Effective drying processes for Taikor (Garcinia pedunculata Roxb.) fruit by ultrasound-assisted osmotic pretreatment: Analysis of quality and kinetic models

Highlights

• •Combined ultrasound-assisted immersion pretreatments were used prior Taikor drying.
• •Page and Weibull distribution models fitted the best to explain drying kinetics.
• •Immersion pretreatment by 10% glucose solution retained the nutritional quality.
• •Products’ quality gradually degraded as the drying temperature raised from 50 to 70 °C.
• •Higher treatment time and drying temperature showed better microbial load reduction.

Abstract

The present study aimed to analyze and establish an effective combination of ultrasound and immersion pretreatment processes for drying Taikor (Garcinia pendunculata Roxb.) fruits. Taikor slices were first immersed in 10 % sucrose, fructose, and glucose solution. Then, the immersed slices were treated in an ultrasonic bath at 30 °C for 10, 20, and 30 min. Drying operations were carried out at 50, 60, and 70 °C, with a fixed relative humidity of 30 %. The Page, Newton, Henderson and Pabis, and Weibull distribution models were fitted to the obtained drying data to determine the best kinetic model that effectively describes the drying properties of Taikor. After drying operations, changes in quality parameters, e.g., β-carotene, vitamin C, B vitamins, color, antioxidant activities, and microbial loads, were measured to obtain the best drying temperature and the most effective pretreatment combination with minimum loss of nutrients of the sample. Among different kinetic models, both Page and Weibull distribution models showed the best R² values of 0.9867 and 0.9366, respectively. The chemical properties were preserved to the greatest extent possible by drying at 50 °C with glucose pretreatment. The color parameters were better preserved by fructose pretreatment. Sonication time also had profound effect on the quality parameters of dried Taikor slices. However, higher temperature drying required a shorter time for drying and exhibited better performance in microbial load reduction. This study's findings will help to establish an effective drying condition for Garcinia pedunculata fruits.

1. Introduction

Garcinia pedunculata Roxb. is a citrus fruit locally known as ‘Taikor’. It has a sour taste and is well-known for its medicinal properties. Taikor fruit contains vitamin C, vitamin B, and antioxidants [77], [39]. Although it was primarily produced in Myanmar and the north-eastern region of India, like many Asian countries, it has become quite popular in Sylhet region of Bangladesh. People of this region know it as ‘Tenga’, which is popular for its beautiful aroma and used as a flavor in any curry or meal. Also, citrus cuisine uses it frequently due to its powerful therapeutic and nutritional properties [86]. Taikor production increases during the peak season, resulting in a flood of products on the market. As a matter of fact, traditional preservation approaches such as the use of chemical agents like synthetic compounds or adding conventional antimicrobials into food like acetic, benzoic, lactic, propionic and sorbic acids, as well as drying methods etc. are continuously being developed to avert Taikor loss triggered by microorganisms, enzymatic reactions, and chemical interactions [61].

Among these methods, drying is regarded as the most banal yet crucial preservation method for enhancing the shelf life of any fruits or vegetables. It improves the stability of food by removing moisture and inactivating microorganisms. Moreover, it reduces the number of chemical reactions, such as enzymatic browning, which changes the color and quality of fresh produces [16]. Convective hot air drying is the most common technique as it is the cheapest way of drying food products. A heating source is used to warm the supplied air during this process. This leads to even temperature distribution, cleanliness, and superior quality foods with ideal drying kinetics [63]. Although drying has various advantages, it also has some drawbacks. Several physiochemical, structural, color, and nutritional changes are frequently occurred during the drying process [85], [40], [13], [14]. Depending on the type of food, drying technique, level of treatment, and operational parameters, drying can drastically change the chemical structure and nutritional content of food. Food preparation (pre-treatments), drying parameters (especially temperature), and storage conditions can all affect the nutrient content of dried foods [32]. Unfortunately, we cannot overlook this problem; hence, proper design should be implemented before drying.

Different pretreatments have been proven to be very beneficial in overcoming these limitations. Pretreatment before drying can aid in minimizing nutritional loss and, in most cases, keep the structure intact. It prevents the loss of color [20], texture and loss of bioactive components [82]. Now, pre-treatments are typically used to shorten the drying time and accelerate the moisture exchange rate over time [47]. There are numerous pre-treatments, the most well-known of which are osmotic pre-treatment, hot water blanching, ultrasonic treatment, and immersion in various chemical solutions. These are mostly used in various drying situations [3].

Osmotic dehydration or dewatering impregnation soaking (DIS) in concentrated solution has become a common pretreatment in combined techniques over the last few decades [69], [93]. The insertion of solutes into the food material distinguishes DIS from other dehydration processes [89]. In previous studies, osmotic pretreatments were found to be effective in maintaining the physiochemical quality of different fruits and vegetables during drying [93], [85], [14], [13]. Hossain et al. [40] studied the effect of osmotic pretreatment on Garcinia pedunculata drying. They found that fructose-pretreated samples dried at 55 °C retained the maximum physical and chemical quality after drying. However, this was still insufficient to preserve the quality parameters of fruits. Therefore, we decided to use osmotic pretreatment and ultrasonic water bath treatment. Using ultrasonic waves in liquid medium is known as an ultrasonic bath. High-frequency sound waves cause the formation of cavitation bubbles to agitate the liquid in an ultrasonic bath. Using ultrasound in the food processing industries extends shelf life and supports efficient heat and mass transfer [53]; Hoque et al., 2022). Pretreatment using ultrasonic and osmotic solutions improves the quality and safety of food products while reducing processing time and moisture content (Rodríguez et al., 2018a). From a study by Chandra et al. [18], a DCG-150H model from MRC Lab Equipment with a 6 l capacity was employed for the ultrasonic pretreatment at 30 °C with the osmotic solution, and this pretreatment before drying improved the quality of dried papaya slices.

In the literature, no previous study was found where the combination of ultrasonic and osmotic pretreatment was used to preserve the nutritional qualities of Taikor. Hence, in the present study, the osmotic pretreatment process was done using 10% sucrose, 10% fructose, and 10% glucose at a ratio of fruits: solution = 1:4 (w/w) to prevent the solution from being diluted due to osmosis [14], [13]. The samples with the solution were subjected to the ultrasonic water bath. The experiment was conducted at 30±2 °C for 10, 20, and 30 min. Control samples were dipped in only distilled water. Following the pretreatment, convective drying was performed at three temperatures of 50, 60, and 70 °C with a constant 30% relative humidity. The study aimed to investigate the drying effects on Taikor slices with and without osmotic and ultrasonic pretreatment. The drying kinetics were determined by four popular mathematical models. Then, the physiochemical properties of dried Taikor slices were evaluated to identify the best possible treatment.

2. Materials and methods

2.1. Sample preparation

Fresh Garcinia pedunculata fruits were obtained from the Bondor Bazar wholesale market in Sylhet, Bangladesh. After careful visual observation, diseased, defective, or damaged samples were disposed of to reduce biological variability. All samples had the same shape, diameter, and weight upon screening. Before use, samples were thoroughly washed with clean water to remove dust, sand, and other unwanted materials. Then, the samples were peeled, and the core was removed, followed by cutting into 1±0.04 cm thick slices using a stainless-steel knife.

2.2. Osmotic pre-treatment process in ultrasonic water bath (UWB)

After cutting, samples were immediately immersed in beakers with four different solutions of 10% sucrose (S), 10% fructose (F), 10% glucose (G) and water (W) at 25±2 °C. To prevent a significant reduction in osmotic driving force during processing, the solution to solid mass ratio was 4:1 (w/w), avoiding excessive water removal [14], [13]. The beakers containing samples were then placed into an ultrasonic water bath (UWB) (GT Sonic, 6l, 40kHz, 150W, China), where the samples were pre-treated at 30 °C for three different times of 10, 20, and 30 min. The samples were symbolized as S10, S20, S30, F10, F20, F30, G10, G20, G30, W10, W20, and W30 concerning the solution type used and pretreatment time in the ultrasonic water bath.

2.3. Drying process

After pretreatment, the samples were taken out of the water and dried with tissue paper. The samples were then dried in a temperature and humidity-controlled chamber (VS-8111H-150, Vision Scientific Co. Ltd., South Korea), where drying temperatures of 50, 60, and 70 °C and a constant 30% RH were used. The relative humidity (RH) was kept at a minimum level to aid in rapid drying [82], [14], [13]. On the trays, the samples were arranged in a single layer. Drying data were collected at regular intervals until an equilibrium moisture content was achieved for each drying setting. A constant air velocity of 3 ms⁻¹ was maintained for each drying experiment. The moisture content data were recorded at 30 min intervals up to 1h; then, data were taken at 1h intervals until equilibrium moisture content was achieved [43].

