Thin-layer Models Research Articles

Computer vision-based smart monitoring and control system for food drying: A study on carrot slices

Convective dryer embedded with computer vision (CV) system and load cell was used to continuously monitor carrot slices that are either unblanched or blanched (90 °C for 2 min) during product drying (35 °C, 35 % R.H., 3 m s−1 airflow). The CV system and load cell were selected as in-line Process Analytical Technology tools within a proactive Quality-by-Design framework and embedded for, i) monitoring of product features (i.e., weight, colour, and size); and ii) developing shrinkage-dependent moisture prediction models using linear regression. The evaluated shrinkage-dependent linear models showed superior performances (RMSE, 0.005–0.007) benchmarked against selected thin-layer models of increasing complexity. The study tested a smart-enabled prototype dryer with the potential for automation and integrating proactive quality strategies.

Microwave drying method investigation for the process and kinetics of drying characteristics of high-grade rutile TiO2

Titanium dioxide has been extensively applied in aviation, cosmetics, the chemical industry, and coatings. Currently, the primary way to prepare high-grade rutile TiO2 is the chlorination method, which mainly uses ilmenite or titanium slag as raw material through the chlorination process and then reacts it in an oxidation furnace to prepare titanium powders. However, the TiO2 material produced by the liquid-phase method contains a large amount of water, which makes the equipment vulnerable to corrosion in the subsequent process. Meanwhile, the sharp temperature change will lead to the accumulation of water vapor, which may lead to explosion and severe agglomeration, resulting in high research costs and reduced product performance. Therefore, drying equipment with high drying efficiency, high product quality, and low carbon is urgently needed. This paper used microwave drying equipment to assist in drying rutile TiO2 powders. Results indicated that the microwave power, moisture content, and initial mass positively related to the drying rate. The drying process was simulated and analyzed using four common thin-layer kinetic models. A good agreement was that the Modified Page model was in good agreement with the actual drying process of TiO2. The effective diffusion coefficient was calculated. After calculation, the activation energy of microwave-drying TiO2 was 8.22 g/W. This article offers a kinetic theoretical basis and abundant data guidelines for actual products to reinforce the drying of high-grade TiO2 powders.

Thin Layer Modeling of Corn Grains Using a Hybrid Solar Dryer with Lpg

Thin Layer Modeling of Corn Grains Using a Hybrid Solar Dryer with Lpg

A robust discontinuous Galerkin time domain algorithm for penetrable thin layers

<sec>The thin layer problem is common in some engineering cases, such as a coating target or dielectric radome. If the skin depth of the medium behind the thin layer is much smaller than the medium scale, the transmission line impedance boundary can be used to solve the thin layer problem . When both sides of the thin layer are free space or the skin depth of the medium behind the thin layer is greater than or comparable to the scale of the medium, the transmission line impedance boundary condition is not applicable. Such problems need incident and reflected wave data and are also known as penetrable thin-layer problems.</sec><sec>When dealing with penetrable thin-layer problems, we need to give the electromagnetic wave data on both sides. In addition, the thin layer problem can belong with multi-scale problems. The EM simulation is difficult to implement because of the high resource consumption of accurate modeling.</sec><sec>The accurate modeling is a very expensive algorithm, and the mesh-size difference between the thin layer region and the surrounding ordinary region is too large, thus seriously affecting the quality of the elements (tetrahedrons). So, it is difficult to solve the problem of thin layer quickly by using the time-domain discontinuous Galerkin method or even by using local time steps or other optimization methods. To acquire a fast solution, the approximate boundary condition can be used to describe the thin layer. The DGTD has also the advantage of the geometric fitting property. If a thin layer model is curved, we can build a conformal geometric model to deal with the thin layer, thus avoiding the complicated interpolation correction scheme.</sec><sec>In this work, A robust DGTD method for penetrable thin layers is proposed. In our study, we find that the current excitation scheme is prone to divergence when large dielectric coefficients are dealt with and its robustness is poor. To solve this problem, we use the electromagnetic field correction scheme in DGTD to deal with the thin layer problems. In addition, engineering problems may encounter multiple thin layers. In this work, a simulation scheme for multiple thin layers is presented and relevant numerical examples are given to verify it. The results illustrate the accuracy and effectiveness of the method in this work, and the method presented in this work can be used for the fast calculation of complex thin layer problems.</sec>

Drying Kinetic of Jaboticaba Berries and Natural Fermentation for Anthocyanin-Rich Fruit Vinegar.

