
==== Front
Data Brief
Data Brief
Data in Brief
2352-3409
Elsevier

S2352-3409(24)00825-4
10.1016/j.dib.2024.110861
110861
Data Article
Data on drying kinetics, moisture sorption isotherm, composition study of Ethiopian oyster mushroom (Pleurotus ostreatus mushroom) drying in tray dryer
Nadew Talbachew Tadesse ab
Tedla Tsegaye Sissay tsegaye.sissay@aastu.edu.et
cd⁎
Bizualem Yonas Desta b
Abate Shimeles Nigussie b
Teklehaymanot Lemlem Tadesse a
a Department of Food Engineering, School of Chemical and Mechanical Engineering, Kombolcha Institute of Technology, Wollo University, 208, Kombolcha, Ethiopia
b Department of Chemical Engineering, School of Chemical and Mechanical Engineering, Kombolcha Institute of Technology, Wollo University, 208, Kombolcha, Ethiopia
c Department of Chemical Engineering, College of Biological and Chemical Engineering, Addis Ababa Science and Technology University, 16417, Addis Ababa, Ethiopia
d Sustainable Energy Centre of Excellence, Addis Ababa Science and Technology University, 16417, Addis Ababa, Ethiopia
⁎ Corresponding author at: Department of Chemical Engineering, College of Biological and Chemical Engineering, Addis Ababa Science and Technology University, 16417, Addis Ababa, Ethiopia. tsegaye.sissay@aastu.edu.et
22 8 2024
10 2024
22 8 2024
56 1108616 6 2024
23 7 2024
15 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Drying of mushroom up to the optimal moisture content is an important preservation technique. This research contains data of the drying kinetics, moisture sorption isotherm, and evaluation of the important functional groups of fresh and dried oyster mushroom (Pleurotus ostreatus) while drying in tray dryer using hot air-drying medium. Mushrooms contains macronutrients that used as supplementary foods and moisture that make it perishable with in short time. Various drying kinetics models at different temperatures (50, 55, 60, 65, 70, and 75 °C) for was studied for oyster mushroom drying. The drying parameters (drying temperature, air speed and mass of mushroom) of mushroom in tray dryer were optimized. Fourier transform infrared (FTIR), and Atomic Absorption Spectroscopy (AAS) was used to investigate the useful functional groups and minerals composition of the dried and fresh oyster mushroom. Further proximity study was conducted. This dataset is publicly available for researchers, industrial sectors, and research laboratory to optimize and save time.

Keywords

Kinetics data
Drying parameters
Moisture removal
Tray dryer
==== Body
pmcSpecifications TableSubject	Agricultural Science/Food Technology or Food Chemistry	
Specific subject area	Food harvesting and preservations	
Data format	Raw data, analyzed and processed	
Type of data	Table, Figures, Graphs	
Data collection	Drying kinetics and moisture sorption isotherm data were obtained from the drying experiments using tray dryer (CCTD/SCADA, Edibon, Spain) and water activity experiments using a water activity meter (Aqua lab 4TE, USA) for oyster mushroom. Functional groups and elemental or mineral compositions of oyster mushroom were obtained using FTIR and AAS. Proximate values of oyster mushroom were obtained from experimental investigations.	
Data source location	Addis Ababa Science and Technology University, Addis Ababa, Ethiopia	
Data accessibility	Repository name: Mendeley Data
Data identification number: DOI: 10.17632/y8yrky75b2.1
Direct URL to data: https://data.mendeley.com/datasets/y8yrky75b2/1	
Related research article	Nadew, T. T., Reshad, A. S., & Tedla, T. S. (2024). Oyster mushroom drying in tray dryer: Parameter optimization using response surface methodology, drying kinetics, and characterization. HELIYON, 34. https://doi.org/10.1016/j.heliyon.2024.e24623	

1 Value of the Data

• The dataset offers insights into drying kinetics and moisture sorption behavior of oyster mushrooms, a valuable agricultural product.

• Detailed information on drying characteristics under various conditions helps understand moisture removal and drying efficiency.

• Moisture sorption data aids in comprehending the interaction between mushrooms and their environment, including sorption capacity and equilibrium moisture content influencing storage conditions.