2.3.1. Determination of moisture Content

At first, 5 g of the dried samples were kept in an oven dryer (OF-21E, Korea) for 24h at 120 °C. Following that, the dry weight of the samples was determined. The products’ moisture content was then calculated on a dry basis by the following Equation (1) [82]:

$${\mathrm{M}\mathrm{C}}_{\mathrm{d}\mathrm{b}}=\frac{W_w-Wd}{W_d}\times 100$$ (1)

where,MC_db = moisture content in dry basis,

W_w = weight of the sample before drying,

W_d = dry weight of the sample.

2.3.2. Mathematical models

The drying characteristics of Taikor slices were evaluated by different thin layer drying models, namely- Page, Henderson and Pabis, Newton, and Weibull’s distribution model as shown in Table 1:

Table 1.

Mathematical models (Drying Kinetics Models) used in this study.

Model name	Mathematical Formula	References
Page	MR = exp (−ktn)	[65]
Henderson and Pabis	MR = a.exp (−kt)	[34]
Newton	MR = exp (−kt)	[17]
Weibull’s distribution	MR = exp [-(t/α)β]	[92]

Where, k = drying constant (h⁻¹), t = drying time (h), and a and n = drying coefficients, α= scale parameter and β = dimensionless shape parameter.

These models are widely utilized for organic materials and most foodstuffs. These models were developed by simplifying Fick's second law. The model developed by Henderson and Pabis is the initial step in the process of finding a generic series solution to Fick's second law. The Newtonian (Lewis) model is a unity-intercept variation of the Henderson and Pabis’ model. The drying properties of a variety of agricultural products were successfully characterized using the Page model, which is an experimental modification of Newton's model [82]. When the scale parameter α is replaced by 1/k, the Weibull model resembles the modified Page model [11]. According to Weibull's distribution model, probability functions are used to characterize the behavior of complex systems with great flexibility [9]. Among all the mathematical models, one of the simplest equations, the Weibull model, only has shape and time parameters. It was used to describe the drying behavior of particular foods [45]. The moisture ratio (MR) was calculated by Eq. (2):

$$\mathrm{M}\mathrm{R}=\frac{M_t-Me}{M_0-M_e}$$ (2)

where,

MR = moisture ratio (dimensionless).

M_t = moisture content at any given time (g water/ g dry matter).

M₀ = initial moisture content (g water/g dry matter).

M_e = equilibrium moisture content (g water/g dry matter).

2.3.3. Fitting of mathematical models

The determination coefficient (R²), root mean square error (RMSE), reduced mean square of the deviation or reduced chi-square (χ2), and sum of squared error (SSE) were considered to determine the model that can sufficiently explain the fluctuation in Taikor’s moisture ratio data while drying. To determine the quality of the fit, the determination coefficient was employed as the key parameter. The total dispersion between response values and the model fit is reflected by the SSE. To estimate the quality of fit of a data distribution, identify whether a set of data series are independent, and construct confidence intervals around variance, the reduced mean square of the deviation is utilized. The model with the minimum SSE, RMSE and χ2 and maximum R² value was determined to be the best-fitted model. The R², RMSE, SSE, and χ² values were calculated by using Eqs (3), (4), (5), (6):

$$R^2=1-\frac{{\sum }_{i-1}^n{{(MR}_{(exp,i)}-{\mathit{MR}}_{\left(pred,i\right)})}^2}{{\sum }_{i-1}^n{({\mathit{MR}}_{(exp,i)}-\overline{\mathit{MR}})}^2}$$ (3)

$$\mathit{RMSE}=\sqrt{\frac{{\sum }_{i-1}^n{({\mathit{MR}}_{(exp,i)}-{\mathit{MR}}_{\left(pred,i\right)})}^2}{N}}$$ (4)

$$\mathit{SSE}=\frac{1}{N}{\sum }_{i-1}^n{\left({\mathit{MR}}_{(exp,i)}-{\mathit{MR}}_{(pred,i)}\right)}^2$$ (5)

$$\mathrm{\Delta }2=\frac{{\sum }_{i-1}^N{\left(M{R}_{\left(\mathit{exp},i\right)}-M{R}_{\left(\mathit{pred},i\right)}\right)}^2}{N-z}$$ (6)

where

MR _(exp,i) = dimensionless experimental moisture ratio.

MR _(pred,i) = dimensionless predicted moisture ratio.

$\overline{\mathit{MR}}$= mean of all experimental moisture ratios.

N = number of observations.

z = number of constants.

2.4. Physiochemical and nutritional quality analysis

2.4.1. Surface color measurement

A colorimeter (PCE-CSM4, PCE instruments, Germany) was used to measure the surface colors of dried ‘Taikar’ samples. Before the measurements, the apparatus was standardized using a white ceramic plate. Color values (L*, a*, and b*) were determined to compare the color changes between fresh and dried samples. Total color difference (ΔE) was determined following Equation (7), previously used by Lemus-Mondaca et al. [55].

$$\mathrm{\Delta }E=\left[{\left(L_f^{\ast }-L_d^{\ast }\right)}^2+{\left(a_f^{\ast }-a_d^{\ast }\right)}^2+{\left(b_f^{\ast }-b_d^{\ast }\right)}^2\right]$$ (7)

where,

L* = Lightness/darkness,

a* = Redness/greenness, and.

b* = Yellowness/blueness of fresh(f) and dried(d) slices.

Hue and chroma of the sample were determined using Eqs. (3), (4):

$$\mathrm{Hue}\mathrm{Angle}={\mathit{tan}}^{-1}\left(\frac{b^{\ast }}{a^{\ast }}\right)$$ (8)

$$\mathrm{C}\mathrm{h}\mathrm{r}\mathrm{o}\mathrm{m}\mathrm{a}=\sqrt{\left\{{\left(a^{\ast }\right)}^2+{\left(b^{\ast }\right)}^2\right\}}$$ (9)

2.5. Determination of bioactive compounds

2.5.1. Determination of B vitamins

Different B vitamins were measured spectrophotometrically in fresh and pre-treated dried samples based on the methods compiled by Fernandes et al. [26]. At first, a 0.5 g sample was mixed with 10 mL distilled water and homogenized for 2 min. The mixture was then mixed with 0.25 M (1 mL) sulfuric acid and placed in a water bath for 30 min at 70 °C. Following that, the pH of the extraction liquid was adjusted to 4.5 by using 0.5 M NaOH solution. After that, the solution was placed in an ice bath. The extraction material was then centrifuged for 25 min at 4000 rpm using a benchtop centrifuge (416G, Gyrozen-Benchtop centrifuge, Korea) followed by filtration. After B vitamins were extracted from the supernatant, the absorbance measurements were taken at 254 nm (B₁), 320 nm (B₂), 265 nm (B₃), and 201 nm (B₆) in a UV–Vis spectrophotometer (T60U, PG instruments limited, UK). Pure thiamine hydrochloride (B₁), riboflavin (B₂), nicotinamide (B₃), and pyridoxine (B₆) were used to create calibration curves.

2.5.2. Determination of ascorbic acid (Vitamin C)

The vitamin C concentration was measured spectrophotometrically in the fresh and pre-treated dried samples based on the process used by Keran et al. [49] after a slight modification. A 1.0 g sample was mixed with 10 mL of 0.056 M sodium oxalate and homogenized for 2 min. The extraction liquid was let to rest for 5 min. Then, the homogenate was filtered, and 0.5 mL aliquot was taken in a separate test tube and diluted to 5.0 mL with 0.056 M sodium oxalate. The absorbance measurements were taken at 266 nm by a UV–Vis spectrophotometer (T60U, PG instruments ltd, UK) using 0.056 M sodium oxalate as a blank. The calibration curve of y = 0.0052x + 0.0161 was prepared for calculation, where L-ascorbic acid was used as standard.

2.5.3. Determination of β-Carotene

The concentration of β-Carotene in Taikor samples was measured by soaking 1 g of dried material and homogenized in 10 mL of distilled water for 2 min. Then, 0.5 mL hexane was added, and the mixture was vigorously agitated for 1 min before being put aside for 5 min to improve mass transfer and then vigorously mixed again for 1 min. Total carotenoids were measured spectrophotometrically at 452nm in the supernatant [79]. The analysis took place in triplicate, and the findings were reported as mg/100 g dry weight based on the developed standard carotene calibration curve, y = 0.5448x + 0.0118.