This study aimed to determine the drying kinetic of jaboticaba berries that were then used for the fermentation of natural fruit vinegar. The drying behavior was fitted well to the thin-layer kinetic model of Midilli et al. in a vacuum oven at 40 °C. Moisture diffusion was the dominant mechanism because two falling rate periods were observed. The effective moisture diffusivity was decreased (2.52 × 10−10 m2/s) after being pretreated with 70% sugar (1.84 × 10−10 m2/s) and 10% salt (6.73 × 10−11 m2/s) solutions. Fresh berry vinegar was found to have higher flavonoids, including anthocyanins, to exhibit higher antiradical and anti-pathogenic microorganism activities. However, the phenolic content in dried berries vinegar was higher, mainly from the bond breaking of tannins and lignins from fruit peel. Some extent of oxidation occurred because of the change in the color index of vinegar samples. The acidity of both vinegars was 3% acetic acid. Headspace GC-MS also detected acetic acid as the major compound (>60%) in the vapor of vinegar samples. A wide range of non-volatile compounds composed of alkaloids, terpenoids, flavonoids, organic acids, and sugar derivatives was detected by UHPLC-TWIMS-QTOFMS. The peak intensity of anthocyanins was reduced by 28−77% in dried berry vinegar. Therefore, it is better to prepare natural fruit vinegar using fresh berries, preserving anthocyanins for high antioxidant capacity.

Suitability of thin-layer drying models for halogen lamp drying of sugarcane bagasse

The drying process of bagasse particles was investigated in this study using an artificial neural network (ANN) and 18 thin-layer drying (TLD) models. These models are used for investigating kinetics and understanding engineering parameters involved in the drying process of food and agricultural products. Bagasse particles were studied at 105 to 135 °C and an initial moisture content of 180% (based on the dry weight) using a halogen moisture analyzer. The results showed that an increase in the temperature decreased the bagasse drying period and increased the constant drying. The whole drying process of bagasse happened in a falling drying rate period. The fitness of drying curves on semi-experimental TLD models based on statistical parameters, including root mean square error (RMSE), sum of square errors (SSE), and coefficient of determination (R2) showed that the Hii et al. model had the highest coefficient of determination and the lowest error percentage. The ANN predicted changes in the bagasse moisture content through time more accurately than the Hii et al model. Also, the results demonstrated that the selected ANN model and a number of semi-empirical models with less than 3 adjustable parameters provided good agreement and can be considered promising tools to predict drying kinetic of bagasse particles.

The Effect of Different Drying Methods on Bioactive and Nutrition Contents of Bee Bread and Mathematical Modeling of Drying Characteristics.

In this study, the aim was to determine the effect of different drying methods (with microwave and hot air) on the color, nutrient and bioactive contents of fresh bee bread. Drying characteristics were also investigated. Microwave and hot air drying were applied at different microwave powers and temperatures, respectively. Lower moisture ratios and highest effective diffusion coefficients were obtained with microwave drying in a shorter time. The Midilli model was found to be the most suitable thin-layer drying model for both methods. Regardless of the drying conditions, moisture, ash, protein, carbohydrate, and lipid proportions were observed to vary in the ranges of 4.9-8.2 %, 1.61-2.67 %, 17.47-32.54 %, 39.92-60.84 %, and 7.10-8.89 %, respectively. The lowest color difference was obtained for the sample dried at 210 W. As a result, it was determined that microwave drying is more suitable for preserving the nutritional and bioactive content of bee bread during drying.

Modelling the drying characteristics of human faeces using thin-layer drying models and calculation of mass transfer properties at ambient conditions

