Introduction

Allspice or Pimenta dioica (L.) leaves are a member of the myrtle family and have a flavor similar to cinnamon, cloves, nutmeg and pepper. They also have sweet, peppery overtones, and hints of juniper besides peppercorn flavor. Research studies reveal that Allspice berries have medicinal properties such as antimicrobial, antipyretic, anti-hypertensive, anti-diabetic, anti-carcinogenic, nematocidal, anti-inflammatory and antioxidants [1], while the leaves exploration remains limited. Allspice trees are grown in tropical and subtropical regions varying with climate, soil conditions, and cultivation practices. Berries and leaves can be harvested multiple times a year from the tree and are traditionally used in culinary and medicinal purposes besides flavor and fragrance. Efficient processing and drying methods, preserve maximum percentage of bioactive compounds (80–90%), enhance the quality of Allspice leaves, providing farmers additional income and supporting sustainable agriculture.

Dehydrating is the technique to preserve medicinal, fragrant and aromatic plants to ensure their quality. It plays a vital role in food processing operations as it reduces the moisture of food and agricultural products, enabling safe storage and minimizing biochemical, chemical and microbiological deterioration. Additionally, drying helps to reduce packing, storage and transportation costs [2]. Natural drying (shade or in the sun) is still a widely used method because of its lower cost. Compared to mechanical dehydration methods, shade drying retains higher levels of nutrients, ascorbic acid, and minerals. However, it requires a longer drying time. The drying process and conditions are critical for herbs and spices; therefore, various methods were employed. Contamination by dirt, dust, insects, rats, and animal infestations can reduce the quantity and quality of the dried product. Mechanical and commercial drying technologies, such as cross-flow (or tray), vacuum drying, low temperature -low humidity and freeze-drying, have been developed to overcome these problems. Tray dryers or cross-flow dryers are safer and more reliable small-batch dehydration techniques. Vacuum drying preserves the color and vitamins in various products. However, to enhance drying efficiency, vacuum drying is often combined with other techniques, such as microwave drying [3]. Low temperature and low humidity (LTLH), accomplished circulation with desiccant material, removes moisture from the air and reduces relative humidity, thereby preserving quality parameters. Freeze-drying, based on the principle of sublimation, involves maintaining ice in a partial vacuum (611 Pa) and at a low temperature (below 0 ºC). Hence, it evaporates without going through the liquid phase and maintains the quality of the product. The process is conducted at low temperatures and vacuum, which prevents enzymatic activity, growth, proliferation of microorganisms thereby retains product's flavor and nutritional value. Freeze drying is effective, more expensive and requires 10 folds energy than hot-air drying [4]. The popular drying mode available today include freeze drying, superheated steam drying, and infrared drying. Combining different drying processes can result in the production of high-quality dried goods at lower energy costs. It is often necessary to optimize the drying process depending on the characteristics of the sample, drying duration, energy cost, and equipment investment [5]. Allspice can be dried using either sun or mechanical dryers. Mechanical dryers provide a faster drying rate, reducing the overall drying time and yielding higher-quality products. Nguyen Thi Thanh Huong et al., [6] investigated the optimal conditions for preserving the highest levels of bioactive ingredients in mangoes during ultrasonic and microwave processing. Their optimization efforts yielded results in terms of antioxidant activity, vitamin C concentration, and polyphenol composition. Thi Yen Nhi Tran et al., [7] noticed that during the shrimp drying process, the product was exposed to hot air for a long time, affecting color, biochemicals or salinity of the product besides oxidation of lipids. Tan Phat Dao et al., [8] optimized the three main processing steps – blanching, osmosis and drying to produce a dried jelly cashew apple product. Their study found that the maximum content of ascorbic acid (TAA), total polyphenol content (TPC), and total tannin content (TTC) was achieved during drying at 55 °C for 267 min. Ultrasound and microwave technologies are emerging as green technologies and have become an inevitable trend. By utilizing these methods in drying and frying, products with a uniform texture, minimal color change, and improved taste can be produced quickly and with low energy consumption [9]. Fruits and vegetables' physicochemical quality attributes, such as color, texture, microstructure, bioactive components, antioxidant capacity, and microbiological quality, were all improved and the drying time was successfully reduced by using ultrasonic drying technology [10]. Recent developments in ultrasound-coupled drying to enhance the quality of fruits and vegetables are presented in the study by Jiaxin Wu et al., [11] which illustrates reduction in time decreased by an ultrasound-coupled device.

The mathematical modeling of dehydration methods is a crucial aspect of drying technology that can effectively characterize a drying process. Bui Thi Thu Thao et al., [3] examined the relationship between the moisture of mango slices at varying times, temperature and drying process and inferred that the sample dries faster and the drainage rate increases with temperature besides impact of longer drying times. The process of extracting essential oils from pomelo (Citrus maxima) peel materials was modelled by Phat T. Dao et al., [12] in both linear and nonlinear forms, using pseudo-first-order and pseudo-second-order kinetic models. The most appropriate kinetic model kinetics were ascertained using the coefficient of determination, R2, and the percentage of deviation, %q. Tan Phat Dao et al., [13] experimental results exhibited that there are statistically significant and positive interactions between process performance and pairs of interacting factors such as temperature-ratio, temperature–time, and ratio-time in the case of optimization studies on hydro distillation of Citrus reticulata essential oil peels. Tan Phat Dao et al., [14] optimized parameters for Pomelo essential oil extraction on a pilot scale, taking into account extraction kinetics, activation energy, thermodynamics, and essential oil quality, to acquire insights for larger-scale production.

An efficient drying technique is essential for reducing moisture to a safe water activity level and preserving leaves to acquire concentrated nutrients in reduced energy consumption [15]. To date, there are no studies investigating the effect of different drying methods and conditions on phytochemicals and nutritional properties of Allspice leaves for further processing. Therefore, this research aimed to evaluate the effects of diverse dehydration techniques, sun, shade, cross-flow, freezing, low temperature-low humidity and vacuum drying, on the kinetics, physicochemical properties, antioxidant activity, configuration of essential oils and nutrient composition which can enable pilot scale processing for industries.

Materials and Methods

Chemicals and Reagents

Gallic acid (≥ 98%), Rutin (≥ 95%), Trolox (≥ 98%), AlCl3 (≥ 99%), FeCl3 (≥ 97%), Potassium Acetate (≥ 99%), Sodium Carbonate (≥ 99.5%), Folin -Ciocalteu, Eugenol (≥ 99%) and mineral standards (≥ 99.9%) were procured from Sigma- Aldrich (St. Louis, MO, USA). All the other reagents and solvents used were of analytical grade and obtained from Sigma Aldrich, India.