2.6. Determination of antioxidant properties

2.6.1. Total phenolic content (TPC)

The Folin-Ciocalteu technique was used to measure the total phenolic content in the extracts as reported by Himel et al. [35], with minor changes. Exactly 2.0 mL of 1 M Folin-Ciocalteu reagent and 1.0 mL aliquot of the methanol extract or blank or serial concentration of standard gallic acid were mixed and the mixture was allowed to rest for 5 min. Then 2.0 mL of 7.5 % (w/v) sodium carbonate was added to the mixture. The mixture was thoroughly mixed, then held at a temperature of 25±2 °C for 30 min followed by centrifugation for 10 min at 2,000 rpm (416G, Gyrozen-Benchtop centrifuge, Korea). The supernatant absorbance was taken at 765 nm against a reagent blank in a UV–Vis spectrophotometer (T60U, PG instruments ltd., UK). The TPC of the extract was calculated using the gallic acid standard curve, y = 0.0495x − 0.0195 and reported as gallic acid equivalents (mg GAE/100 g).

2.6.2. Total flavonoid content (TFC)

The total flavonoid content was measured using the procedure of Rahman et al. [68] with some modifications. At first, 0.5 mL of extracted methanol solutions were mixed with 2.0 mL distilled water and 0.15 mL of 5 % sodium nitrate solution for 6 min. Then, 0.15 mL of 10% aluminum chloride solution was added to the mixture for 6 min. After that, 2 mL of sodium hydroxide (4%) was added to the mixture. The solution was made up to a total volume of 5 mL by adding distilled water, and it was left to stand for 15 min. The absorbance at 510 nm was determined using UV–Vis spectrophotometer (T60U, PG instruments ltd, UK). Results were calculated as quercetin equivalent (mg QE/100 g) of the sample using the standard curve, y = 0.004x + 0.0234.

2.6.3. DPPH radical scavenging activity

The 2,2-diphenyl-2-picryl-hydrazyl (DPPH) radical scavenging assay was employed to assess the antioxidant activity of the extract [5]. Briefly, 2 mL of the methanol solution of the extract was mixed with 3 mL of a 6×10^-5 M methanol solution of DPPH in cuvettes. The mixtures were then left in the dark for 30 min. A change in color from purple to yellow indicated the progress of a reaction in a solution of DPPH that was recorded using a UV–Vis spectrophotometer (T60U, PG Instruments Limited, UK) at a wavelength of 517 nm (A₁). The absorbance of a control blank solution without the extract was recorded and noted. The sample’s DPPH radical scavenging capacity was determined using Equation (10):

$$\mathit{DPPH}radicalscavengingactivity\left(\%\right)=\left[\frac{\left(A_0-A_1\right)}{A_0}\right]\times 100$$ (10)

where,$A_0$= the absorbance of control at initial time

$A_1$= the absorbance of sample.

The ability of the sample to scavenge the DPPH free radical was measured as an EC₅₀ value. The EC₅₀ values, expressed in mg/mL, were calculated from equation (10) and represented the amount of the sample required to prevent 50% of the DPPH radical scavenging activity. A graph of antioxidant properties (%) against sample concentration (mg/mL) were used to calculate the EC₅₀ value.

2.7. Determination of microbial load

The microbial count was used to determine the bacterial and fungal counts in dried samples. Rose Bengal Chloramphenicol agar (HiMedia, India) was used to determine the fungal load. The total bacterial count was done using standard plate count agar (Oxoid, UK). In 1 l of saline water, 18 g agar was dissolved. The sample (1 g) was poured into a test tube, previously filled with 9 mL of 0.89% autoclaved saline solution (0.89% NaCl). The bacterial and fungal counts were determined using the serial dilution approach. Each Petri dish with solidified agar media (20–25 mL) was inoculated with 100 µL of diluted solutions extracted from various materials. After inoculation, Petri plates were incubated at 37 and 30 °C, for bacteria and fungi, respectively in a laboratory incubator (IGS60, Thermo Fisher Science Inc., Germany). The incubated bacterial and fungal plates were allowed to grow for 24 and 72h, respectively. Finally, the bacterial and fungal count was done using a digital colony counter (BEXCO 220 V) [93].

2.8. Statistical analysis

All the experiments were conducted in triplicates and the results were presented as the average ± standard deviation, calculated using SPSS version 22.0 from Chicago, IL, USA. One-way analysis of variance (ANOVA) followed by Duncan’s multiple range test (DMRT) was performed. The significance of the results was determined at a 95% confidence interval and considered significant if p < 0.05.

3. Results & discussion

3.1. Drying behavior of ‘Taikor’ slices

The fresh and pre-treated Taikor samples were dried at 50, 60, and 70 °C. The drying curves in Fig. 1 represent the drying characteristics of Taikor slices as moisture ratio (kg H₂O/kg dry mass) vs drying time (h). Drying times were found to vary depending on the type of pre-treatment used in conjunction with the temperature at which the product was dried. The drying time vs. moisture ratio curves indicate that the time needed to reach a safe moisture ratio varies greatly based on the pre-treatments and drying temperatures. Early in the drying process, the moisture removal rate was extremely high. More than 50% of the initial moisture was removed within the first 1h in all the cases. Following that, the rate greatly declined over time (p<0.05). It was observed from the drying curves that treated samples dried more quickly than untreated samples. Pretreatment-assisted drying showed a quicker drying time to reach the equilibrium state than the untreated samples. The increase in drying temperature from 50 to 60 °C sped up the drying process.

Fig. 1.

Drying behavior of the osmotic and ultrasonic water bath pre-treated Taikor slices dried at 50 (a-c), 60 (d-f), and 70 °C (g-i) temperatures.

Figs 1(a)–(c) represent the effect of the osmotic pre-treatment on the moisture ratio of Taikor at a constant temperature of 50 °C and ultrasonic water bath pre-treatment in different time scales of 10, 20, and 30 min. There was constant decline in MR until 4h before became plateau until equilibrium moisture content was achieved. Then Figs 1(d–f) and 1(f–h) show the same analysis at 60 and 70 °C, respectively. In comparison to drying at 60 and 70, 50 °C required a longer drying time. At 70 °C, the moisture ratio became minimum withing 2–3h of drying operation. An imbalance in water vapor pressure was identified as one of the factors that accelerated drying because it led to a significant increase in moisture diffusivity at high temperatures, as reported by Methakhup et al. [57]. From Fig. 1, it was found that most of the time, fructose and sucrose samples showed better drying rate compared to the other samples. The fructose pre-treated samples dried more quickly when Citrus macroptera and Garcinia pedunculata, respectively, were dried in earlier experiments by Roy et al. [82] and Hossain et al. [39]. In a recent study, Rani and Tripathy [71] observed a reduction in the drying time from 10.5 to 8.0h when pineapple slices were osmotic pre-treated with potassium metabisulphite (KMS) solution. Trehalose pretreatment was also found to significantly shorten the drying time for several fruits [6]. The higher moisture diffusion rate may be the reason why osmotic pre-treatment significantly affected Taikor’s drying rate.

In Fig. 1, at 50 °C, water-treated samples showed a lower drying rate, but as the temperature rose from 60 to 70 °C drying rate increased for water pretreated samples as moisture content decreased gradually. Rahaman et al. [67] observed increased moisture reduction during ultrasound-assisted osmotic dehydration of plum fruits. The moisture content of ultrasound (US) assisted osmotic pre-treated dried saturn peaches was lower compared to the control sample [33]. Numerous investigations have reported similar behaviors, such as for pumpkins [54] and plums [67]. This procedure is connected to the cavitation brought on by US waves, which break down tissue cells and generate microscopic channels when combined with osmotic pressure. This increases the amount of water that leaves the fruit tissue and enters the osmotic solution [29]. Numerous additional elements influence moisture reduction, such as the duration of ultrasound exposure, voltage applied, food product composition, osmotic solution concentration, and solute concentration [58], [8].

Sonication typically has a good effect on shortening the drying time used after osmotic treatment. For instance, it was observed that applying ultrasonication with and without an osmotic dehydration procedure considerably sped up the drying process for pineapple [19]. Furthermore, Nowacka et al. [62] investigated the impact of the duration of ultrasound treatment (10, 20, 30, 45, and 90 min) in water and osmotic solution on water diffusivity, sugar loss, and water loss during papaya dehydration. They claimed that sonication reduces the drying time by around 16% and has a good impact on the effective diffusivity of water. The data also indicate that papayas lost 13.8% of their sugar content after 30 min of sonication, which can be used to develop low-sugar dried fruit snacks [62]. Numerous studies have found that ultrasound assisted osmotic dehydration followed by drying is a constructive approach because the osmotic dehydration process usually takes place before drying [58], [8], [62].