Convective drying was used to investigate the drying characteristics of human faeces. Thin-layer drying semi-empirical models were used to describe the drying characteristics of human faeces under varying conditions of temperature, air velocity and relative humidity. The drying experiments were conducted at moderate near-ambient conditions, with temperatures of 20 °C, 25 °C, 30 °C, 35 °C and 40 °C, and air flows of 0.1 m/s, 0.2 m/s and 0.5 m/s, at relative humidity of 5%, 10%, 20% and 40%, and initial moisture content of 82.2%, 78.1%, 71.7%, 71.1% and 64.2%. The experimental data curves for faeces for varying temperatures were fitted to the Newton, the Henderson and Pabis, the Page, and the Midilli-Kucuk models, while other experimental conditions were kept constant. Page model was the best fitting model, with R2 values ranging from 0.9950 to 09,977. Effective moisture diffusivity and convective mass transfer coefficient were found to vary from 8.81 × 10−8 m2/s and 1.31 × 10−5 m/s at 20 °C to 9.57 × 10−7 m2/s and 3.49 × 10−4 m/s at 40 °C, respectively. The activation energy was found to be 42.38 kJ/mol. The results presented in this study confirm that human faeces can be dried under moderate ambient conditions by using solar and wind energy. The modelled kinetics can inform the development and design of a dry sanitation system that does not require electricity or any other fuels for heating and air convection.

MODELING AND SIMULATION OFCHARCOAL FIRED FISH SMOKING PROCESS USING MATLAB SOFTWARE

This paper presents the theoretical approach for the heat and mass transfer phenomenon at the fish layer during smoking using energy balance equations. Charcoal fired fish smoking kiln is the best preservation technique for faster smoking with efficient utilization of time and energy. The aim of this work is to establish a mathematical model describing the heat and mass transfer phenomena at the fish layer and in the air during smoking and to investigate the effects of two aero thermal factors by simulating the smoking process. Mathematical model was developed using energy balance equation on a various component of the kiln. The smoking process is simulated under real operating conditions based on a thin layer model and experimental drying kinetics. The results revealed that the rate of smoking increased with increase in drying air temperature and velocity respectively.

Energy efficient drying technologies for sweet potatoes: Operating and drying mechanism, quality-related attributes.

Sweet potatoes (SPs) are a versatile tuberous crop used as subsistence and cash crop in raw and processed forms. The major issue with SPs is post-harvest losses, which result in noticeable quality decline because of inappropriate handling, storage, delayed transit, and sales, as well as microbiological and enzymatic activity. Drying is an excellent strategy for managing short postharvest storage life, preserving nutrients, and maximizing long-term benefits. However, several parameters must be considered before drying SPs, such as relative humidity, temperature, drying duration, size, and shape. The current review looks at the factors influencing SPs' moisture loss, drying kinetics, diverse drying methods, pretreatments, operating conditions, and their efficacy in improving the drying process, functional, and nutritional qualities. An optimal drying process is required to preserve SPs to obtain concentrated nutrients and improve energy efficiency to be ecofriendly. Drying sweet potatoes using traditional methods such as sun or open-air drying was found to be a slow process that could result in a lower quality. Various advanced drying techniques, like vacuum, infrared, freeze drying, and pretreatments such as ultrasound and osmotic dehydration, have been developed and are successfully used globally. The best-fit thin-layer models (Hii, Page, two-term, logarithmic) utilized for drying SPs and appropriate modeling methods for optimizing drying procedures are also discussed.

Application of Artificial Neural Network for Predicting the Drying Kinetics and Chemical Attributes of Linden (Tilia platyphyllos Scop.) during the Infrared Drying Process

This study analyzes the possibility of utilizing artificial neural networks (ANNs) to characterize the drying kinetics of linden leaf samples during infrared drying (IRD) at different temperatures (50, 60, and 70 °C) with sample thicknesses between 0.210 mm and 0.230 mm. The statistical parameters were constructed using several thin-layer models and ANN techniques. The coefficient of determination (R2) and root mean square error (RMSE) were utilized to evaluate the appropriateness of the models. The effective moisture diffusivity ranged from 4.13 × 10−12 m2/s to 5.89 × 10−12 m2/s, and the activation energy was 16.339 kJ/mol. The applied Page, Midilli et al., Henderson and Pabis, logarithmic, and Newton models could sufficiently describe the kinetics of linden leaf samples, with R2 values of >0.9900 and RMSE values of <0.0025. The ANN model displayed R2 and RMSE values of 0.9986 and 0.0210, respectively. In addition, the ANN model made significantly accurate predictions of the chemical properties of linden of total phenolic content (TPC), total flavonoid content (TFC), DPPH, and FRAP, with values of R2 of 0.9975, 0.9891, 0.9980, and 0.9854, respectively. The validation of the findings showed a high degree of agreement between the anticipated values generated using the ANN model and the experimental moisture ratio data. The results of this study suggested that ANNs could potentially be applied to characterize the drying process of linden leaves and make predictions of their chemical contents.

