Optimization of Blighia sapida Seed Oil Biodiesel Production: A Sustainable Approach to Renewable Biofuels

Abstract

This study aims to optimize the production of biodiesel from Blighia sapida (Ackee) seed oil, a non-edible and underutilized feedstock, as a sustainable alternative to conventional fossil-based diesel fuels. The transesterification of Blighia sapida seed oil was optimized using Response Surface Methodology (RSM) with a Box–Behnken experimental design. Three process variables, reaction time, temperature, and methanol-to-oil molar ratio, were selected for modeling biodiesel yield. The resulting biodiesel was characterized by physicochemical properties in accordance with ASTM D6751 standards. The optimal transesterification conditions were found to be 60 min, 60 °C, and a methanol-to-oil ratio of 3:1, yielding 98.36% biodiesel. This represents an improvement over the unoptimized yield of 94.3% at a 6:1 molar ratio. Experimental validation produced an average yield of 97.49%, confirming the model’s reliability. The produced biodiesel exhibited a kinematic viscosity of 4.02 mm²/s, cetane number of 54.6, flash point of 138 °C, and acid value of 0.421 mg KOH/g, which are all within the ASTM D6751 standard limits. This work is among the first to systematically optimize Blighia sapida biodiesel production using RSM. The results demonstrate its viability as a clean-burning, high-quality biodiesel fuel with promising fuel properties and environmental benefits. Its high cetane number and low methanol requirement enhance its combustion performance and production efficiency, positioning Blighia sapida as a competitive feedstock for sustainable biofuel development.

1. Introduction

Fossil fuels, including coal, oil, and natural gas, are non-renewable resources formed over millions of years. However, their rate of depletion far exceeds their natural replenishment, making them unsustainable within a human timeframe. Burning fossil fuels releases substantial amounts of carbon dioxide, a major greenhouse gas contributing to global warming [1]. Oil spills from extraction and transport further cause ecological damage, especially to marine ecosystems [2,3]. Despite these drawbacks, fossil fuels continue to dominate global energy use due to their infrastructure compatibility and high energy density [4]. However, their supply is increasingly threatened by geopolitical instability, particularly in regions with concentrated reserves, such as the Middle East [5]. These limitations underscore the urgent need for a transition to renewable, environmentally friendly energy sources.

In this context, biodiesel has emerged as a promising alternative. Derived from renewable biological sources, biodiesel can be used in compression–ignition engines with minimal or no modification [6,7]. It is non-toxic, biodegradable, and emits significantly fewer pollutants compared to petroleum diesel [8]. Biodiesel also supports energy diversification, rural employment, and reduced dependency on fossil imports [9].

Among potential biodiesel feedstocks, Blighia sapida, commonly known as Ackee apple, is underutilized despite its promise. This evergreen African tree yields oil-rich seeds encased within the arils of mature fruits [10,11]. Annual yields range from 45 to 75 kg/ha [12,13], and while unripe fruits contain toxic hypoglycin, ripening reduces these levels significantly [14]. The reported seed oil content varies between 12.5% and 23.41%, depending on the extraction methods [15,16,17]. This variability highlights the need for improved cultivation strategies and process optimization to maximize biodiesel yield.

Despite its availability, Blighia sapida oil remains largely underexplored in biodiesel research. Prior studies have primarily addressed oil extraction and basic transesterification, with limited focus on process optimization or biodiesel quality characterization. To address this gap, the present study applies RSM to optimize the transesterification parameters, reaction time, temperature, and methanol-to-oil ratio of Blighia sapida oil for biodiesel production. The objective is to maximize yield while ensuring compliance with ASTM D6751 standards.

Given the urgent need for sustainable, non-food-based biodiesel alternatives and the limited research on optimizing Blighia sapida oil for this purpose, the present study addresses a critical gap in renewable fuel development. This work is among the first to systematically optimize biodiesel production from Blighia sapida using RSM. While earlier studies focused on extraction yields or general fuel properties [18,19,20], few have considered integrated modeling, techno-economic viability, or sustainability comparisons. By refining the production process, this study achieved a yield improvement from 94.3% to 98.36%, establishing Blighia sapida as a competitive feedstock. In contrast to more established sources like Jatropha curcas [21,22,23] and Pongamia pinnata [24,25,26,27], Blighia sapida offers high cetane quality and adaptability to marginal lands. By using a non-food, low-cost feedstock, this research supports broader goals in sustainable fuel development, food security, and biodiesel cost reduction.

2. Materials and Methods

The instruments utilized in this study comprise a measuring cylinder, an electronic weighing balance, an electric heater, a thermometer, 200 mL capacity beakers, a shaker, a metallic spatula, and a conical separating funnel.

2.1. Collection and Preparation of Blighia sapida Seeds

Ripe Blighia sapida fruits were collected from Ahmadiya, Lagos, positioned at coordinates 6°41′5.964″ N and 3°13′47.0712″ E in southwestern Nigeria. The seeds were extracted from the arils and thoroughly cleaned to eliminate any impurities. Their outer coatings were peeled off using a knife, after which the seeds were sun-dried for seven days to reduce their moisture content. The dried seeds were then ground into smaller particles using a ball milling machine. Subsequently, an electric blender was employed to further reduce the particle size, achieving a fine consistency of approximately 1 mm, which is optimal for effective solvent interaction during extraction. Subsequently, the ground seeds were stored in an airtight container to preserve their quality. Figure 1 illustrates a schematic representation of the process for collecting and preparing Blighia sapida seeds.

