Comparison of the effect of hydrofluidization and immersion freezing on the qualitative features of a model plant material

doi:10.21203/rs.3.rs-4990003/v1

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Comparison of the effect of hydrofluidization and immersion freezing on the qualitative features of a model plant material

https://doi.org/10.21203/rs.3.rs-4990003/v1

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One of the most promising food freezing methods in terms of high heat transfer coefficients and resulting in reduced freezing times is a hydrofluidization method that potentially offers a higher quality of small food products compared to other well-established methods. For this reason, this work aimed to assess the effect of hydrofluidization freezing on the quality characteristics of the model plant material. Namely, the raw material in the form of apple cubes was used for the hydrofluidization freezing process in a 50% glycerol solution and a 40% ethanol solution and then compared to immersion freezing in the same media and chamber freezing. In the test carried out, the hydrofluidization method was characterized by an average heat transfer coefficient of 1055 W/(m²K) and 835 W/(m²K) for the glycerol and ethanol solutions, respectively, which resulted in a 40% reduction in freezing time compared to the immersion freezing in the corresponding solution. Then color, drip loss, texture parameters, the content of phenolic compounds, vitamin C, and polyphenol oxidase activity were evaluated for all three methods. As a result, the obtained product was characterized by a lower drip loss and a significantly better color after thawing. However, no substantial advantages of this method were found, compared to the immersion method, regarding the content of phenolic compounds, vitamin C, and the activity of polyphenol oxidase.

hydrofluidization

freezing medium

freezing rate

food freezing

apple

The freezing of fruits is associated with qualitative changes regarding, e.g., the destruction of the structure by ice crystals. This causes both textural changes and affects biochemical processes. Due to mechanical damage within organelles and cell walls, enzymatic and chemical reactions may occur, resulting, among others, in the partial decomposition of vitamins and a reduction of antioxidant activity. After thawing, drip loss, loss of firmness, and color changes induced by enzymatic browning were observed (Neri et al., 2020). In the works on various species of frozen plant materials by various methods, a decrease in the content of the determined components and the lack of such an effect as a result of the freezing process was found. For example, Lisiewska and Kmiecik (1997), after freezing two types of non-blanched parsley, observed a significant loss of vitamin C and ß-carotene content, a slight loss of chlorophyll, and an increase in the content of nitrates. The same authors (Lisiewska and Kmiecik, 2000) after freezing tomatoes in the form of cubes found a decrease in the content of pectin and protopectin, a decrease in peroxidase activity, a slight effect of freezing on the content of vitamin C and the activity of catalase and lipase. However, de Ancos et al. (2000) showed no significant effect of freezing four raspberry cultivars on the ellagic acid, total phenolic, and vitamin C content. Mullen et al. (2002) also found no effect of freezing on the content of vitamin C and phenolics or on the antioxidant capacity of red raspberries. However, Piekut et al. (2018) after freezing and one week of storage at -15°C showed significant losses in vitamin C content in lemon, cranberry, apple, paprika, broccoli, and sweet potato.

The minimization of qualitative changes resulting from the freezing of food raw materials can be based on modifications of the process itself and the addition of cryoprotective substances. The speed of freezing is of essential importance for the quality of products. The freezing rate affects both the size of the formed ice crystals and their distribution. With slow freezing, larger crystals are formed, more unevenly distributed, and located especially in extracellular regions (Charoenrein and Owcharoen, 2016; Zhu et al., 2019). The freezing rate depends, among others, on the heat transfer coefficient, the freezing temperature, and the size of frozen particles (Van der Sman, 2020). Another factor affecting the number and size of crystals is supercooling. From the point of view of producing as many crystallization nuclei as possible, high supercooling is advantageous (Neri et al., 2020).

One of the methods that allows for a high freezing rate is hydrofluidization. This emerging technique is based on freezing small foods in a liquid medium under highly turbulent conditions, which additionally results in the fluidization of the small food product group. A fluidized bed of foods is created by pumping the cooled solution upwards through an array of jets creating the fluid flow agitation (Fikiin, 2008). According to the aforementioned author, among the advantages of this method is the high heat transfer rate obtained despite the small temperature difference between the frozen products and the medium. Due to the high freezing rate, the fine crystalline structure of the ice can be formed and the reduction of osmotic transfer can be achieved, which is associated with the rapid freezing of the surface layer.

In both the hydrofluidization and immersion methods, it is important to select the composition of the freezing medium. Among the media used for hydrofluidization mentioned in the publications were brines, sugar-ethanol solutions, and ice slurries (James et al., 2015). So far, different authors discussed the advantages of hydrofluidization freezing regarding the lower operating costs and freezing unit size (Fikiin, 1992) and the possibility of using ice slurry for the process (Fikiin and Fikiin, 1998). The method was also experimentally investigated to determine heat transfer coefficients (Verboven et al., 2003; Peralta et al., 2009), capture fluid flow within the jet area with the Particle Image Velocimetry (PIV) method (Palacz et al., 2019), or compare freezing times with immersion method for different foods (Palacz et al., 2021). Furthermore, extensive work has been done in terms of numerical modeling of fluid flow (Peralta et al., 2010; Stebel et al., 2019), freezing of food samples (Peralta et al., 2012; Stebel et al., 2021) or modeling system hydrodynamics (Orona et al., 2017; Stebel et al., 2022a). However, to the best knowledge of the authors, the quality aspects of frozen foods with the hydrofluidization method were not discussed, especially in the context of similar immersion freezing or conventional air freezing.

