Optimizing the Process Conditions of Corn Oil Methyl Ester for Bioresin Production

Optimizing the Process Conditions of Corn Oil Methyl Ester for Bioresin Production | 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 Optimizing the Process Conditions of Corn Oil Methyl Ester for Bioresin Production Md Sanaul Huda, Michael Odegaard, Niloy Sarker, Dean Webster, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3136748/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The conversion of corn oil into quality methyl ester through the transesterification process is an age-old concept. Because of its higher degree of unsaturation, similar to soybean oil, transesterified corn oil has promising properties to produce bio-based resin. Replicating published methods did not result in desired quantity and quality of corn methyl ester needed for bio-resin production, which requires further investigation. This research investigated the effect of different reaction conditions on the yield and quality of methyl ester produced from corn oil. The reaction was conducted at 60°C with a methanol-oil ratio of 6:1 and NaOH as a catalyst. Hypothesized recovered yield (> 70%) of corn methyl ester was achieved after stopping the reaction with HCl. The process was conducted at different reaction times (0.5, 1, and 1.5 h) and acid amounts (0, 1.3, 2.6, 3.9, and 5.2 mL). The methyl ester yield ranged from 45–79%. A statistical model was obtained with linear and quadratic terms, and the recovered yield varied significantly with the acid amount, reaction time, and their interactions. The addition of 2.6 mL acid after the transesterification process resulted in a 15–25% increased yield compared to no acid treatment. On the other hand, the yield was reduced 18–24% with increasing time when no acid was added. All the measured characteristics of the produced corn methyl ester sample were found within the limits of ASTM D6751 pure methyl ester. Overall, the optimization of the transesterification process showed promise in increasing the yield of quality methyl ester from corn oil. Biodiesel Transesterification Reaction time Neutralization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Epoxy resins can be synthesized from plant-based oils. Most of the commercially available epoxy resins are derived from petroleum sources and have many environmental and sustainability concerns. Vegetable oils can compete with petroleum sources because they are readily biodegradable and grown in a sustainable manner [ 1 ]. Vegetable oils with higher amount of unsaturated fatty acids can be converted into epoxidized oils. The best compositions of unsaturated fatty acids for use in the production of epoxy fatty acid are oleic, linoleic and linolenic groups [ 2 ]. These fatty acids are plentiful in linseed oil, rapeseed oil, soybean oil, corn oil, and sunflower oil [ 3 ]. Epoxidized sucrose esters of fatty acid (ESEFA) are novel bio-based resins pioneered at North Dakota State University from different vegetable oils, including soybean oil, for over a decade [ 4 ], and the produced ESEFA and their derivatives have been used in a number of coatings and thermoset materials applications. Corn oil has a similar degree of unsaturation as soybean oil; hence, it can be another potential source for producing ESEFA resins. Corn oil is usually produced from corn germ by combining expelling in continuous screw presses with solvent extraction of the press cake. The corn germ extraction methods can be classified as dry and wet methods. The ethanol industry mainly uses the dry method, and the oil from the wet process is primarily intended for human consumption. In 2021, 3.52 MT (million tons) of corn oil was produced worldwide, representing about 2% of the total worldwide vegetable oil production [ 5 ]. The United States is the largest corn oil producer in the world with 1.9 MT (million tons) of production per year which is half of the world's corn oil production per year. Compared with the worldwide production of other vegetable oils, corn oil ranks tenth [ 6 ] and corn oil is less expensive than most other types of vegetable oils. According to National Weekly Ag Energy Round-Up-2022 (on second week of June, 2022), the average US wholesale price for crude corn oil was $ 0.80 per pound whereas crude soybean oil is priced at $ 0.92 per pound [ 7 ]. The production of ESEFA from corn oil requires highly purified corn methyl ester. Transesterification of vegetable oils is the most effective process for transforming the triglyceride molecules into molecules of fatty acid methyl or ethyl esters. As a renewable resource, corn oil (usually rich in oleic and linoleic acids) can be epoxidized using hydrogen peroxide in the presence of either acetic acid or formic acid. The same reaction principle can be applied to corn oil methyl ester after it has been esterified with sucrose to produce a bio-based resin. Some specific quality of the methyl ester influences the production of ESEFA. Glycerol and water content of the methyl ester are important, because transesterification