Abstract
Hot air drying is widely adopted to extend the shelf life of Pleurotus eryngii, which is an edible fungus with high nutritional value and large market demand. Understanding moisture transfer during hot air drying is essential for both quality improvement and energyefficient dryer design. In this study, we investigated the drying kinetics of P. eryngii slices with different thicknesses (4, 8, and 12 mm) under different hot air temperature levels (40, 50, 60, 70, and 80°C) and a constant air velocity (2 m/s). It is found that the drying rate increases with the increase of the hot air temperature or the decrease of the thickness of P. eryngii slices. Only a falling rate period was observed during the hot air drying. We used eight mathematical models to describe the drying kinetics of P. eryngii slices and found that the logarithmic model fits the experimental data best. The fitted effective moisture diffusivity of P. eryngii slices is in the range of
1 Introduction
Pleurotus eryngii is a kind of edible fungus which has high nutritional value, thick flesh, and large market demand [1]. However, it is challenging to store fresh P. eryngii with high moisture content at room temperature due to its relatively high metabolic activity. Therefore, fresh P. eryngii needs to be consumed or processed immediately after harvest. Drying is an important method to remove the water inside P. eryngii. Generally, the moisture content of fresh P. eryngii can be effectively reduced from up to 90% (wet basis) to a safe moisture level of 13% (wet basis), which simultaneously reduces their water activity, inhibits microbial growth, and enlarges shelf life [2]. More importantly, drying maintains the nutritional ingredients and flavor of fresh products.
Owing to simplicity and low cost, open sun drying has been adopted to process agricultural products from thousands of years ago. However, it involves drawbacks, including dust and microbial contamination of the dried materials as well as overlong drying time [3], which is not suitable for drying P. eryngii. A simple and costeffective hot air drying, which accelerates the drying process by blowing hot air into the oven or drying room, can overcome the drawbacks of open sun drying and be used for drying P. eryngii [4]. During hot air drying, moisture inside of a product first diffuses to its surface and then transfers to the surrounding air under temperature and moisture gradient. Therefore, understanding the effect of ambient conditions (e.g., temperature, humidity) and moisture transport inside the product on the drying process is important to optimize the drying process, improve product quality, design new dryers, and save energy. In early studies on hot air drying, most works focused on product quality, including shrinkage, rehydration, hardness, content, and type of amino acid. With the gradual recognition of the importance of drying kinetics, a number of recent works centered on the moisture diffusion of various vegetables and fruits, such as parsley leaves [5], golden apples [6], banana [7], berberis [8], and tomato [9]. However, few are known about the drying kinetics of P. eryngii.
In this study, we aim to experimentally investigate the drying kinetics of P. eryngii slices during the hot air drying process. The effects of hot air temperature and slice thickness on drying kinetics were studied. The effective moisture diffusivity and drying activation energy were obtained based on the empirical mathematical models. Besides, the quality of dried P. eryngii slices was assessed according to the color change after drying.
2 Experiment
2.1 Materials
P. eryngii (5–6 cm in diameter and ∼150 cm in length) was purchased from a local vegetable market in Zhengzhou, China. The samples with an average initial moisture content of 88–92% (wet basis, g water/g matter) were selected as the raw materials for the drying experiment [10]. Then, the fungi were stored in a refrigerator at a temperature of 4°C. Before drying experiments, the P. eryngii was first placed in room temperature (20°C) for about 2 h for thermal equilibrium.
2.2 Experimental apparatus
A temperaturecontrolled and wind velocitycontrolled electric blast oven (Model DHG9070, Shanghai Yiheng Scientific Instrument Co., Ltd, China) was used to perform hot air drying. The initial mass and the mass during drying were determined with precise digital balance with the accuracy of 0.001 g (Model ES500, Shanghai Yueping Scientific Instrument Co., Ltd, China).
2.3 Experimental procedure
Before each experiment, the P. eryngii was washed quickly with distilled water and wiped with paper towels. The same sections of fungus were manually cut into thin cylindrical slices with a diameter of 30 mm and various thicknesses (4, 8, and 12 mm, Figure 1). Since the skin of the P. eryngii in contact with distilled water would be removed, the effect of the cleaning process on the moisture content of the fungus slices could be neglected. Then, the slices were placed in the drying chamber with a constant temperature (40, 50, 60, 70, and 80°C, respectively), a relative humidity of 20%, and an air velocity of 2 m/s (Figure 2). To avoid the influence of temperature rise process, the oven was kept for at least 20 min at the set point. The mass of samples was measured and recorded every 15 min. The weighing time is controlled within 20 s to ensure that the weight loss of the sample before and after weighing is less than 0.01 g. The experiments were stopped when the moisture content of the samples reached the equilibrium moisture content (10–13%, wet basis). Each drying process was repeated five times, and the average value was used for the subsequent analysis (Table 1).
Group  Number  Experimental parameters  Value  Constant parameters 

