual cooling
4.2.1. Prompt cooling Gradual cooling was beneficial to maintain fruit quality in some
The lag time between harvest and cooling must be minimized, studies. As shown in the studies by Lurie and Sabehat (1997) and
particularly for very perishable or highly mature fruit, to avoid ex- Gálvez, García, Corrales, López, and Valenzuela (2010), gradual cooling
cessive quality loss and reduce the detrimental effects of internal reduces the extent of CI of green mature tomato during the cold storage
breakdown (Choi et al., 2015). Johnston, Hewett, and Hertog (2005) period. Gradual cooling increased the chilling tolerance of tomato fruit,
identified a positive effect of lowering the fruit temperature instantly likely because of the perception of the temperature change by the fruit
after harvest on delaying the onset of rapid softening of ‘Royal Gala’ (Gálvez et al., 2010). Yang et al. (2012) gradually cooled ‘Hongyang’
and ‘Cox's Orange Pippin’ apple fruit, which might related to delaying kiwifruit from 15 °C to 5 °C at steps of 5 °C over an interval of 1 d and
autocatalytic ethylene production in the fruit. According to Zhao et al. then maintained the temperature at 5 °C for 3 d and at 2 °C for 7 d
(2018), 0 h of delayed precooling time maintained a good appearance before storage at 0 ± 0.5 °C for 80 d. The CI index and CI incidence of
of ‘Bartlett’ pear due to the delayed degradation of chlorophyll in the gradually cooled fruit were lower than fruit directly cooled at 0 °C. The
fruit. authors attributed these results to the increase in antioxidant enzyme
activity and the inhibition of the accumulation of reactive oxygen
4.2.2. Delayed cooling species in fruit treated with gradual cooling (Yang et al., 2012).
Results for delayed cooling with negative effects on fruit quality are Gradual cooling exerts a positive effect on alleviating disorders such
mainly derived from research conducted on highly perishable fruit. As as pericarp blackening and peel browning. Yan, Li, He, Liang, and Li
shown in the study by Nunes et al. (1995), delaying the start of pre- (2013) observed less browning of the core and flesh tissues from slowly
cooling, which is accomplished by storing strawberries at 30 °C for 6 h, cooled ‘Yali’ pears than rapidly cooled fruit. The higher browning index
resulted in greater losses of firmness, ascorbic acid, soluble solids and might be due to the increased expression of polyphenol oxidase caused
water than in control fruit. In another study, Guerra and Casquero by rapid cooling (Yan et al., 2013). Wang et al. (2017a) further reported
(2009) reported effects of delayed cooling on the sensory attributes of a delay in the incidence of peel browning of ‘Nanguo’ pears after brief
European plums, together with an increase in the internal breakdown, storage at 10 °C and then gradual cooling to 0 °C over 20 d, which might
and the market life of plums subjected to a cooling delay was 10 d be related to the maintenance of high levels of ATP and energy in
shorter than plums cooled to 2 °C immediately after harvest. Both of ‘Nanguo’ pears. For loquat fruit, tissue browning, adhesive peel, and
these studies mentioned the importance of prompt precooling and tissue lignification are the main CI symptoms (Cai et al., 2006). Cai
subsequent storage at low temperature for maintaining fruit quality. et al. (2006) observed a distinct decrease in tissue browning and a delay
Nevertheless, some studies have also reported positive results. In the in the increase in the lignin content of loquat fruit after the application
study by Bernalte et al. (2003), delayed cooling of ‘Van’ sweet cherries, of LTC at 5 °C for 6 d before storage at 0 °C compared with fruit directly