• The data set is useful for designing tray dryers for food preservation at both lab and pilot scales and enables researchers and practitioners to optimize storage conditions for dried oyster mushrooms

• Availability of the dataset promotes further analysis, modeling, and exploration of mushroom processing and storage, leading to advancements in food technology.

2 Background

Mushrooms, including oyster mushrooms (Pleurotus ostreatus), are a valuable source of nutrients but highly perishable due to their high moisture content [1,2]. Drying is a crucial preservation technique to extend shelf life and prevent spoilage [3]. This dataset aims to provide a comprehensive resource for researchers and industry professionals interested in optimizing the drying process of Ethiopian oyster mushrooms in tray dryers. The data compilat1ion stems from the need for in-depth understanding of drying kinetics, moisture sorption behavior, and compositional changes during the drying process. Traditionally, mushrooms are dried using open sun drying, leading to inconsistencies and potential quality deterioration. This dataset focuses on controlled drying conditions in a tray dryer with hot air, allowing for optimized drying parameters like temperature, airspeed and mass loading.

By including data on drying kinetics models, moisture sorption isotherms, and compositional analysis using techniques like FTIR and AAS, this dataset offers a well-rounded perspective on Ethiopian oyster mushroom drying. This information is valuable for designing efficient drying processes, predicting drying behavior, and ensuring the preservation of essential nutrients and functional groups during drying. Overall, this data article makes a significant contribution by providing valuable insights for researchers and practitioners in food science, agriculture, and biotechnology to enhance mushroom drying processes, optimize storage, and develop innovative preservation techniques.

3 Data Description

3.1 Drying parameter optimization using RSM-BBD

Table 1 represent the RSM-BBD experimental matrix with predicted response and actual moisture content of oyster mushroom in drying by tray dryer. The drying variables consists of temperature (50 °C, 70 °C), hot air speed (2 m s-1, 5 m s-1), and mass loading (100 g, 300 g) with their upper and lower limits of the parameters. Based on the fitted model numerical optimization using RSM, the optimum drying temperature, air-speed and mass of slice mushroom are 59.81 °C, 2.96 m s-1, and 200 g, respectively. The response was moisture content of the mushroom and was evaluated using the following equation (Table 2).(1) MC(wt.%)=112.99483−2.54225T−10.36958A−0.035564M+0.090583TA+0.000330TM−0.004883AM+0.015839T2+0.862813A2+0.000133M2

where MC is moisture content, T is temperature, A is air speed and M is mass loadTable 1 BBD experimental matrix of the three factors and their corresponding response.

Table 1:Factor 1	Factor 2	Factor 3	Response 1: Moisture content (wt%)	
A: temperature	B: air-speed	C: mass loading	Actual
(wt%)	Predicted
(wt%)	
(°C)	(m s-1)	(g)	
50	3.5	100	17.29 ± 0.02	18.12	
60	5	100	12.8 ± 0.10	12.70	
70	3.5	300	16.63 ± 0.02	15.80	
60	3.5	200	10.11 ± 0.01	9.67	
50	2	200	26.46 ± 0.02	25.43	
70	5	200	12.34 ± 0.02	13.37	
50	3.5	300	22.5 ± 0.02	23.43	
60	2	100	12.5 ± 0.04	12.71	
60	3.5	200	8.84 ± 0.01	9.67	
60	3.5	200	9.87 ± 0.02	9.67	
70	2	200	10.15 ± 0.02	10.88	
60	3.5	200	9.85 ± 0.01	9.67	
60	5	300	16.78 ± 0.02	16.57	
60	2	300	22.34 ± 0.03	22.44	
50	5	200	17.78 ± 0.01	17.05	
70	3.5	100	8.45 ± 0.02	7.52	

Table 2 ANOVA results of response surface quadratic regression model.