2.2. Oil Extraction from Blighia sapida Seeds

Oil extraction from the milled Blighia sapida seeds was carried out using n-hexane as a solvent via the solvent extraction technique. While n-hexane was selected for its high extraction efficiency [28], it is recognized that this petroleum-based solvent poses environmental and safety concerns [29]. Future work should explore greener alternatives such as ethanol or enzyme-assisted aqueous extraction to improve the process’s environmental footprint and align with green chemistry principles. Oil extraction was carried out using 50 g of finely milled Blighia sapida seeds per batch. The milled seeds were placed in a thimble situated within the main chamber of the extractor. A condenser was attached to the upper section of the extractor, while a flask was positioned at the base. The process was conducted at a temperature of 60 °C for 6 h. During extraction, n-hexane vapor ascended into the chamber containing the seed sample, where it was cooled by the condenser and returned to liquid form. The solvent then flowed through a siphon back into the flask. This cycle was repeated several times until the flask’s contents were sufficiently concentrated.

At the conclusion of the process, n-hexane was evaporated, and the extracted oil yield was calculated using Equation (1). To further minimize moisture content, the extracted oil was placed in an oven at 110 °C for one hour:

$$\mathrm{O}\mathrm{i}\mathrm{l} \mathrm{y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d} \left(\%\right)={\displaystyle \frac{{\mathrm{W}}_{\mathrm{o}}}{{\mathrm{W}}_{\mathrm{b}}}}\times 100\%$$

(1)

where

W_b = weight of the milled apple Blighia sapida seed before oil extraction (g);

W_o = weight of the oil extracted (g).

The FFA content of the extracted oil was analyzed following the AOCS Official Method Cd 3d–63 [30]. A 50 mL quantity of methanol was measured and poured into a 150 mL conical flask, to which five drops of phenolphthalein were added. The Blighia sapida seed oil was then measured and introduced into the flask containing the ethanol and phenolphthalein solution. The mixture was neutralized and titrated with 0.1 N KOH while swirling continuously for about 15 s until a pink coloration appeared. The free fatty acid (FFA) (% (w/w)) content was calculated using Equation (2):

$$\mathrm{F}\mathrm{F}\mathrm{A}={\displaystyle \frac{\mathrm{A}\mathrm{c}\mathrm{i}\mathrm{d} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}}{2}}$$

(2)

The acid value (mg KOH/g oil) was determined using Equation (3):

$$\mathrm{A}\mathrm{c}\mathrm{i}\mathrm{d} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}={\displaystyle \frac{\mathrm{T}\mathrm{i}\mathrm{t}\mathrm{r}\mathrm{e} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}\left(\mathrm{m}\mathrm{L}\right)\times 0.1\times 56.10}{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e} \mathrm{u}\mathrm{s}\mathrm{e}\mathrm{d} \left(\mathrm{g}\right)}}$$

(3)

2.3. Esterification of Blighia sapida Seed Oil

The FFA content of the extracted Blighia sapida seed oil was determined to be 1.5%, which is slightly above the threshold for direct base-catalyzed transesterification. According to Salaheldeen’s assessment of transesterification for biodiesel production, FFA levels should be below 1%, preferably below 0.5%, to prevent soap formation during base-catalyzed transesterification [31]. Therefore, a pre-treatment step (esterification) was necessary to reduce the FFA content and improve the oil’s suitability for transesterification. Esterification is a crucial pre-treatment process that reduces FFA by converting free fatty acids into esters and water using methanol and sulfuric acid as the reactants. In this study, 250 mL of Blighia sapida seed oil was heated to 50 °C on a magnetic stirrer hot plate for 10 min. Afterward, 100 mL of methanol was added and stirred for 5 min, followed by the addition of 3 mL of concentrated sulfuric acid (H₂SO₄). The reaction mixture was maintained at 50 °C with continuous stirring at 350 rpm. Once the esterification process was complete, the mixture was allowed to cool for 2 h before being transferred to a separatory funnel. After 24 h of settling, distinct layers formed, with the top layer containing unreacted methanol and water, the middle layer consisting of impurities, and the bottom layer holding the treated oil. The recovered oil was then dried in an oven at 120 °C for 2 h to eliminate any residual methanol and moisture, ensuring its suitability for subsequent transesterification.

2.4. Experimental Design for Modeling and Optimization of Biodiesel Production from Blighia sapida Biodiesel

This study involved 17 experimental runs, organized using a randomized Box–Behnken design. A quadratic model was employed, enabling the analysis of main effects, interactions, and quadratic terms across the experimental parameters.

Table 1. Design summary of experimental factors and their levels.

Factor	Name	Units	Coded Low	Coded High	Mean	Std. Dev.
A	Time	Minutes	−1 ↔ 60.00	+1 ↔ 180.00	120.00	42.43
B	Temperature	°C	−1 ↔ 60.00	+1 ↔ 70.00	65.00	3.54
C	Methanol-to-oil ratio	Mol	−1 ↔ 3.00	+1 ↔ 9.00	6.00	2.12

provides a summary of the experimental factors and their corresponding levels. The choice of time, temperature, and methanol-to-oil ratio as reaction variables in the transesterification of Blighia sapida oil for biodiesel production is rooted in their fundamental importance to the process’s efficiency and yield. Reaction time plays a crucial role in ensuring the complete conversion of triglycerides into biodiesel. If the reaction time is too short, the process may remain incomplete, while excessively long durations can lead to energy wastage and potential reverse reactions. Similarly, temperature directly affects reaction kinetics by lowering oil viscosity and improving the interaction between methanol and triglycerides. However, precise temperature control is essential, as excessively high temperatures may trigger undesirable side reactions, such as soap formation [32]. The methanol-to-oil ratio is another key factor that influences the reaction’s equilibrium. While an adequate excess of methanol enhances the conversion rate, too much methanol can complicate the separation of glycerol and increase production costs [33]. By carefully selecting and varying these parameters across low and high levels during experimentation, this study aims to identify the optimal conditions for achieving maximum biodiesel yield from Blighia sapida oil via transesterification. Transesterification was performed under ambient atmospheric pressure, which remained constant throughout all experimental runs. Given that the reaction temperatures were below the boiling point of methanol (64.7 °C) and no pressure reactors were employed, pressure effects were assumed to be negligible and thus not considered an input variable.

