Using polyols as alternative solutes for osmotic dehydration of banana slices

Abstract

This study evaluated the efficacy of polyols by comparing them to sucrose in the osmotic dehydration (OD) of banana slices. The OD process was conducted by immersing the banana slices in binary solutions of sucrose, maltitol, xylitol, and erythritol, each with the same water activity, for periods of 30, 60, 120, 180, 240, and 300 minutes at 30 °C. The mass transfer kinetics were analyzed. Fresh and osmo-dehydrated samples were assessed based on quality parameters. During OD, water loss, solid gain, and weight reduction increased, while moisture content decreased. The Peleg model accurately represented the mass transfer kinetics. OD led to reductions in moisture content, water activity, luminosity, and yellowness, while it increased the color intensity of the banana slices. The type of osmotic agent did not significantly affect solid gain or shrinkage. Sucrose was the only solute that increased hardness. Erythritol produced samples with higher luminosity and yellowness, and less overall color alteration. Among the polyols, erythritol emerged as the most effective osmotic agent, according to the desirability function, making it an interesting alternative to sucrose for the production of osmo-dehydrated banana slices with low glycemic and insulinemic indexes.

Key words
Optimization; Osmotic dehydration; Sugar alcohols; Sweeteners; Texture

INTRODUCTION

The alarming increase in chronic diseases such as obesity and diabetes has triggered a profound change in the population’s eating habits, driven by growing concerns about health and well-being. In this context, consumers are becoming increasingly aware and demanding, seeking food options that are not only tasty but also nutritious and as close to their natural form as possible. This movement has encouraged the food industry to adapt by reformulating their products to meet these new demands. One of the challenges faced by the industry is the careful review of the types and quantities of additives and ingredients used in their products to ensure safety and health benefits for consumers. Moreover, the focus on food quality goes beyond simple nutritional composition, encompassing aspects such as the origin of ingredients, production methods, and even environmental and sustainability issues (McClements 2024).

Sucrose, also known as table sugar, is the carbohydrate most widely used by the food industry due to its high availability, low cost, high sweetening power without leaving a residual taste, contribution to product texture, and stability during processing. However, its consumption is associated with various adverse health effects such as obesity, diabetes, cardiovascular diseases, and dental caries (Tian et al. 2019, White 2014). Despite these negative impacts, sucrose remains the most used solute in osmotic dehydration (OD) processes (Araújo et al. 2025, Asghari et al. 2024, Macedo et al. 2023a).

OD is a complex and dynamic unit operation. The material is immersed in a hypertonic osmotic solution, allowing mass exchanges between both systems, including the impregnation of solids from the solution into the food and the loss of water. While the leaching of food solids into the solution also occurs, it is of less relevance in quantitative terms (Abrahão & Corrêa 2023, Asghari et al. 2024, González-Pérez et al. 2021). In recent years, OD has gained prominence as a natural method that minimally affects the color, sensory qualities, and nutritional components of the product. It is a process viable at room temperature, adopts simple and low-cost technologies, and does not require specialized labor. Furthermore, OD results in changes in food properties, particularly regarding physicochemical characteristics (Abrahão & Corrêa 2023, Araújo et al. 2025, do Carmo et al. 2022, Macedo et al. 2022a, 2025). However, the effects caused by OD depend on several factors, especially on the solute used to prepare the hypertonic solution.

Polyols, also known as sugar alcohols or polyhydric alcohols, are carbohydrates but are not considered sugars or alcohols. They are obtained by replacing an aldehyde group with a hydroxyl group, resulting in low or no digestion, which prevents an increase in the glycemic index or insulin synthesis. These characteristics, along with their low-calorie content and relative sweetness ranging from approximately 60% to 100% in relation to sucrose, make polyols recommended for athletes and diabetics. Furthermore, polyols have a low cariogenic index, helping to preserve dental health, exerting a prebiotic effect, and aiding in the normalization of intestinal function (Cichowska et al. 2020, Grembecka 2015, Macedo et al. 2022a, Mendonça et al. 2017).

Banana represents one of the most consumed fruits in the world, owing to its high sensory attributes, nutritional and functional properties, low acquisition cost, and year-round production in almost all regions of the world. However, being a climacteric and highly perishable fruit, the use of preservation techniques for bananas is justified (Al-Dairi et al. 2023), among them, OD (Araújo et al. 2025, Atares et al. 2011, Farhaninejad et al. 2017, Macedo et al. 2025).