For this reason, this work aimed to compare the effect of hydrofluidization freezing with immersion freezing on the quality of frozen raw material. Cubes of apple flesh were selected as model raw material for the study. It was assumed that due to the lack of a protective layer of the skin, this raw material would allow the observation of differences in the intensity of diffusion processes occurring during hydrofluidization and immersion freezing. This will allow, among others, to highlight differences caused by different compositions (ethanol and glycerol solutions) of selected freezing media. In the study, it was also assumed that the increased freezing rate of the hydrofluidization process compared to immersion freezing will allow better preservation of bioactive ingredients in the raw material.

The material selected for this study was fresh apples of the “Grey Reinette” variety purchased from the local market. Skin and inedible parts were removed from the raw material. Cubes with an edge length of 15 mm were cut out of the flesh. Immediately after cutting, the raw material was frozen by hydrofluidization, immersion, and, for comparative purposes, chamber freezing.

Hydrofluidization and immersion freezing of the prepared samples were conducted on the test rig used previously for fluid flow (Palacz et al., 2019) and thermal experiments (Palacz et al., 2021) on the hydrofluidization method. The multistage pump (EBARA EVMSL 5) with inverter (TECO L510s) allowed for maintaining smooth control of the flow conditions for immersion freezing, where only fluid circulation within the heat exchanger was needed, as well as for hydrofluidization freezing, characterized by the intensive flow. The tank in which the freezing was conducted had a volume of approximately 19 l. During freezing, the samples were stored in a box made of a plastic net to ensure that all samples were removed at the same time. Figure 1 presents the hydrofluidization process schematically where the fluid flow from the orifices allows the immersed products to move and the heat and mass transfer between the fluid and frozen samples occur.

The mass flow rate of both solutions used as freezing medium and pumped into the tank was controlled based on the Coriolis-type mass flow meter (Endress + Hauser Promass E300) installed next to the pump as described in detail by Palacz et al. (2019). Such equipment guaranteed an accuracy of ±2% for the mass flow rate measurement in the conditions used for both hydrofluidization and immersion freezing compared in this study. The product temperature during the freezing process was monitored with T-type thermocouples. That sensor was installed in the center of the sample to assess the freezing time. It should be noted that due to the sample movement during the hydrofluidization process, the position of the thermocouple could change slightly, therefore the issue of thermocouple location was the main challenge for thermal measurements. To minimize the effect of the thermocouple's imperfect position or possible movement, thermocouples having a sheath diameter of 0.5 mm were used. It allowed them to be seamlessly inserted into analyzed samples. Moreover, the thermocouple sheath was marked with a permanent marker to keep the same depth while inserting the thermocouple into samples during each run. To follow good practices for preparing experiments, the same researcher installed thermocouples during each run, and every test was repeated at least five times to minimize effects related to possible variation in temperature position and other unavoidable factors.

Nevertheless, the mentioned temperature readings were used to estimate the freezing time for the experiments carried out. Two different water-based solutions were used for both freezing methods, i.e., the ethanol solution having a mass concentration of 50% and the glycerol solution having a concentration of 40%. Ethanol-based solutions were previously used in numerical and experimental studies related to hydrofluidization freezing (Fikiin, 2008; Verboven et al., 2003; Palacz et al., 2021; Stebel et al., 2021) with a good result; however, a more viscous glycerol-based solution was analyzed only in numerical studies of the hydrofluidization method (Stebel et al., 2022a; Stebel et al., 2022b). In the case of a glycerol solution, during freezing experiments, the flow rate was set at 2.2 l/min and 45.2 l/min for the immersion and hydrofluidization freezing processes, respectively. In the case of the ethanol solution, the flow rates were 1.4 l/min and 28.8 l/min for immersion and hydrofluidization methods. The flow rates were different for the two solutions to keep a similar Reynolds number for both fluids. The temperature of the freezing medium was maintained at the level of -16°C. Approximately 160 g of apple samples were frozen for each experimental run. After the freezing process, food samples were immediately transported from one laboratory where the freezing was carried out to another laboratory where quality tests were performed by using a portable medical freezer (DOMETIC CDF-11) and stored until the next day. The temperature of the samples was maintained at -16°C during the transportation and storage phases. The total mass of the apple cubes used for the quality analysis was equal to 500 g for both, hydrofluidization and immersion freezing methods. In addition, a similar number of samples was frozen using chamber freezing. The chamber freezing temperature was carried out at the level of -16°C under conditions of natural convection. Despite efforts to minimize the sample temperature variation at each step of the conducted research (freezing, transportation, and storage), some temperature variation was expected. In order to assess the accuracy of the conducted temperature measurements the uncertainty analysis was performed. The Type-B (Eq. (1)) uncertainty for the T-type class I thermocouples and National Instruments acquisition system was calculated.

$$\:{u}_{{B}_{i}}=\frac{{I}_{i}}{\sqrt{3}}$$

where $\:{u}_{{B}_{i}}$states for Type-B uncertainty and $\:{I}_{i}$ is the accuracy of measurement equipment.

Then, the combined standard uncertainty was calculated (Eq. (2)).

$\:U\left(T\right)=\sqrt{\sum\:_{i=1}^{n}{{u}_{B}}_{i}^{2}}$ where U(T) is the combined standard uncertainty that includes all the equipment.(2)

The accuracy of the applied instrumentation as well as evaluated uncertainty are listed in Table 1.