which is accomplished by storing cherries at 22 °C for 15 h or 25 h, did cooled at 0 °C. The lower browning index correlated with the decrease
not exert significant effects on the skin color, puncture force, sensory in total phenol content and delay in the increase in polyphenol oxidase
data and phenolic content of fruit after 17 days of cold storage. In an- activity in loquat fruit after low-temperature conditioning (Cai et al.,
other study, Hiroaki et al. (2013) reported that the reduction in com- 2006). Jin et al. (2015) reported a lower CI index, ion leakage, and
mercial value caused by serious water loss in strawberries treated with malondialdehyde content in loquat fruit after the application of the LTC
delayed cooling after storage at 20 °C was not observed. The authors treatment, indicating that LTC improves the chilling tolerance of loquat
suggested that 12 h would be the maximum acceptable duration of a fruit by increasing the endogenous glycine betaine content and im-
postharvest cooling delay for strawberry with respect to the decrease in proving the energy status. The LTC treatment also contributes to the
ascorbic acid contents (Hiroaki et al., 2013). Although these studies did alleviation of other CI symptoms in addition to browning. Chaudhary
not provide a specific explanation for why precooling might be delayed et al. (2014) discovered a significant reduction in decay development
for several hours, a temperature of 22 or 20 °C is not particularly high and CI incidence in grapefruit conditioned at 16 °C for 7 d before cold
for fruit. Therefore, a proper delay in precooling (less than 1 d) would storage at 2 °C, and the lower CI incidence of grapefruit might be as-
not substantially affect fruit quality, providing the fruit industry with sociated with different responses of the furocoumarin and flavonoid
more choices to process postharvest fruit from a practical perspective, pathways to LTC. Zhang et al. (2017) showed an increased proline
as many fruits are unable to be precooled as quickly as desired after content and SSC of mangoes and the effective suppression of CI de-
harvest (Bernalte et al., 2003). Nevertheless, the fruit destined for de- velopment after LTC at 12 °C (Fig. 5). Kashash, Doron-Faigenboim,
layed cooling should be stored in a proper environment before pre- Holland, and Porat (2018) implemented a transcriptomic study and
cooling, such as storing it away from direct sunlight (Bernalte et al., found that LTC reduced the CI incidence and severity of ‘Wonderful’
2003). pomegranate fruit by exposing the fruit to 15 °C for 10 d.
Delayed cooling was reported to obtain a better quality of fruit than
prompt cooling in other studies. DeLong, Prange, and Harrison (2004) 4.3. Underlying mechanisms of the effects of precooling on chilling
observed a substantial suppression the development of soft scald and disorders/stresses
low temperature breakdown in ‘Honey crisp’ apple after delayed
cooling for 7 d at 20 °C. The reduction in CI might be attributed to the Although the beneficial effects of cooling fruit to low and non-
moisture loss and potential increase in ethylene production by the fruit freezing temperatures are significant, fruit, mainly tropical or sub-
(DeLong et al., 2004). Luo et al. (2018) observed 8–10% less soft scald tropical fruit, develop CI, which is genetically induced by a combina-
development in ‘Ambrosia’ apple subjected to 4 d of delayed cooling at tion of the temperature and duration of storage (Lurie & Crisosto, 2005;
20 °C during storage than fruit that was immediately cooled to 0.5 °C. Lyons, 1973). CI is a physiological disorder induced by low, but not
Controlled delayed cooling is also beneficial to maintain the quality of freezing, temperatures. Although the mechanisms involved in fruit CI