The use of polyols as an alternative to sucrose for OD has proven to be a good strategy for various food materials, such as apples (Cichowska et al. 2019a, b, Kowalska et al. 2020), green bananas (Chaguri et al. 2017), kiwiberries (Bialik et al. 2018), strawberries (Macedo et al. 2022a), yacon (Mendonça et al. 2017). However, studies on this topic in bananas are still scarce. The investigation of the use of polyols in the OD of banana slices may enable the development of healthier and technologically distinct products, expanding innovation opportunities in the food industry. Therefore, this work aimed to evaluate the influence of using maltitol, xylitol and erythritol as an alternative to sucrose for the OD of banana slices, analyzing both the kinetic parameters of the process and the qualitative aspects of the final product.

MATERIALS AND METHODS

The experiment was carried out as shown in the flowchart in Figure 1.

Figure 1
Schematic representation of the study steps.

Preparation of the samples

Bananas bunches of the Musa Paradisiaca cultivar were purchased from local market (Lavras, Minas Gerais, Brazil). They were washed in running water, sanitized by immersion in chlorinated water (200 ppm) for 10 min, and then rinsed. The fruits were removed from the bunches. Whole bananas, with a ripeness level 4 on a scale from 1 to 8, where the peel color was more yellow than green, were selected (Al-Dairi et al. 2023). They were manually peeled, and the pulp was cut transversely into slices with a thickness of 5.40±0.37 mm and a diameter of 28.08±1.41 mm (Macedo et al. 2021a).

Osmotic dehydration (OD)

Preparation of the osmotic solutions

The osmotic solutions (OS) were prepared by dissolving the solute (sucrose, maltitol, xylitol or erythritol) in deionized water at concentrations as high as their solubility allowed. The water activity of each OS was then measured using an electronic hygrometer (Aqualab, Series 3TE, Washington, USA) at 25 °C. To ensure uniformity, the concentrations were adjusted so that all OS reached the same water activity (p>0.05), set to the lowest possible value, maximizing the osmotic pressure gradient between the OS and the banana slices.

The OS of sucrose and maltitol were prepared at 50% (kg solute per 100 kg solution), while those of erythritol and xylitol were prepared at 30% (kg solute per 100 kg solution) (Table I).

Table I
Molecular mass of solutes, concentration, and water activity of the osmotic solutions.

Osmotic agent	Molecular mass (g mol-1)	Concentration (%, w w-1)	Water activity
Sucrose	342.3	50	0.944±0.002A
Maltitol	344.3	50	0.943±0.001A
Xylitol	152.2	30	0.944±0.001A
Erythritol	122.1	30	0.942±0.001A

• Means followed by the same letter vertically do not differ significantly from each other by Tukey’s test (p<0.05).

OD procedure

The banana slices were immersed in the osmotic solutions at a ratio of 1:20 (w/v) to minimize dilution effects during OD. The OD process was carried out for a total time of 300 min at 30 °C in a temperature-controlled chamber (Eletrolab EL111/4, São Paulo, Brazil). At 30, 60, 120, 180, 240, and 300 min, the samples were removed from the osmotic solutions and immersed in an ice bath for 10 s to halt mass flow. Then, the surface of the samples was drained with absorbent paper (Junqueira et al. 2020, Macedo et al. 2023a).

Mass transfer

The water loss (WL), solid gain (SG), and weight reduction (WR) were calculated according to Equations 1, 2, and 3, respectively (Macedo et al. 2022a).

​$$WL(\mathrm{\%})=\frac{W_0{M}_0-W_t{M}_t}{W_0}\times 100$$ (1)

​$$SG(\mathrm{\%})=\frac{W_t(1-M_t)-W_0(1-M_0)}{W_0}\times 100$$ (2)

​​$$WR(\mathrm{\%})=\frac{W_0-W_t}{W_0}\times 100$$ (3)

Where W is the weight of the sample (kg); M is the moisture content of the sample (kg water kg sample-1); and the subindexes “0” and “t” indicate the initial and t time (min), respectively.

The efficiency index (EI) of OD was calculated according to Equation 4 (Corrêa et al. 2016).

$$EI=\frac{WL}{SG}$$ (4)

The Peleg model was fitted to the experimental data dispersion of WL, SG, MC, and WR over time, according to Equations 5, 6, 7 and 8, respectively.