Table 2:Source	Sum of Squares	df	Mean Square	F-value	p-value	Remark	
Model	450.42	9	50.05	40.79	0.0001	significant	
A-temperature	166.17	1	166.17	135.42	< 0.0001		
B-hot air speed	17.26	1	17.26	14.06	0.0095		
C-mass	92.55	1	92.55	75.42	0.0001		
AB	29.54	1	29.54	24.07	0.0027		
AC	2.21	1	2.21	1.80	0.2286		
BC	8.58	1	8.58	7.00	0.0383		
A²	50.80	1	50.80	41.40	0.0007		
B²	47.64	1	47.64	38.83	0.0008		
C²	35.67	1	35.67	29.07	0.0017		
Residual	7.36	6	1.23				
Lack of Fit	6.41	3	2.14	6.71	0.0761	not significant	
Pure Error	0.9549	3	0.3183				
Cor Total	457.78	15					

Based on the p-value (<0.05) of the pre-defined model, the quadratic model has been significant and selected for drying of mushroom moisture content prediction and optimization of the process parameters during the drying of mushrooms. From ANOVA the model is significant to explain the mushroom drying with p-value less than 0.0001 as shown in Table 2. The Model F-value of 40.79 also implies the model is significant.

3.2 Description of drying kinetics data

Table 3 summarized the dataset encompasses comprehensive drying kinetics data showing the thin layer drying kinetics model to analyze the drying behavior of oyster mushrooms at various temperatures ranging from 50 to 75 °C. The moisture ratio and moisture removal rate with time at different temperature (50, 55, 60, 65, 70, and 75 °C) were presented on Fig. 1. The included graph illustrates the drying kinetics model fitted to the experimental data, depicting the moisture content evolution over time for each temperature condition. Moreover, a detailed table (Table 3) showcases the key parameters derived from the thin layer drying model at different temperature levels, enabling researchers to delve into the specific drying characteristics, kinetics constants, and moisture transfer rates associated with oyster mushroom drying under varying thermal conditions. This data not only facilitates a deeper understanding of the drying process dynamics but also provides a foundation for informed decision-making in optimizing drying protocols and enhancing the overall efficiency of mushroom drying operations.Table 3 Different thin-layer drying kinetic models with their parameters.

Table 3:Models	Temperature (°C)	a	b	c	k	n	R2	RMSE	
Lewis or Newtons	50	NA	NA	NA	0.006589	NA	0.9703	0.05452	
55	NA	NA	NA	0.007551	NA	0.9698	0.05525	
60	NA	NA	NA	0.008239	NA	0.9804	0.0435	
65	NA	NA	NA	0.008238	NA	0.9804	0.0435	
70	NA	NA	NA	0.007381	NA	0.9667	0.05946	
75	NA	NA	NA	0.007083	NA	0.9619	0.06434	
Page Models	50	NA	NA	NA	0.001008	1.361	0.9956	0.02123	
55	NA	NA	NA	0.001003	1.397	0.9965	0.01902	
60	NA	NA	NA	0.001745	1.31	0.9985	0.01225	
65	NA	NA	NA	0.001745	1.31	0.9985	0.01225	
70	NA	NA	NA	0.000768	1.447	0.9996	0.00692	
75	NA	NA	NA	0.0006021	1.484	0.9995	0.007191	
Modified page	50	NA	NA	NA	0.007583	0.8689	0.9703	0.05545	
55	NA	NA	NA	0.03045	0.248	0.9698	0.05619	
60	NA	NA	NA	−0.0668	−0.1233	0.9804	0.04427	
65	NA	NA	NA	0.04247	0.194	0.9804	0.04427	
70	NA	NA	NA	0.3778	0.01954	0.9667	0.06056	
75	NA	NA	NA	0.02538	0.2791	0.9619	0.06552	
Two term exponentials	50	0.6328	0.4504	NA	0.0071	NA	0.9775	0.04914	
55	0.543	0.5468	NA	0.008161	NA	0.9773	0.04955	
60	0.1304	0.9459	NA	0.008813	NA	0.9858	0.03829	
65	0.4012	0.7051	NA	0.008452	NA	0.9799	0.04725	
70	0.5654	0.556	NA	0.008204	NA	0.9805	0.04715	
75	0.09356	1.037	NA	0.007935	NA	0.9781	0.05063	
Henderson–Pabis	50	1.083	NA	NA	0.007101	NA	0.9775	0.04828	
55	1.09	NA	NA	0.008162	NA	0.9773	0.04869	
60	1.076	NA	NA	0.008812	NA	0.9858	0.0376	
65	1.106	NA	NA	0.008451	NA	0.9799	0.0464	
70	1.121	NA	NA	0.008203	NA	0.9805	0.04627	
75	1.131	NA	NA	0.007935	NA	0.9781	0.04968	
Logarithmic	50	1.203	NA	−0.1708	0.004906	NA	0.9949	0.02329	
55	1.16	NA	−0.110	0.006263	NA	0.9906	0.03194	
60	1.123	NA	−0.0793	0.007186	NA	0.9945	0.02387	
65	1.168	NA	−0.0991	0.006664	NA	0.9909	0.03187	
70	1.188	NA	−0.104	0.006464	NA	0.9902	0.03342	
75	1.214	NA	−0.124	0.006038	NA	0.9898	0.03454	
Midilli et al.	50	1.016	−0.04627	NA	0.001061	1.323	0.9985	0.01307	
55	0.9754	0.0007173	NA	−0.01413	1.447	0.9981	0.01456	
60	0.989	−0.01303	NA	0.001546	1.322	0.9993	0.008749	
65	0.985	−0.004788	NA	0.000747	1.456	0.9993	0.008757	
70	0.9875	0.0006516	NA	0.007991	1.483	0.9996	0.006512	
75	0.9992	1.309e-05	NA	0.0005607	1.5	0.9996	0.007188	
Singh et al.	50	0.05955	NA	NA	0.005269	NA	0.9927	0.02751	
55	0.03687	NA	NA	0.006417	NA	0.9865	0.03753	
60	0.02528	NA	NA	0.007291	NA	0.9914	0.02932	
65	0.03615	NA	NA	0.006582	NA	0.9849	0.04029	
70	0.04349	NA	NA	0.006189	NA	0.9822	0.0442	
75	0.05484	NA	NA	0.005755	NA	0.981	0.04631	
NA=not applicable.