Plant Material Collection

Fresh Allspice leaves were collected from Wayanad (11.6797 ̊ N and 75.9748 E) in Kerala, India, in the month of January, 2021. A specimen voucher of the plant material, SFS DH No PSM012020, has been deposited in the Plantation Products, Spices and Flavor Technology department of CFTRI (Central Food Technological Research Institute) in Mysore, Karnataka, India. The initial moisture of the fresh leaves was determined as 55.5% on a wet basis using the Moisture Analyzer (Model DENVER (IR 35), Mettler Toledo, USA).

Dehydrating Techniques

The Allspice leaf samples were washed in clean water, drained subjected to six different dehydrating protocols, namely sun (SD), shade (SHD), cross-flow (CFD), freeze (FD), low temperature low humidity (LTLH), vacuum (VD) drying.

Sun Drying

Sun drying experiments were carried out in Mysuru, Karnataka, between January, 2021, with geographic coordinates of 12.3163° ' N and 76.6380°′ E. Approximately 5000 g of leaves were placed in direct sunlight on a 0.45 m × 0.45 m tray with thickness 0.5 cm, in an average temperature of 30 °C, relative humidity (RH) of 40—50% for 5 h for 2 days till the final moisture reaches to 8.95 ± 0.04%.

Shade Drying

Approximately 5000 g of fresh Allspice leaves were placed in the shade on a 0.45 m × 0.45 m tray in 0.5 cm thickness. Each trial lasted about 5–7 h, roughly for 5 days, with 50 – 55% RH and an average temperature of 28 °C until for 4–5 consecutive days, the weight of the samples was recorded every twelve hours or whenever the leaves were completely dry (9.45 ± 0.33%).

Freeze-Drying

These studies were conducted in a freeze dryer on a small-scale Scanvac (Coolsafe™, Denmark). Fresh Allspice leaves were frozen for 2 h at -80 °C in a deep freezer (REMI RQVD-300 PLUS, Italy). Then leaves with a thickness of 0.2 cm were dried for 8 h with a vacuum level of 0.012 mbar at -102 °C, the final moisture noted as 8.89 ± 0.05%. The weights of the samples were recorded only at the beginning and end of the experiment.

Cross-Flow Drying

The cross-flow drying study for the leaves was carried out in a pilot-scale tray drier (Techno Lab Products Pvt. Ltd.) with 24 trays measuring 0.45 m × 0.25 m and in 0.5 cm thickness, an electrical heater, a centrifugal fan for airflow and a heat controller, with a 1.5 m/s air velocity, 50 °C for 5 h. The weight of the samples was recorded in regular intervals until the leaves were entirely dry (8.67 ± 0.16%).

Low Temperature -Low Humidity Drying

The fresh leaves were placed in a dehumidification system (Alpha, Germany) equipped with six metal trays of 0.25 m × 0.25 m, each at a temperature of 35–45 °C with a relative humidity of 30–40% for 5 h by measuring the weight in regular intervals until the leaves were fully dry (9.51 ± 0.02%).

Vacuum Drying

The Allspice leaves were dried in a vacuum dryer (ORL, Argentina) with a monitored temperature of 60–70 °C at two different vacuum pressures, 550 and 60 mmHg, for 4 h trays measuring 0.25 m × 0.25 m with 0.5 cm thickness. The drying process resulted in a final material moisture of 9.01 ± 0.05%.

Modeling of Drying Kinetics

Thin layer kinetic models for moisture ratio (MR) against time (t) were used to simulate the drying kinetics. MR was determined using Eq. (1).

$$MR=\frac{{M}_{t}-{M}_{e}}{{M}_{0}-{M}_{e}}$$
(1)

where, M0, Mt and Me are the initial moisture, the moisture at any given time and the equilibrium moisture, respectively. Five thin layer models, including the Lewis/Newton (Eq. 2) [16], Page (Eq. 3) [16], Modified Page (Eq. 4) [17], Henderson-Pabis (Eq. 5) [18] and Wang-Singh models (Eq. 6) [19], were used to study the drying kinetics [20]. A systematic understanding of the drying procedure can be attained by examining the drying kinetics of leaves using five distinct thin layer drying models. The various models offer distinct methods for explaining the drying behaviour, heat transmission, moisture diffusion, and the physical characteristics of the material undergoing drying. Fick's second law of diffusion has been applied to explain the declining rate period of the drying process. To find the best mathematical model for the drying process, the experimental data were fitted to a number of thin-layer drying models [21]. The compatibility of experimental data with models has been described for the drying process of soursop slices using twelve different types of classical kinetic models. Statistical values (such as the coefficient of determination (R2), Chi-square value (χ2), etc.) are used to evaluate the conformance. According to Fick's diffusion law, the material's moisture loss is explained [22].

$$MR=\mathit{exp}\left[-{k}_{t}\right]$$
(2)
$$MR=\mathit{exp}\left[-k{t}^{n}\right]$$
(3)
$$MR=\mathrm{exp}{\left[-kt\right]}^{n}$$
(4)
$$MR=a.\mathit{exp}\left[-kt\right]$$
(5)
$$MR=1+at+b{t}^{2}$$
(6)

The best models were determined based on various statistical parameters, comprising the coefficient of determination (R2), root mean square error (RMSE) and reduced chi-square (χ2) values calculated.