3.2. Fitting of mathematical models of Taikor slices for drying Kinetics

The four mathematical models, such as the Page model, Newton’s (Exponential) model, Henderson and Pabis’ model, and Weibull’s distribution model were used to describe the drying process of Taikor slices. The highest determination coefficient (R²) value and the lowest root mean square error (RMSE), sum squared error (SSE), and mean square of the deviation (χ²) values for modelling were used to select the best model (Table 2). According to Table 2, the determination coefficient (R²) values for the Page model ranged from 0.9824 to 0.9978, while values for Newton's model ranged from 0.1025 to 0.3965, for Henderson and Pabis’ model from 0.0124 to 0.8542, and for Weibull distribution's model from 0.9205 to 0.9876. The root mean square error (RMSE) values for Page, Newton, Henderson and Pabis’, and Weibull models ranged from 0.1120 to 0.1776, 0.1420 to 0.7586, 0.1896 to 0.9865, and 0.1147 to 0.1975, respectively. The chi-square values for Page, Henderson and Pabis’, Newton's, and Weibull's models, respectively, ranged from 0.0128 to 0.0317, 0.1730 to 0.9738, 0.0207 to 0.5760, and 0.0138 to 0.0399. The sum square error (SSE) values for Page, Newton, Henderson and Pabis’, and Weibull models, respectively, ranged from 0.0125 to 0.0315, 0.0320 to 0.5755, 0.1724 to 0.9732, and 0.0131 to 0.0389.

Table 2.

R², RMSE, χ², and SSE values for four different models at 50, 60 and 70 °C drying temperature.

Drying Temperature	Pre- treatment	Page Model (K)				Henderson & Pabis’ Model (a)				Newton’s Model (n)				Weibull distribution
		R2	RMSE	χ2	SSE	R2	RMSE	χ2	SSE	R2	RMSE	χ2	SSE	R2	RMSE	χ2	SSE
Drying at 50 °C	S10	0.9867	0.1142	0.0136	0.0130	0.3256	0.5472	0.2998	0.2994	0.1574	0.2564	0.0660	0.0657	0.9366	0.1277	0.0170	0.0163
	F10	0.9866	0.1147	0.0138	0.0131	0.0145	0.6824	0.4659	0.4657	0.3678	0.3472	0.1211	0.1205	0.9398	0.1684	0.0295	0.0283
	W10	0.9862	0.1174	0.0139	0.0138	0.3689	0.5718	0.3276	0.3270	0.1498	0.4863	0.2371	0.2365	0.9398	0.1875	0.0358	0.0351
	G10	0.9865	0.1196	0.0153	0.0143	0.2610	0.7584	0.5756	0.5752	0.2582	0.2485	0.0620	0.0617	0.9205	0.1482	0.0230	0.0221
	S20	0.9865	0.1139	0.0131	0.0129	0.4589	0.8596	0.7391	0.7389	0.3748	0.1458	0.0217	0.0212	0.9653	0.1354	0.0190	0.0183
	F20	0.9865	0.1147	0.0138	0.0131	0.1477	0.7421	0.5511	0.5508	0.2478	0.1586	0.0256	0.0251	0.9654	0.1284	0.0177	0.0164
	W20	0.9862	0.1198	0.0151	0.0143	0.1456	0.6689	0.4478	0.4474	0.2436	0.1758	0.0312	0.0309	0.9368	0.1473	0.0222	0.0217
	G20	0.9824	0.1169	0.0140	0.0136	0.3569	0.7586	0.5756	0.5755	0.1875	0.5422	0.2947	0.2940	0.9658	0.1196	0.0152	0.0143
	S30	0.9866	0.1147	0.0139	0.0131	0.0124	0.8695	0.7565	0.7561	0.1748	0.4566	0.2090	0.2085	0.9676	0.1358	0.0192	0.0184
	F30	0.9860	0.1120	0.0128	0.0125	0.6458	0.8249	0.6807	0.6805	0.2489	0.3511	0.1238	0.1232	0.9635	0.1924	0.0377	0.0370
	W30	0.9865	0.1175	0.0143	0.0138	0.3354	0.7184	0.5166	0.5161	0.2635	0.3674	0.1355	0.1350	0.9668	0.1147	0.0138	0.0131
	G30	0.9863	0.1198	0.0150	0.0143	0.2928	0.5674	0.3224	0.3220	0.2147	0.2459	0.0613	0.0605	0.9665	0.1975	0.0399	0.0390
	Average ±SD	0.9861 ±0.01	0.1165 ±0.0171	0.0143 ±0.0032	0.0146 ±0.0026	0.2813 ±0.1819	0.7143 ±0.1132	0.5223 ±0.1618	0.5214 ±0.1635	0.2413 ±0.0738	0.3153 ±0.1325	0.1126 ±0.0937	0.1153 ±0.0933	0.9531 ±0.0236	0.1506 ±0.0369	0.0247 ±0.0154	0.0234 ±0.0117
Drying at 60 °C	S10	0.9862	0.1147	0.0138	0.0131	0.3793	0.5806	0.3375	0.3371	0.1789	0.1789	0.0325	0.0320	0.9675	0.1739	0.0311	0.0302
	F10	0.9863	0.1168	0.0138	0.0136	0.7352	0.5456	0.2980	0.2977	0.1475	0.4211	0.1779	0.1773	0.9689	0.1835	0.0340	0.0337
	W10	0.9866	0.1148	0.0139	0.0131	0.3548	0.7681	0.5910	0.5900	0.3478	0.3458	0.1199	0.1196	0.9674	0.1836	0.0341	0.0337
	G10	0.9867	0.1145	0.0139	0.0131	0.2896	0.5842	0.3418	0.3413	0.1424	0.2644	0.0701	0.0699	0.9636	0.1257	0.0162	0.0158
	S20	0.9862	0.1274	0.0168	0.0162	0.3544	0.4877	0.2381	0.2378	0.1397	0.4583	0.2109	0.2100	0.9784	0.1458	0.0222	0.0212
	F20	0.9895	0.1244	0.0159	0.0154	0.4657	0.4592	0.2116	0.2108	0.1496	0.3556	0.1272	0.1265	0.9748	0.1298	0.0174	0.0168
	W20	0.9892	0.1292	0.0169	0.0167	0.2284	0.7458	0.5572	0.5562	0.2766	0.1420	0.0207	0.0201	0.9768	0.1748	0.0311	0.0305
	G20	0.9891	0.1274	0.0167	0.0162	0.0328	0.1896	0.0361	0.0359	0.2745	0.2609	0.0688	0.0681	0.9748	0.1974	0.0399	0.0389
	S30	0.9896	0.1347	0.0183	0.0181	0.6751	0.4152	0.1730	0.1724	0.1983	0.4755	0.2269	0.2261	0.9789	0.1784	0.0322	0.0318
	F30	0.9894	0.1274	0.0167	0.0162	0.5574	0.5874	0.3458	0.3451	0.3149	0.3678	0.1357	0.1353	0.9784	0.1485	0.0227	0.0220
	W30	0.9892	0.1247	0.0159	0.0155	0.3456	0.4583	0.2110	0.2100	0.1449	0.1452	0.0216	0.0210	0.9786	0.1506	0.0233	0.0227
	G30	0.9897	0.1255	0.0161	0.0157	0.4963	0.6852	0.4699	0.4695	0.2763	0.2365	0.0563	0.0559	0.9748	0.1142	0.0139	0.0130
	Average ±SD	0.9883 ±0.0117	0.124 ±0.0165	0.0166 ±0.0016	0.0152 ±0.0009	0.4097 ±0.1921	0.5427 ±0.1641	0.3182 ±0.1636	0.3172 ±0.1651	0.2162 ±0.0735	0.3042 ±0.1234	0.1062 ±0.07	0.1051 ±0.0738	0.9741 ±0.0542	0.1594 ±0.0326	0.0263 ±0.0122	0.0266 ±0.0019
Drying at 70 °C	S10	0.9910	0.1472	0.0221	0.0216	0.6952	0.4852	0.2360	0.2354	0.2499	0.2499	0.0633	0.0624	0.9786	0.1740	0.0308	0.0302
	F10	0.9914	0.1398	0.0198	0.0195	0.4758	0.8546	0.7308	0.7303	0.3452	0.3782	0.1433	0.1430	0.9741	0.1236	0.0163	0.0152
	W10	0.9968	0.1472	0.0224	0.0216	0.6355	0.4157	0.1730	0.1728	0.3965	0.2415	0.0590	0.0583	0.9768	0.1472	0.0224	0.0216
	G10	0.9978	0.1398	0.0199	0.0195	0.2569	0.6895	0.4758	0.4754	0.2749	0.2455	0.0611	0.0603	0.9725	0.1548	0.0241	0.0239
	S20	0.9912	0.1247	0.0159	0.0155	0.2455	0.7422	0.5511	0.5509	0.1965	0.3489	0.1221	0.1217	0.9869	0.1963	0.0391	0.0385
	F20	0.9935	0.1777	0.0317	0.0315	0.2245	0.9863	0.9730	0.9728	0.1798	0.7586	0.5760	0.5755	0.9838	0.1887	0.0360	0.0356
	W20	0.9912	0.1748	0.0307	0.0305	0.4183	0.7852	0.6170	0.6165	0.2486	0.3684	0.1362	0.1357	0.9849	0.1932	0.0385	0.0373
	G20	0.9965	0.1422	0.0206	0.0202	0.1358	0.8452	0.7150	0.7143	0.3418	0.3589	0.1293	0.1288	0.9874	0.1498	0.0230	0.0224
	S30	0.9947	0.1247	0.0157	0.0155	0.5688	0.4711	0.2221	0.2219	0.3644	0.6899	0.4768	0.4760	0.9876	0.1478	0.0221	0.0218
	F30	0.9964	0.1258	0.0159	0.0158	0.8542	0.6892	0.4755	0.4750	0.1025	0.2445	0.0600	0.0598	0.9835	0.1659	0.0283	0.0275
	W30	0.9948	0.1695	0.0290	0.0287	0.4392	0.7845	0.6160	0.6154	0.3677	0.3999	0.1600	0.1599	0.9867	0.1420	0.0209	0.0201
	G30	0.9926	0.1745	0.0305	0.0304	0.1482	0.9865	0.9738	0.9732	0.2541	0.3985	0.1592	0.1587	0.9863	0.1754	0.0311	0.0307
	Average ±SD	0.9937 ±0.0113	0.1493 ±0.0201	0.0235 ±0.0012	0.0232 ±0.0121	0.4258 ±0.2312	0.7282 ±0.1919	0.5623 ±0.2713	0.5637 ±0.2741	0.2774 ±0.0951	0.3901 ±0.1745	0.1791 ±0.1723	0.1788 ±0.1781	0.9821 ±0.0152	0.1635 ±0.0232	0.0282 ±0.0143	0.0274 ±0.0112

