Experimental optimization of oil extraction from Moringa Seed by using application of response surface methodology (RSM)

Experimental optimization of oil extraction from Moringa Seed by using application of response surface methodology (RSM) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Experimental optimization of oil extraction from Moringa Seed by using application of response surface methodology (RSM) Hawi Jihad Kedir, Kasahun Tsegaye Mekonnen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7724671/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract This work aimed to extract oil from moringa seeds by optimizing the oil extraction process parameters with the aid of response surface methodology (RSM). The effects of three independent oil extraction process factors particle sizes (0.3–0.7mm), temperature (50–70°C) and time (6–8hr) for oil extraction from moringa seeds were studied. The proximate analysis of moringa seeds: ash content, acid value, ester value and saponification value were 5 ± 0.46, 2 ± 0.77, 257 ± 73 and, 260 ± 0.50wt.%, respectively. A quadratic model was used to correlate the interaction effects of the independent variables for maximum oil extraction at the optimum process parameters by employing central composite design (CCD) with RSM. The work indicates that the interaction of temperature and particle sizes is the most significant parameters among the model terms, followed by the interaction of temperature and extraction time effect on oil yield and finally, interaction of particle sizes and extraction time had no significant effect on oil yield. The studied results reported a better oil yield: 43.18% at extraction temperature of 59.79°C, particle size of 0.41mm and extraction time of 6.54hr with supported a maximum desirability of 1. The oil obtained was analysed for various parameters: acidity value 2.2 ± 0.05, iodine value 63.4 ± 0.08, refractive index 1.52 ± 0.01 and density 0.90 ± 0.01. This study concludes that oil obtained from moringa seeds could be utilized as a source of edible oil for human consumption. Moringa seeds Optimization Central composite design Extracted oil Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Moringa oleifera, often dubbed the “miracle tree”, has garnered global attention for its exceptional nutritional, medicinal, and industrial potential. Native to the Indian subcontinent and now widely cultivated across Africa, Asia, and Latin America, nearly every part of the tree is utilized for food, health, or industrial applications [ 1 , 2 , 3 ]. In Ethiopia, particularly in the Southern Nations, Nationalities, and Peoples' Region (SNNPR), moringa was increasingly cultivated alongside the indigenous moringa stenopetala, especially in areas like Arba Minch Zuria Woreda, where agroecological conditions favor its growth[ 4 , 5 , 6 ]. Among its most valuable components were the seeds, which contain up to 40% oil by weight and were rich in oleic acid, sterols, tocopherols, and other bioactive compounds that contribute to their oxidative stability and therapeutic value [ 7 , 8 , 9 , 10 ]. The oil extracted from Moringa seeds commonly referred to as ben oil is characterized by its light texture, resistance to rancidity, and high content of monounsaturated fatty acids, making it suitable for use in cosmetics, pharmaceuticals, and food formulations [ 7 , 11 ]. As the demand for sustainable, plant-based oils continues to rise, moringa seed oil had emerged as a promising alternative to conventional oils, especially in regions seeking to reduce reliance on imported or food-competitive oil crops [ 7 ]. Efficient extraction methods were critical to unlocking the full potential of Moringa oil. Among the various techniques, Soxhlet extraction using n-hexane remains a widely adopted method due to its ability to achieve high oil yields and extract a broad spectrum of lipophilic compounds[ 3 , 12 ]. Recent studies have demonstrated that Soxhlet extraction can yield up to 39–42% oil [ 3 , 7 ]. Even though several research works have been carried out on oil production from moringa seeds, the effect of both extraction temperature and time at different particle size and optimization of the oil extraction process variables have not yet been investigated in detail. Hence, different from previous reports, our study employed response surface method (RSM) to optimize the oil extraction process variables including temperature (50–70°C), particle sizes (0.3–0.7mm) and time (6–8hr.) [ 13 , 14 ]. RSM encompasses statistical and mathematical techniques that are vital for optimization (needs less experiment runs) and studying the interaction between the variables. Central composite design (CCD) was employed for extraction oil from moringa seeds as the method is more efficient and practical design which is ideal for consecutive experimentation [ 15 ]. The results of this work support the development of value-added applications for moringa oil in both local and global markets. 2. Experimental 2.1 Materials The raw materials ( i.e. Moringa seeds) were purchased at Arba Minch (Gamo Zone) in Ethiopia. N-hexane (Standard ASTM D1836) and Sulphuric Acid were employed in this study. Distilled DI) water was employed during the oil extraction. 2.2. Synthesis 2.2.1 Raw material preparation A step-by-step procedure in essential oil extraction is presented in Fig. 1 . Initially, harvested seeds were sun-dried for two days to reduce surface moisture. Following this, seed husks were manually removed to obtain clean seed kernels. The dehulled kernels were further sun-dried for 6 hours to lower the internal moisture content to below 7%, which is optimal for solvent-based extraction [ 16 ]. The dried kernels were then ground using a grinded by using pestle and mortar, and the resulting powder was sieved through a 2 mm mesh to ensure uniform particle size, which enhances solvent penetration and oil yield [ 17 ]. Size reduction was done for ease of high extraction and to maximize the essential oil extraction. The complete flow chart of experimental procedures is provided in Fig. 2 . [ 16 , 18 ]. 2.2.2 Proximate composition analysis of moringa seed The proximate analysis gives ash content, acid value, ester value and saponification value. Proximate analysis was carried out based on the ASTM standard protocol[ 19 ]. 2.2.3 Solvent Extraction of Oil The weighed moringa seed powder was placed in a thimble made of filter paper. The thimble was inserted into the Soxhlet extractor. A volume of 250mL of n-hexane was added to the round-bottom flask. The Soxhlet apparatus was assembled, and all connections were tightened to prevent solvent loss [ 20 ]. The flask was gently heated using a heating water bath, allowing the solvent to boil and reflux [ 21 ]. Extraction was continued until the solvent in the siphon tube was observed to be colourless, indicating that oil was no longer being extracted[ 20 , 22 ]. 2.2.4 Experimental design The experimental design for this study was done by using design expert software version (STAT-EASE 360). The effect of three operating variables of the extraction process such as extraction temperature (50, 60 and 70 o C), particle size (0.3, 0.5 and 0.7mm) and extraction time (6, 7 and 8hr) on yield were analysed[ 23 , 24 ]. The response surface methodology (RSM) was used for optimization of this study. RSM that consists of statistical and mathematical techniques are is vital for modelling and analysing problems in which the response is determined by numerous factors [ 25 ]. The main objective of the response surface is to obtain value of each factor. A quadratic model was used to correlate the interaction effects of the independent variables for maximum oil extraction at the optimum process parameters by employing central composite design (CCD) with RSM[ 14 , 26 ]. Three-level with three-factor CCD was used in order to optimize the process parameter to minimize the experimental error. Hence, CCD was generated 20 experiments with three-level and three-factor and the percentage oil yield was taken as response parameter [ 23 , 26 ]. The experimental data were analysed by using ANOVA in order to cheek the significance of each variable and their interaction effect on the yield of oil [ 27 ]. The ANOVA study also was used to develop the model equation for the percentage conversion of the produced oil as a function of the independent variables and their interaction effect in order to maximize the yield. 