separates the glycerol from the fatty acid, and moisture content can impact the efficiency of the catalyst used in the esterification reaction to produce sucrose ester. Several published reports showed corn oil methyl ester yield in the range of 85–95% [ 8 – 10 ]. However, most of these yields were based on the conversion rate of triglycerides, which does not provide the actual amount of ester produced during transesterification. KOH and NaOH are commonly used catalysts in the transesterification of vegetable oils, due to their low cost, high efficiency, and ease of availability [ 11 ]. The homogeneously catalyzed reaction is commonly known as a one-step process in the presence of base catalysts. According to previous studies, base catalysts initiate the saponification reaction, which reduces the yield of methyl esters and makes separation of methyl esters from the glycerol phase difficult [ 12 , 13 ]. Vávra et al. [ 14 ], stated that the transesterification reaction is reversible and has to be stopped before the methanol is removed. During the methanol removal process from the entire reaction mixture in the presence of the base catalyst, reverse transesterification to raw materials occurred [ 15 ], leading to the low yield of methyl ester. To increase methyl ester yield by reducing saponification and reverse transesterification, some acid can be added to neutralize the catalytically active methoxide ions and to stop the transesterification process [ 16 , 17 ]. In some previous studies, the problem associated with phase separation between glycerol and methyl ester was reported [ 18 , 19 ], and the neutralization step after the reaction by adding acid can minimize this problem [ 20 , 21 ]. However, this catalyst neutralization step is usually used in kinetics studies during methyl ester production and to recover quality glycerol as a valuable by-product of transesterification. Some critical parameters of transesterification reaction, such as temperature, alcohol to oil molar ratio, and catalyst concentration, have been studied for methyl ester yield from corn oil. Veljković et al. [ 22 ], reviewed these conditions and concluded that higher corn oil triacylglycerol conversion (> 90%) was achieved using NaOH catalyst at a concentration of 1.25% at 60 ºC and 6:1 methanol to oil molar ratio. However, there is little available information about stopping the transesterification reaction after corn oil was transesterified. El Boulifi et al. [ 8 ], reduced the pH of the system by washing with distilled water during separation. Moreover, various reports mentioned different reaction times for corn oil transesterification, ranging from 0.5–1.5 h [ 22 ]. In this context, it is necessary to optimize the corn oil methyl ester yield in terms of stopping the reaction with different amounts of acid added after different reaction times. It is also essential to compare if the neutralization affects the yield and quality of corn oil methyl ester compared to other commonly used vegetable oils such as soybean and canola oils. In this study, the objective was to optimize the yield and quality of corn methyl ester for the production of epoxidized sucrose esters of fatty acid and also to illustrate the effect of using acid at the end of the base-catalyzed transesterification of different vegetable oil in terms of methyl ester yield. Materials and Methods Materials Commercial edible grade (brand name: Our Family) corn oil, soybean oil and canola oil were bought from the local supermarket. Methanol of 99.8% purity was supplied from VWR (PA, USA). Sodium hydroxide (NaOH) pellets (reagent grade, ≥ 98%, anhydrous) purchased from Sigma-Aldrich. Magnesium sulfate (MgSO 4 ), anhydrous ≥ 99%, powder was purchased from J.T. Baker (PA, USA). A working solution of 6M HCl was prepared from ACS grade HCl solution (supplied from EMD Millipore, Germany). All the chemicals were used without any further purification. Methyl Ester Production The methyl esters were produced via a transesterification process in which NaOH was used as a catalyst. 100 g of different oil samples (corn, canola and soybean) were heated to 50°C in a 250-mL Erlenmeyer flask. The heating helped to decrease the viscosity of the oil and thus facilitated the activity for methanol. Sodium methoxide solution was prepared separately by dissolving 1.25 g of NaOH in 22-mL of methanol using a magnetic hotplate stirrer. The methanol amount for the sodium methoxide solution was based on the molar ratio of the methanol and corn oil at 6:1. Prepared sodium methoxide solution was poured into the reaction flask when the corn oil reached 50°C. Heating continued and was maintained at 60 ± 2°C, below the boiling point of methanol (63°C). The temperature of the reactant was monitored using Graphtec mini data logger (Model GL220). Stirring on the hot plate was done using a magnetic stirrer at 600 rpm. The reaction was timed as soon as the methanol/catalyst mixture was added. The total reaction time was 1 h for the neutralization experiment when different vegetable oils were used for methyl ester