Effects of temperature on drying kinetics and biochemical composition of Caulerpa lentillifera

Caulerpa lentillifera (phylum: Chlorophyta) is a seaweed that is widely consumed by local communities across Asia. The effects of different oven-dried temperatures on the drying kinetics and phytochemical constituents of C. lentillifera were studied. This kinetic study used three different thin-layer models, i.e., Lewis, Henderson and Pabis, and Logarithmic models. Among these, the Logarithmic model was the most suitable model that could be determined the seaweed drying behaviours (R-square > 0.9923, RMSE < 0.0004). Drying the C. lentillifera at 50oC resulted in a higher extraction yield (1.00%) with a significant concentration of total phenolic content and total flavonoid content at 1.027 mg GAE/g, and 59.655 mg RU/g, respectively.

Effect of yerba mate ( Ilex paraguariensis St. Hil.) extract on the drying behavior of cassava starch films enriched with rebaudioside A

In this study, the drying behavior of cassava starch-based edible films was investigated. Formulations were elaborated with rebaudioside A, glycerol, and low concentrations (0.5, 2, and 4%, w/w) of yerba mate (Ilex paraguariensis St. Hil.) extract (YM%). Physicochemical properties (pH, apparent viscosity, and density) and film-forming capacity (dip-coating method) were evaluated at 25°C. Films were casted by drying and mathematically described using the Henderson and Pabis thin-layer model. Effective moisture diffusion coefficients (Deff) were determined using theoretical film thicknesses evaluated at the critical moisture content. The Deff dependency on temperature and YM% was analyzed using an Arrhenius-type model. Based on the results, as YM% increased, values of pH, and apparent viscosity decreased. Low YM% increased the drying rates and the values of Deff of cassava starch-based edible films elaborated with rebaudioside A as a sweetener and bioactive compound, obtaining the highest values at 4% (w/w) and 70°C. Novelty impact statement The optimization and control of the drying process are important to produce coated foods with high-quality and nutritional value in the industry. Yerba mate extract powder added to cassava starch-based formulations at low concentrations (<5%, w/w) is suitable for obtaining edible films and coatings with higher drying rates and effective moisture diffusion coefficients that control film casting due to the better hydrophobicity and plasticizing effect. This information could be useful to manufacture new film-forming fluids with bioactive compounds (e.g., rebaudioside A), such as alternative bio-packages that allow to replace the disposable composite synthetic plastic containers, and products for people with special diet requirements due to its low or sugar-free nature.

Modeling of dehydration and color degradation kinetics of maize grain for mixed flow dryer

Effects of drying temperature (60, 70, and 80 °C) and air velocity (3.0, 6.0, and 9.0 m/s) on thin layer and color kinetics of maize grain during mixed flow dryer (MFD) were investigated for the present study. Five thin layer grain drying models (Henderson and Pabis, Page, Lewis, Midilli et al. and Wang and Singh) as well as Zero order reaction rate were applied with the experimental data to predict the drying and color kinetics of maize, respectively. Increased drying temperature had significant leverage on drying time whereas proliferation of air velocity (>6.0 m/s) is scarcely imperative. Model fitting analysis revealed that Lewis and Page model is aptly applied in evaluating drying kinetics for mixed flow drying of maize as coefficient of determination (R 2 ) is higher. Effective moisture diffusivity (4.92 × 10 −7 to 8.38 × 10 −7 m 2 /s) was maximum both for higher temperature and air flow whereas specific energy consumption was lowest (2.75 MJ/kg) for lower temperature and air flow. Regression analysis of color attributes (L*, a*, and b*) designates that color kinetics of maize grain occurred according to the zero order reaction. L* and b* indices of color decreases while a* and color difference (ΔE) increases with drying temperature and time. Thin layer and kinetic constant (k) is proportionate with drying temperature while adverse results were noticed for color attributes. Drying and color degradation kinetics of maize can readily be described by Lewis and Page model and zero order reaction, respectively for mixed flow drying. • Effect of temperature & air flow thin layer modeling of maize for mixed flow drying. • Determination of effective moisture diffusivity of maize. • Color kinetics evaluation of maize grain for mixed flow dryer. • Evaluation of specific energy consumption for maize drying.