Table 1

The accuracy of the temperature measurements.
Instrumentation	Accuracy	$\:{\varvec{u}}_{\varvec{B}}$
T-type thermocouple class I	± 0.5°C	± 0.29°C
National Instruments 9214 module	± 0.4°C	± 0.23°C
$\:U\left(T\right)$	± 0.37°C

As it can be seen in that table, the combined standard uncertainty was below ±0.5°C. On the other hand, the errors related to the misplacement of the thermocouple were not included in the calculations above. Therefore, the expanded uncertainty (coverage factor equal of 3) equal to ±1.1°C was used to evaluate the accuracy of the temperature measurements. On the other hand, that factor is related just to the temperature reading not the temperature variation during the transportation. In that case, it was assumed that the temperature variation does not exceed ±0.5°C due to their heat capacity.

The difference between immersion and hydrofluidization methods is the convection regime. In immersion freezing, the liquid medium cools down the food product by natural convection, while the hydrofluidization is based on forced convection. The food samples analyzed in this study were frozen in the glycerol solution under conditions with a heat transfer coefficient of 1055 W/(m²K) and 190 W/(m²K) for the hydrofluidization and immersion freezing, respectively. In the case of the ethanol solution, the heat transfer coefficients for these two methods were 835 W/(m²K) and 154 W/(m²K). For the latter solution, the values were lower because the viscosity of this medium is lower, which determines the Prandtl number. To determine the heat transfer coefficients for hydrofluidization freezing, the correlation proposed by Whitaker (1972) was used as in previous studies of this method (Orona et al., 2017; Stebel et al., 2022a). The bulk velocity of the fluid flowing towards the food products was determined based on the measured volumetric flow rate of a fluid and a known cross-section area of the tank where the fluid flow had a vertical direction (100x60 mm) according to Eq. (3):

$$\:v=\dot{Q}/A$$

where $\:v$ is the bulk velocity of the fluid, $\:\dot{Q}$ is the volumetric flow rate of the fluid based on measurements, and $\:A$ is the cross-section area of the tank region where the flow was observed.

The characteristic length for Reynolds and Nusselt number determination was a cube edge length (15 mm) which reports for the food product according to Whitaker’s correlation and the studies referred to above. Reynolds number given in Eq. (4) describes whether the flow is turbulent, and Prandtl number given in Eq. (5) is related to the fluid properties.

$$\:\text{R}\text{e}=\frac{\rho\:\:v\:L}{\mu\:}$$

where Re is the Reynolds number, $\:\rho\:$ is the fluid density, $\:L$ is the characteristic length of the frozen sample, and $\:\mu\:$ is the dynamic viscosity of the fluid.

$$\:\text{P}\text{r}=\frac{{c}_{p}\:\mu\:\:}{k}$$

where Pr is the Prandtl number, $\:{c}_{p}$ is the specific heat capacity, and $\:k$ is the thermal conductivity of the fluid, respectively.

The mentioned Nusselt number for the hydrofluidization freezing was based on the correlation by Whitaker (1972) given in Eq. (6):

$$\:\text{N}\text{u}=2+(0.4\:{\text{R}\text{e}}^{0.5}+0.06\:{\text{R}\text{e}}^{0.67}){\text{P}\text{r}}^{0.4}{\left(\mu\:/{\mu\:}_{w}\right)}^{0.25}$$

where Nu is the Nusselt number and $\:\left(\mu\:/{\mu\:}_{w}\right)$ is the ratio of the viscosity of the fluid at bulk temperature and the cooled object wall temperature (assumed in this study as 1 due to immediate reduction of the food sample surface temperature).

In the case of immersion freezing, the correlation of Kramers (1946), given in Eq. (7) below was used which is more suitable for a still flow of the fluid:

$$\:\text{N}\text{u}=(0.35+0.56\:{\text{R}\text{e}}^{0.52}){\text{P}\text{r}}^{0.3}$$

Eventually, after determining the Nusselt number from one of the correlations assumed for hydrofluidization and immersion freezing, the convective heat transfer coefficient can be evaluated using Eq. (8):

$$\:h=\frac{\text{N}\text{u}\:k\:}{L}$$

where $\:h$ is the heat transfer coefficient for immersion or hydrofluidization freezing.

All the values for thermodynamic parameters used in Eqs. (4)-(8) for both fluids are summarized in Table 2.

Table 2

Thermodynamic properties of fluids used for heat transfer coefficient determination evaluated in -16°C (Melinder, 2010).
Parameter	Unit	Water-glycerol (50%)	Water-ethanol (40%)
Density	kg/m³	1 142	959.8
Dynamic viscosity	kg/(m·s)	0.03521	0.01852
Thermal conductivity	W/(m·K)	0.3926	0.3453
Specific heat capacity	J/(kg·K)	3 024	3 745

In the case of the reference chamber freezing method, the heat transfer coefficient reaches a significantly lower range of 6–9 W/(m²K) according to Fellows (2000) due to the still air used as a medium.

Analyzes

Analysis of residual ethanol content by the SPME-GC-FID (Solid Phase Microextraction-Gas Chromatography-Flame Ionization Detector) method

The sample was transferred to a 15 ml vial (Supelco). Then 2 ml of distilled water with 40 mg/l of 4-methyl-2-pentanol (Fluka) and 1 g of NaCl were added to the vial. The method of extracting the compound was performed on the SPME fiber (Supelco INC., Bellefonte PA, USA) according to the methodology prepared by Satora et al. (2008).