production. In the methyl ester yield optimization study with corn oil the reaction time was varied from 0.5–1.5 h (Table 1 ). After completion of the reaction time mentioned, a fixed amount of acid (5.2 mL) was added in the neutralization experiment and different acid amounts (0-5.2 mL) were used for the optimization study with corn oil (Table 1 ) to produce methyl ester. Neutralization was done by using 6M HCl and the amounts were calculated based on the stoichiometry between HCl and NaOH used. The neutralized reaction mixture was transferred into a 500-mL separatory funnel and left overnight for cooling and separation of the phases of glycerol and corn oil methyl ester. Dark glycerol phase was discarded followed by the phase separation and the methyl esters phase was washed and purified with distilled water. Table 1 Experimental matrix with corn oil and their results Run Factors Yield of corn oil methyl ester (%) Reaction time (h) Acid amount (mL) Neutralization (%) Experimental* Predicted Relative error (%)** 01 0.5 0 69.6 ± 1.5 ab 65.1 6.5 02 1 0 0 52.3 ± 4.6 c 56.7 8.3 03 1.5 0 45.9 ± 5.1 c 48.3 5.2 04 0.5 1.3 70.1 ± 3.2 ab 73.5 4.8 05 1 1.3 25 71.4 ± 6.1 ab 67.8 5.0 06 1.5 1.3 66.7 ± 2.9 b 62.2 6.8 07 0.5 2.6 75.9 ± 6.1 ab 77.8 2.4 08 1 2.6 50 75.9 ± 4.9 ab 74.8 1.4 09 1.5 2.6 71.9 ± 3.2 ab 71.9 0.1 10 0.5 3.9 75.9 ± 2.5 ab 77.8 2.5 11 1 3.9 75 77.7 ± 2.8 ab 77.6 0.1 12 1.5 3.9 75.7 ± 0.8 ab 77.5 2.4 13 0.5 5.2 74.9 ± 1.7 ab 73.8 1.5 14 1 5.2 100 79.1 ± 4.8 a 76.4 3.4 15 1.5 5.2 77.1 ± 2.9 ab 78.9 2.4 *different letters indicate significant differences (at α = 0.05); **Relative error (%) = [abs value of (Experimental-Predicted)/Experimental]×100 Firstly, the excess methanol from the methyl esters phase was removed by evaporation under vacuum. This was done by heating the washed methyl ester under 85–100 kPa vacuum pressure at 65°C for 30 min. The methyl esters were further purified by gentle washing with distilled water to remove residual catalyst, glycerol and soaps (aqueous phase). The mixture was allowed to settle for 20 min followed by each washing for complete removal of the aqueous phase. After three successive washes with distilled water (25 mL in each wash), the aqueous phase became clear. Afterwards, the resulting solution was dried overnight using anhydrous MgSO 4 . Finally, the produced methyl ester was filtered under vacuum to remove the hydrated MgSO 4 . Neutralization Experiment using Three Different Vegetable Oils To investigate the effect of neutralization on yield, methyl ester was produced from corn oil, soybean oil, and canola oil. Two different reaction conditions, each with three replicates were used in this experiment. The first reaction condition was to produce methyl ester without adding any acid, and the other was to add 5.2 mL of 6M HCl to stop the reaction before separation. The reaction ran for 60 min, and other parameters were the same as described in the previous section. The yield of the produced methyl ester was determined using Eq. ( 1 ). $$\text{Yield (%)=}\frac{\text{Weight of refined methyl ester}}{\text{Theoretical weight of methyl ester}}\text{× 100}$$ 1 where the theoretical weight of the methyl ester was calculated by multiplying the weight of oil used with a conversion factor of 0.96. This conversion factor was based on the average molecular weight of the corn oil triglyceride and its fatty acid methyl esters, and the stoichiometry of the transesterification reaction. The percent yield in Eq. ( 1 ) is the recovered yield indicating how much methyl ester can be isolated from the reaction mixture, and the theoretical weight of the methyl ester is the reaction yield which means how much oil is converted to methyl ester. The fatty acid profile of corn oil (Table 2 ) was used to calculate the average molecular weight of the triglyceride in corn oil (869 g/mol) and its fatty acid methyl ester (277.5 g/mol). For soybean oil, the average molecular weight of the triglyceride and its fatty acid methyl ester was 870.5 g/mol and 278 g/mol, respectively. For canola oil it was 900.23 g/mol and 287.4 g/mol, respectively. Experimental Design to Optimize Corn Oil Methyl Ester A full factorial design with two factors was designed to optimize the methyl ester production from corn oil. The two selected factors were the reaction time (A) and the acid amounts used to stop the reaction (B). Factor A had three levels (0.5, 1 and 1.5 h) and factor B had five levels (0, 1.3, 2.6, 3.9 and 5.2 mL). The experimental matrix was tabulated in Table 1 . A total of 15 treatment combinations were obtained and each treatment was conducted in triplicate. The response variable was the yield of methyl ester. Following the completed experiments, the response variable (methyl ester yield) was fitted into a second order polynomial model in order to correlate the response variable to the independent variable. The general form of the model equation was as follows in Eq. ( 2 ): $$\text{Y}= {\text{b}}_{0}+ \sum {\text{b}}_{\text{i }}{\text{X}}_{\text{i}}+\sum {\text{b}}_{\text{ii }}{{\text{X}}_{\text{i}}}^{2}+\sum {\text{b}}_{\text{ij }}{\text{X}}_{\text{i}}{\text{ X}}_{\text{j}}$$ 2 where Y is the yield of methyl ester, X i and X ij are the factors/independent variables, b 0 is the constant regression coefficient, b i , b ii and b ij (i,j = 1,2) are linear, quadratic and two-way regression coefficients, respectively. Statistical Analysis Statistical analysis was performed using Minitab 21 (State College, PA) at a 0.05 significance level. In addition, One-way analysis of variance (ANOVA) was also computed to evaluate the statistical significance and validity of the model. The influence of the process factors on methyl ester yield was analyzed using main effect and interaction effect. The optimal condition providing the maximum methyl ester content was determined by solving the model equation. Analytical Methods The Official American Oil Chemists' Society [ 23 ] methods were used to determine the fatty acid composition (Ce 1e-62), acid value (Cd 3a-63) and saponification value (Cd 3a-94) of the oils. The quality of the produced methyl ester was analyzed in terms of viscosity (ASTM D445), acid value (ASTM D664), cloud and pour point (ASTM D2500) using the methods according to ASTM standards. The water content of the methyl ester was determined using Karl Fischer titration. The total glycerin was calculated using the SafTest™ total glycerin kit [ 24 ]. This glycerin kit was brought from MP biomedical; Solon, OH, USA. A total glycerin reagent which is a lipase enzyme was used to convert bound glycerin into free glycerin of the sample. Then a SafTest™ analyzer which is a spectrophotometer at 570 nm was used to quantify the total free glycerin content. The obtained characteristics of methyl ester were then compared with the standards such as American Society for Testing and Materials (ASTM D6751) and previously published literature. Results and Discussion Effect of Neutralization on Yield of Corn Oil Methyl Ester Compared to Other Vegetable Oils This research started by producing corn oil methyl ester using homogeneous base catalyst (NaOH pellets) in lab-scale. However, the recovered yield of the corn methyl ester was very low (< 50%) because it was difficult to separate the methyl ester from the glycerol phase (Fig. 1 ). There was no distinct separation phase for the corn methyl ester compared to that of vegetable (soybean) oil methyl ester as shown in Fig. 1 . The corn methyl ester had significant soap formation and was mixed in the aqueous phase. It was important to investigate the best way to address the poor separation of corn methyl ester. Poor separation of corn oil methyl ester can be explained by looking at some properties of the different oils tabulated in Table 2 . Corn oil has the highest saponification value and ester value among three oils (Table 2 ). A low saponification value usually indicates easy soap formation at a higher temperature. Canola oil had the lowest saponification value (Table 2 ) causing more soap formation during transesterification reaction. The soap increases the methyl ester solubility in glycerol and results in emulsification of the ester and glycerol, which causes difficulties in the separation of the esters, thus reduces the recovered yield. Table 2 The iodine, acid and saponification value of corn, canola and soybean oils including distribution of fatty acids Oils Saponification value (mg KOH g − 1 ) Ester value (mg KOH g − 1 ) Distribution of Fatty acid, % Palmitic (16:0) Stearic (18:0) Oleic (18:1) Linoleic (18:2) Linolenic (18:3) Others Corn 193.3 182.4 13.2 1.6 28.2 54.7 N/A 2.2 Canola 186.9 179.5 4.5 0.2 63.1 1.9 19.5 10.8 Soybean 192.9 179.6 11.5 3.7 21.0 55.8 7.3 0.8 Saponification values include the neutral fatty acids and free fatty acid content present in the oil. On the other hand, the ester value represents the amount of neutral fat in the oil, which is directly associated with acid and saponification values. A high ester value indicates a high amount of ester with a low molecular weight fatty acid indicates the availability of short-chain fatty acid. Table 2 shows that the ester value is higher in corn oil than in other oils, and it may hinder the separation of glycerol and ester. Saponification is a side reaction happening along with transesterification. Saponification occurs when the free hydroxide of a catalyst breaks the ester bonds between fatty acids and glycerol in a triglyceride, resulting in more free fatty acids and glycerol. The ester bond is more prone to break down with short chain fatty acid. The sodium used for a catalyst is then bound with the fatty acid and unusable, thus complicating the separation and recovery of esters. The soybean oil had a similar saponification value to the corn oil and a similar ester value to the canola oil (Table 2 ). Nevertheless, it is already evident from Fig. 1 that the soybean oil had less soap formation during reaction, when compared to the corn oil resulting in better methyl ester yield. Soybean oil had the lowest amount of oleic acid among others, and free fatty acid is often expressed as percent oleic