Calculation of Effective Moisture Diffusivity

The effective diffusion coefficient of the Allspice leaves during the dehydration progression was designed using a simplified Fick's second law equation for diffusion. Equation (7) is the analytical solution of Fick’s second law, while considering constant moisture diffusivity, infinite slab geometry and uniform initial moisture [21].

$$MR=\frac{8}{\Pi 2 }\sum \frac{1}{ \left(2n-1\right)2}exp \left[\frac{{\left(-2n-1\right)}^{2}{\pi }^{2}Dt}{4{L}^{2}}\right]$$
(7)

M0 is the initial moisture (kg of water per kg of dry solid), MR is the moisture ratio, M is the moisture at any time (kg of water per kg of dry solid), n = 1,2,3… is the number of terms taken into consideration, t, is the time in seconds, D, is the effective moisture diffusivity in m2/s, and L, is the slice thickness in meters (m). The previous equation can be simplified to simply the first term of the series and written in logarithmic forms over extended dehydration times by disregarding the higher-order terms [23](Eq. 8).

$$\begin{array}{ccc}MR=\frac{8}{{\Pi }^{2}}exp \left[-\frac{{\Pi }^{2}Dt}{4{L}^{2}}\right]& or& \mathit{ln}\left(MR\right)=\mathit{ln}\left[\frac{8}{{\pi }^{2}}\right]-\left[\begin{array}{c}{\Pi }^{2}D\\ \overline{4{L }^{2}}\end{array}\right]t\end{array}$$
(8)

The method of slopes is employed to calculate the effective diffusion coefficient. The slopes were gained from the linear regression of ln (MR) against time (t) according to Eq. (9).

$${k}_{0}=\frac{{\Pi }^{2}D}{4{L}^{2}}$$
(9)

Determination of Physical Parameters

Color

The color retention of Allspice leaves was evaluated using a color measurement tool from Minolta Co., Osaka, Japan, both before and after drying. The CIE standard illuminant C was used to calibrate the color meter against a white calibration plate. The L*, a* and b* values were calculated as the average of three readings. The color brightness coordinates ‘L*’ are used to measure the brightness of a color and it ranges from 0 to 100. The chromaticity coordinates 'a*' and 'b*’values represent redness ( +); greenness (-), yellowness ( +) and blue (-), respectively.

$$\text{Total color change}=\sqrt{{\left[L-{L}^{1}\right]}^{2}+\left[a-{a}^{1}\right]+\left[b-{b}^{1}\right]}$$
(10)

where, L, L1, a, a1, b, b1 represent color coordinates of the sample after change, respectively.

Chlorophyll

The samples (10 g) were ground using 80% acetone and centrifuged at 5000 rpm for 5 min. to determine the chlorophyll. The absorbance read at 645 nm and 663 nm by using UV spectrophotometer. The chlorophylls were calculated according to the following formula.

$$\text{Chlorophyll a }=\frac{\left[ 12.7*\mathrm{ A}663- 2.69*\mathrm{A}645\right]*\mathrm{V}}{1000*W}$$
(11)
$$\text{Chlorophyll b}=\frac{\left[22.9*\mathrm{ A}645 - 4.68*\mathrm{ A}663\right]*\mathrm{V}}{1000*W}$$
(12)
$$\text{Total chlorophyll}=\frac{[20.2*\mathrm{A}645 + 8.02*\mathrm{A}663]*\mathrm{V}}{1000*W}$$
(13)

where,

A:

Absorbance at specific wavelengths

V:

Final volume of chlorophyll extract in 80% acetone

W:

Weight of the fresh tissues extracted

Rehydration Capacity

The dried and pre-weighed Allspice leaves were immersed in hot water at 80 °C for 15 min. The rehydrated samples were poured over a sieve for 2 min and gently wiped with filter paper three to four times to remove the adhering water. The rehydration capacity was calculated based following equation:

$$\text{Rehydration capacity }=\frac{\mathrm{Wr}}{\mathrm{Wd}}$$
(14)

where, Wd stood for the weight of Allspice leaves dried samples and Wr for the weight of leaves following rehydration. The measurements were carried out in triplicates.

Microstructure

The Allspice leaves (SHD, CFD and C) were mounted on the aluminum holder stubs using a double sticky carbon tape. The adaxial surface of leaves was examined in a ZEISS scanning electronic microscope (EVO LS 15, Germany). All the samples were analyzed under high vacuum conditions at an accelerating voltage of 15 kV. The images were captured using 500 × magnification for SHD and CFD, while 2 KX for the fresh leaf samples.

Determination of Chemical Parameters

Total Polyphenol Content and Total Flavonoid Content

The Folin-Ciocalteu (FC) method was employed to measure the total polyphenol content in the extract, using gallic acid (2–10 g/ml) as the standard. 1 ml of each extract (1:100 diluted) was mixed with 1.5 ml of FC reagent and left in the dark for 5 min. A UV spectrometer was then used to detect absorbance at 765 nm following the addition of 2 ml of a 20% sodium carbonate solution and a brief heating period in a boiling water bath [24]. The total polyphenol content was expressed as mg of gallic acid equivalents per gram of dry weight (mg GE/g DW) [25].

A colorimetric method described by Cai et al., [26], was employed to determine the total flavonoid content of the Allspice leaf extracts. In brief, 0.1 mL of each extract was added to 10 mL test tubes, followed by 0.3 mL of 5% NaNO2 solution. After 5 min, 0.3 mL of 10% AlCl3 was added to the mixture and left for an additional 6 min, then 2 ml of 1 M NaOH was added, followed by dilution to a total volume of 10 ml using distilled water. The optical density was measured at 510 nm against a blank. The total flavonoid content of the sample was reported as mg rutin equivalents per gram of dry weight (mg RE/g DW) [27].

$$\mathrm{Yeild}\;\mathrm{of}\;\mathrm{polyphenol}\;\left(\%\frac{\mathrm w}{\mathrm w}\right)=\frac{\mathrm{Polyphenol}/\mathrm{flavonoid}\;\mathrm{in}\;\mathrm{extract}\;\left(\frac{\mathrm g}{\mathrm{DW}}\right)}{\mathrm{Weight}\;\mathrm{of}\;\mathrm{extract}\;\mathrm{obtained}\;\left(\frac{\mathrm g}{\mathrm{DW}}\right)}\;\ast\;100$$
(15)

Antioxidant Activity

The FRAP (Ferric Reducing Antioxidant Power) assay was conducted by following a previously described method [28]. The FRAP reagent was prepared by diluting a mixture of acetate buffer (300 M, pH 3.36), 10 M TPTZ solution, 40 M HCl and 20 M FeCl3 was diluted 10:1:1 (v/v/v). The sample mixture was formed by mixing 3 mL of the FRAP reagent with 1 mL of the extract solution and the absorbance was measured at 595 nm using a UV-2401 PC spectrometer (Shimadzu, Kyoto, Japan). All experiments were carried out in triplicate and the mean values were reported. The antioxidant activity was expressed in terms of mg Trolox equivalents (mg TE/g).