​​$$W{L}_t=W{L}_0+\frac{t}{k_{1WL}+k_{2WL}t}$$ (5)

​​$$S{G}_t=S{G}_0+\frac{t}{k_{1SG}+k_{2SG}t}$$ (6)

$$M{C}_t=M{C}_0+\frac{t}{k_{1MC}+k_{2MC}t}$$ (7)

​​$$W{R}_t=W{R}_0+\frac{t}{k_1^{WR}+k_2^{WR}t}$$ (8)

Where ​​WL​ 0​​​, ​​SG​ 0​​​ and ​​WR​ 0​​​ are the values of WL, SG and WR no tempo zero, respectively; ​​MC​ 0​​​ is the value of moisture content at time zero; ​​k​ 1​ WL​​ is the Peleg rate parameter (min−1) for WL; ​​k​ 2​ WL​​ is the Peleg capacity parameter for WL; ​​k​ 1​ SG​​ is the Peleg rate parameter (min−1) for SG; ​​k​ 2​ SG​​ is the Peleg capacity parameter for SG; ​​k​ 1​ MC​​ is the Peleg rate parameter (min−1) for MC; ​​k​ 2​ MC​​ is the Peleg capacity parameter for MC; ​​k​ 1​ WR​​ is the Peleg rate parameter (min−1) for WR; ​​k​ 2​ WR​​ is the Peleg capacity parameter for WR; t is the time (min).

The parameters ​​WL​ 0​​​, ​​SG​ 0​​​ and ​​WR​ 0​​​ of Equations 5, 6 and 8 were replaced by a constant value, equal to zero. Similarly, the parameter ​​MC​ 0​​​ of Equation 7 was assigned the constant value of 72.90%(_w._b.), obtained experimentally.

The initial rate of mass transfer was calculated as the reciprocal of parameter k₁ (1/k₁), representing the initial rate of mass transfer (t=0). Similarly, the reciprocal of parameter k₂ (1/k₂) was calculated to obtain the value for mass transfer parameters at the equilibrium condition (t→∞) (Macedo et al. 2023a, Mendonça et al. 2017).

Sample characterization

Moisture content

The moisture content was determined by the gravimetric method established by method 934.06 of (AOAC 2010), wherein the samples were placed in an oven at 70 °C, under vacuum.

Water activ_ity (aw)

The a_w of the samples was determined on an electronic hygrometer (Aqualab, series 3TE, Washington, USA), at 25 °C.

Shrinkage

The thickness and diameter of both fresh and osmo-dehydrated samples were measured at three different points on each slice using a digital Vernier caliper (±0.01 mm) (Western, DC-60 model, Zhejiang, China). The volume of the samples was calculated assuming they were in a cylindrical shape. Then, the volumetric shrinkage of the samples was calculated according to Equation 9.

$$\text{Shrinkage}(\mathrm{\%})=(1-\frac{V}{V_0})\times 100$$ (9)

Where V and V₀ are the volumes (m3) after and before osmotic dehydration, respectively.

Hardness

The hardness of fresh and osmo-dehydrated samples was determined using a texture analyzer (Stable Micro Systems, TA-X2T, Surrey, England). The equipment included a 50-kg load cell, a 6-mm diameter probe, a test speed of 2 mm s-1, and a penetration distance of 3 mm (Macedo et al. 2023b). The hardness was expressed in newtons (N).

Color

The colorimetric parameters (L*, a* and b*) of the samples were obtained by direct reading on a colorimeter (Konica Minolta, model CR-10, Osaka, Japan), with illuminant D65, using color scale CIELab. Chroma (C*) and hue (h*) were calculated according to Equations 10 and 11, respectively. The total color difference (ΔE) of the samples in relation to the fresh sample whose parameter is represented by the sub-index “0” was calculated according to the Equation 12.

​​$$C^{\ast }=\sqrt{a^{\ast 2}+b^{\ast 2}}$$ (10)

​$$h^{\ast }={\tan }^{-1}\left(\frac{b^{\ast }}{a^{\ast }}\right)$$ (11)

$$\mathrm{\Delta }E=\sqrt{(L^{\ast }-L_0^{\ast }{)}^2+(a^{\ast }-a_0^{\ast }{)}^2+(b^{\ast }-b_0^{\ast }{)}^2}$$ (12)

Statistical analyzes

The experiment was conducted in a completely randomized design, with five repetitions. The Tukey test was performed to compare the four treatments with each other, and the Dunnett test was used to compare each treatment individually with the control sample (fresh sample). Statistical significance was defined as p<0.05.

A multivariate analysis was conducted using principal component analysis (PCA) on the parameters of WL, SG, MC, WR, a_w, shrinkage, hardness, and color parameters to analyze their specific interrelations as influenced by the type of osmotic agent.

Statistical analyses were performed using the Statistica (StatSoft, Tulsa, Oklahoma, USA) software.

Optimal condition

The desirability function (Derringer & Suich 1980) was used to determine the optimal condition among the osmotic agents. The responses were used individually to calculate the individual desirability (di) of each treatment. Equations 13 and 14 were used for the responses that were desired to minimize and maximize, respectively.

$$d_i=\{\begin{array}{ll}1,& y_i\le T_i\\ \frac{U_i-y_i}{U_i-T_i},& T_i<y_i<U_i\\ 0,& y_i>U_i\end{array}$$ (13)

$$d_i=\{\begin{array}{ll}0,& y_i\le L_i\\ \frac{y_i-L_i}{T_i-L_i},& L_i<y_i<T_i\\ 1,& y_i>T_i\end{array}$$ (14)

Where y is the response; T_i is the target value desired; U_i is the maximum value for responses that are desired to be minimized; L_i is the minimum value for responses that are desired to be maximized.