acid. The presence of low oleic acid could be the reason for less soap formation during saponification towards transesterification of soybean oil. To improve the recovered yield, the effect of stopping or neutralizing the reaction of the different corn, canola, and soybean methyl esters was studied. These are commonly used oils in the US and the expectation is that the yield of methyl ester production will be similar since the refining steps are also similar. The results illustrated in Fig. 2 revealed that neutralization has a positive effect on the yield of methyl ester. The recovered yield increased with the use of acid to stop the reaction. The methyl ester yield was 52–55% for corn and canola oil samples that were not neutralized. This yield significantly increased to 75% when the reaction was neutralized using acid. However, it was also visible that soybean methyl ester yield in reaction with no neutralization was around 72%, which was not significantly different with corn and canola methyl ester yield neutralized with acid. Neutralizing the reaction of soybean methyl ester significantly increased the yield to 88%. and was comparable to the maximum expected theoretical yield of 90%. The small variation might be an indication of some esters were washed during washing. This finding is interesting because the recovered yield is dependent on how well the organic phase separated from the aqueous phase and also the formation of soap that usually dissolves in the aqueous phase. The higher recovered yield seen with soybean oil is likely due to less soap formation. Moreover, the added HCl is more strongly attracted to the metal ion on the sodium soap than the fatty acid chain. So, the metal ion combines with the Cl from the HCl to produce NaCl, and the hydrogen freed from the HCl converts the fatty acid chain to free fatty acid. In this way, the soap formation was reduced, and an increasing recovered yield was observed when acid was added after the transesterification reaction. Most previous studies on the transesterification of these three mentioned oils were mainly focused on the property of methyl ester from different oils and their combustion performance. The findings of this present study is quite similar to Karademir and Karademir [ 25 ] who measured the efficiency of biodiesel production from soybean, corn and canola oil. Their result also showed a better ester conversion rate in soybean compared to corn or canola. But their yield measurement was based on total ester rate and the percent of linoleic acid conversion through gas chromatography instrument rather than the recovered yield. Moreover, the previous studies did not use any neutralization step during their experiment. The neutralization step of stopping transesterification reaction and the recovered yield on the basis of weight differentiates the present study from previous studies. Overall, the differences observed with the recovered yield of methyl ester justified why optimizing the process steps for each type of vegetable oil used is important. Hence, it was essential to optimize the process for corn oil which was the focus of this research. Modelling the Factors Influence the Yield of Corn Oil Methyl Ester With the finding of the importance of neutralization towards increasing the yield during transesterification, it was important to identify the amount of acid needed and its interaction with the total reaction time. The experimental runs corresponding to the factorial design along with the values of the yield for each run are presented in Table 1 , where the predicted value is based on the statistical model. The model to predict the yield of methyl ester was first developed by considering both the linear and quadratic terms in Eq. 2 . For developing a quadratic model, the present experimental design was expanded to a central composite design by the addition of three new runs (at time 1 h and stopping the reaction with 2.6 mL HCl). A statistical analysis was carried out on these experimental values, and the main effects and interaction effects of the factors were determined. Initially, both time (A) and square of time (A 2 ) in the model were not statistically significant at p-value < 0.05. Therefore, a reduced model was developed using forward selection method as seen in Eq. ( 3 ) and the ANOVA results of the developed model are shown in Table 3 . $$\text{Yield (%) = 73.45-16.77A+0.31B-0.003}{\text{B}}^{\text{2}}\text{+0.22 AB}$$ 3 Table 3 ANOVA results for the reduced quadratic model Source of variation Degree of freedom Adjusted Sum of squares Adjusted Mean Square F-Value P-Value Model 4 3421.9 855.5 43.2 < 0.0001 Linear 2 2432.9 1216.4 61.4 < 0.0001 Time (A) 1 253.7 (6.0%) 253.7 12.8 0.001 Acid amount (B) 1 2179.2 (51.7%) 2179.2 110.0 < 0.0001 Acid Amount× Acid Amount (B 2 ) 1 539.2 (12.8%) 539.2 27.2 < 0.0001 Interactions (A×B) 1 449.8 (10.7%) 449.8 22.7 < 0.0001 Error 40 792.2 (18.8%) 19.8 Lack-of-Fit 10 339.6 (8.1%) 34.0 2.3 0.042 Pure Error 30 452.6 (10.7%) 15.1 Total 44 4214.1 According to the ANOVA result (Table 3 ), the reaction