2.2.5 Oil yield determination Oil yield values were calculated in order to identify the optimum values of extraction variables such as (extraction temperature, particle size and extraction time) and to determine the effect of each variable on final yield. The oil yield extracted from moringa seed was calculated using Eq. 1 [ 21 ]. Oil yield (%) = (Weight of oil extracted / Weight of dry moringa seed sample) × 100 3 Results and Discussion 3.1 Proximate analysis of raw materials The proximate analysis results of the raw materials (moringa seeds) are presented in Table 1 . All the experiments were done on a dry basis (wt. %) in triplicate, and the analysis results were presented as means ± standard deviation. The ash analysis result showed that an average ash content of 5 ± 0.46 was obtained this shows that the moringa seed had rich source of minerals [ 28 ]. It indicating the high percentage value of oil yield can earned from the seed. This result is basically matched with the previous study reported 3.38 % to8% [ 29 ]. The acid value of moringa has been reported to vary depending on factors such as the extraction method employed, the maturity stage of the seeds, and the conditions under which they were stored [ 30 ]. The acid value result showed that an average acid value of 2 ± 0.77 was obtained this shows that the moringa as an indicator of high-quality moringa oleifera seed oil, as minimal degradation is suggested by such a low level of free fatty acids [ 31 , 32 ]. The oil was considered suitable for both nutritional and industrial applications, including biodiesel production and cosmetic formulations, due to its chemical stability and low rancidity potential [ 33 , 8 , 34 ]. An ester value of 257 ± 73 was obtained from moringa oleifera seed, by which a relatively high level of esterified fatty acids or triglycerides in the oil was indicated [ 35 , 3 , 8 , 36 ]. These esters, formed from fatty acids and alcohols, were primarily present as triglycerides recognized as the main constituents of vegetable oils [ 3 , 37 ]. A saponification value of 260 ± 0.50 had been recorded from moringa oleifera seed, and this result had been interpreted as an indicator of a high proportion of short- to medium-chain fatty acids the results were consistent with the previous studies reported somewhere else [ 38 , 39 , 40 ]. Table 1 Proximate analysis results of moringa seeds Parameters This study References (wt%) Ash content 5 ± 0.46 mgNaOH 5.7–8.9 [ 41 ] Acid value 2 ± 0.77 mgNaOH 0.32- 8 mg KOH/g [ 42 ] Ester value 257 ± 73mgNaOH 169.2–314.27 mg NaOH[ 3 ] Saponification value 260 ± 0.50mgNaOH/g 270.9 NaOH/mg[ 43 , 35 ] 3.2 Model development and statistical analysis In this study, the design expert software version (STAT-EASE 360. trial version) was employed to examine the experimental data regression analysis and to plot the response surface curves. In order to determine the influence of the factors and their interactions effect, the statistical variables have been estimated by employing Analysis of variance (ANOVA) in the optimal Central Composite Design (CCD) test[ 14 , 25 , 26 ]. The temperature ranged from 50–70°C, the particle size ranged from 0.3 to 0.7mm and time 6 to 8hr., high (coded + 1) and low (coded-1) set points, for oil extraction process variables have been selected according to the values achieved in preliminary tests. Table 2 presents the required experimental variables and ranges for oil extraction process and the experimental results of 20 runs of the design of experiments using CCD on three factors is shown in Table 2 . The experimental analysis of our results (Table 2 ) provides to mathematical relationship that convey oil yield as function of interaction and individual contribution of parameters (Eq. 2). Hence, in terms of a coded variables, the final regression model (second-order polynomial) for oil extraction was indicated in Eq. 2 : Oil Yield = + 42.99 + 0.0469*A-0.1494*B -0.6271*C + 0.4750*AB-0.2750*AC + 0.1000*BC- 0.5784A 2 -0.2249 2 -0.6668C 2 ( 2) where the positive sign presents the synergistic effects and the negative sign shows the antagonistic effects The test for significance of the individual model and regression model coefficients with lack of fit test was conducted to fit a good model. Often, the significant variables have been ranked according to the P-value (probability value) or F-value with 95% confidence level. Table 3 presents the ANOVA of regression factors for the data obtained by using Eq. 2 for oil extraction from moringa seeds. The smaller ‘P’ value and the larger F-value (Prob.>F), indicate more significant of the model for corresponding coefficient [ 23 , 26 ]. The F-value of 24.86 revealed that the model is significant for oil yield. Moreover, the model terms are not significant only when the Prob.>F values of are > 0.1000 whereas values < 0.05 indicate the significant model terms [ 44 ]. In this case, C, AB, AC, A 2 , B 2 and C² were significant model terms on response while A, B and interactional effects between BC are not significant model terms that had limited effect. The model adequate precision ratio of 14.4209, which was > 4, revealed the adequacy of the signal model [ 45 ]. Thus, the model developed can be employed to guide the design space [ 26 ]. Furthermore, the multiple correlation coefficient (R 2 ) value of 0.9572 was obtained for oil extraction, which was > 0.80, revealing that only 4.28% of the total variation might not be described by the empirical model. For a good fit of a model, the R 2 should be at least 0.8 as described by [ 26 , 45 ]. The High R 2 results reveals good similarity between the actual and predicted values in the range of experiment. Similar results had been demonstrated and discussed elsewhere [ 23 , 26 , 46 ]. Table 2 Experimental variables in actual and coded units and experimental response (oil yield) for the CCD. *Experimental results of response. **Predicted results of response by CCD proposed model. Run Order A B C Actual value* Predicted Value** 1 60 0.5 7 43.00 42.99 2 70 0.3 6 42.00 42.25 3 70 0.3 8 40.50 40.24 4 70 0.7 6 43.00 42.70 5 60 0.5 8.7 40.00 40.05 6 76.8 0.5 7 41.50 41.44 7 60 0.2 7 42.50 42.61 8 50 0.3 8 41.50 41.65 9 70 0.7 8 40.80 41.09 10 50 0.3 6 43.00 42.55 11 43.2 0.5 7 41.00 41.28 12 60 0.5 7 43.00 42.99 13 50 0.7 8 41.00 40.60 14 50 0.7 6 41.00 41.10 15 60 0.5 7 43.00 42.99 16 60 0.8 7 42.00 42.11 17 60 0.5 7 43.00 42.99 18 60 0.5 5.3 42.00 42.16 19 60 0.5 7 43.00 42.99 20 60 0.5 7 43.00 42.99 Table 3 ANOVA for analysis of variance and adequacy of the response surface quadratic model for oil extraction for CCD obtained by the design expert software).; R2 = 0.9572; Adeq Precision = 14.4209. DF- Degree of freedom; S- Significant; NS-Not significant Source Sum of Squares df Mean Square F-value p-value Remark Model 18.61 9 2.07 24.86 < 0.0001 S A-Temperature 0.0301 1 0.0301 0.3617 0.5610 NS B-Particle Sizes 0.3050 1 0.3050 3.67 0.0845 NS C-Extraction Time 5.37 1 5.37 64.57 < 0.0001 S AB 1.81 1 5.37 21.71 0.0009 S AC 0.6050 1 0.6050 7.28 0.0224 S BC 0.0800 1 0.0800 