Fig. 1 Moisture removal at various temperature A) Moisture content versus drying time B) Moisture ratio versus drying time.

Fig1

3.3 Description of moisture sorption data

The moisture sorption data includes the different comprehensive moisture sorption models with the determined parameters data obtained from water activity versus moisture content experiments conducted at temperatures ranging from 25 °C to 50 °C, capturing the equilibrium moisture content of oyster mushrooms under varying environmental conditions. The sorption data was meticulously fitted with multiple moisture sorption models to analyze the moisture sorption behavior and predict the equilibrium moisture content at different water activities and temperatures. Table 4 presents the sorption isotherms along with a detailed table incorporating the model-fitted parameters, offers a clear visualization and interpretation of the moisture sorption characteristics of oyster mushrooms. By leveraging this rich dataset, researchers can gain valuable insights into the sorption mechanisms, humidity susceptibility, and moisture equilibrium properties of oyster mushrooms, fostering advancements in food preservation strategies, product formulation, and quality control measures within the food science and technology domain.Table 4 Moisture Sorption model constants and statistical parameters.

Table 4:Sorption models	Temperature (°C)	Coefficients	Statistical parameters	
a	b	c	R2	RMSE	
Modified Halsey	50	2.588	0.002258	1.742	0.6679	17.42	
40	−5.346	0.2193	3.464	0.6194	17.13	
30	0.1407	0.1105	3.406	0.6103	17.01	
Modified Chung-Pfost	50	4.909	0.0004011	0.1039	0.9184	8.633	
40	5.656	0.0002936	0.08017	0.9406	6.765	
30	5.157	0.0004713	0.08761	0.9462	6.323	
Iglesias and Chi rife	50	91.13	4.291	NA	0.9532	6.361	
40	96.8	−0.308	NA	0.9654	5.042	
30	95.82	0.2115	NA	0.967	4.845	
Modified Henderson	50	−0.000952	−43.8	1.36	0.9762	4.664	
40	−0.004215	−37.53	1.228	0.9891	2.895	
30	−0.001588	−24.1	1.252	0.9871	3.093	
GAB	50	C = −2.314e+05	K = 0.8854	Mo=16.56	0.9707	5.174	
40	C = −1.524e+05	K = 0.8897	Mo=16.34	0.9782	4.102	
30	C = −2.546e+05	K = 0.8857	Mo=16.77	0.9687	4.819	
BET	50	−0.005688	0.1251	NA	0.7527	13.49	
40	−0.005692	0.1251	NA	0.7527	13.49	
30	−0.003156	0.1174	NA	0.7294	13.88	
Ferro-Fontan	50	4.909	0.0004011	0.1039	0.9184	8.633	
40	5.656	0.0002936	0.08017	0.9406	6.765	
30	5.157	0.0004713	0.08761	0.9462	6.323	
NA=not applicable.