Extraction and Volatile Compounds Analysis by GC–MS

The leaves were cleaned and ground using a mortar and pestle. For each sample (100 g each), hydro-distillation was performed using a Clevenger distillation apparatus with 1000 ml water for 2 h. The chemical characterization of volatile oils from Allspice leaves was carried out using GC–MS analysis. The phytochemicals in the essential oil and n-alkane standards were analyzed using the Perkin-Elmer Turbomass Gold GC system equipped with a quadrupole mass spectrometer (Massachusetts, USA). The GC–MS analysis was performed using a Rtx-5MS column (30.0 m × 250 μm) under the following conditions: an initial temperature of 60 ºC for 1 min, followed by a rate of 4 ºC /min to 240 ºC/min, holding for 3 min. The injection temperature was set at 250 ºC and the carrier gas used was helium (99.999%) at a flow rate of 1 mL/min. Diluted samples (Essential oil is diluted as 1:100 in HPLC grade hexane) of 1 µl were manually injected into the GC–MS system under split mode (split ratio 50:1). The detector was operated at a temperature of 300 ºC, and the ionization voltage was set to 70 eV. The detection of the volatile chemicals with a mass range of 40 to 300 AMU was done using full scan mode. Under the same GC conditions as previously stated, the Kovats indices (KI) for each molecule were computed using a sequence of n-alkanes (C8-C21). By comparing each mass spectrum with either the GC–MS retention times of the authentic standards or the mass spectra of reference libraries NIST17 (NIST MS Search 2.0d software, Gaithersburg, MD, USA), the components in the Allspice essential oil were identified. Using peak-area ratios, the relative amount present was estimated.

Nutrient Composition

The proximate composition of the Allspice leaves was determined using various AOAC methods. The moisture was determined using AOAC method such as 925.09, crude ash using method 925.03, crude fat using method 920.39, crude protein using method 954.01 and crude fiber using method 962.09. The carbohydrate content was calculated as the nitrogen-free extract by subtracting the remaining components from the total dry weight.

The homogenized ashes gained after dry digestion were used for mineral determination. The analysis was performed using Microwave Plasma Atomic Emission Spectroscopy (MP-AES Agilent Technologies 4210). The wavelengths for each element used were as follows: Zn (213.857 nm), Ca (393.366 nm), Fe (371.993 nm), K (766.491 nm), Mg (285.213 nm), Mn (403.076 nm) and Na (588.995 nm). The detection limits ranged from 0.07 ppm (Mn) to 30.14 ppm (K). The concentration of the respective minerals was determined by reading from the standard absorbance curve versus concentrations (mg/100 g).

Statistical Analysis

The dehydrating experiments were conducted in triplicate and reported as mean values with standard deviation (SD). The data were examined using a one-way analysis of variance (ANOVA) to determine whether there were significant differences between the samples. Multivariate analysis, specifically Principal component analysis (PCA) was performed to evaluate the statistical significance of volatile chemicals obtained from various dehydration approaches. GraphPad software (San Diego, California, USA, www.graphpad.com) was used for the PCA analysis and Heat map for volatiles. Microsoft Excel 2016 (Microsoft Corporation, Redmond, Washington, USA) was applied for other mathematical calculations and kinetic models.

Regression Coefficient, Root Mean Square Error and Chi-square Values

The regression coefficient (R2), root mean square error (RMSE) and chi-square values (χ.2) were calculated by following equations Eq. (16), Eq. (17) and Eq. (18)

$${R}^{2}=1-\frac{\sum {\left[{y}_{i}-{\widehat{y}}_{i}\right]}^{2}}{\sum {\left[{y}_{i}-\overline{y }\right]}^{2}}$$
(16)
$$\sqrt[\mathrm{RMSE}=]{\sum \frac{\left[{\widehat{y}}_{i}-{y}_{i}\right]2}{n}}$$
(17)

where \({\widehat{y}}_{i}, {y}_{i}\) is the ith predicted moisture ratio and experimental ratio, ∑ is the average of all experimental moisture ratios, n is the number of observations.

$${\upchi }^{2}=\sum [\frac{MR\;exp-MR\;pre]2}{N-n}$$
(18)

where MR pre, MR exp is the ith predicted moisture ratio and experimental moisture ratio, n is the number of observations and N is the total number of observations.

Results and Discussion

Dehydration Techniques and Kinetic study of Allspice leaves

The main goal of dehydration is to retain quality, extend the product’s shelf life by reducing bulk weight and packaging requirements, inhibit microbiological activities and preserve organoleptic features. Limited information is available on the processing of Allspice leaves. Determining the optimal drying conditions for Allspice leaves is crucial for extracting bioactive compounds and preserving nutrients with radical scavenging properties, thereby enabling the development of value-added products. The time taken for the leaves to achieve equilibrium moisture value was different for various drying methods because of temperature variation. The dehydration periods for SD, SHD and FD were noticeably more extended than VD, LTLH and CFD drying due to the fluctuating thermal condition throughout the dehydration process. The results of fitting experimental data to empirical models are presented in Table 1, highlighting the R2, RMSE and χ2 values. Various drying models such as Lewis, Page, Modified Page, Henderson-Pabis and Wang- Singh were utilized to analyze the drying kinetics of Allspice leaves (SD, SHD, CFD, FD, LTLH and VD) processes. The calculated R2 for all experiments was more significant than 0.97, indicating a good fit between the models and experimental data. Additionally, the RMSE values were very low (< 0.05) in most cases and χ2 values closely related to zero, further confirming the suitability of chosen models and the experimental data. The criteria for fit accuracy were determined based on higher R2 values and lower RMSE and χ2 values [29].

Table 1 Thin layer models and respective kinetic constants for drying techniques
Full size table

