Available online on 15.12.2022 at http://jddtonline.info

Journal of Drug Delivery and Therapeutics

Open Access to Pharmaceutical and Medical Research

Copyright   © 2022 The  Author(s): This is an open-access article distributed under the terms of the CC BY-NC 4.0 which permits unrestricted use, distribution, and reproduction in any medium for non-commercial use provided the original author and source are credited

Open Access  Full Text Article                                                                                                                                                                              Research Article 

Formulation Development of Flaxseed Oil Beads Containing w-Fatty Acid

Tirupati M. Rasala*^{1, 2}, Rajesh J. Mujariya¹, Shubham. S. Gupta², Abhay. M. Ittadwar²

¹ Institute of Pharmaceutical Science and Research, Sardar Patel University, Balaghat, MP, India, 481331

² Department of Pharmaceutics, Gurunanak College of Pharmacy, Nagpur, Maharashtra, India, 440026

Nowadays "Nutraceutical" movement has created a huge need for the creation of novel dietary supplement formulations. These are the supplements which are used as medication in addition to nutrition to benefit health, prevent chronic diseases, modulate the immune system, lengthen life expectancy, and many other things. The idea of essential fatty acids derives from the fact that they are necessary lipids for the human body because of their cellular roles linked to inflammatory and immune responses. They are also endogenously incapable of synthesis, necessitating their consumption¹.

Omega-3 essential fatty acids are a class of nutraceuticals under the study for food enrichment due to their functional properties. The main classes of essential fatty acids are omega-3 and omega-6, represented by the major compounds in foods: Alpha-Linolenic Acid (ALA, C18:3) and Linoleic Acid (LA, C17:2), respectively^2,3.

Long-chain polyunsaturated fatty acids in the omega-3 family, such as docosahexaenoic acids (DHA, C20:5) and eicosapentaenoic acids (EPA, C22:6, n- 3)., have drawn interest because of their potential to protect cardiovascular illnesses and to regulate body homeostasis Omega-3 fatty acids, which have important cardioprotective qualities, also have anti-inflammatory, antiarrhythmic, vasodilatory, and active effects on dyslipidaemia, diabetes mellitus, and obesity ^4,5. LA and ALA are essential fatty acids since neither humans nor other higher animals are able to manufacture them. Eicosanoids, which are produced from these Fatty Acids, are also referred to as locally acting bioactive signalling lipids. EPA and DHA create anti-inflammatory eicosanoids, whereas arachidonic acid (ARA) produces pro-inflammatory eicosanoids^6,7.

α-Linolenic acid makes a notable contribution to the fatty acids within green leafy tissues of plants, typically comprising over 50 % of the fatty acids present. This is because α-linolenic acid is an essential component of the membranes of thylakoids within chloroplasts. α-Linolenic acid is found in significant amounts in several seeds, seed oils and nuts. Linseeds (popularly known as flaxseeds) and their oil typically consists of 45–55 % of fatty acids as α- linolenic acid. In contrast, soyabean oil, rapeseed oil and walnuts contain 5–10 % of fatty acids as α- linolenic acid⁸.

The oils are more prone to oxidation on exposure to different environmental conditions. The oil containing omega fatty acid to encapsulate in beads was one of the difficult approaches to encapsulate in bead formulation. The aim of current research work was aimed to design and develop w -fatty acid containing pectin beads using QBD.

1. MATERIALS AND METHOD
   1. Materials

Flaxseeds were obtained from Wagh Brothers Pvt. Ltd. (Nagpur, India). Pectin, Chitosan and Calcium Chloride were purchased from Himedia Laboratories Pvt. Ltd. Acetic acid and Tween 20 was obtained from Merck Specialities Pvt. Ltd. and SD fine-chem Ltd. Fish oil was purchased from Triveni Chemicals, Gujrat.