3.4 Description of mineral composition, proximate analysis and functional group data

Elemental/mineral analysis: The basic metals (Magnesium, Calcium, Sodium, potassium, Copper, and Zinc) of fresh and dried oyster mushrooms are presented in Table 5. The result obtained from AAS are given with standard deviations for each metal. The values indicate that drying of oyster mushroom with the optimal drying condition have no side effect on the important mineral compositions.Table 5 Mineral composition of fresh and dried mushrooms.

Table 5:Type of metals	Composition value (mg/l)	
Fresh Mushroom	Dried mushroom	
Magnesium (Mg)	5.861 ± 0.192	4.992 ± 0.2	
Calcium (Ca)	8.724 ± 0.138	8.413 ± 0.16	
Sodium (Na)	12.74 ± 0.195	12.528 ± 0.12	
Potassium (K)	10.1937 ± 0.261	9.834 ± 0.3	
Copper (Cu)	2.971 ± 0.095	2.302 ± 0.01	
Zinc (Zn)	2.607 ± 0.079	1.949 ± 0.04	

Proximate Analysis: The results of the proximate composition for dried and fresh oyster mushrooms are summarized in Table 6. The proximate data of oyster mushroom also included comparison data with other mushroom types (Calocybe gambosa, Pleurotus ostreatus) of previous study. The details the analysis of fresh and dried oyster mushrooms includes the key nutritional components such as moisture Content, Carbohydrates, Protein, ash content, fat and crude fiber content. Fresh mushrooms had a high moisture content of 93.8 wt% compared to just 9.52 wt% in dried mushrooms. This highlights the substantial water removal achieved through drying. The total carbohydrates were the most abundant component in both fresh (51.03 wt%) and dried (50.24 wt%) mushrooms. Drying resulted in a minimal decrease in carbohydrate content. Protein content also showed a minor decrease from 29.51 wt% in fresh mushrooms to 27.83 wt% in dried ones. The drying process had minimal impact on ash content (8.83 wt% in fresh vs. 8.61 wt% in dried mushrooms) and crude fat content (1.94 wt% in fresh vs. 1.86 wt% in dried mushrooms). This suggests that drying effectively preserved the inorganic components (ash) and the low levels of lipids (fat) present in the mushrooms. Overall, drying oyster mushrooms to the optimal moisture content effectively preserved the important nutritional components (protein, carbohydrates, and gross energy value) with the exception of moisture content itself.Table 6 Proximate analysis of fresh mushroom and dried mushroom.

Table 6:Proximate parameters	Fresh mushrooma	Dried Mushrooma	Calocybe gambosab	Pleurotus ostreatusc	
Moisture content (wt%)	93.5 ± 1.23	9.52 ± 0.49	90.92 ± 1.08	4.80 ± 0.59	
Ash content (wt%)	8.83 ± 0.36	8.61 ± 0.61	13.89 ± 1.41	6.60 ± 0.45	
Fat content (wt%)	1.94 ± 0.1	1.86 ± 0.06	0.83 ± 0.11	1.50 ± 0.10	
Protein content (wt%)	29.51 ± 0.53	27.83 ± 1.01	16.38 ± 0.24	30.50 ± 0.44	
Crude fiber (wt%)	8.69 ± 0.42	11.46 ± 0.73	ND	8.20 ± 0.77	
Total carbohydrate (wt%)	51.03 ± 0.91	50.24 ± 0.8	69.83 ± 1.22	51.9 ± 0.25	
Gross Energy value (kcal/100 g)	367.6 ± 2.73	329.02 ± 2.35	400.65 ± 3.58	ND	
a present study.

b Fresh mushroom (Calocybe gambosa) [4].

c Dried mushroom (pleurotus ostreatus) [5], ND: not determined.