The best-fit models for SD were the Modified page and Wang-Singh models, while the Lewis and Henderson- Pabis models for SHD. For CFD, the Page and Modified page were the most suitable. In the case of VD, the Lewis, Page and Henderson- Pabis model was the most suitable. Furthermore, for both LTLH and FD, the Lewis model yielded the best fit. The experimental moisture ratio was compared to the length of drying time to validate these five models further. The results are presented in Fig. 1a. It was discovered that the Page and modified Page models aligned well with the drying behaviour under conditions during the investigation of the drying kinetics of Allspice leaves. This alignment can be attributed to the characteristics of cross-flow drying, which favour the constant rate period and surface evaporation as the main processes, both of which are consistent with the assumptions of the preferred models. A better fit was attained with the Lewis model under VD conditions. The Lewis model's empirical time-dependent component successfully captures the more dramatic falling rate period caused by the accelerated internal moisture migration caused by the lower pressure environment. The Lewis model likewise presented the best agreement for LTLH drying. The model accurately reflected the slower drying kinetics and decreased moisture diffusivity at lower temperatures, as it was able to account for both the constant and falling rate phases. The Henderson-Pabis model, among other theoretical models, was primarily applicable to drying processes such as SHD here, that relied on the principle of mass transfer and could offer more comprehensive insights under a wider range of situations. The observations align with the previous findings, indicating that no universal model can fit all data and that a model's applicability is highly influenced by the product’s characteristics and the drying methods used [30]. Lewis is the best model for FD, LTLH, and VD with R2 = 0.985, 0.973, and 0.999, respectively. The results exposed that the modified page model offered the highest R2 (0.989) in the case of SD, Henderson and Pabis with R2 = 0.999 for SHD, page and modified page with R2 = 0.999 for CFD. In a study by Dao et al., [7] found that the drying time drops dramatically from 231 ± 20.07 to 28.33 ± 3.06 min when the drying temperature is raised from 50 to 80 °C. The product recovery efficiency is greatly impacted by the moisture, which results in a large loss in volume. The recovery efficiency improved proportionately from 13.85 ± 0.75 to 14.13 ± 0.17 (p > 0.05), when the temperature rose from 50 to 80 °C.

Fig. 1
figure 1figure 1

Experimental moisture content (MC) versus time (h) values for (a) SD- sun, (b) SHD- shade, (c) CFD- cross flow drying, (d) FD-freeze, (e) LTLH- low temperature and low humidity and (f) VD-vacuum dried Allspice leaves. Data are expressed as mean ± standard deviation (n = 3). Figure 1b Experimental and Prediction values of moisture ratio (MR) versus time (h) values for (a) SD- sun, (b) SHD- shade, (c) CFD- cross flow drying, (d) FD-freeze, (e) LTLH- low temperature and low humidity and (f) VD-vacuum dried Allspice leaves. Data are expressed as mean ± standard deviation (n = 3)

Full size image

Allspice leaves dried under various dehydration conditions reflected disparity ranging from 0.02 to 0.5 kg water/kg dry matter (Fig. 2). The fast diminishing falling-rate period began when the water/dry matter ratio was less than 0.55 kg in FD, 0.45 kg in VD, 0.38 kg in LTLH, 0.18 kg in CFD, 0.05 kg in SD and 0.02 kg in SHD. The period of falling velocity has been reached once the droplet surface has stopped being saturated and the internal mass transfer of the volatile solvent to the surface has taken over. The drying rate is only constant in equilibrium with a constant rate period. As drying progressed, the loss of moisture in the sample led to a decrease in heat absorption, which subsequently reduced the drying speed. The drying frequency of the samples decreased with increasing temperature, as well as with decreasing humidity or pressure. The maximum drying speed was reached at 50 °C for CFD and 60 °C for VD compared to others. SD and FD rates decline with decreasing time and humidity. The drying speed in the CFD accelerated due to water molecules’ rapid energy absorption, resulting in the water’s fast evaporation and consequently, faster drying speed of the samples [31].

Fig. 2
figure 2

(a)-Moisture versus time plot (b)- Drying rate (dM/dt) versus average moisture (AvM) plot for SD- sun, SHD- shade, CFD- cross-flow drying, FD-freeze, LTLH- low temperature and low humidity and VD-vacuum dried Allspice leaves. Data are expressed as mean ± standard deviation (n = 3)

Full size image

Calculation of Effective Moisture Diffusivity

Effective moisture diffusivity is influenced by various factors, such as the material's composition, moisture content, heat, and porosity. It provides valuable insights into the mechanism of moisture transport during the drying process and helps explain the differences observed in Deff values. The effective moisture diffusivity (Deff) values of Allspice leave dried using the SD, SHD, CFD, FD, LTLH and VD methods were found to be in the range of 0.268 × 10-9 to 7.471 × 10-9 m2/s. The values obtained from our investigation (0.268 × 10-9 m2/s for SD drying) were higher than the Deff value for basil leaves dried under sun exposure, where ambient temperatures ranged from 29–35 ºC and relative humidity (RH) was measured at 23.6–27.9%, which was 0.064 × 10-9 m2/s [29]. Our results revealed that the lowest Deff values were obtained from VD (0.906 × 10-9 m2/s) and FD (0.973 × 10-9 m2/s) drying methods. The Deff value of Allspice leaves amplified over time under SHD (7.471 × 10-9 m2/s) with lower relative humidity. Regarding LTLH drying, the Deff value was 0.103 × 10-9 m2/s. Additionally, the CFD drying at 50 ºC raised the Deff value of 0.525 × 10-9 m2/s (Table 1 and Table 2). These can be attributed to the fast movement of water towards the surface due to the higher evaporation rate resulting from elevated temperatures.

Table 2 Effect of dehydration approaches on physical parameters of Allspice leaves
Full size table

The activity of water molecules in the samples improved at higher temperatures and air velocities, resulting in higher moisture diffusivity [32]. As temperature rises, water molecules tend to diffuse more readily through the capillaries of the product, leading to an intensification in the moisture diffusivity. Higher temperatures will contribute to shorter drying times, which can further enhance moisture diffusivity at any level of moisture [20]. A study on tray and tunnel-dried basil leaves at 55 ºC, 60 ºC and 65 ºC revealed various dehydration conditions, with corresponding Deff values ranging from 3.93 × 10-10 to 5.69 × 10-10 m2/s [33]. These findings highlight the influence of different drying temperatures on the behavior of basil leaves. In another study focusing on the thin layer drying kinetics of mint leaves using a cabinet dryer, the temperature range was set from 35–60 ºC, with an airflow rate of 4.1 m/s. The Deff values applied for mint leaves were 5.84 × 10-10 m2/s at 45 ºC and 1.24 × 10-10 m2/s at 55 ºC, which align with the present study’s findings.

Effect of Drying Techniques on Color and Chlorophyll

The effect of different dehydration treatments on various parameters is presented in Table 2, the drying time significantly decreased (p < 0.05) for the Allspice leaves due to the excitation states of molecules. The degree of greenness is a significant characteristic that customers will use to evaluate the quality of the final dried product. Color changes were measured and compared using the L*, a* and b* color coordinates. The LTLH drying method resulted in a significant elevation in a* value. The SHD, VD and LTLH samples exhibited the highest b* values among the dried samples. In a* coordinate system, a negative value indicates a bluish color, while a positive value indicates a yellowish color. The b* values unveiled insignificant differences and slight changes observed can be attributed to carotenoid degradation [34]. The L* value, representing lightness, was higher in CFD and LTLH samples than in other dried samples (Table 2.). Higher L* values and lower a*/b* values were generally preferred in dried products. The a*/b* values of the CFD and VD leaves were lower than those of the other dried samples. The impact of dehydrating plants at high temperatures on product quality was discussed. Heating can cause the replacement of magnesium in chlorophyll by two hydrogen atoms, leading to the formation of pheophytin, which alters the color and there will be the presence of mild acids like oxalic or acetic acid [35].