1. Experimental method
   1. Risk Assessment

The fish-bone diagram was considered to identify the potential risk factors (CQAs) of formulation and development, which affects % encapsulation efficiency and % drug release. Based on literature review and prior knowledge, the failure mode and effect analysis (FMEA) method were further applied in the initial risk analysis parameters of the beads. The RPN limit was set at 36 and 38. Any procedure parameter with an RPN 12 was viewed as a potential basic factor based on terms of severity (S), detectability (D) and probability (P)^9,10.

Extraction of omega fatty acid oil containing Seeds: 100gm flaxseeds were cold macerated in a 1:1 ratio with petroleum ether and n-hexane. The supernatant solvent is distilled at 50-60°C after 10-12 days and the oil is collected¹¹.

The different phytochemical components were evaluated for the collected oil such as alkaloids, steroids, terpenoids, flavonoids, saponins, tannins, phenolic compounds, cardiac glycoside, proteins, and carbohydrates^12,13.

Hexabromide test: Pipette one ml of oil into a boiling tube (wide-mouthed 100 ml capacity). Drop-wise add 5 mL of chloroform and about 1 mL of bromine until the mixture turns a deep red colour, then cool the test-tube in an ice water bath. Add 1.5 mL of rectified spirit drop-wise while shaking the mixture until the precipitate that formed dissolves, and then add 10 mL of diethyl ether. Place the tube in an ice water bath for 20 minutes after mixing the contents. The presence of polyunsaturated fatty acids is indicated by the appearance of precipitate¹⁵.

1. Drug Excipient Compatibility Studies
   1. Fourier Transform Infrared Spectroscopy 

The FTIR analysis method scans test samples with infrared light to observe chemical properties. The FTIR spectra of extracted flaxseed oil samples from RTMNU, Nagpur were analysed using a Bruker FTIR spectrophotometer¹⁶. 

Preparation of stock solution of drug: 100mg of pure fish oil weighed accurately and carefully transferred into 100 ml volumetric flask was dissolved in 100 mL of pure methanol and left to stand for 30 minutes. 

Preparation of sample solutions for analysis: By diluting the stock solution with methanol, various drug concentrations ranging from 5 to 25 mg/ml were prepared and absorbance was taken at 203nm.

The dripping method was used to create chitosan-pectin hydrogel beads, with calcium chloride (CaCl2) in deionised water serving as a continuous media. At 70 °C, chitosan solution was prepared by dissolving it in 5% (v/v) acetic acid. Using a magnetic stirrer, pectin was dissolved in deionized water at 40 °C. After dissolving 300 mg flaxseed oil in the pectin solution, the mixture was homogenised for 5 minutes with 0.5% (v/v) Tween 20 as an emulsifying agent. The pectin-containing oil was placed in a syringe and dripped into a CaCl₂ solution while magnetically stirring at 351 °C. After being washed with deionized water, the beads were immersed in chitosan for 30 minutes. The beads were washed again, oven-dried for 4 hours at 60 °C, wrapped in an aluminium foil bag, and stored at 4-6 °C for further testing^17–19.

1. Screening, Optimisation and Validation of Flaxseed Oil Containing Pectin Chitosan Beads
   1. Quality by design (QbD)

A potential approach for the element of pharmaceutical development to provide a framework of the current status of QbD for pharmaceutical product is Quality Target Product Profile (QTPP), Critical quality Attributes (CQAs), Risk Assessment, Design space, Control strategy, Product life cycle Management, and Continual Improvement^20–22 (Table 1).

Table 1: Quality Target Product Profile (QTPP) with reference to in process critical quality attribute 

Depending on the RPN number based on FMEA and multivariate data analysis, the effect of CQA on finished product quality were analysed for establishment of design space with a goal to ensure the quality of product (Table 2).

Table 2: Failure Modes and Effects Analysis (FMEA)

The Plackett-Burman factorial design was used to screen three variables in order to identify significant factors influencing the characteristics of the beads. Each variable was represented at two levels of range covered by each variable and the responses (1+ and -1). Response surface methodology was used to further optimise the variables that had a significant effect on critical quality attributes of the granules based on the regression analysis of the variables. The value of probe F less than 0.05 implied that model term was significant^23,24 (Table 3 & 4). 