0.9620 0.3498 NS A² 4.82 1 4.82 57.98 < 0.0001 S B² 0.7287 1 0.7287 8.76 0.0143 S C² 6.41 1 6.41 77.05 < 0.0001 S Residual 0.8316 10 0.0832 Lack of Fit 0.8316 5 0.0000 Pure Error 0.0000 5 19 Cor Total 19.44 19 In general, it is crucial to check the adequacy of real system approximation with the developed model in order to verify the data analysis of the experiment [ 47 , 23 ]. By employing the diagnostic plots, like internal studentized residuals versus normal probability plots, the adequacy of the model can be checked. The normal probability of studentized residual plot was presented in Fig. 3 . for extraction of oil from moringa seed. It has been found from Fig. 3 . that there was neither response transformation nor any apparent problem with normality [ 48 ]. It can be found that there was a normal distribution of data Fig. 3 . The predicted oil yield and internally studentized residual is presented in Fig. 4 . This indicates that the variance of original value is constant for the entire response values ( i.e. the random scatter plot) and there was no need for response factors transformation. Figure 5 . shows the actual versus the predicted percentage for oil extraction from moringa seeds. Three-dimensional (3-D) response surface plots The RSM assigned to CCD model was illustrated and examined to optimize the crucial variables and depict the response surface nature in the experiment [ 26 ]. Based on the ANOVA, the 3-D response plots were discovered according to the quadratic model from the combined effect of the three parameters on oil yield from moringa seeds. In each plot, as presented in Fig. 6 . one variable was maintained constant while the other two factors were tested on oil yield in the experimental ranges. The combined effect of temperature (A) and particle size (B) on oil yield at constant time of 7hr. is demonstrated in Fig. 6 A. It can be observed from the results, the interaction of temperature (A) and particle size (B) had higher effects on oil extraction from moringa seeds owing to high value result of F statistics (low p-value). Similarly, Fig. 6 B. presents the combined effect of temperature (A) and time (C) on oil production form moringa seeds at 0.5mm (constant particle sizes) results indicated medium (lower than interaction of AB) effect oil yield Similar results with analogous situations and supposition had been presented [ 16 ]. A) Optimization of oil extraction process variables by RSM Profiling the desirability option and the predicted values in the Design Expert software (trial version) was employed for process optimization. The profile of desirability responses comprises stating the function for desirability for the dependent factor (Oil yield) by allocating a score for predicted values ranging from 0 (very undesirable) to 1 (very desirable). Based on the desirability score of 1.0 Table 4 . oil extraction was optimized at 43.1843% at optimized oil extraction parameters of temperature (59.7942°C), particle sizes (0.409696) and time (6.53709hr.). For validation at these optimized oil extraction parameters, the experiment was performed in triplicate and the results revealed that there was < 0.05% error between the actual (43.1843%) and predicted (43.00%) values for the oil yield from moringa seeds. The results were estimated and discussed on the bases of the analysis approached reported by [ 26 , 16 ]. Hence, the present research concluded that designed model could predict the relation between the variables and oil yield. Table 4 Optimization results derived by CCD for oil yield Parameters Oil Yield (%) Solution no A (°C) B (mm) C (hrs.) Experimental value Predicted value Desirability 1 59.7924 0.409696 6.53709 43.1843 43 1 3.2 Characterization of Extracted oil The oil obtained was analysed various parameters as shown in Table 5 . The oil had Acidity value 2.2 ± 0.05, Iodine value 63.4 ± 0.08, refractive index 1.516 ± 0.01 and density 0.90 ± 0.01. This value was interpreted as an indicator of the oil’s purity and degree of unsaturation, and was found to be consistent with the refractive indices typically observed in high-oleic vegetable oils [ 26 ]. And the oil had high oleic acid content and oxidative stability [ 16 ]. Table 5 Characterization of extracted oil Parameters Composition Acidity (% as oleic acid) 2.2 ± 0.05 [ 26 , 48 , 16 ] Iodine value (g of I/100 g of oil) 63.4 ± 0.08 [ 3 , 26 ] Refractive index (25 0 C) 1.516 ± 0.01 [ 26 , 48 ] Density (g/cm3) 25 0 C 0.90 ± 0.01[ 48 ] 4. Conclusion In this study, oil extraction from moringa seeds was optimized using CCD with RSM. The effects of three independent oil extraction process variables including temperature (50–70°C), particle sizes (1–3mm), and time (6–8hr.) using a quadratic model for maximum oil extraction was determined. The present study demonstrates that the interaction effect of temperature and particle sizes is the most significant parameters among the model terms, followed by interaction effect of temperature and extraction times on oil extraction. At the optimized oil extraction variables, the experimental and predicted values, for the oil yield from moringa seeds were found as 43.18% and 43.00%, respectively, with error less than 0.05%. Hence, the results indicated that the model developed could precisely predict the oil extraction. The characterization revealed that the oil could be utilized as a source of edible oil for human consumption. Declarations Data availability The authors state that the data supporting the results of this work are available within the paper. The raw data can be provided from the corresponding author on reasonable request. Acknowledgements The authors acknowledged Arba Minch University; College of Natural Science, Arba Minch University, Ethiopia for supporting the laboratory facilities. Author contributions Hawi Jihad Kedir: Designed the experiments, collected and analyzed the data, interpretation of results, wrote the original draft, designed the experiments and Editing. Kasahun Tsegaye Mekonnen: performed characterization tests and conceptualization, supervised, statistical analysis, editing and reviewed the paper. Declarations Competing interests The authors declare no competing interests. Consent to Publish Not applicable Consent to participate Not applicable Permissions to collect the plants/plant parts: Not applicable Funding This study had not fund Ethics Not applicable Clinical trial number Not applicable References Pal P, Mahant V. Moringa 360: a comprehensive review of its nutritional, medicinal and industrial brilliance. Phytochemistry Reviews Sep. 2025. 10.1007/s11101-025-10178-7 . Kaur N, Sontakke M. Exploring nutritional and phytochemical potentials of a miracle tree Moringa oleifera: A review, 12, 5, pp. 3046–55, 2023, [Online]. Available: www.thepharmajournal.com. Suliman AM, Osman ME, Galander AA. Extraction and characterisation of the oil from Moringa oleifera seeds, 5, 2021, [Online]. Available: www.chemicaljournals.com. Sultana S. 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PHYSICOCHEMICAL ANALYSIS AND PHARMACEUTICAL POTENTIAL OF MORINGA OIL EXTRACT. [Online]. Available: www.noveltyjournals.com. Anwar F, Zafar SN, Rashid U. Characterization of Moringa oleifera seed oil from drought and irrigated regions of Punjab, Pakistan. Grasas Aceites. 2006;57(2):160–8. 10.3989/gya.2006.v57.i2.32 . * Jawonisi OI, Olayemi, Lawal RF, International Journal of Engineering Technology and Scientific Innovation PHYSICOCHEMICAL AND PHYTOCHEMICAL EVALUATION OF Moringa oleifera POD AND SEED International. J Eng Technol Sci Innov, 2017, [Online]. Available: Morah EJ, Eboagu NC, Nwakife NC, Chinelo Ezeonu C. Characterization and Phytochemical Evaluation of the Seed, Seed Oil and Leaves of Moringa oleifera. Adv J Chem Sect B Nat Prod Med Chem. 2024;6:144–62. 