time (A), the acid amounts used to stop the reaction (B), square term of acid amount (B 2 ) and interaction term (A×B) significantly affected the yield at 95% confident level. The p-values (< 0.0001) indicate that all of the factors were important in modeling the transesterification reaction. The ANOVA table shows that almost 82% of the source of variation (SOV) in the process was due to variation in the levels of the selected factors. Acid amount (B) contributed more than 50% to the variation in the model. Both the squared term of acid amount (B 2 ) and interaction term (A×B) had similar contribution to predict the yield of methyl ester (12.8% and 10.7%, respectively). Time (A) had contributed only 6% in the variation of the developed model. The source of variation for each factor is represented in the Pareto chart in Fig. 3 . to present the magnitude and the importance of the effects. On the Pareto chart, bars that cross the reference line are statistically significant. However, the lack of fit was slightly significant at p-value = 0.042 in Table 3 , which was very close to being insignificant at p-value > 0.05. The significant error term was probably due to the elimination of square term of time (A 2 ) from the initial model and higher relative deviation (greater than 5%) occurred in experimental run 1 to 6 (Table 1 ). The developed model indicates that for the reactions with no acid addition, the separation between methyl ester and glycerol becomes more difficult, as the reaction time increases. The significance of each coefficient in Eq. ( 3 ) was evaluated by the p-value shown in Table 4 . The smaller the magnitude of the P-value, the more significant is the corresponding coefficient. From Table 4 , it can be seen that all terms in the model were found to be statistically significant. The acid amount (B) term had the most significant effect, followed by the square of acid amount (B 2 ) and interaction (AB) term. The reaction time (A) had the least impact and a similar trend is also seen at 5% significance level with the Pareto chart at Fig. 3 . Table 4 Regression coefficients of the predicted model Term Coefficient P-Value Constant 74.80 0.000 Time (A) -2.91 0.001 Acid Amount (B) 9.84 0.000 Acid Amount × Acid Amount (B 2 ) -8.27 0.000 Time × Acid Amount (AB) 5.48 0.000 Reaction time (A), amount of acid (B), and time-acid amount interaction effects (AB) were fitted by multiple regression analysis to develop a linear model. This linear model was developed to improve on the quadratic models. The adequacy of all the statistical models (linear, quadratic, quadratic with forward selection) was compared by model summary statistics (Table 5 ). The linear model maximizes the value of R 2 and R 2 adj and minimizes the standard deviation compared to the other quadratic models. The high R 2 value refers to the acceptable goodness of fit of the linear model. The R 2 value 0.893 of the linear model revealed that 89.3% of the variation in the response was due to the difference observed in the factors. The linear model to predict methyl ester yield (response function) for the significant main effects and interactions is in Eq. ( 4 ). $$\text{Y}\text{i}\text{e}\text{l}\text{d} \left(\text{%}\right) = 70.66-2.91\text{A}+9.84\text{B}+5.48 \text{A}\text{B}$$ 4 Table 5 Model summary statistics of different model Model type Standard Deviation R 2 R 2 adj R 2 pred Linear 3.885 0.893 0.843 0.758 Quadratic 4.484 0.814 0.793 0.751 Quadratic with forward selection 4.450 0.812 0.793 0.763 Main Effect and Interaction Effect on Corn Oil Methyl Ester Yield Figure 4 and 5 illustrate the main effects and interaction effects of the treatment combinations on the yield of corn oil methyl ester. The model results indicate that both the main effects’ such as reaction time and acid amounts were statistically significant. Moreover, the interaction between the reaction time and amount of acid added was also significant. In the main effects plot (Fig. 4 ), reaction time at 0.5 h and 1 h were associated with the highest mean yield. The methyl ester yield at 1.5 h was significantly different than the yield at 0.5 h and 1 h. The decreasing trend of the yields with increasing time was also evident in Table 4 . The negative coefficient of factor time (A) in Table 4 indicates a reduction in methyl ester yield with the increasing reaction time. Highest yield was achieved by stopping the transesterification reaction with 5.2 mL of 6 M HCl. However, the highest yield was not statistically different for 2.6 mL and 3.9 mL of acid addition to the reaction. Lowest yield of methyl ester was found when no acid was added. Even with a little acid added to stop the reaction, the yield increases significantly (from 55.9% with no acid to 69.4% with 1.3 mL of acid). The positive coefficient of factor acid amount (B) in Table 4 indicates an increasing trend of methyl ester yield with the increasing acid amount. The negative coefficient of the square of acid amount (B 2 ) indicates a concave curvature relationship with yield (Table 4 ; Fig. 4 ). In the interaction