The d_i values were used to calculate the overall desirability (D), according to Equation 15.

$$D={\left(\prod _{i=1}^N{d}_i\right)}^{\frac{1}{N}}$$ (15)

Where Π is the product over the set of terms; N is the individual desirability number.

RESULTS

The dispersions of water loss (WL), solid gain (SG), moisture content (MC) and weight reduction (WR) data throughout the osmotic dehydration (OD) processes are showed in Figures 2a, 2b, 2c, and 2d, respectively, where each curve represents a type of osmotic solution (OS). According to Figure 2, the data showed behavior close to exponential, where the main rates of increase in WL, SG, and WR, and reduction in MC occurred during the first minutes of the osmotic process.

Figure 2
Kinetics of water loss (a), solids gain (b), moisture content (c) and weight reduction (d).

The types of osmotic agents influenced mass transfer (MT) during OD (Figure 2). The use of xylitol resulted in the lowest WL during OD (Figure 2a), followed by maltitol. Erythritol and sucrose caused the highest WL, with very similar behaviors to each other. Therefore, according to Table I, it can be seen that molecular weight was not predominant in MT rates during OD. Furthermore, the dispersion of SG data throughout the OD processes was similar among the osmotic agents (Figure 2a). Only xylitol showed a slightly higher SG in the first minutes of OD (Figure 2b), but by the end of the process, its behavior tended to be similar to the other agents.

The MC of banana slices started at 72.90±0.38%(_w._b.), decreasing during OD (Figure 2c).

The behavior of the WR data throughout the OD processes (Figure 2d) was similar to that of WL.

The parameter values of Peleg model are presented in Table II. According to Table II, sucrose resulted in the highest value of 1/k₁ for WL and WR, and the highest k₂ for SG. Maltitol caused the highest k₁ for SG, but lower 1/k₁ for SG; highest k₂ for WR and highest 1/k₂ for SG and MC. Xylitol resulted in higher k₁ values for WL, MC, and WR, but lower 1/k₁ for WL; lower k₂ for WL and WR, and higher 1/k₂ for WL and WR. Erythritol had a more significant effect on MC, achieving the highest 1/k₁ and highest k₂.

Table II
Model and kinetic parameters and coefficient of determination of the Peleg model.

Responses	Parameters	Sucrose	Maltitol	Xylitol	Erythritol
WL		2.9087	4.8063	9.6346	3.1649
		0.0318	0.0312	0.0233	0.0309
		0.3438	0.2081	0.1038	0.3160
		31.4001	32.0113	42.8964	32.3939
	R2	0.9920	0.9826	0.9975	0.9971
SG		8.2653	17.5437	8.3781	7.5862
		0.3638	0.2508	0.2763	0.3267
		0.1210	0.0570	0.1194	0.1318
		2.7491	3.9873	3.6195	3.0611
	R2	0.9565	0.9706	0.9237	0.9781
MC		12.6118	23.7745	27.9314	10.6220
		0.0628	0.0447	0.0616	0.0761
		0.0793	0.0421	0.0358	0.0941
		15.9269	22.3944	16.2401	13.1344
	R2	0.9772	0.9632	0.9935	0.9952
WR		2.7466	4.4240	10.8317	3.3406
		0.0340	0.0339	0.0211	0.0309
		0.3641	0.2260	0.0923	0.2993
		29.3953	29.4829	47.3238	32.3750
	R2	0.9946	0.9894	0.9963	0.9948

The values of WL, SG, efficiency index (EI) of OD, MC, and WR at the end of the osmotic processes are presented in Table III. The use of maltitol and erythritol resulted in osmo-dehydrated banana slices with WL and SG statistically similar to those obtained with sucrose (Table III). Only xylitol led to a lower WL, while SG remained the same.

Table III
Water loss (WL), solid gain (SG), efficiency index of osmotic dehydration (EI), moisture content (MC) and weight reduction (WR) of fresh and after 300 min of OD samples.

Sample	WL (%)	SG (%)	EI	MC (%)	WR (%)
Fresh	-	-	-	72.90±0.38	-
Sucrose	24.85±2.56A	2.75±0.51A	8.80±0.55A	62.94±3.15B+	23.67±0.84A
Maltitol	22.04±0.72A	3.37±0.55A	6.67±0.69BC	64.50±0.63B+	21.15±1.07AB
Xylitol	18.18±2.32B	3.33±1.33A	5.81±1.13C	66.34±1.84A+	17.54±2.01B
Erythritol	24.62±2.39A	3.04±0.81A	8.39±1.42AB	63.59±0.51B+	24.08±3.68A

• Means followed by the same letter vertically do not differ from each other according to Tukey’s test (p<0.05). The plus sign (+) indicates a significant difference between each treatment and the fresh sample, according to Dunnett’s test (p<0.05).