Table 3: Levels of Plackett- Burman screening experiment

Table 4: Two level Plackett– Burman Factorial Design

The central composite design was used to optimise the two factors i.e. Chitosan and Stirring speed which was found significant in screening with plackett- Burman design²⁵(Table 5 & 6).

Table 5: Levels of design experiment

Table 6: Three levels Central composite design

The Response optimization design was used to optimize the two factors screened using Central composite design i.e. Chitosan and Speed²⁶ (Table 7).

Table 7: Levels of design experiment

Six batches of optimized formulation were prepared and evaluated for % Drug release and % Encapsulation efficiency (Table 8).

Table 8: Validation batch of Optimized formulation

% Drug Release:       

Where, c = y -intercept (the point in which the line crosses the y -axis).

 y = Absorbance, x = concentration, m= slope 

Where, V1- Concentration of oil encapsulated in beads

V2- Total oil taken

SEM was used to examine the surface morphology of oil beads loaded with pectin and chitosan. A set of lenses in the electron column then focus the beam on the sample surface. The beads were smooth, distinct, round, and had sharp edges without any surface degradation or fissures²⁸.

Gas chromatography–mass spectrometry (GC-MS) is an analytical method that combines the features of gas-chromatography and mass spectrometry to identify different substances within a test sample. Oil samples were analysed using GCMS at ANACON Labs Pvt. Ltd. Butibori, Nagpur^29,30.

1. RESULTS AND DISCUSSION
   1. Phytochemical Evaluation

The different phytochemical components were evaluated for the collected oil such as alkaloids, steroids, terpenoids, flavonoids, saponins, tannins, phenolic compounds, cardiac glycoside, proteins, and carbohydrates (Table 9).

Table 9: Phytochemical Test Results

The solvent system used for sample compound was Benzene: Chloroform. The sample compound shows RF value (Table 10) near to that of standard compound as shown in Figure 1.

Table 10: RF value of sample and Standards compound

Figure 1: Comparative TLC of Sample compound and Standard compound

To determine the level of linolenic acid present, a hexabromide test is performed. The test results show precipitates when fish oils, which are high in linolenic acid, are present. When examined in this manner, the vegetable oil fats result in white precipitate. Precipitate formed, which is a sign that unsaturated fatty acids are present (Figure 2).

Figure 2: Hexabromide Test Results

Calibration curve is a regression model used to predict the unknown concentrations of analytes of interest based on the response of the instrument to the known standards. The figure 3, shows the standard calibration curve of fish oil. The linear relationship was evaluated by calculation of the regression line by the method of least squares.

The chemical structure of the material as well as core-polymer interaction and degradation of beads were evaluated by FTIR (Figure 4-7) No substantial variation was observed between spectra of pectin and chitosan loaded beads. There was no shift of spectrum after the formulation of pectin loaded beads that revealed no strong chemical interaction of chitosan with pectin and oil was physically dispersed in the matrix of polymeric dispersion. The results thus obtained from these characteristic peaks indicated that oil was encapsulated by pectin and chitosan.

Figure 3: Calibration Curve of Fish oil

Figure 4: FTIR Spectra of Flaxseed Oil

The FT-IR spectra of flaxseed seed oil shows the characteristic C-H stretch (~2923.23 cm-1), C=O stretch (~1744.12 cm–1), and C-O stretch (~1159.03 cm–1) of triglyceride component which confirms the presence of polyunsaturated fatty acid in oil sample (Figure 4).

Figure 5: FTIR Spectra of Pectin

The spectrum of pectin indicated peak at 3729.20 cm^-1 due to stretching of O-H group, the peak at 2933.05 cm^-1 indicated C-H stretching vibration. The peak at 1424.21 cm^-1 and 1232.30 cm^-1 could be assigned to CH₂ and OH bending vibrations (Figure 5).