The model with the best goodness of fit should have the highest R² and lowest χ², SSE, and RMSE values [31]. Both the Page and the Weibull models correctly predicted the drying behavior of Taikor slices. However, when all the parameters were considered, the Page model was the best-fitted model. In earlier investigations on purple-fleshed sweet potatoes [56] and asparagus roots [50], the Page model was validated as an appropriate drying model to predict the moisture data. According to Rashid et al. [72], the Page model accurately describes the drying process of US and osmotic pretreated sweet potatoes. In a separate study, Hossain et al. [39] found the Page model as the best-fitted model to predict the experimental MR for osmotic pre-treated dried Garcinia pedunculata. Similar results were reported in the literature on the application of the Page model to characterize the drying qualities of foodstuffs for purslane [46], sour-cherry [24], tomatoes [23], pineapple (Ramallo & Mascheroni, 2012a), mango [22], and C. macroptera [82]. These findings underscore the importance of utilizing appropriate mathematical models for understanding the complex mechanisms involved in food drying.

3.3. Changes in color

Table 3 presents the color values of fresh and all dried samples. Color has been identified as one of the most important quality parameters of dry products. From Table 3, the lightness value dropped as the drying temperature increased. The fresh sample’s surface color had the maximum L* value (43.72±0.03), whereas the lowest (33.79±0.12) was in glucose-treated samples dried at 70 °C. The accelerated non-enzymatic browning reactions at high temperatures might be the major cause of reduced L* values at elevated temperatures. This considerable browning reactivity and accelerated crust growth may be caused by exposure to high temperatures, as suggested by many previous studies [25], [84], [14]. The redness/greenness parameter a* and the yellowness/blueness index b* of the samples increase with drying temperature. The highest a* (9.12±0.12) and b* (19.48±0.08) values were found in samples US treated in only water and dried at 50 °C. This finding is nearly equivalent to the results obtained from drying of Taikor and pineapple slices in previous studies by Hossain et al. (2021) and Zzaman et al. [93], respectively. In a previous study, Garcia-Noguera et al. [30] found that osmotic dehydration improves the color retention of strawberries during drying when assisted with US pretreatment. Chroma is the degree to which a color differs from an utterly grayscale image. It reaches the highest possible level of a pure color. The chroma value of a color is how bright and pure it is. Higher chroma values were associated with lower drying temperatures, meaning that lower drying temperatures had less impact on chroma values and thus preserved color purity. In this case, sample F30 showed the highest chroma value (21.51±0.24) when dried at 50 °C. Hue is an essential analytical tool for characterizing color because it reveals how red, yellow, green, or blue a product is, among other attributes. The hue values are measured in the range of 0 to 360°, where 0, 90, 180, and 270° reflect pure red, yellow, green, and blue colors [70]. Customers use this parameter to decide whether a product is acceptable [12]. It is evident from the findings of the study that elevated drying temperatures and prolonged ultrasonic pretreatment durations invariably resulted in a rise in hue angle values. The total color change ($\mathrm{\Delta }\mathrm{E}$) increased with drying temperature, which concludes that high drying temperature has a higher impact on color change. The total color change also increased with the ultrasound treatment time. However, this change shows variability with the types of sugar solution. Overall, fructose showed the lowest change in color, and glucose solution exhibited the highest color change. The colorimetric indices were also affected when osmotic solutions like sugar solution were used instead of distilled water (p < 0.05). Changes in the color index may be influenced by the colorful pigments of osmotic solutions, which can occur as a result of chemical processes like the Milliard reaction between sugar and protein or the formation of melanoidin. According to Aadil et al. [1], glucose and fructose have a more significant role in the synthesis and interactions of color pigments due to their chemical composition.

Table 3.

Color values of fresh and pretreated dried Taikor slices.