The analysis of leaf powder obtained through different drying treatments exhibited insignificant levels of chlorophyll a and b. The total chlorophyll was highest in the SHD sample, followed by FD, VD, SD, LTLH and CFD (Table 2.). Chlorophyll is sensitive to heat, and its retention depends on the temperature and duration of the heat treatment. The CFD (50–60 °C) dried leaves had the lowest chlorophyll compared to natural drying methods, consistent with other findings [23].

Effect of Drying Techniques on Rehydration Capacity

The rehydration behavior of dried material is often considered as an indicator of the damage caused by dehydration and was significantly influenced by the drying techniques employed. The drying temperature notably impacts the rehydration ratio values. In CFD, SHD and FD (1.73–1.79) showing moderately higher ratios of rehydration capacity than SD, LTLH and VD (1.5–1.65). The use of high-efficiency physical fields in freeze drying can improve drying kinetics, expand drying rates, and maintain maximum product quality, providing energy, time, and cost benefits [4]. The higher drying temperature leads to improved rehydration properties. According to Ahmed et al. (2011) [36], the rehydration capacity values for the vegetables (except from Atama leaves) were less than that of coriander leaves (0.201). For customers and food technologists alike, the dried samples' ability to rehydrate is crucial.

The influence of temperature on rehydration can be attributed to the greater vapor pressure gradient created by higher temperatures. This gradient promotes the development of a more porous structure within the material, facilitating water reabsorption during rehydration [37]. Nevertheless, it is imperative to note that excessively high temperatures can cause the structural collapse of the product matrix, hindering water reabsorption. To achieve optimal rehydration properties, a careful balance of drying temperature can enhance rehydration by creating a more porous structure and it should be controlled to avoid structural damage that prevents water reabsorption. This understanding is crucial in selecting appropriate drying techniques to preserve the desired rehydration behavior of the dried materials.

Effect of Drying Techniques on Microstructure

The temperature impacted on the tissue structure of Allspice leaves, while the effect of different drying techniques was relatively minor. SEM images displayed in Fig. 3 depict both fresh and dried Allspice leaves. The image revealed damaged cell walls and punctured cellular membranes formed at various locations, causing the cell to appear slightly irregular. However, the cells’ properties remained relatively intact in the CFD (mechanical drying) leaves. The microstructure of leaves dried at 50 °C (CFD) exhibited an irregular pore structure. There was no discernible difference between SHD (natural drying) and CFD (mechanical drying). Heat application during the drying process induces microstructural deformation, primarily driven by the rapid evaporation and diffusion of water from the inside to the surface [38]. When a product is dried, water will evaporate from the intercellular space and cell walls, leaving behind air. This leads to the collapse of the cell wall's structure and microscopic shrinking.

Fig. 3
figure 3

Scanning electronic microscope images on the adaxial surface of Allspice leaves (a) SHD- shade, (b) CFD- cross flow drying, and (c) C- fresh Allspice leaves (Control), respectively. The magnification was set as 500X (a-b) and 2 K X (c)

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Effect of Different Drying Techniques on Total Polyphenols, Flavonoids and Antioxidant Activity

In this study, the influences of different drying processes on the bio-actives of Allspice leaves were investigated (Fig. 4). The total polyphenol content (TPC) was found to be higher in FD (70.67 ± 2.13 mg GE/g) and CFD (65.58 ± 1.95 mg GE/g) dried Allspice leaves compared to fresh ones (31.43 ± 1.05 mg GE/g). This upsurge may be connected to developmental changes and the drying-induced wound-like reaction. It is possible that the relatively higher TPC in dried leaves compared to fresh ones is due to water loss during dehydration procedures. It is worth noting that various factors can influence the TPC in plants, including variety, genotype, sweetening source material, climate, processing, and other treatments [39]. Total polyphenol content is low in sun-dried samples (57.79 ± 0.02 mg GE/g). The low TPC of the sun-dried samples may be explained by the extended drying period, which exposed the samples to the atmosphere and caused phenolic component oxidation and degradation. Conventional drying methods may potentially cause the phenolic compounds to be lost due to enzymatic reactions. Flavonoids are key phyto-compounds in plants and were found to be higher in FD (61.58 ± 0.95 mg RE/g) and CFD (43.34 ± 1.23 mg RE/g) dried Allspice leaves, compared to fresh leaves sample (24.6 ± 1.56 mg RE/g). The application of low heat can also degrade polyphenols and other bio actives, which may have detrimental effects on antioxidant capacity, as is evident. The amount of flavonoid was considerably lower and consisted mainly of quercetin glycosides [40]. In another study by Kai Fan et al., [41], ultrasound and its combined applications on fruits and vegetables have shown a beneficial effect on reducing mass loss, preserving color, maintaining firmness, controlling enzyme activity, and retaining nutritional components.

Fig. 4
figure 4

Effect of drying methods on the bioactivity of SD- sun, SHD- shade, CFD- cross-flow drying, FD-freeze, LTLH- Low temperature and low humidity and VD-vacuum dried leaves and C -Control or fresh Allspice leaves. Data are expressed as mean ± standard deviation (n = 3). (a) TPC- Total polyphenol content, TFC- Total flavonoid content, (b) TAA- Total antioxidant activity

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The chief property of Allspice is its antioxidant activity due to the high amount of eugenol or methyl eugenol and other phenolics [42]. According to Saifullah et al., [43], the antioxidant capacity of lemon myrtle that was dried in the sun and shade presented the lowest output as compared to hot-air, vacuum, and freeze-dried specimens. The best results were obtained with FD (109.43 ± 1.15 mg TE/g) and CFD (105.88 ± 2.51 mg TE/g) in FRAP assay, which may be because of the higher quantity of polyphenols and flavonoids. Previous investigations have also revealed a beneficial relationship between total polyphenol content and antioxidant activity [44]. SD had the least TAA (67.42 ± 0.85 mg TE/g) as per FRAP reducing power assay. The outcomes were consistent with a study that found conventionally dried spearmints particularly those that were sun- and shade-dried had noticeably lower FRAP values compared to samples that had been freeze-dried [45].