Figure 6: FTIR Spectra of Chitosan

FTIR spectra of chitosan shows the main corresponding peaks of chitosan at 3359 cm-1 (– OH stretch), 2872 cm-1 (C–H stretch), 1637 cm-1 and 1561 cm-1 (N–H bend), 1375 cm-1 (bridge O stretch) and 1025 cm-1 (C–O stretch) (Figure 6).

Figure 7: FTIR Spectra of Flaxseed oil beads

The FT-IR spectra of flaxseed seed oil beads shows the characteristic C-H stretch (~2924.15 cm–1), C=O stretch (~1740.46 cm–1), and C-O stretch (~1149.90 cm–1) of triglyceride component which confirms the presence of polyunsaturated fatty acid in oil sample (Figure 7).

1. Screening, Optimisation and Validation of Flaxseed Oil Containing Pectin Chitosan Beads 
   1. Screening

Screening of three factors (CMA's and CQA's) at two distinct levels was demonstrated for a flaxseed oil batch using Minitab 21.1.0 software and the Plackett-Burman Design of Experiment (DOE). Full factorial design, for example. Pectin, chitosan, and speed were the variables examined. Plackett-Burman design screenings of these variables were carried out using Minitab 21.1.0 software (Table 11). Total 12 batches of the Plackett-Burman design were given following the design screening. These 12 batches underwent formulation and, separately, encapsulation efficiency and in-vitro drug release evaluations.

Table 11: Evaluation of beads using Plackett-Burman Design

Table 12: Analysis of Variance

The best outcomes after applying the Plackett-Burman design were F3, F6, F11, and F12. Chitosan and speed were found to be significant VS% drug release features when in-vitro drug release and encapsulation efficiency were tested. Since chitosan and speed both had P-values around 0.25, these 2 factors were analysed and found to be significant. 

Minitab 21.1.0 software, the Response surface method (RSM) was used to optimise these parameters. RSM distributed 13 batches following a design screening. These 13 batches were created and tested for the % DR and % EE characteristics, respectively. After these Response Surface Methodology (RSM) parameters were tested, as indicated respectively in table 13, no factor demonstrated any interaction with other factors.

Table 13: Evaluation of beads using Response surface methodology 

Table 14: Coded Coefficients (α = 0.25)

Table 15: Analysis of Variance

% DR = 113.1 – 84.6 Chitosan - 0.1240 Speed + 0.000276 Speed*Speed

Table 16: Analysis of Variance (α = 0.25)

% EE = 93.32 – 13.2 Chitosan - 0.0909 Speed – 71.0 Chitosan*Chitosan + 0.000221 Speed*Speed

To illustrate the link between the response and the variables, factorial plots were created. For example, the responses vs. %DR variables were speed and chitosan, as shown in figure 8. However the outcome shows that the major effect was not statistically significant.

Figure 8: The response % DR vs. variables speed and chitosan

The variation in the components, level, and slope of the line may result from random change. Chitosan seems to be more linked to influencing the % DR in the main effect plot. But according to the results of the general linear model, the main effect was not statistically significant.

Figure 9: Interaction plot of % DR Vs chitosan

Examined the two-way interaction effect in the interaction plot. This graph demonstrates how the value of a second predictor affects the connection between a predictor and the response variable. The lines in this interaction plot were not straight. As demonstrated in figure 9, this interaction effect demonstrates that the relationship between chitosan and speed has no impact on the value of% DR. According to the interaction plot, chitosan does not interact with speed influence on %DR, however all other plots exhibited interaction because the lines were not parallel.