Drying Temperature	Sample	L*	a*	b*	Chroma	Hue Angle	$\mathrm{\Delta }\mathrm{E}$
50 °C	Fresh	43.72 ± 0.03b	4.08 ± 0.12 h	18.08 ± 0.17a	18.53 ± 0.32b	77.28 ± 0.18a	---
	S10	42.00 ± 0.10c	7.92 ± 0.23a	15.91 ± 0.21d	17.47 ± 0.11c	65.58 ± 0.13 h	12.01 ± 0.14 l
	F10	45.00 ± 0.21a	8.88 ± 0.11a	18.03 ± 0.28a	20.00 ± 0.15a	63.77 ± 0.15i	8.75 ± 0.18n
	W10	40.00 ± 0.23e	8.43 ± 0.25a	17.04 ± 0.11b	19.01 ± 0.17b	63.67 ± 0.22i	13.12 ± 0.31 k
	G10	41.00 ± 0.15 g	6.24 ± 0.13c	14.14 ± 0.20e	15.45 ± 0.10e	66.18 ± 1.03 g	27.58 ± 0.58d
	S20	46.40 ± 0.12a	8.38 ± 0.13a	16.99 ± 0.15b	18.95 ± 0.23b	63.74 ± 0.26i	8.89 ± 0.30n
	F20	45.00 ± 0.3a	6.86 ± 0.22c	16.94 ± 0.25b	18.27 ± 0.28b	67.94 ± 0.28f	6.33 ± 0.18o
	W20	41.04 ± 0.11d	7.73 ± 0.15a	17.45 ± 0.31b	19.09 ± 0.14b	66.10 ± 0.21gh	11.93 ± 0.61 l
	G20	44.31 ± 0.12b	7.05 ± 0.10b	15.21 ± 0.11d	16.76 ± 0.10d	65.13 ± 0.42j	17.52 ± 0.96 g
	S30	44.40 ± 0.12b	7.08 ± 0.17b	16.16 ± 0.19c	17.64 ± 0.11c	66.35 ± 0.28 g	10.11 ± 0.19 m
	F30	44.70 ± 0.18b	8.12 ± 0.12a	19.48 ± 0.08a	21.51 ± 0.24a	64.90 ± 0.30 h	8.20 ± 0.11n
	W30	44.11 ± 0.24b	7.05 ± 0.25b	16.03 ± 0.26c	17.51 ± 0.29c	66.27 ± 0.41gh	7.55 ± 0.18f
	G30	44.18 ± 0.10b	7.19 ± 0.26b	15.97 ± 0.19d	15.97 ± 0.14d	65.76 ± 0.22gh	14.08 ± 1.17hij
60 °C	S10	40.96 ± 0.08e	5.30 ± 0.23d	12.84 ± 0.21f	13.89 ± 0.11f	67.57 ± 0.13 h	14.86 ± 0.14hi
	F10	43.80 ± 0.13b	6.90 ± 0.11b	17.17 ± 0.28b	18.50 ± 0.15b	68.10 ± 0.15f	9.80 ± 0.18 m
	W10	39.40 ± 0.29f	7.29 ± 0.25b	16.35 ± 0.11c	17.90 ± 0.17c	65.96 ± 0.22 h	13.84 ± 0.31 k
	G10	38.55 ± 0.06 g	3.97 ± 0.33ef	15.14 ± 0.11d	15.65 ± 0.58e	75.30 ± 0.88ab	35.38 ± 0.79b
	S20	40.91 ± 0.23e	6.20 ± 0.13c	14.84 ± 0.15c	16.08 ± 0.23d	67.32 ± 0.26 g	12.05 ± 0.30 l
	F20	42.18 ± 0.33c	5.34 ± 0.22d	15.90 ± 0.25d	16.77 ± 0.28d	71.43 ± 0.28e	11.86 ± 0.18 l
	W20	40.00 ± 0.12e	6.95 ± 0.15b	17.00 ± 0.31b	18.36 ± 0.14b	67.76 ± 0.21 g	12.97 ± 0.61 k
	G20	40.10 ± 0.25e	4.19 ± 0.11e	15.82 ± 0.20d	16.36 ± 0.18d	75.15 ± 0.52ab	28.32 ± 0.51d
	S30	40.02 ± 0.24e	5.10 ± 0.17d	13.09 ± 0.19f	14.04 ± 0.11f	68.71 ± 0.28f	15.36 ± 0.19 h
	F30	43.19 ± 0.21 l	8.14 ± 0.12e	18.30 ± 0.08b	20.02 ± 0.24a	66.02 ± 0.30 g	9.76 ± 0.11 m
	W30	43.00 ± 0.10 g	6.83 ± 0.25b	15.10 ± 0.26d	16.57 ± 0.29d	65.66 ± 0.41 h	11.81 ± 0.18 l
	G30	41.17 ± 0.26d	4.87 ± 0.15e	16.11 ± 0.13c	16.83 ± 0.21d	73.18 ± 0.08d	19.72 ± 0.26f
70 °C	S10	36.17 ± 0.13 h	2.90 ± 0.20 g	10.30 ± 0.31 g	10.70 ± 0.21i	74.27 ± 0.10c	20.30 ± 0.14e
	F10	39.90 ± 0.28f	3.80 ± 0.10f	13.03 ± 0.08f	13.57 ± 0.5 l	73.74 ± 0.12d	15.63 ± 0.18 h
	W10	35.30 ± 0.23i	4.00 ± 0.35e	13.30 ± 0.10f	13.88 ± 0.18f	73.26 ± 0.32d	19.02 ± 0.31f
	G10	37.13 ± 0.13d	3.64 ± 0.10f	12.56 ± 0.21 h	9.81 ± 0.28j	74.39 ± 0.86bc	32.38 ± 0.19c
	S20	34.09 ± 0.22i	3.08 ± 0.23f	9.80 ± 0.14 h	10.27 ± 0.13j	72.55 ± 0.36e	22.16 ± 0.30e
	F20	38.30 ± 0.03 g	2.12 ± 0.12 h	12.84 ± 0.15f	13.04 ± 0.28 g	75.93 ± 0.18b	17.21 ± 0.18 g
	W20	37.17 ± 0.11 h	2.92 ± 0.17 g	14.48 ± 0.21e	14.77 ± 0.34f	78.59 ± 0.22a	16.99 ± 0.61 g
	G20	33.79 ± 0.12j	2.98 ± 0.33 g	10.20 ± 0.40gh	10.62 ± 0.44i	73.71 ± 0.70d	36.91 ± 0.99b
	S30	37.14 ± 0.12 h	2.87 ± 0.28 g	10.84 ± 0.39 g	11.21 ± 0.31i	75.17 ± 0.24b	19.24 ± 0.19f
	F30	39.00 ± 0.28f	5.02 ± 0.20d	16.05 ± 0.29c	16.18 ± 0.22d	72.63 ± 0.30e	14.34 ± 0.11j
	W30	39.18 ± 0.14f	3.10 ± 0.15f	11.14 ± 0.46 g	11.56 ± 0.26i	74.43 ± 0.48bc	17.56 ± 0.18 g
	G30	34.54 ± 0.10i	3.14 ± 0.18d	11.63 ± 0.33 g	12.04 ± 0.56 h	74.89 ± 0.88bc	39.72 ± 0.43a

*The values with the different superscripts in the same column are significantly different from each other.

3.4. Effect of pretreatment on bioactive compounds

3.4.1. Impact on ascorbic acid (Vitamin C)

One of the most important indicators of the nutritional value of a dried food sample is believed to be vitamin C, also known as ascorbic acid. Vitamin C is sensitive to light and heat. In addition to quickly leaching out, it can be depleted when the moisture content of a food evaporates at high temperatures [80]. The fresh Taikor sample had the highest ascorbic acid concentration (147.68 ± 0.19 mg/100 g) (Fig. 2). It was reduced in samples treated at elevated drying temperatures from 50 °C to 70 °C. The maximum amount (130.40 ± 0.51 mg/100 g) of ascorbic acid was found in glucose-treated Garcinia pedunculata dried at 50 °C. In contrast, the minimum concentration (82.89±0.78 mg/100 g) of vitamin C was found in fructose-treated Garcinia pedunculata dried at 70 °C. It was found that the samples with longer ultrasonic and osmotic pretreatment had slightly lower values of ascorbic acid content than short-time treatments. Ascorbic acid may be lost through leaching when Taikor is absorbed in the osmotic solution, as it is a water-soluble vitamin [82]. Furthermore, it is most likely that vitamin C was lost during drying due to the presence of the ascorbic acid oxidase enzyme, which catalyzes the oxidation of vitamin C for breakdown [60]. Previously, the osmotic pretreated tomato samples were found to retain the most vitamin C, and this was because of the proliferating coating on the cut surface of the sample [37].

Fig. 2.

Ascorbic acid (Vitamin C) of Taikor samples dried at 50, 60 and 70 °C.

3.4.2. Impact on β-Carotene (Vitamin A)

Fig. 3 exhibits the results of β-carotene content in osmotic and ultrasound treated dried Taikor samples. β-carotene is a type of hydrocarbon carotenoid that can be converted into vitamin A in the human body, as stated by Hiranvarachat et al. [36]. A fresh Taikor sample has the highest (46± 0.22 mg/100 g) level of β-carotene. The maximum reduction (19.47±0.39 mg/100 g) of β-carotene was identified in sucrose-treated Garcinia pedunculata dried at 70 °C, whereas the minimum reduction (39.49±0.33 mg/100 g) was reported in glucose-treated Garcinia pedunculata dried at 50 °C. Because β-carotene is insoluble in water, it was kept for all the Garcinia pedunculata samples' pre-treatments. According to a previous study, Fernandes et al. [27] also observed a drop in β-carotene concentration in ultrasound-assisted dried apples. Even though Vitamin A is protected from oxidation within the fruit's lipid matrix because of the presence of vitamin E and other antioxidants, the degradation of vitamin A can occur due to prolonged exposure to ultrasound. Since vitamin E has a low retention rate, it was unable to exert its protective function on vitamin A (Fernandes et al., 2015). Furthermore, when the drying temperature was increased from 50 to 70 °C, the vitamin C content in the treated samples decreased. This is due to the fact that ascorbic acid is susceptible to degradation from heat, oxygen, light, and enzymes [51].

Fig. 3.

β-Carotene (vitamin A) of fresh and pretreated Taikor samples dried at different temperatures.

3.4.3. Impact on B vitamins

The quantities of B vitamins in treated Taikor samples, such as thiamine hydrochloride (B₁), riboflavin (B₂), nicotinamide (B₃), and pyridoxine (B₆₎ contents are shown in Table 4. The concentration of different B vitamins in fresh samples were 3.75±0.45 mg/g (B₁), 2.10±0.11 mg/g (B₂), 1.42±0.19 mg/g (B₃), and 1.01±0.11 mg/g (B₆). The B vitamins are known as water-soluble vitamins. Hence, it was crucial to determine if any B vitamins were lost during the dipping pre-treatment process in this study.

Table 4.

Vitamin B_1, B₂, B₃ & B₆ contents of fresh and dried Garcinia pedunculata slices at 50, 60, and 70 °C.