1  1  Hot air temperature (°C)  40  Sample thickness 8 mm 
2  50  
3  60  
4  70  
5  80  
2  6  Sample thickness (mm)  4  Hot air temperature 70°C 
7  8  
8  12 
3 Drying kinetics
3.1 Drying models
Eight thinlayer mathematical drying models were chosen to fit the variation of dimensionless moisture ratio (MR) as a function of time (t) during the drying process of P. eryngii slices (Table 2), where the dimensionless MR of P. eryngii slices can be calculated by ref. [19],
where M
_{
t
}, M
_{0}, and M
_{e} are the moisture content at time
Number  Model  Expression  References 

1  Newton 

[11] 
2  Page 

[12] 
3  Henderson & Pabis 

[13] 
4  Wang & Singh 

[14] 
5  Midilli & others 

[15] 
6  Logarithmic 

[16] 
7  Demir & others 

[17] 
8  Two terms 

[18] 
The moisture content is defined as,
where W
_{
t
} and W
_{d} are the mass of samples at time
where DR is the drying rate,
where
3.2 Effective moisture diffusivity
The effective moisture diffusivity can be determined by solving Fick’s second diffusion model [3], which states,
For long drying periods, since the diameters of the P. eryngii slices are much larger than their thickness, the moisture transport in thickness direction dominates the drying process. Here, the onedimensional diffusion equation is used to describe the mass transfer process, and Eq. (7) can be simplified as ref. [18],
where D _{eff} is the effective moisture diffusivity and L is the thickness of P. eryngii slice.
3.3 Drying activation energy
The relationship between the drying activation energy (E _{a}) and the effective moisture diffusivity can be described by the Arrhenius equation [22].
where
3.4 Color assessment
A color difference meter was used to investigate the color changes of P. eryngii slices during the hot air drying. Since the color difference meter perceives color as Red Green Blue signals, the images were converted into
where
Also, the browning index (BI) was calculated by ref. [24],
4 Results and discussion
4.1 Drying kinetics of P. eryngii slice
4.1.1 Effect of hot air temperature
Figure 3 shows the hot air drying kinetics of P. eryngii slice with a thickness of 8 mm at the temperature of 40–80°C and an air velocity of 2 m/s. It is observed that the moisture content of the fungus slices decreases fast with the increase of hot air temperature (Figure 3(a)), resulting in a decreased drying time. As shown in Figure 3(b), it took 250, 210, 160, 140, and 130 min to dry the slices to the equilibrium moisture content at the temperature of 40, 50, 60, 70, and 80°C respectively. This is because the higher temperature gradient between the P. eryngii slices and the surrounding environment (hot air) accelerates the evaporation and movement of moisture inside the fungus slices during the hot air drying. Our results are consistent with the reported trends in literature [3,22,25]. Additionally, when the hot air temperature increases from 50 to 60°C, we noticed that the drying time drops sharply, reducing by 85 min. Figure 3(c) shows the drying rate as a function of moisture content. Interestingly, we only observed a falling rate drying period during the entire drying process, and no constant rate drying period was observed. The reason is that the large oven size, compared with the fungus slice, makes the moisture inside and permeating in the drying chamber the slice can be taken away by the hot air in time during the drying process. Therefore, there is no saturated steam around the slice surface. As the drying process progresses, the temperature and moisture gradients between the P. eryngii slices and the surrounding hot air decrease gradually. Thus, the drying rate of the slices decreases as moisture content reduces after the initial stage of heating up (Figure 3(c)). Figure 3(d) shows the average drying rate of the slices under different temperatures. It is obvious that the average drying rate increases as the temperature increases because of the larger temperature gradients between the P. eryngii slices and the surrounding hot air.
4.1.2 Effect of sample thickness
Figure 4 depicts the drying kinetics of P. eryngii slices with different thicknesses (4, 8, and 12 mm) at the hot air temperature of 70°C and an air velocity of 2.0 m/s. It is observed from Figure 4(a) that the drying time of P. eryngii slices increases with the increase of sample thickness. For example, the drying time increases from 110 to 220 min when the sample thickness increases from 4 to 12 mm. This is because the moisture migration path inside P. eryngii slices increases as the sample thickness increases, and the relative contact area between the sample and the surrounding (hot air) becomes smaller. Figure 4(b) also shows that the duration of the falling rate drying period increases with the increase of sample thickness. Since the drying process mainly occurs inside the sample during the falling rate drying period, the total moisture content and moisture migration path increase with the increase of the sample thickness, leading to the decreased drying rate. The similar variation trend is also found in ref. [22].
4.2 Evaluation of drying models
We adopted eight mathematical models to fit the drying kinetics of P. eryngii slices under various temperatures. The fitting results are shown in Table 3. It is found that the logarithmic model fit the drying kinetics of the slices best since it results in the highest value of R ^{2} and the lowest values of SSE and RMSE. The values of R ^{2}, SSE, and RMSE are in the range of 0.9970–0.9994, 0.0006–0.0051, 0.0098–0.0184, respectively. Our results are similar to the drying behavior of thinlayer mushroom slices in literature [26]. Figure 5 shows the comparison of the experimental data and the predicted results from the logarithmic model. The results show that the empirical mathematical model can describe the experimental results well, which provides good results for the engineering application of the food industry [27].
Model  T (℃)  Parameters  R ^{2}  SSE  RMSE 