The principal components analysis (PCA) biplot was employed to assess the differences and similarities among the types of osmotic agents used in OD. The first two principal components (PC1 and PC2) explained 55.62% and 35.01% of the total data variance, respectively (Figure 3). Thus, these two main components explained 90.63% of the total variance. PCA effectively distinguished the four treatments studied, as each osmotic agent occupied a quadrant of the biplot (Figure 3). The water activity, shrinkage and hardness values of the fresh and osmo-dehydrated samples are shown in Table IV.

Table IV
Water activity, shrinkage and hardness of fresh and osmotically dehydrated samples.

Sample	Water activity	Shrinkage (%)	Hardness (N)
Fresh	0.953±0.006	-	2.24±0.06
Sucrose	0.917±0.005A+	24.64±5.19A	7.36±0.89A+
Maltitol	0.892±0.017B+	24.14±3.49A	3.12±0.36B
Xylitol	0.924±0.005A+	26.83±1.13A	2.64±0.84B
Erythritol	0.896±0.016B+	25.09±1.17A	3.83±1.64B

• Means followed by the same letter vertically do not differ from each other according to the Tukey test (p<0.05). The plus sign (+) indicates a significant difference between each treatment and the fresh sample, according to the Dunnett test (p<0.05).

Figure 3
Loading and score plots based on principal components analysis (PCA). h*, hue; aw, water activity; C*, chroma; EI, efficiency index of osmotic dehydration; H, hardness; L*, luminosity; MC, moisture content; SG, solid gain; WL, water loss; WR, weight reduction; ΔE, total color difference.

OD, irrespective of the osmotic agent used, significantly reduced (p<0.05) the a_w of the fruit (Table IV). Among the osmotic agents, the use of maltitol and erythritol resulted in lower a_w compared to using sucrose and xylitol.

It was observed that the type of osmotic agent used in the OD of banana slices did not influence the shrinkage, as the results were statistically equal among them (p>0.05) (Table IV).

Fresh banana exhibited a low hardness value (Table IV). Samples subjected to OD using maltitol, xylitol, and erythritol showed hardness values statistically similar to fresh banana. Only the process using sucrose increased the hardness of the sample (p<0.05).

The color responses of the fresh and osmo-dehydrated samples are shown in Table V. The fresh sample exhibited higher L* than all osmo-dehydrated samples (p<0.05). The use of all osmotic agents significantly increased (p<0.05) the C* after OD. The fresh sample exhibited the highest h* value, indicating the characteristic yellow hue of banana pulp. All osmo-dehydrated samples showed lower h* values than fresh banana. Among the osmotic agents, erythritol had the least influence on color, showing the lowest ΔE value, while maltitol resulted in samples with a higher ΔE.

Table V
Colorimetric parameters of fresh and osmotically dehydrated samples.

Sample	L*	C*	h*	∆E
Fresh	77.22±0.21	43.26±0.78	84.52±0.11	-
Sucrose	68.80±0.60B+	51.89±1.01BC+	78.03±0.08B+	13.21±1.09B
Maltitol	54.23±0.82C+	61.44±3.79A+	69.66±0.77C+	32.29±2.61A
Xylitol	68.28±0.20B+	53.03±0.37B+	77.67±0.01B+	14.43±0.38B
Erythritol	75.90±0.06A+	48.43±0.22C+	82.66±0.07A+	5.55±0.17C

• Means followed by the same letter vertically do not differ from each other according to the Tukey test (p<0.05). The plus sign (+) indicates a significant difference between each treatment and the fresh sample, according to the Dunnett test (p<0.05).

The overall desirability values of each treatment are presented in Table VI.

Table VI
Values of overall desirability for each osmotic agent.

Osmotic agent	Overall desirability
Sucrose	0.5607
Maltitol	0.0021
Xylitol	0.0003
Erythritol	0.0440

DISCUSSION

The difference in the concentration of the OS is due to the solutes having different molecular weights (Table I). According to Lewicki & Lenart (2020), the a_w in an OS is influenced by the molecular weight of the solute. The lower the molecular weight of the solute, the higher the osmotic pressure for an equivalent concentration. Therefore, when using a lower molecular weight solute, the resulting OS will be less concentrated, and vice versa, to maintain the same a_w as an OS using a higher molecular weight solute. Other studies of OD have also been carried out using OS prepared with different solutes but with the same a_w (Junqueira et al. 2017, Mavroudis et al. 2012).