Functional group analysis:Fig. 2 presents the qualitative functional group analysis of both dried and fresh mushrooms obtained from Fourier transform infrared (FTIR) spectroscopy. The spectra of the samples were similar, with slight differences in the intensity of the peaks. The functional groups were identified were Inorganic phosphate, Amides, Aliphatic groups, Amino acids, Methyl groups in protein, Carbohydrates, Aliphatic hydrocarbons, Phenolic compounds, and water. Overall, the FTIR analysis indicates that the dried and fresh mushroom samples contain a variety of functional groups, including those associated with proteins, carbohydrates, lipids, and phenolic compounds. These functional groups are responsible for the various properties of mushrooms, such as their nutritional value, antioxidant activity, and potential health benefits.Fig. 2 FTIR results of Fresh and dried mushroom.

Fig 2:

4 Experimental Design, Materials and Methods

4.1 Materials, equipment and software

Raw material: Oyster mushroom used for the present study was collected from Menagesha Integrated Organic Farm mushroom harvesting company, Oromia, Ethiopia.

Instruments: Water activity meter, Tray dryer, Hotwire velocity meter, AAS, FT-IR used for measurements and data analysis.

Software: Design expert, MATLAB, Excel are used for simulations and data analysis.

4.2 Methods

4.2.1 Sample preparation and drying experiments

Fresh mushrooms were washed, sliced for drying. The Sliced mushrooms were placed on trays in a computer-controlled tray dryer. Hot air was used to remove moisture from the mushrooms. Drying temperature (40–80 °C), airspeed (1–5.5 m s-1), and mass load (50–500 g) were varied to investigate their effects and to obtain the optimal drying conditions.

Initial moisture content determination: About 5 g sample was taken in a dried crucible and in an Oven (700LT-No. TD-1315, Cooper Technology, UK) set at 105 °C ± 2 for 24 h. Then after the dried sample (wd) was measured and subtracted from the initial weight of the sample (wo) to determine the moisture content (MC) of the sample as given by the following equation [6].(2) MC(wt%)=wo−wdwo×100

Design of experiment (DOE) for tray dryer: Experiments were conducted to investigate the effects of drying temperature, airspeed, and mass load on the final moisture content of the dried mushrooms. The lower and upper limit of the drying parameters were given in Table 7. A statistical method (Response surface methodology (RSM) – Box–Behnken Design (BBD)) was used to optimize the drying conditions and a total of sixteen drying experiments were conducted and each was triplicated.Table 7 Experimental matrix for RSM-BBD for oyster mushroom drying.

Table 7:Process parameters	Labels	Units	Low level	Middle	High level	
Temperature	T	οC	50	60	70	
Hot air-speed	V	m s-1	2	3.5	5	
Mass loading	W	g	100	200	300	

Statistical Analysis: All drying experiments were done in triplicate, and the mean values of the results were taken and processed using design expert software (Design-Expert version 12). The One-way analysis of variance (ANOVA) was done using response surface methodology (RSM), with p-values of <0.05 representing a significant level. R2 and RSME were used to analyze and select the good fit drying kinetics models.

4.2.2 Drying kinetics models

Drying experiments were conducted at different temperatures to study the drying rate of mushrooms. By taking optimum air speed at 3 m s-1 and mass loading of distributed 200 g of mushrooms on a tray of tray dryer at six different temperatures (50, 55, 60, 65, 70 and 75 °C) drying experiments were done. Mathematical models were used to describe the relationship between moisture content and drying time. Eight well-known thin-layer drying kinetics models were used to study the drying kinetic for mushroom drying (Table 8) [[7], [8], [9]]. The best model was selected based on its ability to fit the experimental data.Table 8 Various drying kinetics models proposed by several researchers for fruit sample.