10.48309/ajcb.2023.394689.1166 . Genene D. Extraction of Oil from Azadirachta indica and Moringa stenopetala Seeds and Evaluation of its Physicochemical Properties, MANAS Journal of Engineering , vol. 12, no. 2, pp. 163–176, Dec. 2024, 10.51354/mjen.1377816 Souza DES, et al. Microwave-Assisted vs. Conventional Extraction of Moringa oleifera Seed Oil: Process Optimization and Efficiency Comparison. Foods. Oct. 2024;13(19). 10.3390/foods13193141 . Sandeep G, Arumugam T, Janavi GJ, Anitha T, Senthil K, Lakshmanan A. Optimization of Microwave-assisted Extraction Method for the Yield of Extraction and Total Phenol Content from Moringa Leaves (Moringa oleifera Lam.) var. PKM 1, 2023. Goldstein M, Seheult A, Vernon I. Assessing Model Adequacy, 2010. Rashwan MRA, Seleim MAA, Hassan MAM, Mohammed HMM. Physicochemical Properties of Oils Extracted from Two Moringa Cultivars Seeds. Assiut J Agricultural Sci, 55, 4, pp. 31–42, 10.21608/10.21608/AJAS.2024.302945.1378 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 21 Nov, 2025 Reviews received at journal 15 Nov, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviews received at journal 29 Oct, 2025 Reviewers agreed at journal 29 Oct, 2025 Reviewers invited by journal 29 Oct, 2025 Editor invited by journal 28 Oct, 2025 Editor assigned by journal 23 Oct, 2025 Submission checks completed at journal 19 Oct, 2025 First submitted to journal 19 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7724671","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":541967035,"identity":"e16ef2a6-0873-4d8b-ae24-1990cf27c9c2","order_by":0,"name":"Hawi Jihad Kedir","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYBACAyA+IGFwgIHh/vnHDz4AeWzsRGu5wcNmOAOkhZkILSBdIC0M0jwgNiEt5uxnDA9YFNyR57vde8DY5tc2eT5mBsYPH3Nwa7HsyTEAOuyZ4cw75xIe5/bdNmxjZmCWnLkNj8MO5G4AajnMuOFAgoFxbs9tRqAWNmZefFrOvwVrsQdpkbbsuW1PWMsNiC2JG27kGEgz/LidSISW9x9AWpJnnjmWZtjbcDu5jZmxGb9fzqclf5b4c9i273jz4Qc//ty2nd/efPDDRzxaQIBZAsZibAOTDfjVg5R8gDP/EFQ8CkbBKBgFIxAAAJD3Xs2VcKdPAAAAAElFTkSuQmCC","orcid":"","institution":"Arba Minch University","correspondingAuthor":true,"prefix":"","firstName":"Hawi","middleName":"Jihad","lastName":"Kedir","suffix":""},{"id":541967036,"identity":"3bd9fada-1e08-486b-ad4a-2b01793fd0ab","order_by":1,"name":"Kasahun Tsegaye Mekonnen","email":"","orcid":"","institution":"Arba Minch University","correspondingAuthor":false,"prefix":"","firstName":"Kasahun","middleName":"Tsegaye","lastName":"Mekonnen","suffix":""}],"badges":[],"createdAt":"2025-09-26 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10:54:54","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":118821,"visible":true,"origin":"","legend":"","description":"","filename":"72901530692d4685b6b49e5a535a538c1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7724671/v1/8037362fa4aaa3ca012c7a12.xml"},{"id":95657849,"identity":"168a41ef-5e46-48c0-9faf-2dbee995fc02","added_by":"auto","created_at":"2025-11-11 16:22:12","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":128007,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7724671/v1/ae5edcb99096695f92f4b548.html"},{"id":95627326,"identity":"d5b35b49-923d-46cd-9f56-e5b19473c80a","added_by":"auto","created_at":"2025-11-11 10:54:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37330,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic flow chart showing the step-by-step procedure to extract essential oil from moringa seeds.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7724671/v1/a57ef761270945249577ac29.png"},{"id":95658051,"identity":"3443f220-7a09-4c3c-b093-79a3a3e6324e","added_by":"auto","created_at":"2025-11-11 16:22:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":469202,"visible":true,"origin":"","legend":"\u003cp\u003ePictural illustration of the scheme of our experimental setup.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7724671/v1/5778ec871e9138ef3537c9bd.png"},{"id":95656458,"identity":"59d2cfea-ff40-495b-bfc1-6eca9d01e4d1","added_by":"auto","created_at":"2025-11-11 16:18:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":18909,"visible":true,"origin":"","legend":"\u003cp\u003eStudentized residuals versus normal percentage probability plot for oil extraction.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7724671/v1/ebc860b7034480b1079cf5cd.png"},{"id":95627327,"identity":"a434f337-4fce-4966-bc85-8094ca953185","added_by":"auto","created_at":"2025-11-11 10:54:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":16016,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted oil extraction of moringa seeds and studentized residuals plot.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7724671/v1/e5330124e75c466b64ebd9b7.png"},{"id":95627333,"identity":"e5e9b228-5494-4b28-a6bb-7823aa351ebe","added_by":"auto","created_at":"2025-11-11 10:54:53","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":13553,"visible":true,"origin":"","legend":"\u003cp\u003eThe observed values (experimental data) versus predicted values for oil extraction.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7724671/v1/14c279ffa8f482110572b1cd.png"},{"id":95658155,"identity":"b3113667-3b62-4189-a8ea-0929b45a8848","added_by":"auto","created_at":"2025-11-11 16:23:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":214930,"visible":true,"origin":"","legend":"\u003cp\u003eResponse surface plots for the CCD for oil extraction as a function of: (\u003cstrong\u003eA\u003c/strong\u003e) temperature and Particle size (at time 7hr.) (\u003cstrong\u003eB\u003c/strong\u003e) temperature and time (at particle size 0.5mm).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7724671/v1/10ff32d192613cd2f4dc482f.png"},{"id":95660692,"identity":"053529a5-f105-49d5-b348-ab99901059af","added_by":"auto","created_at":"2025-11-11 16:32:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1703634,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7724671/v1/9221d5ab-e5db-4fc0-9f6a-274d35358a82.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Experimental optimization of oil extraction from Moringa Seed by using application of response surface methodology (RSM)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMoringa oleifera, often dubbed the \u0026ldquo;miracle tree\u0026rdquo;, has garnered global attention for its exceptional nutritional, medicinal, and industrial potential. Native to the Indian subcontinent and now widely cultivated across Africa, Asia, and Latin America, nearly every part of the tree is utilized for food, health, or industrial applications [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In Ethiopia, particularly in the Southern Nations, Nationalities, and Peoples' Region (SNNPR), moringa was increasingly cultivated alongside the indigenous moringa stenopetala, especially in areas like Arba Minch Zuria Woreda, where agroecological conditions favor its growth[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Among its most valuable components were the seeds, which contain up to 40% oil by weight and were rich in oleic acid, sterols, tocopherols, and other bioactive compounds that contribute to their oxidative stability and therapeutic value [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe oil extracted from Moringa seeds commonly referred to as ben oil is characterized by its light texture, resistance to rancidity, and high content of monounsaturated fatty acids, making it suitable for use in cosmetics, pharmaceuticals, and food formulations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. As the demand for sustainable, plant-based oils continues to rise, moringa seed oil had emerged as a promising alternative to conventional oils, especially in regions seeking to reduce reliance on imported or food-competitive oil crops [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEfficient extraction methods were critical to unlocking the full potential of Moringa oil. Among the various techniques, Soxhlet extraction using n-hexane remains a widely adopted method due to its ability to achieve high oil yields and extract a broad spectrum of lipophilic compounds[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Recent studies have demonstrated that Soxhlet extraction can yield up to 39\u0026ndash;42% oil [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Even though several research works have been carried out on oil production from moringa seeds, the effect of both extraction temperature and time at different particle size and optimization of the oil extraction process variables have not yet been investigated in detail. Hence, different from previous reports, our study employed response surface method (RSM) to optimize the oil extraction process variables including temperature (50\u0026ndash;70\u0026deg;C), particle sizes (0.3\u0026ndash;0.7mm) and time (6\u0026ndash;8hr.) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. RSM encompasses statistical and mathematical techniques that are vital for optimization (needs less experiment runs) and studying the interaction between the variables. Central composite design (CCD) was employed for extraction oil from moringa seeds as the method is more efficient and practical design which is ideal for consecutive experimentation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The results of this work support the development of value-added applications for moringa oil in both local and global markets.\u003c/p\u003e"},{"header":"2. Experimental","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e2.1 Materials\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe raw materials (\u003cem\u003ei.e.\u003c/em\u003e Moringa seeds) were purchased at Arba Minch (Gamo Zone) in Ethiopia. N-hexane (Standard ASTM D1836) and Sulphuric Acid were employed in this study. Distilled DI) water was employed during the oil extraction.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Synthesis\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Raw material preparation\u003c/h2\u003e\u003cp\u003eA step-by-step procedure in essential oil extraction is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Initially, harvested seeds were sun-dried for two days to reduce surface moisture. Following this, seed husks were manually removed to obtain clean seed kernels. The dehulled kernels were further sun-dried for 6 hours to lower the internal moisture content to below 7%, which is optimal for solvent-based extraction [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The dried kernels were then ground using a grinded by using pestle and mortar, and the resulting powder was sieved through a 2 mm mesh to ensure uniform particle size, which enhances solvent penetration and oil yield [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Size reduction was done for ease of high extraction and to maximize the essential oil extraction. The complete flow chart of experimental procedures is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Proximate composition analysis of moringa seed\u003c/h2\u003e\u003cp\u003eThe proximate analysis gives ash content, acid value, ester value and saponification value. Proximate analysis was carried out based on the ASTM standard protocol[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 Solvent Extraction of Oil\u003c/h2\u003e\u003cp\u003eThe weighed moringa seed powder was placed in a thimble made of filter paper. The thimble was inserted into the Soxhlet extractor. A volume of 250mL of n-hexane was added to the round-bottom flask. The Soxhlet apparatus was assembled, and all connections were tightened to prevent solvent loss [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The flask was gently heated using a heating water bath, allowing the solvent to boil and reflux [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Extraction was continued until the solvent in the siphon tube was observed to be colourless, indicating that oil was no longer being extracted[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.2.4 Experimental design\u003c/h2\u003e\u003cp\u003eThe experimental design for this study was done by using design expert software version (STAT-EASE 360). The effect of three operating variables of the extraction process such as extraction temperature (50, 60 and 70\u003csup\u003eo\u003c/sup\u003eC), particle size (0.3, 0.5 and 0.7mm) and extraction time (6, 7 and 8hr) on yield were analysed[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The response surface methodology (RSM) was used for optimization of this study. RSM that consists of statistical and mathematical techniques are is vital for modelling and analysing problems in which the response is determined by numerous factors [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The main objective of the response surface is to obtain value of each factor. A quadratic model was used to correlate the interaction effects of the independent variables for maximum oil extraction at the optimum process parameters by employing central composite design (CCD) with RSM[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Three-level with three-factor CCD was used in order to optimize the process parameter to minimize the experimental error. Hence, CCD was generated 20 experiments with three-level and three-factor and the percentage oil yield was taken as response parameter [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The experimental data were analysed by using ANOVA in order to cheek the significance of each variable and their interaction effect on the yield of oil [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The ANOVA study also was used to develop the model equation for the percentage conversion of the produced oil as a function of the independent variables and their interaction effect in order to maximize the yield.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.2.5 Oil yield determination\u003c/h2\u003e\u003cp\u003eOil yield values were calculated in order to identify the optimum values of extraction variables such as (extraction temperature, particle size and extraction time) and to determine the effect of each variable on final yield. The oil yield extracted from moringa seed was calculated using \u003cb\u003eEq.\u0026nbsp;1\u003c/b\u003e [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOil yield (%) = (Weight of oil extracted / Weight of dry moringa seed sample) \u0026times; 100\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3 Results and Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Proximate analysis of raw materials\u003c/h2\u003e\u003cp\u003eThe proximate analysis results of the raw materials (moringa seeds) are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All the experiments were done on a dry basis (wt. %) in triplicate, and the analysis results were presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/p\u003e\u003cp\u003eThe ash analysis result showed that an average ash content of 5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 was obtained this shows that the moringa seed had rich source of minerals [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. It indicating the high percentage value of oil yield can earned from the seed. This result is basically matched with the previous study reported 3.38 % to8% [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The acid value of moringa has been reported to vary depending on factors such as the extraction method employed, the maturity stage of the seeds, and the conditions under which they were stored [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The acid value result showed that an average acid value of 2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77 was obtained this shows that the moringa as an indicator of high-quality moringa oleifera seed oil, as minimal degradation is suggested by such a low level of free fatty acids [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The oil was considered suitable for both nutritional and industrial applications, including biodiesel production and cosmetic formulations, due to its chemical stability and low rancidity potential [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. An ester value of 257\u0026thinsp;\u0026plusmn;\u0026thinsp;73 was obtained from moringa oleifera seed, by which a relatively high level of esterified fatty acids or triglycerides in the oil was indicated [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. These esters, formed from fatty acids and alcohols, were primarily present as triglycerides recognized as the main constituents of vegetable oils [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. A saponification value of 260\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50 had been recorded from moringa oleifera seed, and this result had been interpreted as an indicator of a high proportion of short- to medium-chain fatty acids the results were consistent with the previous studies reported somewhere else [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eProximate analysis results of moringa seeds\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThis study\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReferences (wt%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsh content\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 mgNaOH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.7\u0026ndash;8.9 [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcid value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77 mgNaOH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.32- 8 mg KOH/g [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEster value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e257\u0026thinsp;\u0026plusmn;\u0026thinsp;73mgNaOH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e169.2\u0026ndash;314.27 mg NaOH[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaponification value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e260\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50mgNaOH/g\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e270.9 NaOH/mg[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Model development and statistical analysis\u003c/h2\u003e\u003cp\u003eIn this study, the design expert software version (STAT-EASE 360. trial version) was employed to examine the experimental data regression analysis and to plot the response surface curves. In order to determine the influence of the factors and their interactions effect, the statistical variables have been estimated by employing Analysis of variance (ANOVA) in the optimal Central Composite Design (CCD) test[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The temperature ranged from 50\u0026ndash;70\u0026deg;C, the particle size ranged from 0.3 to 0.7mm and time 6 to 8hr., high (coded\u0026thinsp;+\u0026thinsp;1) and low (coded-1) set points, for oil extraction process variables have been selected according to the values achieved in preliminary tests. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the required experimental variables and ranges for oil extraction process and the experimental results of 20 runs of the design of experiments using CCD on three factors is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eThe experimental analysis of our results (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) provides to mathematical relationship that convey oil yield as function of interaction and individual contribution of parameters \u003cb\u003e(Eq.\u0026nbsp;2).\u003c/b\u003e Hence, in terms of a coded variables, the final regression model (second-order polynomial) for oil extraction was indicated in \u003cb\u003eEq.\u0026nbsp;2\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eOil Yield\u0026thinsp;=\u0026thinsp;+\u0026thinsp;42.99\u0026thinsp;+\u0026thinsp;0.0469*A-0.1494*B -0.6271*C\u0026thinsp;+\u0026thinsp;0.4750*AB-0.2750*AC\u0026thinsp;+\u0026thinsp;0.1000*BC- 0.5784A\u003csup\u003e2\u003c/sup\u003e-0.2249\u003csup\u003e2\u003c/sup\u003e-0.6668C\u003csup\u003e2 (\u003c/sup\u003e\u003cb\u003e2)\u003c/b\u003e\u003c/p\u003e\u003cp\u003ewhere the positive sign presents the synergistic effects and the negative sign shows the antagonistic effects\u003c/p\u003e\u003cp\u003eThe test for significance of the individual model and regression model coefficients with lack of fit test was conducted to fit a good model. Often, the significant variables have been ranked according to the P-value (probability value) or F-value with 95% confidence level. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the ANOVA of regression factors for the data obtained by using Eq.\u0026nbsp;2 for oil extraction from moringa seeds. The smaller \u0026lsquo;P\u0026rsquo; value and the larger F-value (Prob.\u0026gt;F), indicate more significant of the model for corresponding coefficient [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The F-value of 24.86 revealed that the model is significant for oil yield. Moreover, the model terms are not significant only when the Prob.\u0026gt;F values of are \u0026gt;\u0026thinsp;0.1000 whereas values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicate the significant model terms [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In this case, C, AB, AC, A\u003csup\u003e2\u003c/sup\u003e, B\u003csup\u003e2\u003c/sup\u003e and C\u0026sup2; were significant model terms on response while A, B and interactional effects between BC are not significant model terms that had limited effect.\u003c/p\u003e\u003cp\u003eThe model adequate precision ratio of 14.4209, which was \u0026gt;\u0026thinsp;4, revealed the adequacy of the signal model [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Thus, the model developed can be employed to guide the design space [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Furthermore, the multiple correlation coefficient (R\u003csup\u003e2\u003c/sup\u003e) value of 0.9572 was obtained for oil extraction, which was \u0026gt;\u0026thinsp;0.80, revealing that only 4.28% of the total variation might not be described by the empirical model. For a good fit of a model, the R\u003csup\u003e2\u003c/sup\u003e should be at least 0.8 as described by [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The High R\u003csup\u003e2\u003c/sup\u003e results reveals good similarity between the actual and predicted values in the range of experiment. Similar results had been demonstrated and discussed elsewhere [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExperimental variables in actual and coded units and experimental response (oil yield) for the CCD. *Experimental results of response. **Predicted results of response by CCD proposed model.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRun\u003c/p\u003e\u003cp\u003eOrder\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eActual value*\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePredicted\u003c/p\u003e\u003cp\u003eValue**\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e42.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e40.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e40.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e41.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e41.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e42.