Mass transfer (MT)

The exponential behavior of kinetic data (Figure 2) was also observed in other studies (Bialik et al. 2018, Macedo et al. 2022b, 2023a, Mendonça et al. 2017). The driving force of MT that occurs during OD is the osmotic pressure gradient between the OS and the material. At the beginning of OD, this gradient is greater, decreasing throughout the process as water from the cellular tissue migrates to the OS, diluting it, and the OS solute impregnates the material (Abrahão & Corrêa 2023), causing MT rates to reduce until a steady state occurs.

There are several factors that influence MT during OD, whether they are related to the food matrix, process conditions, or the OS (Asghari et al. 2024, González-Pérez et al. 2021). In the present study, the first two groups of factors were the same for all treatments. Regarding the OS, the type of solute, viscosity, and concentration are the properties that influence the MT rate (Asghari et al. 2024). There is variation in the type of solute as well as the viscosity of the OS. However, viscosity is closely related to the type of solute, as it tends to be lower in OS made with solutes of lower molecular weight (Assis et al. 2017, Zacharis 2012). The concentration dictates the osmotic pressure of the OS (Asghari et al. 2024), which were designed to have a_w values that were statistically equal to each other (Table I).

As reported in some studies (Brochier et al. 2015, González-Pérez et al. 2021, Mendonça et al. 2017, Yao & Le Maguer 1997), OS made with a low molecular weight solute promote SG, as smaller molecules diffuse more easily through the product matrix, causing greater impregnation of the solute. In contrast, high molecular weight solutes are useful for WL purposes, i.e., dehydration, as they tend to be retained on the tissue surface, resulting in a lower SG.

Furthermore, it can be observed that WL values continued to increase even after hours of OD. On the other hand, SG showed a higher MT rate in the first hours of the osmotic process and more quickly reached values close to those observed at the end of OD (Figure 2b). This suggests that the total process time can be adjusted according to the objective of the study; OD of banana slices with a shorter duration favors the impregnation of solutes, while longer processes are useful for dehydration purposes.

The MC reduction (Figure 2c) occurs due to WL and SG. These processes led to the removal of free water from the food matrix and increased the dry matter content of the product. These same phenomena resulted in an increase in WR over time (Figure 2d), as WL exceeded SG throughout the entire process.

The Peleg model is commonly used to represent and explain processes involving MT kinetics due to its simplicity and excellent capability to adequately represent data from OD of fruits and vegetables (Macedo et al. 2023a). This can also be observed in the present study, where the Peleg model exhibited a coefficient of determination (R2) greater than 0.95 (Table II).

The parameter k₁ represents the MT rate constant, indicating how quickly the solute is transferred from the solution to the sample during OD, and 1/k₁ indicates the initial rate of mass transfer, highlighting how rapidly the process initiates at the beginning of OD. The parameter k₂ denotes the MT capacity, reflecting the maximum amount of solute that can be transferred to the sample under equilibrium conditions. Similarly, 1/k₂ represents the estimated value under equilibrium conditions (Mendonça et al. 2017, Peleg 1988).

Sucrose, which exhibited the highest 1/k₁ for WL and WR and the highest k₂ for SG, suggests a rapid initial water loss and a high equilibrium uptake of solute in these conditions. Maltitol, on the other hand, led to the highest k₁ for SG but a lower 1/k₁ for the same parameter, indicating a rapid solute transfer but a slower initial mass transfer rate. Additionally, its highest k₂ for WR and highest 1/k₂ for SG and MC suggest a higher equilibrium retention of solute. Xylitol, which resulted in higher k₁ values for WL, MC, and WR but lower 1/k₁ for WL, suggests a more effective penetration rate but a reduced initial water removal. The lower k₂ for WL and WR, combined with higher 1/k₂ for these conditions, implies that xylitol limits the equilibrium solute uptake while still promoting water loss. Erythritol’s significant effect on MC, characterized by the highest 1/k₁ and k₂, suggests an accelerated initial mass transfer and a greater solute retention capacity in this condition. These findings reinforce that mass transfer behavior during osmotic dehydration is highly dependent on the type of osmotic agent used, as different solutes exhibit distinct affinities for water and varying diffusion capacities, ultimately influencing both the kinetics and the equilibrium of the process.

The influence of solute type on WL and SG responses (Table III) was observed by others authors. Kowalska et al. (2020) studied the OD of apple slices using erythritol, xylitol, and maltitol as alternative osmotic agents to sucrose. It was revealed that erythritol caused the highest WL in the samples, while xylitol resulted in the lowest. Macedo et al. (2022a) used sucrose, maltitol, and erythritol for the OD of strawberries, both with and without a vacuum pulse. It was observed that erythritol also caused the highest WL.