Analysis of residual glycerol content by the UHPLC-IR (Ultra-High Performance Liquid Chromatography) method

Glycerol content was determined by UHPLC using a Shimadzu NEXERA XR series device with an RF-20A refractometer detector (Kyoto, Japan). Separation was carried out using a Shodex Asahipak NH2P-50 4.6 × 250 mm column (Showa Denko Europe, Germany), thermostated at 30°C. The mobile phase consisted of aqueous acetonitrile (70%). The isocratic elution program (0.8 ml/min) lasted 16 minutes (Satora and Pater, 2023). Quantitative determinations were made using standard curves prepared for glycerol.

Analysis of vitamin C by HPLC

The vitamin C content was determined as the sum of L-ascorbic acid and L-dehydroascorbic acid by HPLC (PN-EN 14130:2003) using a Merck-Hitachi HPLC-System LaChrome with UV/VIS detector (model 7420), degasser (model L-7612), programmable autosampler (model L-7250), pump (model L-7100) and column oven thermostat (model L-7360). For the identification of vitamin C and its quantitative analysis, an external standard was used, which consisted of L-ascorbic acid dissolved in 2% metaphosphoric acid.

Analysis of selected polyphenols by the UHPLC method

A 10 g of food material was weighed and mixed with 20 ml of 70% methanol containing 0.5% HCl. The sample was crushed with a homogenizer for 1 min and then centrifuged at 4,000 rpm (temperature 5°C, 10 min) (Tarko et al. 2017).

A liquid chromatograph of the Shimadzu NEXERA XR series (Kyoto, Japan) with a DAD detector was used for analysis. The separation was carried out on a Synergi Fusion RP-80A 150×4.6 mm (4 µm) Phenomenex column (Torrance, CA, USA), thermostated at 30°C. Acetic acid with a concentration of 2.5% (solution A) and acetonitrile (solution B) was used as the mobile phase. Gallic acid, ellagic acid, (+) catechin and phloridzin were detected at λ = 280 nm, caffeic acid, p-coumaric acid, chlorogenic acid, ferulic acid, vitexin and resveratrol at λ = 325 nm, quercetin, quercetin glucoside, rutin and kaempferol at λ = 360 nm, and hippuric acid, protocatechuic acid, and hyperoside at λ = 250 nm (Tarko et al., 2020). Standard curves prepared for ferulic acid, hippuric acid, caffeic acid, p-coumaric acid, gallic acid, chlorogenic acid, (+) catechin, quercetin (Sigma), protocatechuic acid, ellagic acid, phloridzin, apigenin-8-glucoside (vitexin), resveratrol, rutin, kaempferol, delphinidin-3-O-glucoside (myrtyline), cyanidin-3-O-galactoside (ideaine), cyanidin-3-O-glucoside (curomanine), cyanidin, cyanidin-3-O-rutinoside (keracyanin), pelargonidin-3-O-glucoside (calistefin), peonidine-3-O-glucoside and quercetin-3-O-glucoside (Extrasynthese, France) were used for quantitative determinations.

Polyphenol oxidase (PPO) activity

The polyphenol oxidase activity determination was performed according to the method reported by Cano et al. (1997). The products were grounded (Mikrotron MB 550 Kinematica AG, Switzerland) with pH 7 phosphate buffer extracted for 2 hours at 4°C and centrifuged (4200 g, 10 min, MPW-352RH, MPW Med. Instruments, Poland). To the sample containing active polyphenol oxidase, a solution of catechol in phosphate buffer was added. The determination of polyphenol oxidase activity was based on determining the increase in absorbance at a wavelength of λ = 420 nm (spectrophotometer Shimadzu UV-160 UV-VIS, Tokyo, Japan). Results were expressed in units of polyphenol oxidase activity corresponding to the increase in optical density of the substrate in 1 min per 1 g of raw material.

Color analysis

The color in the CIE L*a*b* system was analyzed using a Konica-Minolta CM-5 spectrophotometer (Japan) with the following measurement parameters: D65, 10º, SCE, calibrated on white and black standards. Based on the obtained results, the color change (ΔE) was calculated (Kriaa and Nassar, 2022) between the samples frozen and thawed at 20ºC for 1 hour. The cubes obtained from fresh apples were stored for 1 hour under the same conditions and ΔE was calculated for them.

Drip loss assessment

Drip loss analysis was performed by placing weighted frozen samples between layers of filter paper in hermetically sealed plastic bags. The thawing and storage of the samples (5 hours) was carried out in a thermostatic chamber at 4°C. Drip loss was expressed as the percentage of moisture contained in the paper with respect to the weight of the sample before thawing (Charoenrein and Owcharoen, 2016).

Texture analysis

Instrumental texture analysis was performed using a TA-XT2 texture meter (Stable Micro Systems, United Kingdom). The force needed for 50% compression of the frozen sample was recorded using the P/45 probe with a movement speed set to 0.5 mm/s. The comparison of the samples was made by analyzing the maximum force and compression work recorded during the 50% sample compression test (Charoenrein and Owcharoen, 2016).

Dry mass analysis

The dry mass was determined using a moisture analyzer (Radwag MA 50.R.NS) at 105°C.