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e41.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e41.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e40.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e41.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e41.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e41.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e41.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e40.60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e41.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e41.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e42.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e42.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eANOVA for analysis of variance and adequacy of the response surface quadratic model for oil extraction for CCD obtained by the design expert software).; R2\u0026thinsp;=\u0026thinsp;0.9572; Adeq Precision\u0026thinsp;=\u0026thinsp;14.4209. DF- Degree of freedom; S- Significant; NS-Not significant\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSum of Squares\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eF-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eRemark\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA-Temperature\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3617\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.5610\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB-Particle Sizes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.3050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.3050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0845\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC-Extraction Time\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e64.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.6050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.6050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.9620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e57.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.7287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.7287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e77.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResidual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.8316\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLack of Fit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.8316\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePure Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.0000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCor Total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn general, it is crucial to check the adequacy of real system approximation with the developed model in order to verify the data analysis of the experiment [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. By employing the diagnostic plots, like internal studentized residuals versus normal probability plots, the adequacy of the model can be checked. The normal probability of studentized residual plot was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. for extraction of oil from moringa seed. It has been found from Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. that there was neither response transformation nor any apparent problem with normality [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. It can be found that there was a normal distribution of data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The predicted oil yield and internally studentized residual is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. This indicates that the variance of original value is constant for the entire response values (\u003cem\u003ei.e.\u003c/em\u003e the random scatter plot) and there was no need for response factors transformation. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. shows the actual versus the predicted percentage for oil extraction from moringa seeds.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eThree-dimensional (3-D) response surface plots\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe RSM assigned to CCD model was illustrated and examined to optimize the crucial variables and depict the response surface nature in the experiment [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Based on the ANOVA, the 3-D response plots were discovered according to the quadratic model from the combined effect of the three parameters on oil yield from moringa seeds. In each plot, as presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. one variable was maintained constant while the other two factors were tested on oil yield in the experimental ranges. The combined effect of temperature (A) and particle size (B) on oil yield at constant time of 7hr. is demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA. It can be observed from the results, the interaction of temperature (A) and particle size (B) had higher effects on oil extraction from moringa seeds owing to high value result of F statistics (low p-value). Similarly, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB. presents the combined effect of temperature (A) and time (C) on oil production form moringa seeds at 0.5mm (constant particle sizes) results indicated medium (lower than interaction of AB) effect oil yield Similar results with analogous situations and supposition had been presented [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eOptimization of oil extraction process variables by RSM\u003c/b\u003e\u003c/p\u003e\u003cp\u003eProfiling the desirability option and the predicted values in the Design Expert software (trial version) was employed for process optimization. The profile of desirability responses comprises stating the function for desirability for the dependent factor (Oil yield) by allocating a score for predicted values ranging from 0 (very undesirable) to 1 (very desirable). Based on the desirability score of 1.0 Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. oil extraction was optimized at 43.1843% at optimized oil extraction parameters of temperature (59.7942\u0026deg;C), particle sizes (0.409696) and time (6.53709hr.). For validation at these optimized oil extraction parameters, the experiment was performed in triplicate and the results revealed that there was \u0026lt;\u0026thinsp;0.05% error between the actual (43.1843%) and predicted (43.00%) values for the oil yield from moringa seeds. The results were estimated and discussed on the bases of the analysis approached reported by [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Hence, the present research concluded that designed model could predict the relation between the variables and oil yield.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOptimization results derived by CCD for oil yield\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eOil Yield (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSolution no\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA (\u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB (mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC (hrs.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eExperimental value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePredicted value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDesirability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.7924\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.409696\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.53709\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e43.1843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e43\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Characterization of Extracted oil\u003c/h2\u003e\u003cp\u003eThe oil obtained was analysed various parameters as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The oil had Acidity value 2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05, Iodine value 63.