The biodiesel production process from Blighia sapida seed oil was analyzed and optimized using RSM. This method was utilized to examine the impact of process parameters on biodiesel yield with the objective of modeling the production process, identifying the optimal variable combinations, and maximizing yield. The RSM approach involved conducting a series of experiments to investigate various combinations of reaction parameters. An empirical model was derived from the experimental data to predict biodiesel yield under different conditions. Analysis of Variance (ANOVA) was carried out to evaluate the significance of individual factors and their interactions. Response surface plots were generated through statistical modeling to depict the relationships between variables and yield. The optimization aimed to determine the conditions that produce the maximum yield, with desirability functions used to select the optimal solution from multiple options, ensuring both high efficiency and practicality in the reaction conditions.

2.5. Biodiesel Production from Blighia sapida Oil

The biodiesel production process followed the transesterification method described by Ogunkunle and Ahmed [34]. A methoxide solution was prepared by dissolving potassium hydroxide in methanol, ensuring a catalyst concentration of 1% by weight of the oil. This solution was then heated on an electric plate while maintaining a consistent stirring speed of 700 rpm. The prepared methoxide was mixed with preheated Blighia sapida oil, and the flask was closed with aluminum foil before being stirred at the designated experimental temperature and duration. After the reaction time elapsed, approximately 20% distilled water [35], relative to the oil volume, was added, and the mixture was stirred for an additional 20 min to facilitate phase separation of the reaction products. The mixture was transferred into a separating funnel and allowed to stand for 24 h, enabling the separation of biodiesel, unreacted oil, catalyst, and methanol into distinct layers. To ensure a clear biodiesel sample, the crude biodiesel underwent three cycles of wet washing, followed by gravity settling for water removal and drying at 70 °C. After separation, distilled water, added in a 1:4 ratio to the biodiesel, was gently agitated for five minutes to avoid emulsification and then allowed to settle for 30 min. The heavier water layer containing impurities was drained off. The process was repeated in the second cycle with reduced agitation and a 20 min settling time, producing a cleaner biodiesel. For the third cycle, minimal agitation and settling for another 20 min ensured the wash water was nearly clear, indicating the removal of residual contaminants. The washed biodiesel was then dried in an oven at 70 °C for two hours to evaporate residual moisture, resulting in a visibly clear and high-quality biodiesel sample free from impurities and water contamination.

The biodiesel yield was computed using Equation (4):

$$\mathrm{B}\mathrm{Y}={\displaystyle \frac{M_b}{M_o}}\times 100\%$$

(4)

where BY = biodiesel yield, $M_{b }$= Mass of biodiesel recovered (g), and $M_o$ = Mass of the pre–heated Blighia sapida seed oil used (g).

The physicochemical properties of Ackee methyl esters, including specific gravity, kinematic viscosity, pour point, acid value, pH, cloud point, flash point, iodine value, and cetane number, were evaluated in accordance with ASTM D6751 standards and compared to the corresponding properties of diesel fuel standards.

3. Results and Discussion

This section is divided by subheadings. It provides a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn.

3.1. Extracted Oil from Blighia sapida Oil

The oil extracted from Blighia sapida seeds was determined to be 21.75%, which is higher than the yields reported in several earlier studies. For instance, Aladekoyi et al. [36] recorded 15.5%, Onuekwusi et al. [37] reported 12.5%, and Aloko et al. [15] achieved 20.02%, while Omosuli [16], Tsado et al. [38], and Sinmisola et al. [39] documented 15.26%, 15.61%, and 17.93%, respectively. Oladiji et al. [40] reported a comparable value of 21.6%. In contrast, a slightly higher yield of 23.41% was reported by Orhevba et al. [17].

3.2. Biodiesel Yields from Blighia sapida Oil

Table 2. Biodiesel yields from Blighia sapida oil transesterification.

	Factor A	Factor B	Factor C	Response
Run	Time	Temperature	Methanol-to-Oil Ratio	Biodiesel Yield
	Minutes	°C	Mol	%
1	120	65	6	85.2
2	120	65	6	84.9
3	120	70	3	81.5
4	120	65	6	84.6
5	120	70	9	74.2
6	180	65	9	76.8
7	180	65	3	84.4
8	120	60	3	94.3
9	60	65	3	91.4
10	120	60	9	83.6
11	180	60	6	85.5
12	60	65	9	82.4
13	120	65	6	84.4
14	180	70	6	74.5
15	60	70	6	81.5
16	60	60	6	94.3
17	120	65	6	85.5

presents the results of various experimental conditions, such as time, temperature, and methanol-to-oil ratios, which significantly affect the biodiesel yield. From Table 2, it can be observed that the highest biodiesel yield (94.3%) was observed at 60 min, 60 °C, and a 6:1 methanol-to-oil ratio, as well as 120 min, 60 °C, and a 3:1 methanol-to-oil ratio, indicating an optimal balance between reaction time, temperature, and methanol concentration. At 60 °C, the reaction proceeds efficiently without excessive methanol evaporation, ensuring maximum conversion. The higher methanol ratio (6:1) accelerates reaction kinetics, leading to high yield within a shorter time, while the lower ratio (3:1) requires a longer reaction duration to reach equilibrium. This aligns with Le Chatelier’s Principle, where excess methanol shifts the equilibrium toward biodiesel production, but prolonged reaction time compensates for lower methanol availability, ultimately achieving similar yields [41]. Conversely, higher temperatures (e.g., 70 °C) may have led to methanol loss or side reactions, reducing efficiency. These findings emphasize the importance of optimizing reaction conditions for maximum biodiesel yield.