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Fig. 5. Effects of LTC on the development CI ‘in Guifei’ mango fruits. Photographs of control and LTC-treated fruits after 25 d of cold storage at 5 ± 1 °C + 5 d at
25 ± 1 °C. A: Photographs of mango fruits with peel. B: Photographs of mango fruit pulp (Zhang et al., 2017).

and quality changes are very complex and vary from fruit to fruit, cell with increased and more rapidly induced expression in LTC-treated
membrane integrity is the primary cell structure affected by CI (Rui fruit. The authors suggested that the changes in MiCBF1 expression
et al., 2010). The phase transition of cell membranes from a flexible induced by LTC might lead to an earlier and higher induction of the
liquid-crystalline structure to a solid-gel structure that occurs at lower expression downstream cold-responsive genes, thus contributing to the
chilling temperatures increases the risk of a loss of controlled cell chilling tolerance of mango fruit (Fig. 5) (Zhang et al., 2017). An RNA-
membrane semi-permeability (Aghdam & Bodbodak, 2013; Lyons, Seq analysis of the inner membrane tissue of pomegranate fruit was
1973). Prolonged exposure of fruit to damaging temperatures might conducted to explore the molecular mechanisms linking the fruit re-
result in the rupture of cell membranes, causing leakage of intracellular sponses and LTC treatment (Kashash et al., 2018). The overall changes
water, ions and metabolites (Aghdam & Bodbodak, 2013; Sharom, in the levels of transcripts associated with exposure to cold storage in
Willemot, & Thompson, 1994). Some cooling strategies have been ap- pomegranate fruit were mitigated by the LTC treatment, and the reg-
plied to reduce or delay the development of CI symptoms, such as de- ulatory and stress mechanisms related to the gene expression patterns
layed cooling and gradual cooling (Aghdam & Bodbodak, 2013; Lurie & were also affected. These changes were most likely involved in con-
Crisosto, 2005). However, even with the best delayed or gradual tributing to the observed increase in the chilling tolerance of pome-
cooling approaches, some commodities will develop CI, and the me- granate fruit (Kashash et al., 2018).
chanism should be further investigated. Existing molecular genetic Although some studies have been conducted to elucidate CI devel-
technologies must be used to understand the genetic and biochemical opment at the biochemical, metabolomic and genomic levels, and the
mechanisms controlling CI and further prevent CI in fruit (Lurie & possible functional roles of the genes have been considered, the mole-
Crisosto, 2005). Hence, researchers have recently begun to investigate cular mechanisms underlying the effects of precooling on fruit CI and
the potential mechanism underlying the effect of precooling on fruit quality are not yet completely understood, and future research in this
(Table 2) to further understand the effects of different precooling area is required.
treatment on fruit quality, improve the precooling effect and develop
new precooling strategies. 5. Future research directions
Accordign According to Luo et al. (2018), ‘Ambrosia’ apple sub-
jected to 4 d of delayed cooling at 20 °C exhibited 8–10% less soft scald Precooling strategies include prompt precooling, delayed cooling,
development during storage than fruit that were immediately cooled to and gradual cooling, among which prompt precooling is the most
0.5 °C. Changes in the levels of 78 and 88 proteins were observed in commonly used approach in the industry. Some progress has been
response to delayed cooling after one and three months of cold storage achieved in elucidating the effects of these precooling strategies. Other
using a quantitative proteomic investigation. The identification of these precooling strategies may, in some cases, reduce the CI of fruit and
proteins indicates that metabolic pathways, including lipid metabolism, vegetables during low-temperature storage, delay or reduce the for-
glycolysis, redox, amino, acids (including GABA shunt), stress and mation of some diseases, and increase the resistance of produce to
signaling, hormone response and glutathione metabolism, are the main mechanical injury (Martı́nez-Romero, Castillo and Valero, 2003;
pathways altered by delayed cooling. The study described above re- DeLong et al., 2004; Wang et al., 2017a). However, little is known
presents the first step toward revealing the potential mechanisms un- about the biological mechanisms responsible for these effects of pre-
derlying the biological effect of delayed cooling on apple fruit at the cooling. Although a few studies have recently been conducted to ex-
proteomic level (Luo et al., 2018). Maul, Mccollum, Guy, and Porat plore the effects of different precooling treatments on produce at the
(2011) noted an increase in the chilling tolerance of grapefruit after the cellular and molecular levels (Luo et al., 2018; Maul et al., 2011), ad-
application of LTC at 16 °C for one week prior to transfer to 5 °C. The ditional research is required and may aid in optimizing the precooling
transcript levels of six grapefruit genes in the flavedo of conditioned strategy, establishing other combinations of precooling delays and
fruit were consistently higher than in nonconditioned fruit. These genes temperature change patterns, and providing a theoretical basis for the
were associated with the chilling response, oxidative stress, and lipid breeding of varieties of fruit and vegetables with a reduced requirement
metabolism, and play potential roles in signal transduction mechan- for precooling to reduce the cost of fruit precooling after harvest.
isms. However, conditioning alters the transcript levels of several Many factors associated with the production of fruit and vegetables
chilling stress-related genes, suggesting a potential quantitative re- determine the optimal precooling effect, including the species, ma-
lationship between chilling tolerance induced by conditioning and gene turity, quality after harvest, cultivation method, orchard management,
expression. These gene expression changes are not necessarily asso- and production areas. Different species of fruit and vegetables are sui-
ciated with chilling tolerance per se (Maul et al., 2011). Zhang et al. table for different precooling methods. For example, litchi is very sui-
(2017) performed a study to elucidate the molecular mechanism reg- table for hydrocooling, while strawberries tend to rot after hydro-
ulating LTC-induced chilling tolerance in mango fruit and identified a cooling (Liang et al., 2013); the precooling of vegetables mainly focuses
C-repeat/dehydration-responsive element binding factor gene, MiCBF1, on vacuum precooling of leaf vegetables and mushrooms (Zhang et al.,