Newton  40  k = 0.00830  0.9889  0.0211  0.0317 
50  k = 0.00879  0.9805  0.0330  0.0441  
60  k = 0.01348  0.9775  0.0261  0.0510  
70  k = 0.01565  0.9791  0.0200  0.0500  
80  k = 0.01705  0.9821  0.0168  0.0459  
Page  40  k = 0.00439, n = 1.127  0.9900  0.0211  0.0267 
50  k = 0.00313, n = 1.218  0.9922  0.0094  0.0250  
60  k = 0.00354, n = 1.299  0.9947  0.0061  0.0261  
70  k = 0.00445, n = 1.292  0.9950  0.0047  0.0260  
80  k = 0.00696, n = 1.210  0.9908  0.0087  0.0352  
Henderson & Pabis  40  k = 0.00856, a = 1.032  0.9852  0.0200  0.0324 
50  k = 0.00993, a = 1.092  0.9850  0.0179  0.0346  
60  k = 0.01436, a = 1.070  0.9805  0.0226  0.0476  
70  k = 0.01639, a = 1.050  0.9815  0.0176  0.0470  
80  k = 0.01744, a = 1.024  0.9830  0.0160  0.0479  
Wang & Singh  40  a = −0.00576, b = 8.317 × 10^{−6}  0.9852  0.0205  0.0325 
50  a = −0.00653, b = 1.079 × 10^{−5}  0.9996  0.0047  0.0177  
60  a = −0.00968, b = 2.342 × 10^{−5}  0.9993  0.0008  0.0093  
70  a = −0.01134, b = 3.222 × 10^{−5}  0.9960  0.0004  0.0071  
80  a = −0.01226, b = 3.794 × 10^{−5}  0.9962  0.0036  0.0227  
Midilli & others  40  a = 0.989, k = 0.00732, b = −0.00017  0.9972  0.0053  0.0168 
50  a = 1.002, k = 0.00733, b = −0.00033  0.9964  0.0061  0.0201  
60  a = 1.013, k = 0.01076, b = −0.00072  0.9985  0.0017  0.0147  
70  a = 1.006, k = 0.01211, b = −0.00096  0.9991  0.0008  0.0118  
80  a = 0.993, k = 0.01358, b = −0.00080  0.9977  0.0021  0.0189  
Logarithmic  40  a = 1.071, k = 0.00672, c = −0.08657  0.9976  0.0046  0.0155 
50  a = 1.155, k = 0.006439, c = −0.15640  0.9970  0.0051  0.0184  
60  a = 1.230, k = 0.00917, c = −0.21980  0.9989  0.0013  0.0127  
70  a = 1.259, k = 0.01017, c = −0.25450  0.9994  0.0006  0.0098  
80  a = 1.186, k = 0.01172, c = −0.19540  0.9979  0.0020  0.0183  
Demir and others  40  a = 0.831, b = 0.055, k = 1.676, n = 0.00509  0.9459  0.1025  0.0755 
50  a = 0.814, b = 0.097, k = 0.703, n = 0.01448  0.9163  0.1421  0.1007  
60  a = 0.841, b = 0.092, k = 0.007, n = 2.07300  0.9262  0.0856  0.1106  
70  a = 0.958, b = 0.032, k = 0.014, n = 1.19200  0.9694  0.0292  0.0765  
80  a = 0.986, b = −0.094, k = 0.233, n = 0.10360  0.9979  0.0020  0.0201  
Two terms  40  a = 1.032, k _{1} = 0.0086, b = −0.0323, k _{2} = 1.066  0.9895  0.0200  0.0333 
50  a = 1.082, k _{1} = 0.0095, b = −0.0824, k _{2} = 1.681  0.9844  0.0264  0.0434  
60  a = 1.159, k _{1} = 0.0155, b = −0.1590, k _{2} = 1.189  0.9878  0.0142  0.0450  
70  a = 1.159, k _{1} = 0.0180, b = −0.1589, k _{2} = 1.152  0.9884  0.0111  0.0471  
80  a = 1.098, k _{1} = 0.0186, b = −0.0979, k _{2} = 0.999  0.9855  0.0137  0.0524 
4.3 Effective moisture diffusivity and drying activation energy
The effective moisture diffusivities of P. eryngii slices listed in Table 4 were fitted on the basis of Eq. (8). The obtained effective moisture diffusivities of the slices range from to
Number  Hot air temperature (°C)  Sample thickness (mm) 