Temperature profiles

Figure 2 shows an example of the temperature profiles recorded during hydrofluidization and immersion freezing of the apple cubes in glycerol solution. As seen, even though the initial temperature of the sample for immersion freezing was slightly lower, the freezing time was significantly longer. In the case of the hydrofluidization freezing in glycerol solution, the sample temperature of -16°C was achieved after 4.5 minutes, while in the case of the immersion freezing the same temperature was reached after 7.5 minutes. In general, the freezing time was approximately 40% shorter for hydrofluidization freezing when compared to immersion freezing, which shows good agreement with the hydrofluidization freezing time analysis presented by Palacz et al. (2021) and Stebel et al. (2021). The use of the hydrofluidization method significantly shortened the freezing time. The samples frozen in ethanol-based solution reached the temperature of -16°C after 4.5 minutes, while in the case of immersion freezing, the time necessary to reach this temperature was 7 minutes. The heat transfer coefficients for all the compared freezing methods were determined as follows: chamber freezing (CF) 6–9 W/(m²K); immersion method, glycerol (IG) – 190 W/(m²K), ethanol (IE) − 154 W/(m²K); hydrofluidization method, glycerol (HG) – 1055 W/(m²K), ethanol (HE) – 835 W/(m²K). Based on these values, it was expected to improve the measured quality parameters of the raw material in the case of the hydrofluidization method with respect to the immersion method. In some of the measured parameters, such a relationship was observed, but not for all of them. In addition, the composition of the cooling medium, which was an aqueous solution of glycerol or ethanol, also influenced the parameters studied in this paper.

Color analysis

The color of crushed apple flesh was influenced by enzymatic transformations of phenolic compounds leading to browning, to which apples are extremely prone (Fang et al., 2022). However, there is no clear statement on whether the phenomenon of enzymatic browning is associated primarily with the activity of PPO or mainly with the phenolic content of apples (Amiot et al. 1992). He and Luo (2007), on the other hand, reported that the browning of apples is often in a positive correlation with the content of chlorogenic acid. The color of the frozen and thawed samples and the color difference between them were measured instrumentally, and the results are summarized in Table 3.

Table 3

Results of the instrumental color analysis of fresh, frozen, and thawed apple cubes.
Processing method	Type of sample						ΔE
	Frozen			Thawed and stored
	L*	a*	b*	L*	a*	b*
Fresh	72.1 ± 1.8^a*	-0.6 ± 0.3^a	19.7 ± 2.3^ab	63.9 ± 2.8^a	7.0 ± 1.3^a	31.1 ± 1.6^c	16.0
CF**	71.9 ± 1.5^a	0.5 ± 0.5^b	22.5 ± 1.5^a	48.5 ± 4.7^b	6.4 ± 2.6^ab	20.8 ± 2.5^a	24.2
HG	65.7 ± 1.7^b	0.4 ± 0.8^b	20.9 ± 2.5^a	51.5 ± 4.9^b	3.5 ± 3.0^bc	20.3 ± 3.8^ab	14.6
IG	67.2 ± 1.9^b	-0.5 ± 0.9^a	19.0 ± 2.7^b	47.1 ± 5.07^b	7.1 ± 2.8^a	21.69 ± 4.0^a	21.7
HE	63.9 ± 2.2^b	0.1 ± 0.9^ab	19.6 ± 2.6^ab	59.0 ± 1.9^a	0.3 ± 0.8^c	16.9 ± 1.4^b	5.6
IE	66.4 ± 1.3^b	-0.1 ± 0.8^ab	20.1 ± 1.9^ab	49.3 ± 4.8^b	7.4 ± 3.0^a	20.9 ± 2.5^a	18.7
*Values in columns marked with different letters differ significantly (p < 0.05)
** CF - chamber-freezing, HG - hydrofluidization in glycerol solution, IG - immersion in glycerol solution,
HE - hydrofluidization in the ethanol solution, IE - immersion in the ethanol solution.

The highest value of the L* parameter, which expresses brightness, was found in a fresh apple. The chamber frozen apple had the most similar parameter L* value to the fresh apple. Other freezing methods resulted in a slight decrease in this parameter. Chamber freezing associated with a slow freezing rate favors the formation of large ice crystals (Charoenrein and Owcharoen, 2016; Zhu et al., 2019). The high parameter L* value for chamber-frozen apples may be related to the optical properties of large ice crystals. The freezing process, in most cases, did not have a significant effect on the parameters a* and b*. However, in the method of chamber freezing in air, the presence of oxygen could allow for the oxidation process on the surface of apple cubes. The storage of the sliced apple and the thawing process influenced the changes in the measured color parameters. Both the fresh apple after storage and the thawed samples were characterized by apparently darker surfaces and therefore lower parameter L* values than the frozen samples and the fresh apple. However, the values of the parameter a* increased, which indicates an increase in the red (+ a) components in the color of the samples. The value of the b* parameter fluctuated slightly in the range of positive values, which was associated with the yellow color. A clear increase of the parameter b* was observed only in fresh samples. The color change of the apple was mainly due to the oxidation of phenolic compounds to quinones by polyphenol oxidase. Then the quinones undergo a polymerization process to transform into brown, red, or black compounds (Janovitz-Klapp et al., 1990). The browning process of fresh apples was observed in order to evaluate the dynamics of this process. However, changes in the color of fresh and thawed apples cannot be directly compared, e.g. due to temperature differences of both types of samples during 1-hour incubation. The smallest change in color (ΔE) between the thawed and frozen samples was observed in the case of an apple frozen by hydrofluidization in an ethanol solution. However, quite surprising was the relatively large ΔE between the thawed and frozen sample in the case of an apple frozen by immersion in an ethanol solution. Nevertheless, it was lower than in the case of immersion-frozen apples in a glycerol solution. The greatest color change was observed in the case of chamber freezing of apples. Based on the collected results, it can be concluded that hydrofluidization freezing, compared to immersion freezing, reduced color changes and that ethanol had a positive effect on this parameter. Factors that influenced the better preservation of the color of the thawed product were most likely the higher rate of freezing and the denaturing effect of ethanol. The use of the ethanol solution probably also led to the partial extraction of polyphenolic components from the surface of the samples, which reduced the concentration of substrates involved in the browning of the raw material. The intensity of the browning process in the examined case was affected by both possible changes in enzyme activity caused by the freezing process and the extent of cell destruction. In addition to polyphenol oxidase, peroxidase contributes to enzymatic darkening, although to a lesser extent (Arnold and Gramza-Michałowska, 2022). The method proposed in the literature that can affect the reduction of color changes in thawed fruit is, for example, dipping pretreatment with lemon juice solutions (Yu and Liao, 2016; Neri et al. 2019).