WL was the major MT flux during the OD of banana slices. This is because water permeates more easily through the food matrix than the solute (Macedo et al. 2022a). When OD is employed as a pre-treatment for drying, it is advisable to achieve a product that exhibits higher WL than SG (González-Pérez et al. 2021). Therefore, the WL/SG ratio is used to indicate the efficiency index (EI) of OD. The EI values at the end of the OD processes (Table III) were similar to those observed in other studies (Kowalska et al. 2020). It was observed that sucrose and erythritol had statistically similar EI, while xylitol had the lowest EI among the osmotic agents. Therefore, for the purpose of dehydration, sucrose and erythritol are recommended for the OD of banana slices.

After OD, the MC of the samples showed a significant reduction compared to fresh banana (Table III), with erythritol, maltitol, and sucrose resulting in samples with statistically similar MC, all lower than those treated with xylitol. The use of other osmotic agents instead of xylitol increased the reduction in MC by up to 51.89%. This outcome is due to the lower WL achieved using xylitol. Similarly, erythritol, maltitol, and sucrose resulted in WR that were statistically equal to each other after OD (Table III).

The use of sucrose tended to be associated with higher values of WL, WR, and EI, and lower values of SG and MC (Figure 3). Among the other solutes, erythritol was the one that most closely approached sucrose in terms of MT, as can be observed in Table III and Figure 3.

Water activ_ity (aw)

The a_w signifies the availability of water for chemical reactions, enzymatic activities, and microbial growth. Therefore, it is an important quality parameter in food products (Alp & Bulantekin 2021).

Fresh bananas showed a high a_w value (Table IV), indicating their high perishability, combined with the fruit’s high respiration rate. The reduction caused by OD (Table IV) is attributed to the solids uptake and WL that occur during this process, thereby decreasing the free water available in the material (Abrahão & Corrêa 2023, Mendonça et al. 2017). However, the a_w values of the osmo-dehydrated samples still remained relatively high, which does not ensure product stability over long periods, as characteristic of the OD process (Abrahão & Corrêa 2023). Therefore, OD is often applied as a pretreatment in various processes, including refrigeration, freezing, convection drying, freeze-drying, vacuum packaging, canning, food irradiation, and the addition of preservatives or inert gases such as nitrogen and carbon dioxide, aiming to contribute to the preservation of the product (Yadav & Singh 2014).

The influence of the osmotic agent on a_w depends not only on SG and WL, as discussed earlier, but also on the alteration of the food’s composition and structure, influencing the nature and intensity of chemical interactions between the solute and other constituents of the product (Damodaran & Parkin 2017, Macedo et al. 2021b). Polyols have a higher number of hydroxyl groups compared to sucrose, which favors the formation of hydrogen bonds with water, reducing the fraction of free water and consequently the a_w of the product. However, the use of xylitol did not result in a lower a_w than that observed with sucrose, as it led to a smaller reduction in MC due to low WL (Table II). Although the MC of the sample treated with xylitol was higher than that obtained with sucrose, the a_w was statistically equal (Table IV), highlighting the potential of polyols to enhance interactions with water molecules (Grembecka 2015).

Shrinkage

Shrinkage is an important quality attribute of osmo-dehydrated foods because it refers to how much the volume of the material decreases, which directly affects the product’s appearance. It is one of the physical changes caused by MT processes during the OD process (Farhaninejad et al. 2017, Macedo et al. 2023b). The removal of moisture from food creates an imbalance in pressure between the interior and exterior. This imbalance generates contraction stresses, causing significant changes in cellular structure such as wall deformation, separation of the middle lamella, membrane rupture, and primarily tissue shrinkage, leading the material to shrink or collapse (Abrahão & Corrêa 2023, Nahimana et al. 2011). Rarely does shrinkage of a food during OD occur isotropically. Typically, shrinkage results in product deformation. Therefore, shrinkage should be minimized (Macedo et al. 2023a).

Macedo et al. (2023a) also observed that the type of osmotic agent did not influence the shrinkage of strawberry cubes subjected to OD using sucrose and coconut sugar.

Hardness

Hardness can be defined as the force required to deform a material between molars and is therefore another important parameter of food quality (Macedo et al. 2021a).

The low hardness value of fresh banana (Table IV) is characteristic of the pulp of this fruit (Al-Dairi et al. 2023, Verma et al. 2014). This indicates the physical fragility of the banana, which, combined with its high a_w value and high respiration rate, makes it a highly perishable fruit. This justifies the study of preservation techniques for bananas.