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2018; Zhu et al., 2018). Hence, additional studies of other precooling

The gene family of cold-induced transcription factors (CBF/DREBs) plays a central role
Chilling-responsive genes, oxidative stress genes, lipid-metabolizing genes and genes
Cell wall degradation, amino acid metabolism, lipid metabolism, protein synthesis,

Regulatory and stress mechanisms, including modification of specific transcription

techniques for vegetables are needed in the future. Moreover, different

Stress, cell wall degradation, redox, RNA transcription and binding, nucleotide
cultivation methods, orchard management measures, and production

in cold acclimation by triggering the downstream cold-responsive pathway

areas result in different physiological characteristics of fruit and vege-
tables, which might subsequently alter the effect of precooling. Luo
et al. (2018) noted different alterations in protein levels in response to
delayed cooling treatment among different growers. Nevertheless, few
studies have been conducted to explore the potential associations be-
tween fruit preharvest factors and the precooling effect, and these in-
with potential roles in signal transduction mechanisms

vestigations are important to propose more targeted precooling strate-

gies. Research designed to examine the preharvest factors of fruit and
vegetables merits further investigation. Precooling treatments are
usually designed for commercially mature fruit and vegetables and not
factor, signaling and stress-related genes
Biological functions of proteins or genes

for other maturity levels. Additionally, research on the effects of pre-

isoprenoids, and cell vesicle transport

cooling has mainly focused on the cooling rate, weight loss, decay in-
cidence, and firmness of fruit and vegetables. Additional research is
metabolism and DNA synthesis

required to examine the effects of precooling on the flavor of fruit and

vegetables. Furthermore, commercial aspects are also important. After
precooling, a portion of the fruit and vegetables may be transported to a
wide range of destinations and directly sold, while another portion of
the fruit and vegetables will be transferred to cold storage. The pre-
cooling treatment of fruit and vegetables is different for different
groups. The available refrigeration equipment in developing countries
may be not sufficient for optimal precooling. A compromise between
the extent of precooling and cost may need to be established.
Changes in the levels of 78 proteins occurred in response to delayed

Changes in the levels of 88 proteins occurred in response to delayed

The precooling rate and cooling uniformity exert important effects

Changes in the transcript levels of 10 genes were confirmed in

The levels of 1997 transcripts were significantly increased or

on the quality of fruit and vegetables. In addition to the precooling

methods and characteristics of fruit and vegetables, packaging and
decreased (974 upregulated and 1023 downregulated)

stacking patterns are two other factors that affect the precooling rate
and cooling uniformity by modulating the distribution of air flow. The
air distribution should be optimized through packaging and stacking
LTC resulted in a higher MiCBF1 expression

patterns to obtain efficient and uniform precooling, which may be ac-

complished by experimental studies, but these studies are costly and
time-consuming. Alternatively, CFD may be used for the computer-
aided design of precooling processes (Norton & Sun, 2006). Turbulence
response to delayed cooling

modeling, however, remains an issue. Until now, only Reynolds

Average Navier Stokes (RANS) approaches have been used, but more
advanced turbulence models, such as large eddy simulations (LES), are
expected to provide more accurate results. Furthermore, little is known
Studies examining the mechanisms underlying the effect of precooling on fruit quality.

about the extent of turbulence in the porous stack. For example, novel
validation studies involve detailed approaches for visualizing the flow
cooling

cooling
Result

using particle image velocimetry (PIV). Although the feasibility of using

CFD to design and optimize precooling processes and packaging ma-
terials has recently been reported (Defraeye et al., 2015; Wu &
21 d of storage at

25 d of storage at

14 d of storage at
Three months at

Defraeye, 2018; Zhao et al., 2016), this computational approach must

One month at

be adopted by the horticultural industry.