Analysis of selected polyphenols and polyphenol oxidase activity

Enzymatic browning not only creates an undesirable brown color but also reduces the nutritional quality and sensory properties of the fruits and is an important cause of fresh fruit loss (Moon et al., 2020). Polyphenol oxidase converts substrates in the presence of oxygen, causing undesirable color changes. Its activity is usually regulated by cooling, lowering the pH, or using enzyme inhibitors (Tomás-Barberán and Espín, 2001). Peroxidase converts substrates in the presence of hydrogen peroxide, whose availability in apples is low. These enzymes are found in cell walls and chloroplasts, while phenolic compounds are found in the vacuole (Arnold and Gramza-Michałowska, 2022). Freezing and ice crystal formation, especially in the case of fruit, resulting in vacuole rupture cause loss of turgor pressure and structural damage of cells and cell walls, which can lead to polyphenol loss due to enzymatic browning and oxidation (Loncaric et al., 2014). Chassagne-Berces et al. (2009) frozen apple tissue at different rates, including through immersion in liquid nitrogen, and did not observe intact vacuoles in the images obtained. On the other hand, freezing could also reduce enzymatic browning as it decreases the water available for taking part in enzymatic reactions and thus reduces the browning (Singh et al., 2018). A wider range of tissue damage caused by the freezing process facilitates the contact of enzymes with substrates to a greater extent. The data in Fig. 3 indicate that the freezing process itself significantly reduced the activity of polyphenol oxidase, with respect to the fresh samples. Very rapid freezing by hydrofluidization caused the smallest decrease in polyphenol oxidase activity (by approximately 62–68%). The greatest decrease compared to the control sample was observed in the case of samples frozen using the chamber freezing method (by approximately 80%). A different relationship was found in the case of polyphenolic compounds, the content of which is presented in Fig. 4. Apple cubes frozen by chamber method were characterized by the highest sum of these components. The immersion frozen apple cubes were characterized by polyphenol concentrations similar to unprocessed samples. On the other hand, the lowest content of these components was found in samples frozen by hydrofluidization. Within individual polyphenols, the solution used for freezing affected only the content of catechin and p-coumaric acid. After freezing the raw material in the ethanol solution, the listed components were less than in the case of using glycerol. However, the sum of polyphenolic components in the case of both freezing solutions did not differ significantly. The polyphenols present in the evaluated apples were mainly chlorogenic acid, epicatechin, and catechin. Other compounds listed in Fig. 4 were present in concentrations less than 2 mg/100 g. Both chlorogenic acid and flavan-3-ols, such as catechin and epicatechin, are substrates for the enzymatic browning of apples, while p-coumaric acid does not play such a role. In addition, pigments obtained by reactions involving chlorogenic acid can co-oxidize other substances (Amiot et al., 1992).

Vitamin C content

Freezing the samples caused a drastic reduction in vitamin C (Fig. 3). However, in this case, the freezing rate had no significant effect on its content. The medium used was more significant. Glycerol allowed for retaining a small part of the initial content of vitamin C, while the use of ethanol led to its reduction below the level of detection. Perhaps, a thin layer of glycerol present on the surface of the cubes limited the access of oxygen and enabled a slightly better preservation of vitamin C, which is one of the least stable vitamins, it is easily subject to enzymatic and non-enzymatic oxidation, and additionally, in contact with water, it can also be leached. Moreover, the solubility of vitamin C is lower in glycerol than in ethanol, which further limits its losses (Ball 2006). As reported by Tu et al. (2015), freezing of lotus root resulted in approximately 38–55% losses of vitamin C, depending on the freezing method. According to the cited authors, the better methods were air blast freezing and immersion freezing in 29% calcium chloride water solution (losses 38–43%) than ultrasound-assisted immersion freezing in the same solution (losses 45–55%). In this study, in the case of frozen apple cubes, vitamin C loss was probably caused by oxidation and the transition to a freezing medium. The residual ethanol content in the food samples was 3.43 ± 0.61 g/kg for HE and 3.19 ± 0.39 g/kg for IE. Similarly, samples frozen by hydrofluidization and immersion did not differ significantly in the content of glycerol residues, which amounted to 63.37 ± 4.20 g/kg and 68.70 ± 2.34 g/kg of raw material, respectively. For the aqueous solutions used in this work, the increased freezing rate was not found to reduce the proportion of ethanol and glycerol in the frozen products. The residual ethanol content was similar to the values described by Cipolletti et al (1977) for carrot dice (3/8 in.) frozen in an aqueous freezant containing 15% NaCl and 15% ethanol. The reported value was 0.27%. In the present work, the residual ethanol or glycerol content was influenced by, among others, the porosity of the apple, the ratio of the surface area of the cubes to their volume, and the viscosity of the solutions used. Factors affecting solute uptake also include the temperature of the freezing solution, its composition and concentration, and the length of time the product is held in a liquid medium. One of the two main drawbacks of immersion freezing listed by Lucas and Raoult-Wack (1998) is the uptake of solutes by foods. The advantage of ethanol in this context is the possibility of its evaporation.