Contour plots were used to plot the relationship between a fitted response and two continuous variables. A contour plot displays a two-dimensional view in which points that have the same response value were connected to produce contour lines. (Figure 10)

Figure 10: Counter Plots For %Drug Release Vs Speed, Chitosan and Counter Plots For %Encapsulation efficiency Vs Speed, Chitosan

Surface plots were used to plot the relationship between a fitted response and two continuous variables. A surface plot displays the three-dimensional relationship in two dimensions, with the variables on the x-axis and y-axis and the response variable represented by a smooth surface. (Figure 11)

Figure 11: Surface Plots of %Drug Release Vs Speed, Chitosan and Surface Plot of % Encapsulation Efficiency Vs Speed, Chitosan

Table 17: Response Optimization: %Drug Release, %Encapsulation Efficiency

Figure 11: Response optimizer analyzer

If factorial plots and interaction plots graph shows any significant effect and have at least one stored model and want to find values that optimize one or more responses i.e. %DR and %EE use response optimizer for optimization of these responses as shown in figure11. The % DR target was set to 95% and % EE target was set to 90%. The Response optimizer had screened two factors at three different levels and gave the optimised values of Chitosan 0.2g and speed 250 rpm as shown in table 17. These batches were formulated and evaluate.

After applying RSM to final batches it showed satisfactory results and the results matched Quality Target Product Profile (QTPP) with reference to In Process Critical Quality Attribute (IP CQAs) and Drug Product Critical Quality Attribute (FP CQA) so it was considered to optimize the formula in formulation optimization of pectin chitosan beads.

Six batches of optimized formula were prepared and validated for % Drug Release and % Encapsulation Efficiency.

Figure 12: Scanning Electron Microscopy of Flaxseed Oil Bead

SEM image of formed beads indicate complete encapsulation of oil as there are no oil globules on the surface of beads, indicating a positive result with smooth morphological surface, spherical shape at various magnifications under SEM with various diameters as shown in figure 12.

Figure 13: GCMS Standard graph of Fish oil

Table 18: Polyunsaturated Fatty acids present in fish oil

Figure 14: GCMS of flaxseed oil

Table 19: w-3 and w-6 fatty acids in flaxseed oil

The extracted oils were evaluated for w-3 and w-6 fatty acids using GCMS keeping fish oil as standard. The percent compositions of omega fatty acid in extracted flaxseed oil were compared with standard, which was found to be approximate to the values of omega fatty acid composition of fish oil given in table 18. The w-3 and w-6 fatty acids from flaxseed can be the best alternative as nutraceutical to fish oil as shown in table 19 (Figure 13 & 14).

Nutraceutical flaxseed oil contains omega fatty acids but is prone to oxidation. The Present study was focused to formulate pectin-chitosan beads to entrap the flaxseed oil. In this study, flaxseed oil was extracted using cold maceration method. Extracted oil was evaluated for phytochemical evaluation. Pectin chitosan beads were prepared using Ionic gelation method. Minitab 21.1.0 was used to screen and optimize the process and formulation parameters. Plackett Burman's design was used for the initial screening. Twelve batches were made ready for screening, and each batch was evaluated for optimization based on the percentage of drug release and the percentage of drug encapsulation efficiency. The optimized batches F4, F6 and  F10  were shown the satisfactory results complying with IP specifications. The SEM image of the produced beads shows that the oil has been completely encapsulated. The % compositions of omega fatty acids in extracted flaxseed oil were estimated using the GCMS Quantitative analysis. The ideal substitute for fish oil as a nutraceutical could be the omega-3 and omega-6 fatty acids found in flaxseed oil.

Financial support and sponsorship:  Nil. 

Conflicts of interest: There are no conflicts of interest.

Acknowledgement: The authors are thankful to the Sikh education society, Principal, Gurunanak college of pharmacy and the Principal, Institute of Pharmaceutical Science and Research, Sardar Patel University, Balaghat.

REFERENCES 

1. Pandey M, Verma RK, Saraf SA. Nutraceuticals: New era of medicine and health. Asian J Pharm Clin Res. 2010; 3(1):11-5.