These results suggest that the optimal combination of time, temperature, and methanol ratio for biodiesel production from Blighia sapida oil is moderate across all factors. Longer reaction times and higher temperatures tend to introduce inefficiencies and lower yields, likely due to side reactions and excessive methanol evaporation. The yield results for Blighia sapida oil biodiesel align with findings for other non-edible oil feedstocks such as Jatropha curcas [42,43] and castor oil, which also demonstrate optimal yields at moderate temperatures and methanol-to-oil ratios [44,45].

A sample of the Blighia sapida biodiesel obtained from all the different experimental conditions is shown in Figure 2. The determined fuel properties of the Blighia sapida biodiesel are presented in

Table 3. Comparison of Blighia sapida biodiesel properties with ASTM D6751 and EN 14214 standards.

Fuel Properties	Unit	Blighia sapida Biodiesel	ASTM D6751	EN 14214
Specific gravity		0.883	0.85 to 0.98	0.86 to 0.90
Kinematic viscosity	mm2/s	4.02	1.90 to 6.0	3.5 to 5.0
Pour point	°C	1.50	−15 to 10	–
Acid value	mg KOH/g	0.421	Max 0.50	Max 0.50
pH		7.74	7 to 9	–
Cloud point	°C	4.15	−3 to 12	–
Flash point	°C	138	>120	>120
Iodine value	g iodine/100 g	105.45	Max 120	Max 120
Cetane number		54.6	Min 51.0	Min 51.0
Higher heating value	MJ/kg	36.42	Min 35	Min 35

. The table provides a comparison of the Blighia sapida biodiesel fuel properties with those of EN and ASTM biodiesel standards. The comparison shows that the determined Blighia sapida biodiesel fuel falls within the acceptable range of EN and ASTM biodiesel standards, suggesting that the fuel can be blended with commercial diesel fuel for internal combustion engine applications.

Figure 3 presents the GC-MS mass spectrum of Blighia sapida biodiesel, highlighting its Fatty Acid Methyl Ester (FAME) profile. The dominant component was identified as methyl 2-methylhexadecanoate (also known as methyl 2-methylpalmitate), a branched-chain methyl ester. This identification is based on the base peak at m/z 88 and a molecular ion peak at m/z 284, with a retention time of 18.433 min, all of which align with standard fragmentation patterns for this compound.

The mass fragmentation spectrum shows several key ions: m/z 88 (base peak), likely arising from the McLafferty rearrangement, a typical fragmentation pathway in methyl esters; and m/z 43 (C₃H₇⁺), 101 (C₅H₉O₂⁺), 115, 143, and 157, all consistent with α- and β-cleavages within the alkyl chain. These peaks further confirm the presence of methyl 2-methylhexadecanoate, with no significant ions above 284 m/z, indicating the absence of higher-molecular-weight esters.

A second component, ethyl hexadecanoate (ethyl palmitate), was also detected but with lower intensity. The clear dominance of methyl 2-methylhexadecanoate supports its role as the primary FAME in the Blighia sapida biodiesel sample.

The presence of branched long-chain esters in the profile suggests enhanced fuel quality characteristics, such as a high cetane number (54.6) and reduced unsaturation, both of which improve ignition performance [46] and oxidative stability [46,47]. Although the exact composition percentages could not be quantified due to the absence of internal standards and peak area integration, the spectral dominance and retention data confirm the major role of methyl 2-methylhexadecanoate in the biodiesel sample. To provide a more detailed view of the FAME composition, the total ion chromatogram (TIC) of the sample is shown in Figure 4. The dominant peak at a retention time of 18.433 min corresponds to methyl 2-methylhexadecanoate.

3.3. RSM Model Analysis of Biodiesel Yield

The Analysis of Variance (ANOVA) data of biodiesel yield from ackee oil transesterification are shown in

Table 4. ANOVA for response surface model of biodiesel yield.

Source	Sum of Squares	df	Mean Square	p-Value
Model	525.03	9	58.34	155.09	<0.0001
A—Time	100.82	1	100.82	268.04	<0.0001
B—Temperature	264.5	1	264.5	703.19	<0.0001
C—Methanol-to-oil ratio	149.65	1	149.65	397.84	<0.0001
AB	0.81	1	0.81	2.15	0.1857
AC	0.49	1	0.49	1.3	0.2913
BC	2.89	1	2.89	7.68	0.0276
A2	0.4046	1	0.4046	1.08	0.3341
B2	1.83	1	1.83	4.88	0.063
C2	3.11	1	3.11	8.28	0.0237
Residual	2.63	7	0.3761
Lack of Fit	1.84	3	0.615	3.12	0.1501
Pure Error	0.788	4	0.197
Cor Total	527.66	16
Std. Dev.	0.6133		R2	0.995
Mean	84.06		Adjusted R2	0.9886
C.V. %	0.7296		Predicted R2	0.9417
			Adeq Precision	42.8374

. The RSM analysis in this section uses ANOVA to evaluate the impact of variables such as time, temperature, and the methanol-to-oil ratio on biodiesel yield. According to Table 4, the model is statistically significant with an FF-value of 155.09, indicating that the model effectively explains the variation in biodiesel yield. The p-values for the variables time, temperature, and methanol-to-oil ratio are all less than 0.0001, showing that these factors significantly affect the yield. Additionally, interaction effects such as BC (the interaction between temperature and the methanol-to-oil ratio) and C² (the quadratic effect of the methanol-to-oil ratio) are also significant, though interactions like AB and AC are not. The model’s predicted R² of 0.9417 is close to the adjusted R² of 0.9886, demonstrating strong model performance with minimal overfitting. A key finding from ANOVA is that higher temperatures (above 60 °C) or longer reaction times (beyond 60 min) do not necessarily improve yields, likely due to side reactions like soap formation.