D _{eff} (10^{−9 }m^{2}/s) 

1  40  8 

1.51 
2  50  8 

1.64 
3  60  8 

2.05 
4  70  8 

2.89 
5  80  8 

3.26 
6  70  4 

3.40 
7  70  12 

2.25 
The drying activation energy can be obtained by fitting the variation of effective moisture diffusivity as a function of temperature. According to Eq. (9), the Arrhenius constant and activation energy of the fungus slices are
4.4 Color measurement
Color is an important indicator of the apparent quality of food ingredients, and the ideal color of dried products is close to fresh color. The color of fresh P. eryngii is (
Hot air temperature (°C) 




BI 

40  86.48  1.87  8.77  5.40  12.03 
50  81.07  2.08  9.98  10.57  14.73 
60  75.33  1.96  11.49  16.38  18.11 
70  74.70  2.02  11.62  17.02  18.53 
80  73.52  2.37  13.14  18.73  21.65 
5 Conclusion
In summary, we investigated the hot air drying kinetics and dry quality of P. eryngii slices with different thicknesses (4, 8, and 12 mm) at different hot air temperatures (40, 50, 60, 70, and 80°C) and a constant air velocity of 2 m/s. The experimental results show that, during the hot air drying process of the slices, only falling rate period exists and no constant rate period was observed. The drying time can be shorted with the increase of hot air temperature and/or the decrease of sample thickness. The logarithmic model fits the drying kinetics of the fungus best. The effective moisture diffusivities are in the range of

Funding information: This study was supported by the National Natural Science Foundation of China (No. 51806200), the Foundation of Key Laboratory of ThermoFluid Science and Engineering (Xi’an Jiaotong University), Ministry of Education (No. KLTFSE2020KFJJ03), and Henan Association for Science and Technology (No. 2022HYTP017).