2. Adarme-Vega TC, Lim DKY, Timmins M, Vernen F, Li Y, Schenk PM. Microalgal biofactories: a promising approach towards sustainable omega-3 fatty acid production. Microb Cell Fact [Internet]. 2012; 11(1):1. Available from: Microbial Cell Factories https://doi.org/10.1186/1475-2859-11-96

3. Swanson D, Block R, Mousa SA. Omega-3 fatty acids EPA and DHA: Health benefits throughout life. Adv Nutr. 2012; 3(1):1-7. https://doi.org/10.3945/an.111.000893

4. da Costa Vieira M, Bakof KK, Schuch NJ, Skupien JA, Boeck CR. The benefits of omega-3 fatty acid nanocapsulation for the enrichment of food products: a review: Os benefícios da nanoencapsulação de ácidos graxos da classe ômega-3 para o enriquecimento de produtos alimentícios: uma revisão. Rev Nutr. 2020; 33:1-12. https://doi.org/10.1590/1678-9865202033e190165

5. Innes JK, Calder PC. Marine omega-3 (N-3) fatty acids for cardiovascular health: An update for 2020. Int J Mol Sci. 2020; 21(4):1-21. https://doi.org/10.3390/ijms21041362

6. Gammone MA, Riccioni G, Parrinello G, D'orazio N. Omega-3 polyunsaturated fatty acids: Benefits and endpoints in sport. Nutrients. 2019; 11(1):1-16. https://doi.org/10.3390/nu11010046

7. Saini RK, Keum YS. Omega-3 and omega-6 polyunsaturated fatty acids: Dietary sources, metabolism, and significance - A review. Life Sci. 2018; 203(January):255-67. https://doi.org/10.1016/j.lfs.2018.04.049

8. Meyer BJ, Mann NJ, Lewis JL, Milligan GC, Sinclair AJ, Howe PRC. Dietary intakes and food sources of omega-6 and omega-3 polyunsaturated fatty acids. Lipids. 2003; 38(4):391-8. https://doi.org/10.1007/s11745-003-1074-0

9. Lionberger RA, Lee SL, Lee LM, Raw A, Yu LX. Quality by design: Concepts for ANDAs. AAPS J. 2008; 10(2):268-76. https://doi.org/10.1208/s12248-008-9026-7

10. Wang J, Kan S, Chen T, Liu J. Application of quality by design (QbD) to formulation and processing of naproxen pellets by extrusion-spheronization. Pharm Dev Technol. 2015; 20(2):246-56. https://doi.org/10.3109/10837450.2014.908300

11. Piva GS, Weschenfelder TA, Franceschi E, Cansian RL, Paroul N, Steffens C. Extraction and modeling of flaxseed (Linnum usitatissimum) oil using subcritical propane. J Food Eng. 2018; 228:50-6. https://doi.org/10.1016/j.jfoodeng.2018.02.012

12. Sharma A, Sharma AK, Chand T, Khardiya M, Yadav KC. Preliminary Phytochemical Evaluation of Seed Extracts of Cucurbita Maxima Duchense. J Pharmacol Phytochem. 2013; 2(3):62-5.

13. Altemimi A, Lakhssassi N, Baharlouei A, Watson DG, Lightfoot DA. Phytochemicals: Extraction, isolation, and identification of bioactive compounds from plant extracts. Plants. 2017; 6(4). https://doi.org/10.3390/plants6040042

14. Cai L. Thin layer chromatography. Curr Protoc Essent Lab Tech. 2014 2014(February 2014):6.3.1-6.3.18. https://doi.org/10.1002/9780470089941.et0603s08

15. Safety F, Authority S, Health MOF, Welfare F, Delhi NEW. Manual of Methods of Analysis of Foods Water Food Safety and Standards Authority of India. Pestic residue. 2016; 18.