The model F-value of 155.09 implies the model is significant. There is only a 0.01% chance that an F-value this large could occur due to noise. P-values less than 0.0500 indicate model terms are significant. In this case, A, B, C, BC, and C² are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model. The lack of fit F-value of 3.12 implies the lack of fit is not significant relative to the pure error. There is a 15.01% chance that a lack of fit F-value this large could occur due to noise. A non-significant lack of fit is good for the model to fit. The predicted R² of 0.9417 is in reasonable agreement with the adjusted R² of 0.9886, as their absolute difference (0.0469) is well below 0.2, which is generally considered a threshold for overfitting concerns in regression modeling [48,49]. Adeq Precision measures the signal-to-noise ratio. A ratio greater than 4 is desirable. The signal-to-noise ratio (S/N) of 42.837 indicates that the detected signal is 42.837 times stronger than the baseline noise, confirming a highly reliable and well-resolved measurement. Statistically, an S/N ratio above 10 is generally considered sufficient for quantitative analysis, while values above 3 indicate detectability. Since the obtained ratio far exceeds these thresholds, it ensures that the signal is distinct from background noise, reducing the likelihood of false positives and improving the accuracy and reproducibility of the measurement [49,50]. This model can be used to navigate the design space. The final empirical model equation in terms of coded factors for the biodiesel yield is given by Equation (5). The empirical model equation, expressed in coded terms, predicts biodiesel yield based on varying levels of the independent variables, time (A), temperature (B), and the methanol-to-oil molar ratio (C). The results confirm that moderate levels of these factors optimize biodiesel production from Blighia sapida oil:

$$\begin{gathered} Biodiesel yield=+84.92-3.55A-5.75B-4.33C+0.4500AB+0.3500AC \\ +0.8500BC-0.3100A^2-0.6600B^2-0.8600C^2 \end{gathered}$$

(5)

The equation in terms of coded factors can be used to make predictions about the response for given levels of each factor. By default, the high levels of the factors are coded as +1, and the low levels are coded as −1. The coded equation is useful for identifying the relative impact of the factors by comparing the factor coefficients.

3.4. RSM Predictive Modeling of the Biodiesel Yield

The RSM predictive model offers a robust framework for forecasting biodiesel yield based on experimental variables such as time, temperature, and the methanol-to-oil ratio.

Table 5. Actual and RSM predictive biodiesel values.

Run	Actual Value	Predicted Value	Residual
1	85.2	84.92	0.28
2	84.9	84.92	−0.02
3	81.5	81.13	0.37
4	84.6	84.92	−0.32
5	74.2	74.18	0.02
6	76.8	76.22	0.58
7	84.4	84.18	0.22
8	94.3	94.32	−0.02
9	91.4	91.97	−0.57
10	83.6	83.97	−0.37
11	85.5	85.7	−0.2
12	82.4	82.63	−0.22
13	84.4	84.92	−0.52
14	74.5	75.1	−0.6
15	81.5	81.3	0.2
16	94.3	93.7	0.6
17	85.5	84.92	0.58

compares the actual biodiesel yields with those predicted by the RSM model, highlighting the model’s ability to predict outcomes under various experimental conditions. The residuals, representing the differences between the actual and predicted values, are consistently small across all experimental runs, with most residuals below 1. This indicates the high predictive accuracy of the model [51].

A key observation is that the highest biodiesel yields occur under moderate reaction conditions. These conditions correspond to the smallest residuals, further validating the model’s capability to accurately capture optimal reaction environments for biodiesel production. For instance, in Run 8, the actual yield is 94.3%, while the predicted yield is 94.32%, resulting in a negligible residual of −0.02. Conversely, under more extreme conditions, such as in Runs 5 and 6 (higher methanol-to-oil ratios or extended reaction times), the model shows slightly larger residuals, reflecting minor deviations from the actual values. For example, in Run 6, the actual yield is 76.8%, while the predicted yield is 76.22%, resulting in a residual of 0.58. These findings highlight the importance of maintaining balanced reaction conditions to achieve optimal yields.

The use of RSM for biodiesel yield optimization has been widely reported across various feedstocks, and the results of this study align with similar research. For instance, Dwivedi and Sharma [52] applied the Box–Behnken design to optimize biodiesel production from Pongamia oil, achieving a maximum yield of 98.4% under optimal conditions (a methanol-to-oil ratio of 11.06:1, reaction temperature of 56.6 °C, reaction time of 81.43 min, and KOH catalyst concentration of 1.43% w/w). In contrast, the present study achieved a comparable maximum yield of 98.36% from Blighia sapida oil under more favorable conditions (a methanol-to-oil ratio of 3:1, 60 °C, and 60 min reaction time), demonstrating the environmental advantages of reduced methanol consumption and shorter reaction duration.

Both studies validate the predictive accuracy of RSM, with minimal residual errors confirming model reliability within the tested parameter ranges. However, it is essential to define the domain of model validity to account for deviations observed under extreme conditions. In the Pongamia oil study, yields declined at methanol ratios exceeding 9:1 and at extended reaction times (beyond 90 min) due to separation challenges and methanol retention. Similarly, in this study, the yields plateaued or declined beyond 60–90 min, particularly at higher temperatures (≥70 °C), likely due to soap formation and methanol evaporation. These trends highlight the need to optimize the process parameters within an appropriate range, beyond which the model predictions may no longer hold true due to unwanted side reactions and process inefficiencies.