Texture analysis

Instrumental analysis of the texture of frozen samples indicates the need to use more force and perform more work during the compression of samples frozen by hydrofluidization than by immersion or chamber freezing (Fig. 5). The lowest values of both indicators were related to the compression of chamber-frozen samples. Similar values of the work necessary to move the sampler in the case of fresh and chamber-frozen apples resulted from the crushing of the frozen sample. This resulted in a decrease in the value of work needed to further compress the crushed sample. On the other hand, the densification of the structure of fresh apples increased the value of work. Hence, despite the very large structural differences between the two samples, similar values of this parameter were obtained. The higher the freezing rate, the more numerous and finer crystals that are formed in the product. Different freezing rates also affect the shape of the formed ice crystals. The increase in the parameters assessed of the compression test (force and work) at high freezing rates may be the result of, among others, the increase of the internal friction between numerous ice crystals with an extensive total surface area

Fruit texture is influenced by both the structural organization of cells related to, among other things, the structure of the cell wall and vacuoles, as well as tissue structure (Chassagne-Berces et al. (2009). As reported by Li et al. (2018), the amount of vacuole water in fruit and vegetable food ranges from 50–95%, in addition to this, in these raw materials, water is also contained in the cytoplasm, cell wall, and in gaps between cells, where is most vulnerable during the freezing process. Chassagne-Berces et al. (2009), when freezing apples at -20°C, -80°C and − 196°C, observed the rupture of vacuoles in all freezing protocols, showing that the loss of turgor pressure was crucial for textural changes in the frozen raw material. The authors noted that none of the freezing rates used allowed for the preservation of the surrounding vacuole tonoplast, while in the case of the slowest freezing, they observed not only the largest ice crystals (10 to 30 µm) but also less regular shape of cell walls. In the other freezing conditions, the crystals were about 3 µm and 2 µm. At the same time, they reported that the best-preserved firmness and cellular structure were obtained for apple frozen at -80°C (freezing rate 8.1°C/min). Worse results were obtained for both − 20°C (0.9°C/min) and immersion in liquid nitrogen (310°C/min). On macroscopic images of samples frozen at -20°C, the authors observed cell walls seemed to collapse and larger intracellular spaces. In contrast, freezing with a freezing rate of 310°C/min led to long tissue cracks. Similar insights come from the observation of photomicrographs of carrot tissue immersion and air-blast frozen presented by Cipolletti et al. (1977). Immersion frozen carrot shows much less disruption of the ordered cell structure.

It can be expected that the quick-freezing process has less impact on the food texture (Fikiin, 2018). Advanced methods like scanning electron microscopy (SEM) allow to compare the microstructure of food products preserved by different methods (Kalab et al., 1995). Although such experiments were not performed in this paper, they were often performed to determine the effect of the freezing process on the food microstructure (Chassagne-Berces et al., 2009). Ong et al. (2011) observed the structure of dairy products and concluded that SEM gives good insight into the food structure. More specific studies focused on apple tissues subjected to different freezing rates by Bomben et al. (1985) and Narayana et al. (2023) confirmed that the microstructure and ice crystal growth are highly correlated with the time of the process and the quick-freezing methods allow for better quality preservation after the freezing process. That relationship was confirmed in numerous studies, e.g., for strawberries (Delgado and Rubiolo, 2005, Rayman Ergun et al. 2021) and blueberries (Allan-Wojtas et al., 1999, Cheng et al., 2020), where authors, by using SEM technique, observed the effect of the freezing rate on the microstructure of these fruits.

In more detail, Qinggang et al. (2014) subjected blueberries to fluidized quick-freezing and slow freezing. The authors observed with environmental scanning electron microscopy (ESEM) in the first case better compactness and uniformity within the inner microstructure of fruits. In the picture of ESEM, the authors observed a homogeneous, dense, non-deformed structure of fresh fruits with no obvious boundary between skin and internal organization. Fast-frozen fruit had a very obvious boundary between skin and internal organization, which, however, remained homogeneous and dense but with slight local deformation. In contrast, slow freezing caused a slight disconnection of skin from the internal organization, which became uneven and very loose with collapsed local tissues. Quick freezing in an LN₂-spraying fluidized bed also allowed fruit to be stored longer than was the case with slow-frozen berries. In turn, Khan and Vincent (1996) conducting mechanical damage induced by controlled freezing of apple and potato parenchyma, observed that the results of mechanical tests (wedge penetration, tensile, and compression) conducted after thawing of raw material were directly related to the degree of cell damage.