Drying temperature	Sample	Vitamin B1 (mg/g)	Vitamin B2 (mg/g)	Vitamin B3 (mg/g)	Vitamin B6 (mg/g)
	Fresh	3.75 ± 0.45a	2.10 ± 0.11a	1.42 ± 0.19a	1.01 ± 0.11a
50 °C	S10	1.66 ± 0.23d	1.15 ± 0.20d	0.83 ± 0.12c	0.42 ± 0.13b
	F10	2.73 ± 0.22b	1.83 ± 0.16b	1.17 ± 0.32a	0.85 ± 0.34abc
	W10	2.25 ± 0.23c	1.33 ± 0.34c	1.06 ± 0.23b	0.57 ± 0.17c
	G10	2.51 ± 0.27b	1.65 ± 0.17b	1.18 ± 0.26ab	0.65 ± 0.15c
	S20	1.1 ± 0.35f	1.15 ± 0.38d	0.67 ± 0.31 cd	0.49 ± 0.23bc
	F20	2.21 ± 0.23c	1.25 ± 0.23c	1.01 ± 0.19b	0.67 ± 0.21c
	W20	1.82 ± 0.11d	1.01 ± 0.17d	0.77 ± 0.13d	0.43 ± 0.16c
	G20	2.07 ± 0.13c	1.27 ± 0.23c	0.96 ± 0.19bc	0.57 ± 0.24 cd
	S30	0.92 ± 0.11 g	0.75 ± 0.12da	0.49 ± 0.13de	0.29 ± 0.11f
	F30	1.80 ± 0.22d	1.07 ± 0.11d	0.83 ± 0.31 cd	0.67 ± 0.24c
	W30	1.33 ± 0.43e	0.93 ± 0.14d	0.57 ± 0.12ef	0.32 ± 0.12e
	G30	1.47 ± 0.36e	0.95 ± 0.21d	0.64 ± 0.22 cd	0.48 ± 0.10d
60 °C	S10	1.44 ± 0.31e	1.03 ± 0.12d	0.76 ± 0.37d	0.38 ± 0.13e
	F10	2.55 ± 0.26b	1.79 ± 0.09b	1.03 ± 0.30b	0.78 ± 0.12b
	W10	1.91 ± 0.23 cd	1.34 ± 0.24c	0.98 ± 0.22c	0.55 ± 0.17d
	G10	2.54 ± 0.24b	1.39 ± 0.18c	0.95 ± 0.19c	0.66 ± 0.23 cd
	S20	0.92 ± 0.15a	1.03 ± 0.48d	0.67 ± 0.36d	0.38 ± 0.13de
	F20	1.95 ± 0.23 cd	1.55 ± 0.37bc	1.08 ± 0.17b	0.57 ± 0.12d
	W20	1.83 ± 0.11d	1.18 ± 0.13d	0.78 ± 0.18d	0.25 ± 0.07f
	G20	1.97 ± 0.13 cd	1.34 ± 0.11b	0.89 ± 0.23 cd	0.43 ± 0.12de
	S30	0.88 ± 0.17 g	0.65 ± 0.22e	0.56 ± 0.14de	0.28 ± 0.06f
	F30	1.85 ± 0.21d	1.13 ± 0.11d	0.93 ± 0.43bcd	0.54 ± 0.04d
	W30	1.12 ± 0.33ef	0.69 ± 0.24e	0.66 ± 0.24 cd	0.29 ± 0.02f
	G30	1.21 ± 0.24ef	1.08 ± 0.17d	0.76 ± 0.25 cd	0.34 ± 0.08e
70 °C	S10	1.25 ± 0.17a	1.08 ± 0.22d	0.77 ± 0.37 cd	0.43 ± 0.13b
	F10	2.13 ± 0.25c	1.61 ± 0.43b	1.02 ± 0.23b	0.69 ± 0.24bcd
	W10	1.89 ± 0.23d	1.23 ± 0.34 cd	0.97 ± 0.20c	0.45 ± 0.15de
	G10	2.01 ± 0.33a	1.88 ± 0.25b	1.06 ± 0.33b	0.73 ± 0.14bc
	S20	1.07 ± 0.38efg	1.05 ± 0.23d	0.59 ± 0.36cde	0.36 ± 0.03e
	F20	2.03 ± 0.21c	1.34 ± 0.36 cd	0.92 ± 0.19c	0.62 ± 0.20 cd
	W20	1.41 ± 0.15e	0.97 ± 0.13d	0.47 ± 0.11e	0.33 ± 0.10e
	G20	2.01 ± 0.23c	1.63 ± 0.48bc	0.93 ± 0.23c	0.42 ± 0.14d
	S30	0.72 ± 0.22 g	0.68 ± 0.17ef	0.39 ± 0.11f	0.21 ± 0.09ef
	F30	1.92 ± 0.21 cd	0.87 ± 0.23e	0.66 ± 0.25def	0.45 ± 0.12de
	W30	1.31 ± 0.41e	0.65 ± 0.27ef	0.48 ± 0.17ef	0.22 ± 0.07ef
	G30	1.92 ± 0.27 cd	0.47 ± 0.18f	0.49 ± 0.12ef	0.22 ± 0.05f

* The values with the different superscripts in the same column are significantly different from each other.

Table 4 shows that the amounts of vitamins B₁, B₂, B₃, and B₅ gradually decreased at higher drying temperatures. According to research conducted by Kadakal et al. [44], thiamin (also known as vitamin B₁) is highly sensitive to heat and can be described using first-order kinetic reactions. In this study, thiamin content was reduced from 3.75 mg/g in fresh sample to 0.72 mg/g for sucrose pretreated sample dried at 70 °C. The increase in temperature was observed to result in the reduction of Vitamin B₂, B₃, and B₆. This reduction of B vitamins in fresh fruit samples after drying has been supported by multiple prior studies [28], [93], [40]. Vitamins B₁, B₂, B₃, and B₆ may also be lost due to leaching into sugar solutions during the pre-treatment process. Additionally, it is possible that the high drying temperature after osmosis and UWB pre-treatment may contribute to the loss of these vitamins [52]. The low thermolability of these vitamins caused a significant reduction in their concentration during the drying process, which was accelerated with increasing drying temperatures from 50 to 70 °C. The results also reflect that the B vitamins concentration was decreased at higher US treatment time. The use of ultrasound might increase the availability of vitamins B₁, B₂, B₃, and B₆ in their free form by releasing the vitamin from its protein, membrane, or apoenzyme-bound state [78].

3.5. Antioxidant properties

3.5.1. Total phenolic content (TPC)

The antioxidant properties of fruits are mostly linked to their phenolic compounds [66]. From Fig. 4, the amount of TPC in the fresh Taikor samples was 18.45±0.12 mg/100 g, and after drying, the highest loss of TPC was found in 30 min glucose pretreated samples (7.94±0.55 mg/100 g) when dried at 70 °C. Compared to other samples, fructose-pretreated samples showed better TPC retention when dried at low temperatures. The TPC values decreased substantially with the increasing temperature. In previous research, Vega-Gálvez et al. [90] observed that the TPC in dried apples reduced as the drying temperature increased. The TPC loss at higher temperatures could be attributed to several causes. For instance, drying temperatures, various drying techniques, and earlier pretreatments all have a negative impact on TPC stability in food [37]. The significant TPC loss that was observed could be attributed to the Taikor samples' degraded cell walls, which accelerate a greater transfer of vacuolar liquid to the osmotic solution [93]. Additionally, a lack of oxygen during the osmotic pretreatment procedure may cause the lowest TPC in the sample pretreated with glucose [64].

Fig. 4.

TPC of pretreated Taikor samples dried at 50, 60, and 70 °C.

Moreover, the decrease in TPC concentration may have resulted from ultrasonic cavitation, which hastened the movement of certain minor constituents in the food, mainly soluble nutrients from the sample, and created microspores (channels) during the pretreatments, as stated by Ren et al. [73]. Multiple studies suggested that the use of ultrasound in osmotic dehydration led to an increase in the transfer of phenolic compounds from the fruit tissue to the osmotic solution [73], [83]. This movement might be associated with the lower phenolic content of the fruits samples with longer US treatment. According to research, the drying procedure affects the phenolic compounds and their antioxidant effects in some murtilla fruits [75], [10]. Almeida et al. [7] also claimed that osmotic dehydration preserves the bioactive chemicals of fruits.

3.5.2. Total flavonoid content (TFC)

Heat-sensitive substances known as flavonoids have antioxidant properties. Fresh Taikor sample showed the maximum TFC value (17.77±0.28 mg/100 g), which was decreased after pretreatment and as the temperature increased from 50 to 70 °C (Fig. 5). Fructose and sucrose pretreated samples showed better retention of phenolic substances. Glucose pretreated Garcinia pedunculata dried at 70 °C exhibited the most significant loss (3.94±0.06 mg/100 g), while fructose treated sample dried at 50 °C showed the minimum loss (12.03±0.05 mg/100 g). The reduction in total flavonoids at higher temperatures may be due to the breakdown of flavonoids at high heat. The breakdown of cell walls caused by increased temperature results in the release of hydrolytic and oxidative enzymes, which can damage the antioxidant activity of food [21]. During heat treatment, the structural transformation of flavonoid molecules may also affect the total antioxidant activity of dried products [41], [38].

Fig. 5.

Total flavonoid content of Taikor samples at different temperatures.

However, the TFC did not vary much among the treatment duration, meaning that the phenolic compounds were not readily soluble in water. In a study by Abbaspour-Gilandeh et al. [2], it was found that ultrasonic waves cause the release, modification, and denaturation of particular enzymes that act on polyphenolics. They found that by subjecting hawthorn fruit to ultrasonic pretreatment before drying, the amount of TFC present was significantly increased in comparison to using hot air drying alone.