Thin-layer drying characteristics, modeling and quality attributes of tomato slices dried with infrared radiation heating

An Infrared dryer was used to examine the drying of tomato slices. In this investigation, the influence of infrared radiation (IR) on the rate of drying, physical quality, energy combustion of tomato was estimated at three different levels of intensity at 0.15, 0.20, and 0.35 W/cm² under different air flows of 0.5, 1, and 1.5 m/s. Tomato slices were dried with an initial moisture content of 19.7 to 0.17 g water/g dry solids by infrared drying. The moisture content and drying rates are found to be dramatically affected by infrared density. An increase in the drying rate and a decrease in the drying period occurred with increasing infrared intensity. A decrease in energy consumption was detected with the increase of radiation intensity. The results clarified that the shrinkage ratio increased with increasing infrared intensity. The rehydration ratio raised with the increase in radiation intensity. The change in the colour difference of dried slices increased with an increase in radiation intensity. The models were in comparison using (R²) coefficient of determination, modelling efficiency (EF), and (χ²) reduced chi-square. Midilli model was fit for simulation of all drying conditions and could be used to estimate tomato moisture content at any time during the infrared drying process.

Effect of osmotic dehydration pre‐treatments on physicochemical and energy parameters of Kosia (Nashi) pear slices dried in a convective oven

In this study, the effects of osmotic dehydration pre-treatments in sucrose solutions on dried Kosia pear slices were determined. The effective diffusion, modeling, color, rehydration, specific energy consumption, specific moisture extraction rate (SMER), evaporation latent heat, energy efficiency (EE), convective heat (hc), and mass transfer coefficient (hm) parameters of fruit slices were investigated. The shortest drying time (17 h) was observed in the drying process of the samples subjected to osmotic dehydration in 25% sucrose solution for 1 h. The best thin-layer drying models were identified as Lewis (R2: .9977) and Jane-Das (R2: .9977) models. Effective diffusion values ranged between 2.13–4.94 × 10−5 m2 s−1. Rehydration ratios ranged between 2.09 and 2.71 g g−1 while rehydration capacities ranged between 57.24% and 63.05%. The least color change was observed in control samples. SMER values of the dried samples ranged between 0.0062–0.00011 kg kWh−1. EE values ranged between 4.19% and 0.03%. Mass transfer coefficient values varied between 1.57 × 10−8 and 1.06 × 10−12 m/s. Heat transfer coefficient value was calculated as 5.773 × 10−7 W m−2 K. Uncertainty that stems from measurements and cannot be controlled was calculated as ±2.324%. Novelty impact statement High sucrose solution ratios of drying pre-treatments reduced the drying time of Kosia pear slices. Control samples retained their color values better. Samples subjected to osmotic dehydration in 25% sugar solution for 1 h had is the optimum values drying performance and energy parameters.

A computational slip boundary condition for near-wall turbulence modeling

Near-wall turbulence modeling represents one of challengers in the computational fluid dynamics. To tackle this problem, the near-wall non-overlapping domain decomposition (NDD) method proved to be very efficient. It has been successfully used with different Reynolds-averaged Navier–Stokes models. In NDD the computational domain is split into two non-overlapping sub-domains: an inner region near the wall, which is characterized by high gradients, and the outer region. To simplify the solution, in the inner region the thin-layer model can be used. In this case, NDD represents a trade-off between the accuracy and computational time. It has been demonstrated on numerous test cases that NDD is able to save up to one order of computational time while retaining practically high accuracy. A practical drawback of the algorithm is a need to split the computational domain into two regions. In the present paper, for the first time the NDD is realized implicitly. For this purpose, specific boundary conditions of Robin type are derived at the wall. Such boundary conditions reduce the gradients of the solution near the wall. The key property is that the solution can be obtained on a relatively coarse grid and then be recalculated in the inner region. In the approach it is guaranteed that the original outer and updated inner solutions are linked smoothly. The algorithm with the new boundary conditions can be easily implemented in standard codes. This is demonstrated with the code OpenFOAM. In addition, in the paper a more accurate approach to obtain the solution in the inner region is realized. The efficiency of the entire technique is demonstrated on test cases with modeling turbulent flows in a channel and asymmetric diffuser.