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08, refractive index 1.516\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 and density 0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01. This value was interpreted as an indicator of the oil\u0026rsquo;s purity and degree of unsaturation, and was found to be consistent with the refractive indices typically observed in high-oleic vegetable oils [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. And the oil had high oleic acid content and oxidative stability [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacterization of extracted oil\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eComposition\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcidity (% as oleic acid)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIodine value (g of I/100 g of oil)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRefractive index (25\u003csup\u003e0\u003c/sup\u003eC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.516\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDensity (g/cm3) 25\u003csup\u003e0\u003c/sup\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn this study, oil extraction from moringa seeds was optimized using CCD with RSM. The effects of three independent oil extraction process variables including temperature (50\u0026ndash;70\u0026deg;C), particle sizes (1\u0026ndash;3mm), and time (6\u0026ndash;8hr.) using a quadratic model for maximum oil extraction was determined. The present study demonstrates that the interaction effect of temperature and particle sizes is the most significant parameters among the model terms, followed by interaction effect of temperature and extraction times on oil extraction. At the optimized oil extraction variables, the experimental and predicted values, for the oil yield from moringa seeds were found as 43.18% and 43.00%, respectively, with error less than 0.05%. Hence, the results indicated that the model developed could precisely predict the oil extraction. The characterization revealed that the oil could be utilized as a source of edible oil for human consumption.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors state that the data supporting the results of this work are available within the paper. The raw data can be provided from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledged Arba Minch University; College of Natural Science, Arba Minch University, Ethiopia for supporting the laboratory facilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHawi Jihad Kedir: Designed the experiments, collected and analyzed the data, interpretation of results, wrote the original draft, designed the experiments and Editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKasahun Tsegaye Mekonnen: performed characterization tests and conceptualization, supervised, statistical analysis, editing and reviewed the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePermissions to collect the plants/plant parts:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study had not fund\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePal P, Mahant V. 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Assiut J Agricultural Sci, 55, 4, pp. 31\u0026ndash;42, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21608/10.21608/AJAS.2024.302945.1378\u003c/span\u003e\u003cspan address=\"10.21608/10.21608/AJAS.2024.302945.1378\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-chemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Chemistry](https://link.springer.com/journal/44371)","snPcode":"44371","submissionUrl":"https://submission.nature.com/new-submission/44371/3","title":"Discover Chemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Moringa seeds, Optimization, Central composite design, Extracted oil","lastPublishedDoi":"10.21203/rs.3.rs-7724671/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7724671/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis work aimed to extract oil from moringa seeds by optimizing the oil extraction process parameters with the aid of response surface methodology (RSM). The effects of three independent oil extraction process factors particle sizes (0.3\u0026ndash;0.7mm), temperature (50\u0026ndash;70\u0026deg;C) and time (6\u0026ndash;8hr) for oil extraction from moringa seeds were studied. The proximate analysis of moringa seeds: ash content, acid value, ester value and saponification value were 5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46, 2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77, 257\u0026thinsp;\u0026plusmn;\u0026thinsp;73 and, 260\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50wt.%, respectively. A quadratic model was used to correlate the interaction effects of the independent variables for maximum oil extraction at the optimum process parameters by employing central composite design (CCD) with RSM. The work indicates that the interaction of temperature and particle sizes is the most significant parameters among the model terms, followed by the interaction of temperature and extraction time effect on oil yield and finally, interaction of particle sizes and extraction time had no significant effect on oil yield. The studied results reported a better oil yield: 43.18% at extraction temperature of 59.79\u0026deg;C, particle size of 0.41mm and extraction time of 6.54hr with supported a maximum desirability of 1. The oil obtained was analysed for various parameters: acidity value 2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05, iodine value 63.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08, refractive index 1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 and density 0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01. This study concludes that oil obtained from moringa seeds could be utilized as a source of edible oil for human consumption.\u003c/p\u003e","manuscriptTitle":"Experimental optimization of oil extraction from Moringa Seed by using application of response surface methodology (RSM)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-11 10:54:49","doi":"10.21203/rs.3.rs-7724671/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-21T09:29:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-15T20:17:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"228838851020937720901396266946441365386","date":"2025-11-06T18:08:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-29T15:22:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"169782656773658841604565248096297914785","date":"2025-10-29T15:09:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-29T14:33:46+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-28T13:21:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-23T13:23:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-19T17:39:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Chemistry","date":"2025-10-19T17:36:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-chemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Chemistry](https://link.springer.com/journal/44371)","snPcode":"44371","submissionUrl":"https://submission.nature.com/new-submission/44371/3","title":"Discover Chemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4c84b680-28b0-4f35-97c0-b733133a856c","owner":[],"postedDate":"November 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T12:08:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-11 10:54:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7724671","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7724671","identity":"rs-7724671","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}