Author contributions: H.L. conceived the idea and designed the experiments. J.J., Y.T., and J.L. conducted the experiments. H.L. wrote the manuscript. All authors participated in the discussion of the research. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

Conflict of interest: The authors state no conflict of interest.

Data availability statement: All of the data supporting the findings are presented within the article. All other data are available from the corresponding author upon reasonable request.
References
[1] Su D, Lv W, Wang Y, Wang L, Li D. Influence of microwave hotair flow rolling dryblanching on microstructure, water migration and quality of Pleurotus eryngii during hotair drying. Food Control. 2020;114:107228.10.1016/j.foodcont.2020.107228Search in Google Scholar
[2] TorkiHarchegani M, GhasemiVarnamkhasti M, Ghanbarian D, Sadeghi M, Tohidi M. Dehydration characteristics and mathematical modelling of lemon slices drying undergoing oven treatment. Heat Mass Transf. 2016;52:281–9.10.1007/s002310151546ySearch in Google Scholar
[3] Demiray E, Tulek Y. Thinlayer drying of tomato (Lycopersicum esculentum Mill. cv. Rio Grande) slices in a convective hot air dryer. Heat Mass Transf. 2012;48:841–7.10.1007/s0023101109421Search in Google Scholar
[4] Li K, Zhang Y, Wang YF, ElKolaly W, Gao M, Sun W, et al. Effects of drying variables on the characteristic of the hot air drying for gastrodia elata: Experiments and multivariable model. Energy. 2021;222:119982.10.1016/j.energy.2021.119982Search in Google Scholar
[5] Akpinar EK, Bicer Y, Cetinkaya F. Modelling of thin layer drying of parsley leaves in a convective dryer and under open sun. J Food Eng. 2006;75:308–15.10.1016/j.jfoodeng.2005.04.018Search in Google Scholar
[6] Menges HO, Ertekin C. Mathematical modeling of thin layer drying of Golden apples. J Food Eng. 2006;77(1):119–25.10.1016/j.jfoodeng.2005.06.049Search in Google Scholar
[7] Dandamrongrak R, Young G, Mason R. Evaluation of various pretreatments for the dehydration of banana and selection of suitable drying models. J Food Eng. 2002;55(2):139–46.10.1016/S02608774(02)000286Search in Google Scholar
[8] Aghbashlo M, Kianmehr MH, SamimiAkhijahani H. Influence of drying conditions on the effective moisture diffusivity, energy of activation and energy consumption during the thinlayer drying of berberis fruit (Berberidaceae). Energy Convers Manag. 2008;49(10):2865–71.10.1016/j.enconman.2008.03.009Search in Google Scholar
[9] Demir K, Sacilik K. Solar drying of Ayaş tomato using a natural convection solar tunnel dryer. J Food Agric Environ. 2010;8(1):7–12.Search in Google Scholar
[10] Schössler K, Jäger H, Knorr D. Effect of continuous and intermittent ultrasound on drying time and effective diffusivity during convective drying of apple and red bell pepper. J Food Eng. 2012;108(1):103–10.10.1016/j.jfoodeng.2011.07.018Search in Google Scholar
[11] ElBeltagy A, Gamea GR, Essa AH. Solar drying characteristics of strawberry. J Food Eng. 2007;78(2):456–64.10.1016/j.jfoodeng.2005.10.015Search in Google Scholar
[12] Akoy EOM. Experimental characterization and modeling of thinlayer drying of mango slices. Int Food Res J. 2014;21(5):1911–7.Search in Google Scholar
[13] Hashim N, Daniel O, Rahaman E. A Preliminary Study: Kinetic model of drying process of Pumpkins (Cucurbita Moschata) in a convective hot air dryer. Agric Agric Sci Proc. 2014;2:345–52.10.1016/j.aaspro.2014.11.048Search in Google Scholar