Mathematical Modelling of Potassium Meta-Bisulphite Treated Mango (Mangifera indica) Slices cv Dasheri

Fresh and ripe mango (Mangifera indica) slices cv Dasheri were dehydrated in a cabinet dryer at drying air temperatures of 50, 60, and 70 oC at a slice thickness of 5 mm. Before dehydration, the mango slices were pre-treated with potassium meta-bisulphite (KMS) at three levels (0.5 %, 1.0 %, and 1.5 % KMS, respectively). Five semi-theoretical and empirical thin-layer drying models (Newton [Lewis], Logarithmic, Demir et al. 2004, Henderson &amp; Pabis, and Wang &amp; Singh) were employed to select the best model that describes the drying process. Moisture diffusivity and activation energy of the mango slices were also evaluated. It was observed that the drying took place in the falling rate period. Demir et al. 2004 and Logarithmic models were found to satisfactorily describe the drying process of the mango slices using R2, x2, SSE, and RMSE as the criteria for selecting the best model. The mango slices' moisture diffusivity and activation energy range from 6.79 to 10.02×10-8 m2/s and 10.03 to 14.73 kJ/mol. Thus, KMS pre-treatment can minimise the mango slices' drying duration and drying cost.

EFFECT OF PRE-TREATMENTS ASSISTED MICROWAVE DRYING ON KINETICS AND ENERGY ASPECTS OF DRAGON FRUIT

Drying is one of the most effective preservation methods applied to increase the shelf life of agricultural products. In this study, the effect of different pre-treatments on drying dragon fruit with a microwave was investigated. It is also aimed to determine the drying method with the minimum energy consumption. Dragon fruit slices were dried by microwave at 300 W output power in four different pretreatments as ultrasound, gum arabic, sucrose, and without pretreatment. Pretreatment applications were carried out by performing ultrasound for 10 minutes on dragon fruit slices and soaking them in 10% gum arabic and sucrose solutions before drying. Results showed that the shortest and longest drying times were measured in gum arabic and without pretreatment, respectively. Time-dependent estimation data were calculated by six different thin-layer drying models, considering the drying times and moisture rates. Jena&amp;Das model showed the best fitting performance. As a result, it has been determined that pretreatment applications reduce drying time and energy consumption. In addition, gum arabic pre-treatment is advantageous in terms of energy consumption in microwave drying of dragon fruit.

Thin layer modeling of drying kinetics, rehydration kinetics and color changes of osmotic pre-treated pineapple (Ananas comosus) slices during drying: Development of a mechanistic model for mass transfer

This study aimed to develop an effective and safe drying protocol for pineapple fruits. The combination of different osmotic pre-treatments and drying temperatures were used to evolve a novel method that can reduce drying associated changes in pineapple fruits. The pre-treatment was accomplished by soaking fresh pineapple slices in four osmotic solutions (1% trehalose, 2% NaCl, 10% sucrose, and 10% fructose) for 30 min. A hot air convection dryer carried out the drying at 50, 55, and 60 °C temperatures maintaining a constant 30% relative humidity (RH). During the drying experiment, moisture content data were taken and transformed into moisture ratio (MR) and then fitted to the four thin layer models viz. Page, Logarithmic, Newton (Exponential model), and Henderson and Pabi's Model. The impact of pre-treatments and drying temperature on drying kinetics, mass transfer rate, moisture diffusion, rehydration capacity, and color changes of pineapple slices were observed. The drying process was affected by both osmotic pre-treatments and temperature. A satisfactory curve with good fitting as anticipated by the Page and Logarithmic models, with the Logarithmic model fitting best during the drying of pineapple slices. The ideal drying temperature integrated with pre-treatments was 55 °C at 30% RH based on maintaining the color and rehydration. The Page equation provided an excellent statistical fit to experimental rehydration data, with low mean percentage error values of 2.188–7.479%. The pre-treatment of dried pineapples, particularly with trehalose, improved structural retention as seen by increased rehydration capacity and lower color changes after reconstitution. The mechanistic model, which describes activation energy for the increase of moisture diffusion coefficient and mass transfer coefficient, and their correlation to drying conditions (temperature and time), showed a better fit for mass transfer and diffusion. Weibull's distribution model gave a better fit for the water loss model during drying at various temperatures. As a result, the combination of dipping in 1% trehalose solution and hot air drying at 55 °C appears to be a promising procedure for producing high-quality, nutritious dried pineapple products for consumers. This work will assist future researchers in understanding the influence of osmotic pre-treatments on plant foods and improve the existing literature.