16. Kusuktham B, Prasertgul J, Srinun P. Morphology and Property of Calcium Silicate Encapsulated with Alginate Beads. Silicon. 2014; 6(3):191-7. https://doi.org/10.1007/s12633-013-9173-z

17. Aydìn Z, Akbuǧa J. Preparation and evaluation of pectin beads. Int J Pharm. 1996; 137(1):133-6. https://doi.org/10.1016/0378-5173(95)04458-2

18. CHERIAN AS, Boby Johns G, Praveen Raj R, Daisy P., Jeny S. Formulation and Evaluation of FSM-Alginate Beads of Vildagliptin. J Drug Deliv Ther. 2019; 9(4-A):246-51. https://doi.org/10.22270/jddt.v9i4-A.3289

19. Khazaeli P, Pardakhty A, Hassanzadeh F. Formulation of ibuprofen beads by ionotropic gelation. Iran J Pharm Res. 2008; 7(3):163-70.

20. Kumar VP, Vishal Gupta N. A review on quality by design approach (QBD) for pharmaceuticals. Int J Drug Dev Res. 2015; 7(1):52-60.

21. Waghule T, Dabholkar N, Gorantla S, Rapalli VK, Saha RN, Singhvi G. Quality by design (QbD) in the formulation and optimization of liquid crystalline nanoparticles (LCNPs): A risk based industrial approach. Biomed Pharmacother [Internet]. 2021; 141:111940. https://doi.org/10.1016/j.biopha.2021.111940

22. Mandlik SK, Agarwal PP, Dandgavhal HP. Implementation of quality by design (Qbd) approach in formulation and development of ritonavir pellets using extrusion spheronization method. Int J Appl Pharm. 2020; 12(1):139-46. https://doi.org/10.22159/ijap.2020v12i1.35453

23. Gyawali R, Gupta RK, Shrestha S, Joshi R, Paudel PN. Formulation and Evaluation of Polyherbal Cream Containing Cinnamomum zeylanicum Blume, Glycyrrhiza glabra L and Azadirachta indica A. Juss. Extracts to Topical Use. J Inst Sci Technol. 2020; 25(2):61-71. https://doi.org/10.3126/jist.v25i2.33738

24. De Muth JE. Practical Statistics for Pharmaceutical Analysis: With Minitab Applications [Internet]. AAPS Advances in the Pharmaceutical Sciences Series,. 2019. Available from: https://doi.org/10.1007/978-3-030-33989-0%0Ahttp://ludwig.lub.lu.se/login?url=https://link.springer.com/10.1007/978-3-030-33989-0

25. Sadhukhan B, Mondal NK, Chattoraj S. Optimisation using central composite design (CCD) and the desirability function for sorption of methylene blue from aqueous solution onto Lemna major. Karbala Int J Mod Sci [Internet]. 2016; 2(3):145-55. https://doi.org/10.1016/j.kijoms.2016.03.005

26. Ganesamoorthi B, Kalaivanan S, Dinesh R, kumar TN, Anand K. Optimization Technique using Response Surface Method for USMW process. Procedia - Soc Behav Sci [Internet]. 2015; 189:169-74. https://doi.org/10.1016/j.sbspro.2015.03.211

27. Mandal S, Senthil Kumar S, Krishnamoorthy B, Basu SK. Development and evaluation of calcium alginate beads prepared by sequential and simultaneous methods. Brazilian J Pharm Sci. 2010; 46(4):785-93. https://doi.org/10.1590/S1984-82502010000400021

28. Gomes LC, Mergulhão FJ. SEM analysis of surface impact on biofilm antibiotic treatment. Scanning. 2017; 2017(c). https://doi.org/10.1155/2017/2960194

29. Olivia NU, Goodness UC, Obinna OM. Phytochemical profiling and GC-MS analysis of aqueous methanol fraction of Hibiscus asper leaves. Futur J Pharm Sci. 2021; 7(1). https://doi.org/10.1186/s43094-021-00208-4

30. Iordache A, Culea M, Gherman C, Cozar O. Characterization of some plant extracts by GC-MS. Nucl Instruments Methods Phys Res Sect B Beam Interact with Mater Atoms [Internet]. 2009; 267(2):338-42.  https://doi.org/10.1016/j.nimb.2008.10.021