Drip loss analysis

One of the basic measures of changes resulting from freezing is the drip loss of tissue fluids after thawing the product. A larger drip loss after thawing indicates worse product quality. Drip loss also facilitates the growth of microorganisms. The rate of drip loss is related to the size and distribution of the ice crystals, which are directly affected by the rate of freezing. Slow freezing favors the formation of larger crystals located mainly in intercellular spaces (Jha et al., 2019). Fast freezing allows not only to obtain fine crystals that are uniformly distributed which reduces destruction of cell membranes but also increases specific area, which facilitates water absorption during thawing (Narayana et al., 2023). The highest values of the discussed parameter were obtained in the case of chamber freezing, which should be associated with a low rate of freezing and the formation of relatively large ice crystals, which strongly damage tissues. The best results were obtained in the case of hydrofluidization freezing (Fig. 5). Similar observations are made by Narayana et al. (2023), who processed apple cylinders by static freezing (-18°C), rapid freezing (-40°C, 2 m/s air velocity) and ultra-rapid freezing (-72°C, 1 m/s air velocity), reported that drip loss remained in inverse relationship with the freezing rate. However, the authors found a significant difference (p < 0.05) only between static and ultra-rapid freezing. Similar conclusions regarding the effect of the freezing rate on the amount of drip loss also come from the work of Charoenrein and Owcharoen (2016), in which the authors applied the following freezing rates to frozen mangoes: 2.91°C/min, 1.69°C/min and 0.05°C/min. At present work, among the solutions used, the samples frozen with ethanol were characterized by a much lower drip loss. Ethanol-induced denaturation may have influenced the observed result. Due to the very similar dry mass of all frozen samples (Fig. 5), this phenomenon cannot be attributed to, for example, partial dehydration of the samples. During the slow freezing of apple particles, it was observed that crystals separated cells, destroyed cell walls, compressed cells, and, consequently, led to the formation of radial splits in the tissue (Sterling, 1968). On the contrary, increasing the freezing rate reduced distortion and cell separation. Khan and Vincent (1996), while freezing apple samples, found that the largest increase in the percentage of ruptured cells occurred in the temperature range from − 6°C to -10 ºC. As shown in Fig. 2, this temperature range was overcome within 2 minutes in the case of immersion freezing and 1 minute in the case of hydrofluidization freezing in glycerol solution.

In this study, selected food quality indicators were compared for hydrofluidization and immersion freezing of apple samples in two different fluids, i.e. water solutions of ethanol and glycerol. Significantly shorter freezing time for the hydrofluidization technique allowed for smaller changes in the food samples' color after thawing. The use of ethanol solution as the freezing medium had a particularly positive effect on this quality factor. When hydrofluidization in ethanol solution was used, the color difference was more than four times lower than in the case of chamber freezing. The same method also allowed for the reduction of thawing drip loss. However, despite the very short processing time, the hydrofluidization method did not significantly reduce the loss of vitamin C caused by freezing. No beneficial effect of the hydrofluidization method was found, compared to the immersion method, in the case of the content of polyphenols and the maintenance of the polyphenol oxidase activity. The value of the latter indicator for each freezing method decreased by more than 60%.

Roman Symbols

A Surface area, m²
a* Red/Green Value
b* Blue/Yellow Value

c_p Specific heat capacity, J/(kg K)
ΔE Color change

h Heat transfer coefficient, W/(m²K)

I Accuracy of the measurement equipment

k Thermal conductivity, W/(m K)
L* Lightness

L Characteristic length, m

Q Volumetric flow rate, m³/s

u standard undercity, -

v Velocity, m/s
Nu Nusselt number

Re Reynolds number
Pr Prandtl number
Greek Symbols
λ Wavelength, nm

ρ Density, kg/m³
μ Dynamic viscosity, kg/(m s)
Abbreviations
PIV Particle Image Velocimetry
SPME-GC-FID Solid Phase Microextraction-Gas Chromatography-Flame Ionization Detector
UHPLC-IR Ultra-High Performance Liquid Chromatography
HPLC High Performance Liquid Chromatography
PPO Polyphenol Oxidase
HG Hydrofluidization in Glycerol Solution
IG Immersion in Glycerol Solution

IE Immersion in Ethanol Solution
HE Hydrofluidization in Ethanol Solution

SEM Scanning electron microscopy

Funding

This research was supported by the National Science Center (Poland) project No. DEC-2016/22/E/ST8/00517 and Ministry of Education and Science (Poland) under statutory research funds of the Faculty of Energy and Environmental Engineering of Silesian University of Technology (MP, MS, JS). The work of MS was supported by Silesian University of Technology through project No. 08/060/RGJ22/1057. The work of JS was supported by Silesian University of Technology through project No. 08/060/RGJ23/1098.

Author Contribution

Magdalena Michalczyk: Writing - Original Draft, Investigation, Conceptualization; Emilia Bernaś: Writing - Original Draft, Investigation, Conceptualization; Ireneusz Maciejaszek: Writing - Original Draft, Investigation, Conceptualization; Aneta Pater: Writing - Original Draft, Investigation; Jacek Słupski: Writing - Original Draft, Investigation, Conceptualization; Michał Palacz: Investigation, Writing - Review & Editing; Michał Stebel: Formal analysis, Writing - Review & Editing,;Jacek Smołka: Writing - Review & Editing, Project administration

Acknowledgement

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No competing interests reported.

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Comparison of the effect of hydrofluidization and immersion freezing on the qualitative features of a model plant material

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Abstract

Figures

Introduction

Material and methods

Analyzes

Analysis of residual ethanol content by the SPME-GC-FID (Solid Phase Microextraction-Gas Chromatography-Flame Ionization Detector) method

Analysis of residual glycerol content by the UHPLC-IR (Ultra-High Performance Liquid Chromatography) method

Analysis of vitamin C by HPLC

Analysis of selected polyphenols by the UHPLC method

Polyphenol oxidase (PPO) activity

Color analysis

Drip loss assessment

Texture analysis

Dry mass analysis

Results and discussion

Temperature profiles

Color analysis

Analysis of selected polyphenols and polyphenol oxidase activity

Vitamin C content

Texture analysis

Drip loss analysis

Conclusions

Abbreviations

Declarations

Funding

Author Contribution

Acknowledgement

References

Additional Declarations

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