3.5.3. DPPH radical scavenging activity

Phenolic compounds exhibit distinct properties depending on osmotic solution concentration, ultrasound, oxygen, temperature, and other variables. They also have a considerable antioxidant ability. The increases in the antioxidant activity of the pretreated samples exhibited variations similar to those in the TPC. Reduction in water content and increase in soluble solids are often connected with the leaching out of water-soluble, and low molecular components in sample extract, which include chemicals contributing to the antioxidant activities [59], [48]. The DPPH free radical scavenging activity was employed to assess the antioxidant activity. The ability of various antioxidative substances to donate electrons can be quickly assessed using the DPPH radical scavenging activity assay [76].

According to Fig. 6, in comparison to the fresh sample, the free radical scavenging activity of dried samples was considerably lower. The highest EC₅₀ value (67 ± 0.06 g/100 g) was observed in fresh Taikor sample. The minimum EC₅₀ value (16.40 ± 0.23 g/100 g) was found in the glucose-treated sample dried at 70 °C. Fig. 6 represents that the DPPH radical scavenging activity retained better at low drying temperatures. The reduced DPPH antioxidant activity determined by osmotic pretreatment in US bath is in agreement with the findings stated by Romero and Yépez [81]. They found that sonicating Andean blackberries in distilled water for 30 min at a frequency of 24 kHz reduced their antioxidant activity. This decline was attributed to the fruit's antioxidative compounds migrating into the liquid medium and to changes in the fruit peel that promote the transfer mechanism of its components to the liquid by decreasing resistance (Pirce et al., 2021b). Adiletta et al. [4] and İzli [42] found similar results for grapes and dates, respectively.

Fig. 6.

DPPH radical scavenging activity of Taikor samples dried at different temperatures.

However, the antioxidant activity of the Taikor slices was shown to be better retained after the dipping pretreatments. In earlier research, Hossain et al. [40] and Zzaman et al. [93] observed a comparable impact of high temperature drying on the antioxidant activity of dried pineapple and Gracinia pendaculata, respectively, that had undergone osmotic pretreatment and showed similar characteristics.

3.6. Microbial load

The microbial load in the dried product defines the standard sanitation level. Fruits are dehydrated to enhance the shelf life. Table 5 shows the microbial load in fresh Taikor samples under various treatment settings and after drying. Fresh Taikor samples had bacterial and fungal counts of 5.50±0.06 and 6.66±0.10 log (CFU/g), respectively. In certain situations, the microbial load steadily dropped as the drying temperature increased. The bacterial cell's ability to survive was affected by the pretreatment solutions as well. During pretreatment with the osmotic solution, dehydration of bacteria cells is possible, which can cause protein denaturation, RNA and DNA breakage, cell wall destruction, and modification of cytoplasmic membrane [15].

Table 5.

Microbial load of fresh and dried Garcinia pedunculata slices with different pretreatments and drying temperatures.

Drying temperature	Sample	Bacterial Count log (CFU/g)	Fungal Count log (CFU/g)
50 °C	Fresh	5.50 ± 0.06a	6.66 ± 0.10a
	S10	4.43 ± 0.20b	6.19 ± 0.18a
	F10	4.38 ± 0.1b	5.98 ± 0.15a
	W10	5.69 ± 0.14a	6.57 ± 0.4a
	G10	4.32 ± 0.62b	5.73 ± 0.07b
	S20	4.31 ± 0.23b	6.08 ± 0.33 g
	F20	4.36 ± 0.52b	5.86 ± 0.28b
	W20	5.61 ± 0.23a	6.48 ± 0.1i
	G20	4.31 ± 0.13b	5.71 ± 0.6b
	S30	4.07 ± 0.16bc	5.99 ± 0.37a
	F30	4.27 ± 0.24b	5.89 ± 0.70ab
	W30	5.60 ± 0.37a	6.35 ± 1.30a
	G30	4.29 ± 0.02b	5.63 ± 1.18abc
60 °C	S10	3.94 ± 0.32bc	4.98 ± 0.21c
	F10	3.87 ± 0.41bc	4.40 ± 0.35a
	W10	4.58 ± 0.18b	5.17 ± 0.3c
	G10	3.71 ± 0.51 cd	4.27 ± 1.21de
	S20	3.92 ± 0.56bc	4.97 ± 1.43c
	F20	3.80 ± 0.31c	4.34 ± 0.48f
	W20	4.55 ± 0.02b	5.15 ± 1.03c
	G20	3.69 ± 0.03d	4.23 ± 1.36 k
	S30	3.90 ± 0.16bc	4.97 ± 0.7c
	F30	3.80 ± 0.14c	4.30 ± 1.37 l
	W30	4.50 ± 0.7b	5.14 ± 0.47c
	G30	3.65 ± 0.14 cd	4.20 ± 1.56de
70 °C	S10	3.07 ± 0.52d	3.40 ± 0.13e
	F10	3.39 ± 0.3d	3.19 ± 1.55def
	W10	3.97 ± 0.8bc	4.08 ± 1.6ef
	G10	3.32 ± 0.27d	3.07 ± 1.39ef
	S20	3.01 ± 0.6b	3.38 ± 1.02ef
	F20	3.37 ± 0.10d	3.19 ± 0.9 fg
	W20	3.96 ± 0.3bc	4.06 ± 1.22def
	G20	3.31 ± 0.8d	3.04 ± 0.6efg
	S30	3.00 ± 0.34e	3.33 ± 1.3defg
	F30	3.36 ± 0.9d	3.14 ± 1.21efg
	W30	3.95 ± 0.01bc	4.00 ± 1.7def
	G30	3.30 ± 0.38d	2.99 ± 1.0efg

* The values with the different superscripts in the same column are significantly different from each other.

From Table 5, the maximum value (5.69±0.14 log CFU/g) of the bacterial count was found in W10 sample, and the highest value (6.57±0.4 log CFU/g) of the fungal count was also seen in W10 treated sample when dried at 50 °C. Almost all dried samples showed a significant impact of drying temperatures on the fungal load count. At 70 °C drying temperature, the water-treated sample exhibited the lowest microbial load, which was of 3.00±0.34log CFU/g. The lowest fungal count (2.99±1.0 log CFU/g) was found for G30 sample dried at 70 °C.

The increased drying temperature helped to reduce the fungal load in the dried Taikor sample. It is worth noting that ultrasonic waves generate microbubble cavitation, which could be responsible for the reduction of microbial count in pretreated samples [91]. According to prior research, oxidative stress and free radicals were formed because of the influence of ultrasound. This triggered an increase in damaged cell walls and denatured enzyme activity in microorganisms, which resulted in a slowdown in the growth of bacteria [88].

The Indian microbiological standards for dried plant products stipulate that the aerobic plate count of dried fruits should be below 5 log CFU/g, with a desirable level of 4 log CFU/g. Additionally, the Food Safety and Standards Authority of India determined that dried fruit's acceptable fungal load is 4 log CFU/g, and the satisfactory load is below 2 log CFU/g [76]. According to Ireland's point-of-sale microbiological quality criteria, dried fruit with a CFU/g level of less than 5 log is acceptable [87]. The findings of the current investigation show that, with some exceptions, most dried Taikor slices were within the safety limit of the previously mentioned microbiological safety standards.

4. Conclusion

In this study, the influence of osmotic and ultrasonic water bath pretreatments on the drying characteristics and some quality parameters of Gracinia pendaculata, such as color, β-carotene (vitamin A), vitamin B₁, B₂, B₃, and B₆, vitamin C, TFC, TPC, antioxidant activity, and total microbial count were investigated in fresh and treated dried Taikor slices. The final products’ quality was significantly affected by both the temperature of the samples and the pretreatment they underwent. This study found that by drying at a lower temperature with a glucose solution, the chemical properties were preserved to the greatest extent possible. The color parameters were better preserved by fructose pretreatment. Longer sonication time reduced the microbial and fungal load, though it was associated with a relatively higher loss of nutritional compounds. However, drying at a low temperature took a longer time to complete the drying process. Future research on Garcinia pedunculata, and other underutilized fruits and vegetables may benefit from this study's findings about preserving these foods while preserving as much of their nutritious qualities as possible.

CRediT authorship contribution statement

Mohammad Afzal Hossain: Conceptualization, Data curation, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – review & editing. Sudipta Talukder: Methodology, Writing – original draft. Aftab Uz Zaman: Methodology, Data curation, Writing – original draft. Animesh Sarkar: Resources, Software. Md. Yasin: Methodology, Data curation. Rahul Biswas: Data curation, Software, Methodology.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.