Effect of Drying Techniques on Volatile Composition

About 40 compounds that comprise over 90% of the total composition of the essential oil were identified by GC–MS (Fig. 5). These compounds were classified into monoterpenes, sesquiterpenes, ketones, oxygenated monoterpenes, diterpenoids and a few unknown compounds. The essential oil yield varied depending on the drying conditions. For fresh leaves, the values were 2.08 ± 0.5%. For dried leaves, the values were 3.55 ± 0.02% for SD, 3.48 ± 0.04% for SHD, 3.62 ± 0.01% for CFD, 3.23 ± 0.02% for FD, 3.45 ± 0.04% for LTLH, and 3.60 ± 0.02% for VD (v/w, dry basis). Although there was minimal variation in the types of components in Allspice essential oil handled by various drying procedures, the relative quantities of these components varied depending on the drying techniques used. It is important to note that the yield may also vary based on geography and the time of harvest [46]. Additionally, seasonal changes, cultivator type and plant age can significantly impact the concentration and type of chemicals present in the herb [47]. Similarly, Afolayan et al., [48] found that drying conditions had a significant impact on the essential oil composition of Calendula officinalis, with monoterpenoid components accounting for the majority of the oil's ingredients. The highest quantity of volatiles was retained with CFD at 50 °C and VD at 60 °C. Variations in the loss or increase of oil components throughout the drying process have been attributed to different drying procedures, changes in plant species, and the formation of new chemicals as a result of oxidation, glycoside hydrolysis, esterification, and/or other reactions. The results suggest that low-temperature freeze-drying could lead to decreased enzyme activity and disturbances in metabolic pathways, which would significantly lower the amount of volatile chemicals [49].

Fig. 5
figure 5

The relative intensity of volatiles in Allspice essential oil during different dehydration technologies as SD- sun, SHD- shade, CFD- cross-flow drying, FD-freeze, LTLH- Low temperature and low humidity and VD-vacuum dried leaves and C-fresh Allspice leaves (Control), in heat map red color represents a higher relative area whereas blue represents a lower relative area

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The volatile oil yield of Allspice leaf essential oil was 88.986% for fresh leaves and 93.649%, 90.911%, 99.832%, 94.473%, 89.036% and 90.194% for SD, SHD, CFD, FD, LTLH and VD (dry basis) dried leaves, respectively. Volatile profile of the leaves consisted of phenolics (79.01 ± 4.53%), monoterpene hydrocarbons (13.69 ± 4.47%), oxygenated monoterpenes (3.26 ± 1.83%) and sesquiterpenes hydrocarbon (2.8 ± 1.94%). The most significant chemical constituents in the oil were eugenol (72.06 ± 3.93%) which exhibits a wide range of therapeutic effects [47], followed by β-myrcene (9.29 ± 3.33%), p-chavicol (6.95 ± 0.66%), limonene (3.05 ± 0.71%) and 3-octenol (1.55 ± 1.07%). α-pinene, o-cymene, α-phellandrene, 4-terpineol, linalool, trans-4-thujanaol, δ-cardinol, copaene, caryophyllene, humulene, germacene D, δ- cadinene, decanal and I-hexanol accounted for 0.1% or more, while the remaining compounds were found in trace amounts. Principal compounds such as methyl eugenol, β-caryophyllene and fatty acids were not detected in the samples. This is due to the fact that these compounds are extremely volatile, soluble in organic solvents but insoluble in water, glycol and propylene glycol. A combination of these factors likely prevented the detection of most compounds in the Allspice leaf essential oil [50].

Trivial differences in the volatile composition were observed during drying procedures. In the present study, changes in the levels of monoterpenes and sesquiterpenes and an increment in phenolic compounds, were observed in the volatiles of the Allspice leaf essential oil due to the application of different drying conditions. The quantity of monoterpenes in the essential oil decreased while the amount of sesquiterpenes increased during drying. The rise in sesquiterpenes could be ascribed to the formation of new byproducts resulting from the volatility of other (monoterpenes) compounds. Unsaturated molecules in the oil undergo phytochemical addition cycle reactions, leading to the formation of a variety of products. This behavior was also observed by Silveira Dorneles et al., [51], who investigated the impact of various drying air temperatures on the essential oil content of Piper umbellatum L. leaves.

Principal Component Analysis

The impact of different dehydration approaches on volatile chemicals is depicted in Fig. 6, which explains 82.2% of the data variation through two components: PC1 (63.1%) and PC2 (19.1%). SHD, SD, CFD, LTLH and VD samples were positioned in the positive quadrant of the PC1 component and were associated with a higher abundance of 1-octene 3-ol, α-phellandrene, limonene, o-cymene, and β-myrcene, while exhibiting a lower abundance of linalool. The statistical analysis of the score distribution was presented in Fig. 6a and b. On the other hand, SD and FD were situated on the negative axis of the PC1 component and demonstrated higher levels of terpinen-4-ol, chavicol, eugenol, cadinene and trans-ocimene. Only FD is placed on the positive axis of the PC2 component, indicating an elevated level of eugenol and trans-ocimene. All other volatiles (SD, SHD, CFD, LTLH, and VD) were located on the negative axis (PC2). The main cause of this change is the variation in metabolite levels due to different drying temperatures, although there was not much difference in the volatile composition between the drying techniques.

Fig. 6
figure 6

Principal component analysis a)- Score plot, b)- Biplot showing the relationship between drying methods and volatile compounds for SD- sun, SHD- shade, CFD- cross-flow drying, FD-freeze, LTLH- Low temperature and low humidity and VD-vacuum dried leaves

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Effect of Drying Techniques on Nutrient Composition