Table 8:Model name	Model	
Lewis or Newton	MR=exp(−kt)	
Page	MR=exp(−ktn)	
Modified page	MR=exp(−kt)n	
Two exponentials	MR=aexp(−kt)+(1−a)exp(−kt)	
Henderson and Pabis	MR=aexp(−kt)	
Logarithmic	MR=aexp(−kt)+c	
Midilli et.al.	MR=aexp(−ktn)+c	
Singh et al.	MR=exp(−kt)−akt	

4.2.3 Moisture sorption models

A model was used to describe the relationship between the water activity of the mushrooms and their equilibrium moisture content. There are many moisture sorption isotherm models. Among these, seven selected sorption models were tested with an experimental result and the one with the good-of-fit was used in the modelling (Table 9). Water activity (aw) experiments were done to select the sorption model using water activity meters (AQUA LAB: 4TE, Italy) which measure the water activity of mushrooms when the moisture content reached equilibrium at a given temperature. aw versus equilibrium moisture content data was generated at a temperature of 30, 40, and 50 °C. The goodness-of-fit of the moisture sorption isotherm model for mushrooms was clearly explained with a higher value of R2 and lower values of RMSE.Table 9 Different moisture sorption models selected for mushrooms.

Table 9:Models	Model equation	References	
Modified Chung and pfost	Me =−1Cln⁡(−(T+BA)lnaw)	[10]	
Iglesias and Chirife	Me=A(aw2−aw)+B	[11]	
Modified Henderson	Me=(−ln(1−aw)1CA(T+B))	[12]	
G.A. B	Me =⁡(M0CKaw(1−Kaw)(1−Kaw+CKaw))	[11]	
B.E.T	aw/((1−aw)Me)=A+Baw	[13]	
Modified Halsey	Me=1cln⁡((−e)ln(aω)(A+B))	[10]	
Ferro-Fontan	Me =[−1AlnBaw]1C	[11]	

4.2.4 Mineral composition, proximate analysis and functional analysis

Proximate analysis: Moisture content, ash content, crude fiber, fat, protein, gross energy value, and total carbohydrate are the most widely used properties analyzed for food product characterization under proximate analysis. The analysis was carried out according to the Association of Official Analytical Chemists (AOAC) standard.

Atomic Absorption Spectroscopy (AAS) analysis: The inorganic elemental composition of the dried and fresh mushrooms (Magnesium, Calcium, Sodium, Potassium, Copper, and Zinc) was determined using AAS (Agilent 4200MP-AAS; WI, USA) following the AOAC method. About 1 g of each of the samples was digested with a 1 M nitric acid solution and stirred for 30 min at 300 rpm using a hot plate and the sample was filtered before use. Then the concentration of the metals such as Na, Ca, Mg, K, Cu, and Zn were determined with the blank reference sample.

Functional group analysis: Fourier transform infrared (FTIR) spectroscopy (Thermo Scientific iS50 ABX, WI, USA) instrument equipped with an attenuated total reflection accessory, KBr beam splitter, and detector was used to identify the functional groups present in the dried mushrooms. Initially, the background was taken and the samples were placed on the solid sample holder and data was collected at 32 resolutions and 16 scans. The IR spectrum of scanning the sample was conducted in the range of 4000 and 400 cm−1 wavenumbers.

Limitations

None.

Ethics Statement

This work does not involve human subjects, animal experiments, or any data collected from social media platforms.

CRediT authorship contribution statement

Talbachew Tadesse Nadew: Conceptualization, Methodology, Investigation, Formal analysis, Software, Data curation, Validation, Visualization, Writing – review & editing. Tsegaye Sissay Tedla: Investigation, Formal analysis. Yonas Desta Bizualem: Investigation, Formal analysis. Shimeles Nigussie Abate: Investigation, Formal analysis. Lemlem Tadesse Teklehaymanot: Data curation, Validation, Visualization.

Data Availability

Data on drying kinetics, moisture sorption isotherm, composition study of Ethiopian oyster mushroom (Pleurotus ostreatus mushroom) drying in tray dryer (Original data) (Mendeley Data).

Acknowledgments

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors thanks Wollo University, Kombolcha Institute of Technology, Kombolcha, Ethiopia and Addis Ababa Science and Technology University, Addis Ababa, Ethiopia for their collaboration during the experimental investigations.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could be perceived to have influenced the work reported in this article.
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