The effectiveness of RSM across different biodiesel feedstocks is further evident in studies by Srikanth et al. [53] and Hamze et al. [54]. Srikanth et al. [53] optimized biodiesel production from dairy-washed milk scum (DWMS) oil, obtaining a slightly lower yield (92%) under a 7.5:1 methanol-to-oil ratio, 52.5 °C, and 90 min reaction time. Similarly, Hamze et al. [54] optimized biodiesel production from waste cooking oil, achieving a higher yield (99.38%) with a 7.5:1 methanol ratio, 65 °C, and a 1.4 wt% KOH catalyst concentration. While their yields were slightly different, the lower methanol ratio and shorter reaction time in this study emphasize the higher efficiency and cost-effectiveness of Blighia sapida oil as a biodiesel feedstock. Across all studies, RSM consistently proved to be a robust optimization tool, with strong predictive accuracy and minimal residual errors, reinforcing its reliability for biodiesel production. However, as observed in each case, excessive methanol ratios and prolonged reaction times led to diminished yields due to separation difficulties and side reactions, underscoring the importance of identifying optimal reaction conditions within the model’s validity range for sustainable and cost-effective biodiesel production.

Table 6. Comparative summary of reaction conditions and maximum biodiesel yields for various feedstocks using RSM.

Biodiesel Source	Methanol-to-Oil Ratio	Temperature (°C)	Reaction Time (Minutes)	Catalyst Concentration (wt%)	Maximum Yield (%)	RSM Design	Reference
Waste cooking oil	7.5:1	65	60	1.4	99.38	Box–Behnken	[54]
Dairy-washed milk scum	7.5:1	52.5	90	1.1	92.0	Box–Behnken	[53]
Pongamia oil	11.06:1	56.6	81.43	1.43	98.4	Box–Behnken	[52]
Used cooking oil	16.76:1	Microwave irradiation (800 W)	8.13	4.94	98.62	Central composite design	[55]
Palm oil	18.74:1	57.84	12.69	1.24	98.64	Box–Behnken	[56]
Chlorella protothecoides	8:1	60	90	0.92	97.25	Box–Behnken	[57]
Neem oil	7.1:1	41	98	1.02	96.39	Box–Behnken	[58]
Mixed Jatropha curcas and Ceiba pentandra	30%	60	120	0.5	93.33	Box–Behnken	[21]
Waste cooking oil	6.05:1	62.75	72.63	0.77	93.12	Box–Behnken	[59]
Niger seed oil	9.32:1	57.5	90	1.5	95.3	Box–Behnken	[60]
Sunflower oil	6:1, 9:1, 12:1	25, 50, 75	5	0.75, 1.0, 1.25	97.0–97.6	Box–Behnken	[61]
Karanja oil	11.06:1	56.6	81.43	1.43	98.4	Box–Behnken	[62]
Algal oil	50	60–180	0–2	94.175	94.175	Box–Behnken	[63]
Waste cottonseed cooking oil	12:1	50	Ultrasound-assisted	1.0	96.45	Box–Behnken and CCD	[64]
Cucurbita maxima waste oil	6–10	Microwave-assisted	45–75	2–6	97.76	Box–Behnken	[65]
Brucea javanica seed oil	6:1	65	Not directly specified	1.0	94.34	Box–Behnken	[66]

provides a comparative analysis of biodiesel production processes across different feedstocks, emphasizing the reaction conditions, such as the methanol-to-oil ratio, temperature, reaction time, and catalyst concentration, alongside the maximum yield achieved. The table highlights the diversity in feedstock performance and process optimization techniques used in biodiesel production.

The data in Table 6 underscore the effectiveness of RSM in optimizing biodiesel yields across a range of feedstocks. Blighia sapida oil demonstrates a competitive yield of 98.36% under moderate reaction conditions (a methanol-to-oil ratio of 3:1, temperature of 60 °C, and reaction time of 60 min), showcasing its efficiency and cost-effectiveness compared to other feedstocks. The lower methanol requirement for Blighia sapida oil highlights its potential for reducing production costs and simplifying separation processes. However, feedstocks such as waste cooking oil achieve slightly higher yields with more intensive reaction parameters, suggesting the influence of feedstock-specific characteristics. This comparative analysis reinforces the adaptability of RSM in biodiesel production while emphasizing Blighia sapida’s viability as a sustainable biodiesel source.

3.5. Parametric Effect of Reaction Variables on Biodiesel Yields

Figure 5, Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10 collectively illustrate the influence of both individual and interactive transesterification parameters on biodiesel yield. These 3D response surface plots and trend analyses visually support the narrative findings by highlighting the relationships between time, temperature, and the methanol-to-oil ratio. The graphical representations reinforce the identification of optimal conditions, specifically, moderate temperature (60 °C), a reaction time of 60 min, and a 6:1 methanol-to-oil ratio, as the most effective combination for maximizing biodiesel production efficiency.

In addition to the three-dimensional response surface plots, corresponding two-dimensional contour plots (Figure 11, Figure 12 and Figure 13) were generated to further illustrate the interaction effects between process variables on biodiesel yield. These plots provide a clearer view of the regions of optimal performance and support the identification of favorable process conditions. As shown in Figure 11, Figure 12 and Figure 13, the contour lines form ellipsoidal and saddle-shaped patterns, indicating significant interaction between time, temperature, and the methanol-to-oil ratio. Figure 11 shows the contour plot of reaction time (A) against temperature (B), with the methanol-to-oil molar ratio (C) held constant at 6:1. The plot reveals that biodiesel yield increases progressively with longer reaction times and lower temperatures, reaching a peak in the region of 120–150 min and 60–62 °C. Beyond 65 °C, yield diminishes, likely due to methanol volatilization or side reactions. Figure 12 illustrates the effect of reaction time (A) and the methanol-to-oil ratio (C) at a constant temperature of 65 °C. The contour lines show that higher biodiesel yields are achieved at lower methanol ratios (4:1–5:1) and longer reaction durations (≥120 min). Excess alcohol appears to reduce yield, potentially due to dilution effects or disruption of the reaction equilibrium. Figure 13 presents the interaction between temperature (B) and the methanol-to-oil ratio (C) with the reaction time (A) fixed at 120 min. The plot confirms that optimal yields are observed at temperatures around 60–63 °C and methanol-to-oil ratios between 4:1 and 5:1. Increasing either parameter beyond this range results in a decline in yield, further underscoring the importance of process balance. The contour plots complement the 3D surface plots and provide additional clarity on the interactive effects of key transesterification parameters. Across all combinations, the optimal biodiesel yield was achieved at moderate temperatures (60–65 °C), extended reaction times (120–150 min), and methanol-to-oil ratios between 4:1 and 6:1. These results confirm that excessive alcohol or temperature can reduce conversion efficiency, likely due to equilibrium shifts and methanol volatilization.