The proximate composition of Allspice leaves revealed the following values for the crude ash (2.77 ± 0.06%), crude fat (7.44 ± 0.062%), crude fiber (15.56 ± 1.5%), crude protein (4.05 ± 0.50%) and total carbohydrate (18.18 ± 0.10%), expressed on a dry basis, with a moisture of 52 ± 4.5% for fresh Allspice leaves. The dried leaves exhibited varying percentages of ash (6.14- 9.01%), crude fat (8.65- 12.52%), crude fiber (9.89- 16.55%), protein (6.59–7.68%) and total carbohydrate (49.78 – 56.23%) on a dry basis, with moisture ranging from 8.67 to 9.51% (Table 3.). Freeze-dried sample had the highest crude fiber followed by LTLH samples. Fiber decreases with increasing temperature, as higher temperatures can break the weak connections between polysaccharide chains and glycosidic links in the fiber polysaccharides. The structural integrity of plant cell walls can be affected by drying under shade, sun and mechanical driers, besides altering fiber content, solubility and digestibility. Fiber deterioration in SD and SHD procedures has minimal impact on long drying duration. Fiber content is well conserved and degradation was minimal in the controlled drying environments of CFD, LTLH, and VD. Freeze drying is an excellent method of maintaining both soluble and insoluble fiber density along with retention of fiber structure. Our results demonstrate high crude fiber, which can benefit human and animal health by improving digestion and helping to regulate blood glucose levels [52]. Allspice leaves are a good source of dietary fiber and can modulate the functional and nutritional properties of food products prepared from the leaves. Drying vegetables leads to the breakdown of nutrients; nonetheless, the ash content increases with temperature. The higher ash content in dried samples compared to fresh leaves indicates the presence of inorganic nutrients, especially minerals. Ash is vital for health as it provides an alkaline environment and supports healthy cell function. Crude fat is to some extent higher in all dried samples, contributing significantly to the energy value of food and reducing the reliance on carbohydrates [53]. The fat content is slightly higher in FD and LTLH samples compared to others, indicating a reduction in fat content with increasing temperature. This might be explained by the oxidation of fat as the temperature rises. The lower fat content can enhance the product’s shelf life by reducing the chance of rancid flavor development. The temperature and length of the drying process can have a vast impact on the fat content. Due to prolonged drying times, exposure to oxygen, and sunlight, SD and SHD can cause fat oxidation, thereby lowering the fat content. In CFD, the fat content is better retained due to shorter drying durations and regulated temperatures that lessen fat oxidation. Vacuum or oven drying and other high-temperature techniques can cause lipids to oxidize, which lowers their content and changes their quality. Freeze-drying, have low effect on oxidation and conserves fat molecules. Leaf protein is a vital nutritional aspect and can play a key role in alleviating nutritional deficiencies. In a study comparing dried and fresh Allspice leaves, the protein was marginally higher in all dried leaves than fresh ones [54]. Protein denaturation and degradation can result from high temperatures and extended exposure, and lowers the amount and quality of protein. Compared to SD and SHD, cross-flow drying at regulated temperatures minimized protein loss. Because of the regulated drying conditions used in LTLH and VD, protein content is well preserved; Protein content preservation usually involves freeze-drying because it decreases denaturation of proteins by using lower temperatures. Nevertheless, there was no significant difference in protein among samples dried at different temperatures, which can vary depending on the season and maturity of the leaves. It has been observed that a rise in drying temperature can decrease protein denaturation, potentially leading to an improved protein. However, this increase may also be attributed to the concentration effect, where more protein becomes available when the moisture of the solid matrix is lower. Temperature affected marginally on the composition of carbohydrates. The drying procedure has an effect on carbohydrates. Due to extended drying times and heat exposure, the SD and SHD processes may induce some degradation of carbohydrates, which could result in caramelization or Maillard reactions. Because of the regulated temperatures, CFD maintains carbohydrates more than SD and SHD. Since freeze drying reduces heat deterioration, it is the best method for conserving carbohydrates. Carbohydrates can be effectively maintained using both LTLH and VD procedures. VD due to low oxygen environment, reduces the effect of oxidative destruction.

Table 3 Impact of dehydration on the nutritional composition of Allspice leaves
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Minerals such as Zn, Ca, Fe, K, Mg, Mn, and Na were recorded in Allspice (Table 3). In both fresh and dried samples, Ca (2077–3851 mg/100 g) was the predominant mineral, followed by Mg (1051–1304 mg/100 g) and K (443–755 mg/100 g), while Mn (1.54- 3.38 mg/100 g) was present in trace amounts. Generally, dried samples had higher mineral concentrations than fresh leaves, which tended to increase significantly (p < 0.05) with higher drying temperatures. The moisture elimination during drying is responsible for the overall elevation in mineral contents as the drying temperature rises, leading to greater total soluble solids. The concentration of minerals in the final goods might be affected by drying techniques. In general, cross-flow drying maintains minerals more effectively than SD and SHD because of monitored conditions that lower the possibility of mineral volatilization. The lowest temperature method, called freeze drying, minimizes the loss of volatile minerals, making it the effective method for maintaining mineral content. Food processing methods like drying, soaking and boiling can also increase the amounts of mineral elements in food by removing anti-nutritional components. Calcium and potassium are associated with vitamin D metabolism and the physiological growth of bones, teeth and muscles. Magnesium is essential for the bone metabolism of calcium [55]. Allspice berry has been found to contain Ca, Cu, P, Fe, Mg, Mn, K, Se, Na, and Zn (661.00, 0.55, 113.00, 7.06, 135.00, 2.94, 1044.00, 2.70*10–3, 77.00, and 1.01 mg/100 g, respectively) [56]. The mineral composition of dried Allspice leaves was reported for the first time. The moisture removal during drying leads to higher total soluble solids and minerals with increasing drying temperature.

Conclusion

Drying techniques for herb and spice leaves are crucial, based on their thickness, as they affect the preservation of bio actives, stability of volatiles, and physicochemical properties. The bioactive components in Allspice leaves undergo significant changes through mechanical and natural dehydration methods. The Lewis, Page, and Modified Page models were found to best describe the dehydration process of Allspice leaves at the examined temperatures. Total polyphenol content and other bio actives were found to be higher in FD and CFD (70.67 ± 2.13 and 65.58 ± 1.95 mg GE/g, respectively), along with antioxidant capacity. Allspice leaf essential oil is composed of eugenol, β-myrcene, chavicol, limonene, and 3-octenol as its key compounds. The activity of water molecules increased with higher temperatures and air velocities, resulting in higher moisture diffusivity and significantly reduced drying times (p < 0.05). Drying temperature was insignificant on the rehydration ratio values and tissue structure of the leaves. Allspice leaves are rich in protein, fibre, and nutrients such as K, Ca, Na, Mg, and P, offering substantial health benefits and potential for functional foods. While, freeze-drying (FD) preserves colors and bio actives well, its economic viability is limited. Therefore, convective drying (CFD) appears suitable for developing industrial dehydration technologies that reserve Allspice powder quality, making it ideal for industrial operations, extraction processes, culinary applications, and the development of functional and fortified foods.