The incorporated solute tends to concentrate in the superficial layers of the osmo-dehydrated material, which may have resulted in sugar crystallization, leading to increased hardness of the banana slices. Increased hardness can be advantageous as it enhances the material’s protection against structural damage (Abrahão & Corrêa 2023, Farhaninejad et al. 2017).

The relationship between sucrose and the hardness response can be observed in the PCA biplot (Figure 3). Additionally, Figure 3 also illustrates the relationship of hardness with WL, WR, and EI responses, indicating that the increase in hardness of banana slices may be associated with WL.

Color

Color is the first quality parameter of a product that consumers evaluate, directly influencing their choices and preferences. The color of a product is influenced by chemical, biochemical, microbial, and physical changes that occur during processing and storage. It can be used to indirectly estimate other quality attributes due to its simplicity, directness, low cost, and quick measurement (Pathare et al. 2013).

The parameter L* indicates luminosity, assessing color on a grayscale from black (L*=0) to white (L*=100) (Pathare et al. 2013). Other studies have also reported that OD resulted in a reduction of L* in banana samples (Atares et al. 2011, Verma et al. 2014). The reduction in this colorimetric parameter may have been caused by WL and shrinkage, which increase the opacity of the sample (Verma et al. 2014). This can be confirmed by observing the PCA biplot (Figure 3), where L*, WL, and shrinkage are positioned in different quadrants, indicating that higher values of one response are not associated with higher values of the others. Among the osmotic agents, erythritol resulted in the smallest reduction in L*, whereas maltitol led to banana slices with the lowest L*.

The parameter C* represents chroma, which indicates the intensity of the color of the material (Pathare et al. 2013). The use of all osmotic agents significantly increased (p<0.05) the C* after OD (Table V), due to the concentration of the sample caused by the osmotic process. Maltitol was the solute that resulted in a sample with the highest C*, leading to a product with a more intense color, which can contribute to attracting consumers.

Hue angle (h*) defines colors as reddish, greenish, etc., where angles of 0° (or 360°), 90°, 180°, and 270° represent red, yellow, green, and blue hues, respectively. The reduction in hue of osmo-dehydrated samples may have been caused by leaching of pigments (carotenoids) during the osmotic processes, reducing the yellow hue. Oxidation is a reaction that commonly causes color changes in food; however, it may have had little influence even after a long period under relatively adverse conditions (Atares et al. 2011). This is due to the solute impregnated on the surface of the samples, minimizing contact with oxygen (Verma et al. 2014). Among the solutes, erythritol preserved the yellow hue the best, while maltitol resulted in the lowest h* value for the banana slices (Table V).

The total color difference (ΔE) indicates the color difference of a material compared to a standard, which in this study is fresh banana. All ΔE values were greater than 3.0 (Table II), indicating that the color between the osmo-dehydrated samples and the fresh ones was very distinct (Pathare et al. 2013). The same was observed in other studies that performed OD on banana slices (Atares et al. 2011, Farhaninejad et al. 2017).

Erythritol resulted in osmo-dehydrated samples associated with higher values of L* and h* (Figure 3), giving the samples brighter and more yellowish aspects. Maltitol was associated with higher C* values, indicating a sample with more intense color. However, maltitol was the osmotic agent that caused the greatest color change compared to fresh banana.

Optimal condition

The optimal condition was defined according to desirability function, minimizing responses such as MC, SG, WR, shrinkage, a_w, and ΔE, and maximizing WL, EI, hardness, L*, C*, and h*.

Sucrose presented the highest overall desirability value (Table VI) and emerged as the optimal solute, best combining the desired characteristics for osmo-dehydrated banana slices, while erythritol proved to be the best osmotic agent among the polyols used.

CONCLUSIONS

The production of healthier osmo-dehydrated bananas was made possible by using polyols as alternative osmotic agents to sucrose. Sucrose was identified as the optimal solute, and erythritol was the best among the polyols, according to desirability function. The type of osmotic agent used in the osmotic dehydration of banana slices significantly influenced both kinetic and qualitative parameters. Sucrose resulted in samples with higher hardness values, while erythritol led to higher luminosity, increased yellowness, and less color change in the samples. The efficiency of mass transfer during osmotic dehydration was not compromised when using erythritol instead of sucrose. The Peleg model satisfactorily fit the kinetic data and helped elucidate the osmotic process. This study paves the way for further research to explore the influence of erythritol in the osmotic dehydration of other materials and as a pretreatment for other preservation methods, resulting in foods with different and healthier characteristics and properties compared to those using sucrose.

Acknowledgements

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES); and Fundação de Amparo à Pesquisa e Inovação do Espírito Santo (FAPES) – 704/2022.

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Publication Dates

• Publication in this collection
  24 Oct 2025
• Date of issue
  2025

History

• Received
  11 Nov 2024
• Accepted
  7 June 2025