Optimization of Extraction Parameters of Ethanol Extracts of Propolis Samples Using Artificial Neural Network and Moth-Flame Optimization Algorithm

Ayşenur Gurgen; Huseyin Serencam; Yakup Kara; Zehra Can; Sibel Yıldız

Open Access

Optimization of Extraction Parameters of Ethanol Extracts of Propolis Samples Using Artificial Neural Network and Moth-Flame Optimization Algorithm

and

| Oct 26, 2021

Journal of Apicultural Science

Volume 65 (2021): Issue 2 (December 2021)

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Cite

Published Online: Oct 26, 2021

Page range: 229 - 241

Received: Jun 16, 2020

Accepted: Jul 08, 2021

DOI: https://doi.org/10.2478/jas-2021-0018

Keywords
artificial neural network, extraction parameters, modelling, optimization, propolis

© 2021 Ayşenur Gurgen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Spiral flying path around close light sources (Mirjalili, 2015).

Euclidean distance approach of this study.

The optimum extraction parameters obtained from single objective optimization

Assay	Ethanol content (%)	Extraction time (h)	Estimated value	Unit
TPC	57.50	13.96	91.19	mg GAE/g
FRAP	72.03	18.04	673.05	μmol FeSO₄7H₂O/g

MFO algorithm architecture

Parameters	Value
Number of search agents	20
Maximum number of iterations	30
Run Number	100

The optimum extraction parameters obtained from multi-objective optimization

Objective	Ethanol content (%)	Extraction time (h)	TPC (mg GAE/g)	FRAP (μmol FeSO₄7H₂O/g)
Max. TPCMax. FRAP	70.03	16.93	83.35	667.26

TPC and FRAP activities of propolis ethanol extracts

Experiment number	Ethanol content (%)	Extraction time (h)	TPC (mg GAE/g)	FRAP (μmol FeSO₄·7H₂O/g)
1	40	8	27.56±1.82^a	239.85±6.83^a
2	40	10	32.69±0.87^b	239.76±3.82^a
3	40	12	24.19±0.68^a	233.80±0.65^a
4	40	16	24.85±0.90^a	227.25±2.33^a
5	40	20	34.39±0.82^b	277.01±1.21^b
6	40	24	47.20±0.24^c	311.79±2.83^c
7	50	8	61.64±0.82^def	353.72±0.00^d
8	50	10	57.83±0.45^d	306.93±0.72^c
9	50	12	64.51±2.50^fgh	359.25±3.75^d
10	50	16	59.33±0.19^de	350.92±0.68^d
11	50	20	66.42±0.72^ghi	346.92±3.30^d
12	50	24	68.32±1.42^hij	430.37±38.90^e
13	60	8	83.95±3.61^no	646.89±10.04^no
14	60	10	62.53±3.87^efg	462.13±5.16^f
15	60	12	85.35±0.90^o	578.34±1.92^jk
16	60	16	70.07±1.60^ij	587.76±3.89^kl
17	60	20	81.14±0.09^no	512.79±9.11^gh
18	60	24	74.95±0.69^kl	568.41±2.03^j
19	70	8	82.06±4.46^no	657.25±2.44^o
20	70	10	64.04±4.32^fgh	527.87±17.85^hi
21	70	12	59.28±1.28^de	501.61±3.76^g
22	70	16	85.31±3.33^o	632.80±1.34^mn
23	70	20	75.49±3.02^kl	587.75±7.73^kl
24	70	24	76.44±1.73^lm	597.94±5.31^l
25	80	8	80.01±2.09^mn	617.95±0.00^m
26	80	10	64.34±0.18^fgh	618.87±13.44^m
27	80	12	71.56±0.47^jk	495.96±11.87^g
28	80	16	64.45±3.01^fgh	591.99±11.57^kl
29	80	20	64.28±6.16^fgh	543.13±9.23ⁱ
30	80	24	85.25±2.24^o	623.19±14.57^m

Comparison of some propolis extraction optimization research with the study

Previous study	Input variables	Output variables	Optimization method
Yingjuan et al. (2007)	Ethanol concentrationExtracting timeExtracting powerRatio of liquid to propolis	Flavones	Response Surface Methodology (RSM)
Wang et al. (2009)	Ethanol concentrationRatio of liquidThe holding time of pressurePressure to propolis	Flavones	RSM
Kim et al. (2009)	Ethanol concentrationExtraction time	Total polyphenol content (TPC)Total flavonoid content (TFC)	RSM
Li et al. (2012)	Microwave treatment timeMicrowave powerEthanol concentrationTemperatureTimeSolvent-to-solid	Total flavonoid yield	RSM
Yuan et al. (2013)	Ratio of lipid to drugRatio of soybean phospholipid to cholesterolSpeed of injection	Propolis flavonoids liposome (PFL)	RSM
Zhao et al. (2012)	Extraction timeEthanol concentrationSolid-liquid ratioDistilling frequencyDistilling temperature	Extraction ratio TFC	RSM
Oldoni et al. (2015)	Ethanol ratioTemperature Time	TPCDPPH	2³ factorial design
Nichitoi et al. (2019)	Particle sizeSolvent type (ethanolic aqueous)Extraction duration	TPCTFCAntioxidant capacity	Partial Least Squares Regression
Our study	Ethanol contentExtraction time	TPC (Single objective)FRAP activities (Single objective)TPC and FRAP (Multi-objective)	ANN and MFO

Performance of the best models

Studied assay	Performance of model	Training	Validation	Test	All
TPC	MAPE	4.51	4.48	8.19	5.12
	MSE	17.02	6.46	51.67	21.74
	R²	0.97	0.99	0.96	0.96
FRAP activity	MAPE	1.41	0.69	9.23	2.45
	MSE	81.91	12.73	3929.23	624.12
	R²	0.99	0.99	0.96	0.98

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Optimization of Extraction Parameters of Ethanol Extracts of Propolis Samples Using Artificial Neural Network and Moth-Flame Optimization Algorithm

Article Category: Original Article

Published Online: Oct 26, 2021

Page range: 229 - 241

Received: Jun 16, 2020

Accepted: Jul 08, 2021

DOI: https://doi.org/10.2478/jas-2021-0018

Keywords
artificial neural network, extraction parameters, modelling, optimization, propolis

© 2021 Ayşenur Gurgen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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Fig. 7

The optimum extraction parameters obtained from single objective optimization

MFO algorithm architecture

The optimum extraction parameters obtained from multi-objective optimization

TPC and FRAP activities of propolis ethanol extracts

Comparison of some propolis extraction optimization research with the study

Performance of the best models

Optimization of Extraction Parameters of Ethanol Extracts of Propolis Samples Using Artificial Neural Network and Moth-Flame Optimization Algorithm

Article Category: Original Article

Published Online: Oct 26, 2021

Page range: 229 - 241

Received: Jun 16, 2020

Accepted: Jul 08, 2021

DOI: https://doi.org/10.2478/jas-2021-0018

Keywordsartificial neural network, extraction parameters, modelling, optimization, propolis

© 2021 Ayşenur Gurgen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

The optimum extraction parameters obtained from single objective optimization

MFO algorithm architecture

The optimum extraction parameters obtained from multi-objective optimization

TPC and FRAP activities of propolis ethanol extracts

Comparison of some propolis extraction optimization research with the study

Performance of the best models

Keywords
artificial neural network, extraction parameters, modelling, optimization, propolis