Understanding the influence of transesterification parameters, reaction time, temperature, and the methanol–to–oil ratio is essential to optimizing biodiesel production from Blighia sapida seed oil. Across 17 experimental runs, the biodiesel yield varied in response to individual and interactive parameter effects. Shorter reaction durations (60 min) were often more effective than longer ones (120–180 min), especially under optimized conditions. High yields (e.g., 94.3% in Run 16) were achieved with 60 min at 60 °C and a 6:1 methanol ratio. Extended durations showed no significant advantage and occasionally reduced yields due to side reactions such as saponification or methanol loss [67,68,69,70]. Biodiesel yield peaked at 60 °C. Higher temperatures (≥65 °C) consistently caused reductions in yield, e.g., 74.2% in Run 5 at 70 °C, mainly due to methanol evaporation and increased soap formation. These outcomes confirm the literature findings that optimal transesterification occurs between 60 and 65 °C [71,72,73,74]. The best yields were observed at a 6:1 molar ratio. Increasing this to 9:1 did not improve yields and often reduced them. For example, at 9:1 and 120 min (Run 5), the yield dropped to 74.2%. This decline is likely due to catalyst dilution, hindered phase separation, and reverse reactions [29,75,76]. The 3D surface response plots confirmed that combinations such as 60 °C + 6:1 ratio + 60 min produced synergistically higher yields. Conversely, higher methanol ratios or temperatures beyond the optimal values consistently led to reduced biodiesel output. These interactions reflect the sensitive balance required between energy input and chemical conversion efficiency [77,78,79].

3.6. Optimization and Model Validation of Blighia sapida Biodiesel Yield

3.6.1. Final Yield Under Optimal Conditions

The optimization of the biodiesel yield from Blighia sapida seed oil was conducted using RSM, yielding 36 potential solutions. Among these, the solution with the highest desirability was selected, involving a reaction time of 60 min, a temperature of 60 °C, and a methanol–to–oil ratio of 3:1. This combination resulted in a biodiesel yield of 98.36%, with a desirability value of 1.0, indicating optimal conditions. These optimized conditions were notably different from the initial experimental setup, which achieved a maximum yield of 94.3% under a higher methanol-to-oil ratio of 6:1 at 60 °C with a 60 min reaction time. The optimized conditions suggest that a lower methanol-to-oil ratio can significantly improve yield efficiency by minimizing side reactions such as methanol evaporation and soap formation. Additionally, the reduced methanol-to-oil ratio simplifies the separation of glycerol, leading to higher-purity biodiesel. The improvement in yield from 94.3% to 98.36% under the optimized conditions illustrates the effectiveness of RSM in fine-tuning biodiesel production parameters for maximal efficiency and sustainability.

3.6.2. Experimental Validation of Predicted Biodiesel Yield Under Optimized Transesterification Conditions

To validate the accuracy of the RSM model, three confirmatory experiments were conducted under the optimized conditions of a 60 min reaction time, a temperature of 60 °C, and a 3:1 methanol-to-oil molar ratio. The biodiesel yields obtained from these experiments were 97.34%, 97.46%, and 97.68%, with an average yield of 97.49%. These values are slightly lower than the model’s predicted maximum yield of 98.36%, with a deviation of 0.87%. This small discrepancy may be attributed to experimental variations, measurement uncertainties, or minor deviations in reaction conditions. However, the high level of agreement between the predicted and experimental values reinforces the reliability of the RSM model in optimizing biodiesel yield and confirms the effectiveness of the identified conditions for maximizing production efficiency.

While the initial biodiesel yield was calculated based on the mass of purified Blighia sapida seed oil, this approach does not fully capture the practical yield from raw biomass. To better reflect real-world production feasibility, the overall yield was recalculated based on the original seed mass.

Given that the seed-to-oil extraction yield is 21.75% and the optimal biodiesel conversion efficiency from oil is 97.49%, the biodiesel yield of 97.49% was calculated based on the mass of methyl esters (biodiesel) produced relative to the mass of oil subjected to transesterification. This value reflects the conversion efficiency of the transesterification process under optimal conditions as defined by the RSM analysis.

Thus, the overall biodiesel yield from seeds can be approximated from Equation (6):

$$\begin{gathered} Overall biodiesel yield \left(\%\right)=Oil yield\times Transesterification efficiency \\ =0.2175\times 0.9749 \\ =0.212 \end{gathered}$$

(6)

The overall biodiesel yield was computed to be 21.2%. This means that approximately 212 g of biodiesel can be obtained from 1 kg of Blighia sapida seeds under the optimal process conditions defined in this study. This more conservative metric offers a realistic basis for a techno-economic evaluation, especially for scale–up and supply chain modeling.

3.7. Economic Considerations and Cost Analysis

Although the primary focus of this study was on process optimization, an initial economic assessment was conducted to evaluate the feasibility of biodiesel production from Blighia sapida seed oil. Assuming an average oil yield of 21.75% per kg of seed and a conversion efficiency of 97.49%, approximately 212 g of biodiesel can be obtained from 1 kg of seeds. Based on regional market data and published biodiesel economics [80,81], the cost structure is estimated as follows:

• Seed cost: ~USD 0.50 per kg;
• Processing (extraction + transesterification): ~USD 0.80 per kg;
• Total production cost: ~USD 1.30–1.50 per liter of biodiesel.