[14] Omolola AO, Jideani AIO, Kapila PF. Modeling microwave drying kinetics and moisture diffusivity of Mabonde banana variety. Int J Agric Biol Eng. 2014;7(6):107–13.Search in Google Scholar
[15] Ayadi M, Mabrouk SB, Zouari I, Bellagi A. Kinetic study of the convective drying of spearmint. J Saudi Soc Agric Sci. 2014;13(1):1–7.10.1016/j.jssas.2013.04.004Search in Google Scholar
[16] Kaur K, Singh AK. Drying kinetics and quality characteristics of beetroot slices under hot air followed by microwave finish drying. Afr J Agric Res. 2014;9(12):1036–44.10.5897/AJAR2013.7759Search in Google Scholar
[17] Demir V, Gunhan T, Yagcioglu AK. Mathematical modelling of convection drying of green table olives. Biosyst Eng. 2007;98(1):47–53.10.1016/j.biosystemseng.2007.06.011Search in Google Scholar
[18] Sacilik K. Effect of drying methods on thinlayer drying characteristics of hullless seed pumpkin (Cucurbita pepo L.). J Food Eng. 2007;79:23–30.10.1016/j.jfoodeng.2006.01.023Search in Google Scholar
[19] Onwude DI, Hashim N, Abdan K, Janius R, Chen G. Experimental studies and mathematical simulation of intermittent infrared and convective drying of sweet potato (Ipomoea batatas L.). Food Bioprod Process. 2019;114:163–74.10.1016/j.fbp.2018.12.006Search in Google Scholar
[20] Horuz E, Bozkurt H, Karataş H, Maskan M. Drying kinetics of apricot halves in a microwavehot air hybrid oven. Heat Mass Transf. 2017;53:2117–27.10.1007/s002310171973zSearch in Google Scholar
[21] Arslan D, Özcan MM, Menges HO. Evaluation of drying methods with respect to drying parameters, some nutritional and colour characteristics of peppermint (Mentha x piperita L.). Energy Convers Manag. 2010;51(12):2769–75.10.1016/j.enconman.2010.06.013Search in Google Scholar
[22] Beigi M. Hot air drying of apple slices: dehydration characteristics and quality assessment. Heat Mass Transf. 2016;52:1435–42.10.1007/s0023101516468Search in Google Scholar
[23] Salehi F, Kashaninejad M. Effect of drying methods on rheological and textural properties, and color changes of wild sage seed gum. J Food Sci Technol. 2015;52:7361–8.10.1007/s1319701518495Search in Google Scholar
[24] Maskan M. Kinetics of colour change of kiwifruits during hot air and microwave drying. J Food Eng. 2001;48:169–75.10.1016/S02608774(00)001540Search in Google Scholar
[25] Tulek Y. Drying kinetic of oyster mushroom (Pleurotus ostreatus) in a convective hot air dryer. J Agric Sci Technol. 2011;13:655–64.Search in Google Scholar
[26] Salehi F, Kashaninejad M, Jafarianlari A. Drying kinetics and characteristics of combined infraredvacuum drying of button mushroom slices. Heat Mass Transf. 2017;53:1751–9.10.1007/s0023101619311Search in Google Scholar
[27] Kaleta A, Górnicki K. Evaluation of drying models of apple (var. McIntosh) dried in a convective dryer. Int J Food Sci Technol. 2010;45:891–8.10.1111/j.13652621.2010.02230.xSearch in Google Scholar
[28] Olanipekun BF, TundeAkintunde TY, Oyelade OJ, Adebisi MG, Adenaya TA. Mathematical modelling of thinlayer pineapple drying. J Food Process & Preservation. 2015;39(6):1431–41.10.1111/jfpp.12362Search in Google Scholar
[29] Therdthai N, Zhou WB. Characterization of microwave vacuum drying and hot air drying of mint leaves (Mentha cordifolia Opiz ex Fresen). J Food Eng. 2009;91:482–9.10.1016/j.jfoodeng.2008.09.031Search in Google Scholar
© 2022 He Liu et al., published by De Gruyter
This work is licensed under the Creative Commons Attribution 4.0 International License.