The different spatial scales involved, from the cellular to the cool
Storage

0.5 °C

0.5 °C

5 °C.
5 °C

1 °C

room scale, require multiscale modeling approaches in which the

transport properties of one scale are computed using a numerical ex-
10 d of delayed cooling at

periment at the smaller scale. This computational approach also re-

4 d of delayed cooling at

7 d of delayed cooling at

1 d of delayed cooling at

duces the need for experimental measurements of the transport prop-

Precooling treatment

erties, such as the pressure velocity characteristics of the produce stack,

which, in this approach, is considered a porous medium. This type of
experiment may not require as much available equipment, such as wind
tunnels. Recent attempts to produce stacks of apple and pear fruit with
20 °C

16 °C

12 °C

15 °C

realistic and randomly varying shapes via a discrete element method

have linked the fruit scale to the room scale, but this approach should
Grapefruit (Maul et al., 2011)

be extended to other species of fruit and vegetables (Gruyters et al.,

Pomegranate (Kashash et al.,
Mango (Zhang et al., 2017)

2018). Additionally, smaller scales, such as the cellular scale, must also
Apple (Luo et al., 2018)

be examined. Some preliminary attempts to link water transport at the

cellular level to the fruit level have been reported by Fanta et al. (2014)
and Aregawi, Abera, Fanta, Verboven, and Nicolai (2014). As water
transport causes hygrostresses and the subsequent mechanical de-
2018)

formation of the tissue, this problem requires a multiphysics solution.

Table 2

These multiscale models may be used to predict the effect of precooling

at the room scale and to qualify losses related to mechanical

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deformation, such as shriveling. This area is largely unexplored and study.

requires further investigation.
Climate change is driving the industry to improve energy efficiency. Ethical statement
As the energy consumption for refrigeration during the precooling
process increases with increasing demands for the postharvest storage This article does not contain any studies with human participants or
of fresh fruit and vegetables, more efficient refrigeration techniques animals performed by any of the authors.
using refrigerants with no negative effects on climate change, such as
NH3 and CO2, should be employed. CO2 refrigeration technology is Informed consent
known for its environmental benefits and safe operation, as well as the
compact equipment and pipelines, and it has been widely used to ad- Not applicable.
dress cooling demands. It is suitable for the required precooling tem-
perature and flexible, with different sizes ranging from several kilo- Declaration of competing interest
watts to several megawatts. Moreover, the CO2 system with a lower
refrigeration temperature becomes superior due to the advantages de- Yuan Duan declares that she has no conflict of interest. Guan-Bang
scribed above. Furthermore, new thermodynamic cycles combined with Wang declares that he has no conflict of interest. Olaniyi Amos Fawole
different refrigerants and renewable energy sources should be proposed declares that he has no conflict of interest. Pieter Verboven declares
for efficient process integration. In addition, the use of phase change that he has no conflict of interest. Xin-Rong Zhang declares that he has
materials, such as the room wall for precooling and cold storage, is also no conflict of interest. Di Wu declares that he has no conflict of interest.
a novel technical idea to achieve energy conservation and operation Umezuruike Linus Opara declares that he has no conflict of interest.
cost savings. Novel and improved precooling equipment may also re- Bart Nicolai declares that he has no conflict of interest. Kunsong Chen
duce the energy consumption of precooling and increase energy effi- declares that he has no conflict of interest.
ciency.
Acknowledgments
6. Conclusions
This work was supported by National Key R&D Program of China
Fruit and vegetables contain a considerable amount of field heat (2016YFD0400106), National Natural Science Foundation of China
after harvest. Precooling helps maintain the quality and prolong the (31671902), National the 111 project (B17039), KU Leuven project C1/
shelf life of produce, thus reducing food waste; it also reduces the 16/002, Talent Project of Zhejiang Association for Science and
cooling requirements during the subsequent cold chain process. Technology (2018YCGC006), and Fundamental Research Funds for the
Precooling is typically achieved through room cooling, forced-air Central Universities (2019FZA6010).
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