In comparison, biodiesel derived from waste cooking oil or palm oil typically ranges from USD 0.80 to 1.10 per liter under similar conditions [80,82]. Although Blighia sapida biodiesel is moderately higher in cost, it offers distinct advantages:

• It is a non-edible crop, reducing competition with food supplies;
• It grows in marginal or underutilized land;
• It promotes rural agricultural development.

Standard biodiesel (FAME-based) typically blends up to B15–B20 in diesel engines without modification [34,83]. In contrast, hydrotreated vegetable oil (HVO) or deoxygenated fuels enable higher blending or full substitution due to superior chemical properties. Ultimately, the sustainability and local availability of Blighia sapida may justify its use in niche or decentralized biofuel systems, even at modestly higher costs. While the current analysis provides a cost estimate under lab-scale conditions, scaling up production introduces additional complexities such as methanol recovery, continuous process adaptation, and supply chain logistics. Addressing these challenges is essential for realizing commercial viability and warrants further investigation.

3.8. Environmental Considerations and Potential Sustainability Index

While direct data on the carbon footprint or sustainability index of Blighia sapida biodiesel are currently unavailable in the literature, useful insights can be drawn from studies on comparable non-edible biodiesel feedstocks. Like other biofuels, Blighia sapida biodiesel has the potential to reduce greenhouse gas (GHG) emissions relative to fossil diesel. For instance, palm oil biodiesel has been shown to lower GHG emissions by 46–73%, depending on land use and processing conditions [84]. Assuming similar cultivation and processing characteristics, Blighia sapida biodiesel may offer comparable environmental benefits. In addition to these advantages, Blighia sapida biodiesel demonstrates a high cetane number of 54.6, which is indicative of short ignition delay and efficient combustion [85,86]. Higher cetane numbers are associated with improved engine performance and reduced NOx and particulate emissions, though CO and HC emissions may increase slightly under certain conditions. The cetane number is largely influenced by the fatty acid composition, particularly the presence of saturated and long-chain FAMEs [87,88], which dominate in Blighia sapida biodiesel. This further reinforces its potential as a clean-burning alternative fuel. However, biodiesel production can also pose environmental trade-offs. While it generally results in lower emissions of NOx and particulate matter, studies show that certain biodiesel blends, such as B25, can lead to an increase in CO emissions by up to 52%, even while reducing NOx emissions by over 40% [89]. The transesterification process in producing Blighia sapida biodiesel requires multiple wet washing cycles to purify the ester, involving the use of large volumes of water, leading to excess wastewater generation. The generated wastewater is characterized by high chemical oxygen demand and biological oxygen demand, which can negatively affect water quality if unmanaged [90]. These environmental considerations highlight both the potential of Blighia sapida as a biodiesel feedstock, reinforcing the need for a full lifecycle assessment to quantify its net environmental benefits and guide a sustainable scale-up.

4. Conclusions

This study establishes Blighia sapida seed oil as a promising non-food feedstock for biodiesel production, highlighting its potential to contribute to sustainable energy solutions. Through the optimization of the transesterification process using Response Surface Methodology (RSM), a maximum biodiesel yield of 98.36% was achieved under optimal reaction conditions: a reaction time of 60 min, a reaction temperature of 60 °C, and a methanol-to-oil molar ratio of 3:1. This represents a significant improvement over conventional methods, enhancing both yield and process efficiency. The physicochemical properties of the produced biodiesel, including a kinematic viscosity of 4.02 mm²/s, a cetane number of 54.6, and a flash point of 138 °C, conform to ASTM D6751 standards, reinforcing its suitability as a diesel substitute.

The findings underscore the environmental benefits of utilizing Blighia sapida as a biodiesel feedstock. Its high oil yield, non-edible nature, and adaptability to various climatic conditions make it a sustainable alternative to food-based biodiesel sources. Additionally, its cultivation can support rural economies by providing opportunities for local farmers and reducing dependency on fossil fuels. By utilizing underexplored feedstocks like Blighia sapida, this research contributes to the global effort toward cleaner and renewable energy transitions while addressing concerns related to food security and land-use competition.

However, to enhance the economic feasibility of Blighia sapida biodiesel production, future research should focus on quantifying its economic competitiveness and potential for cost savings by addressing key cost challenges, including low oil content, high oil extraction costs, esterification costs, and transesterification costs. Strategies such as developing more efficient oil extraction techniques, utilizing cost-effective catalysts, and exploring integrated biorefinery approaches to maximize by-product valorization should be considered. Additionally, a comparative economic analysis between Blighia sapida biodiesel and other non-edible biodiesel feedstocks is necessary to determine its competitiveness in the market. Further studies on its oxidative stability, long-term storage performance, and compatibility with existing engine technologies will provide valuable insights into its real-world application. Conducting a full lifecycle assessment will also be critical in quantifying its environmental footprint and ensuring its sustainability in comparison to conventional diesel and other biodiesel sources. By advancing knowledge in this area and addressing cost-related challenges, this study supports the ongoing pursuit of alternative and cleaner energy sources necessary for a more sustainable future.

Furthermore, while this study focused on classical biodiesel synthesis via transesterification, future work should examine the techno-economic potential of upgrading Blighia sapida oil to advanced biofuels like green diesel (HVO), which may enhance market competitiveness and reduce reliance on fossil diesel blends. Owing to the challenging requirements of high-pressure reactors, high hydrogen demand, feedstock impurities (e.g., FFA and phospholipids), and catalyst deactivation, strategies such as feedstock pre-treatment, catalyst regeneration, or co-processing with petroleum diesel in existing hydrotreaters can improve the feasibility of creating a bio-based fuel with superior properties and blending potential that can be applied in decarbonizing transport systems.