plot (Fig. 5 ), the highest yield (79.1%) of methyl ester was achieved with the treatment condition of 1 h reaction time and 5.2 mL acid amounts used to stop the reaction. The significant differences of means were not illustrated here in Fig. 5 , but it was already presented in Table 1 and Fig. 4 . From Fig. 5 , it was evident that the methyl ester yield of corn oil depends both on reaction time and the amount of acid added to stop the reaction. Figure 5 exhibited a trend of increasing yield with the increasing time and acid amount. The only exception happened when no acid was added to stop the reaction. When no acid was used, the yield of methyl ester reduced significantly from 69.6% at 0.5 h to 52.3% and 45.9% at 1.0 h and 1.5 h, respectively. From practical observation, the separation between glycerol and methyl ester became very difficult when no acid was added. Moreover, the interaction effect only occurs between 0.5-1 h. As the reaction time extended beyond 1 h, the interaction was not seen, and methyl ester yield was also slightly reduced. Quality of Methyl Ester Characteristics of the produced methyl ester from the experimental runs were tabulated and compared with standard methyl ester values and other previous studies as shown in Table 6 . The selected characteristics were water content, viscosity, total glycerin content, acid value, cloud point, and pour point. For sucrose esters of fatty acid (bioresin) production using methyl esters, water content of the methyl ester is considered to be the most important parameter. This is because high water content slows down the catalysts by not only participating in the formation of emulsions but also causing hydrolysis or hydrolytic oxidation during the esterification reaction [ 26 ]. The water content of the produced corn oil methyl ester was well below the limit of ASTM D6751 (Table 6 ). Some of the previous studies have reported a very high water content of the methyl ester and might be an indication of using a different drying agent (diatomaceous earth) than that used in present study [ 27 ]. Both diatomaceous earth and MgSO 4 have been reported to be good drying agents for oil but maybe the vacuum drying may have helped lower the moisture content. The amount of drying agent can also impact the water content in the final product. The kinematic viscosity and total glycerin content were also found to be within the limits of ASTM standards and comparable to the previous studies as well (Table 6 ). The low total glycerin content indicated that the conversion was good and very little impurity was present. The acid value found in this study was very similar to [ 28 ]. The low acid value may be due to the difference of acid value in the corn oil used. Table 6 Characterization of corn oil methyl ester Characteristics ASTM D6751 (limit) Corn oil methyl ester (present study) * El Boulifi et al. [ 8 ] Moser and Vaughn [ 28 ] Mata et al. [ 27 ] Water content, ppm < 500 242.05 ± 42.01 323 400 892 Viscosity, mm 2 s − 1 1.9–6.0 4.55 ± 0.18 4.33 4.14 4.55 Total glycerin, % < 0.24 0.05 ± 0.01 0.18 nd nd Acid value, mg KOH g − 1 < 0.5 0.49 ± 0.08 0.04 0.49 0.25 Cloud point, °C Report -1.96 ± 0.51 -3.6 -5 nd Pour point, °C Report -4.41 ± 2.06 -6 -6 nd * n = 30 (15 sample with two replicates) displayed as average ± standard deviation, nd: not determined Cloud point and pour point was a main indicator of cold flow properties of methyl esters. However, ASTM D6751 requires that cloud point and pour point be reported. The observed cloud point and pour point values for the present study were − 1.96°C and − 4.41°C, respectively. Other studies have reported lower cloud point and pour point for their methyl esters, indicating good cold flow properties (Table 6 ). In our study, this characteristic has less attention as it was mainly related with fuel properties. Overall, it was evident that despite having a low yield in some of the experimental runs, the quality was still within acceptable limits. Conclusion The production of methyl ester from commercial corn oil via transesterification was optimized using a full factorial design. Results indicated that the acid amount used to stop the reaction (both linear and quadratic terms), the reaction time (only linear term), and their two-way interaction were statistically significant at 0.05 significance level. The developed quadratic model adequately described the transesterification process. After 1.5 hours of reaction time and complete neutralization of the NaOH catalyst included in the experiment, a maximum corn oil methyl ester yield of 78.9% was predicted. The acid amount factor and its quadratic terms had the most influence on the transesterification reaction. Compared to the treatment with the least amount of acid, the yield was much lower when no acid was added. The characteristics of the corn oil methyl ester generated in this research complemented those of existing standards and prior reports. Present findings of this study will pave the way to synthesize quality bioresin (epoxidized sucrose esters) from corn oil. Future studies will be looking at how the properties of corn oil methyl ester influence the production of sucrose ester. Declarations Funding The authors thank the North Dakota Corn Utilization Council (FAR0032322) for funding this research study. Additional support comes from North Dakota Agricultural Experiment Station and USDA-NIFA Hatch multistate ND01491. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data Availability Data will be made available on request. Author Contribution All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Md. Sanaul Huda, Michael Odegaard , Niloy Chandra Sarker, Dean Webster and Ewumbua Monono. The first draft of the manuscript was written by Md. Sanaul Huda, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors are very grateful to Dr. Brent Hulke from USDA, Sunflower and Plant Biology Research in Fargo, ND for providing the fatty acid analysis of different oils used in the experiment. The authors also would like to acknowledge Andrew Taylor of the North Dakota State University Graduate Center for Writers for his writing consultation to prepare the manuscript. References Alam M, Akram D, Sharmin E, Zafar F, Ahmad S (2014) Vegetable oil based eco-friendly coating materials: A review article. Arab J Chem 7(4):469–479. https://doi.org/10.1016/j.arabjc.2013.12.023 Rafiee-Moghaddam R, Salimon J, Jelas Haron MD, Jahangirian H, Shah Ismail MH, Hosseini S, Rezayi M (2014) Lipase epoxidation optimizing of Jatropha curcas oil using perlauric acid. Dig J Nanomater Biostruct 9(3):1159–1169 Latif A, Zainal Abidin FE, Cardona Z, Awang Biak F, Abdan DR, Mohd Tahir K, Kan Ern P L (2020) Bio-resin production through ethylene unsaturated carbon using vegetable oils. Processes 8(1):48. https://doi.org/10.3390/pr8010048 Pan X, Sengupta P, Webster DC (2011) Novel biobased epoxy compounds: epoxidized sucrose esters of fatty acids. Green Chem 13(4):965–975. https://doi.org/10.1039/C0GC00882F FAOSTAT (2021) Crops and livestock products. https://www.fao.org/faostat/en/#data/QCL . Accessed 13 June 2022 USDA (2021) Foreign Agricultural Service, Oilseeds: World Markets and Trade. https://downloads.usda.library.cornell.edu/usda-esmis/files/tx31qh68h/8g84nh663/3r075q71r/oilseeds.pdf . Accessed 17 December 2022 USDA (2022) National Weekly Ag Energy Round-Up: Livestock, Poultry & Grain Market News. https://www.ams.usda.gov/mnreports/lswagenergy.pdf . Accessed 10 June 2022 El Boulifi N, Bouaid A, Martinez M, Aracil J (2010) Process optimization for biodiesel production from corn oil and its oxidative stability. Int J Chem Eng. https://doi.org/10.1155/2010/518070 Velázquez JM (2007) Conversion of corn oil to alkyl esters. Dissertation, Iowa State University Khan N, Dessouky H (2009) Biodiesel production from corn oil by transesterification process. The Nucl 46(3):241–252. https://thenucleuspak.org.pk/index.php/Nucleus/article/view/953 Leung DY, Wu X, Leung M (2010) A review on biodiesel production using catalyzed transesterification. Appl Energy 87(4):1083–1095. https://doi.org/10.1016/j.apenergy.2009.10.006 Vicente G, Martınez M, Aracil J (2004) Integrated biodiesel production: a comparison of different homogeneous catalysts systems. Bioresour Technol 92(3):297–305. https://doi.org/10.1016/j.biortech.2003.08.014 Anuar MR, Abdullah AZ (2016) Challenges in biodiesel industry with regards to feedstock, environmental, social and sustainability issues: A critical review. Renew Sustain Energy Rev 58:208–223. https://doi.org/10.1016/j.rser.2015.12.296 Vávra A, Hájek M, Skopal F (2017) The removal of free fatty acids from methyl ester. Renew Energy 103:695–700. https://doi.org/10.1016/j.renene.2016.10.084 Hájek M, Skopal F, Černoch M (2012) Effect of phase separation temperature on ester yields from ethanolysis of rapeseed oil in the presence of NaOH and KOH as catalysts. Bioresour Technol 110:288–291. https://doi.org/10.1016/j.biortech.2012.01.143 Vávra A, Hájek M, Kocián D (2021) The influence of vegetable oils composition on separation of transesterification products, especially quality of glycerol. Renew Energy 176:262–268. https://doi.org/10.1016/j.renene.2021.05.050 Georgogianni K, Katsoulidis A, Pomonis P, Manos G, Kontominas M (2009) Transesterification of rapeseed oil for the production of biodiesel using homogeneous and heterogeneous catalysis. Fuel Process. Technol. 90 (7–8):1016–1022. https://doi.org/10.1016/j.fuproc.2009.03.002 Savaliya ML, Dhorajiya BD, Dholakiya BZ (2015) Current trends in separation and purification of fatty acid methyl ester. Separ Purif Rev 44(1):28–40. https://doi.org/10.1080/15422119.2013.872126 Akgün N, İşcan E (2007) Effects of process variables for biodiesel production by transesterification. Eur J Lipid Sci Technol 109(5):486–492. https://doi.org/10.1002/ejlt.200600210 Hájek M, Skopal F, Vávra A, Kocík J (2017) Transesterification of rapeseed oil by butanol and separation of butyl ester. J Clean Prod 155:28–33. https://doi.org/10.1016/j.jclepro.2016.07.007 Vávra A, Hájek M, Skopal F (2018) Acceleration and simplification of separation by addition of inorganic acid in biodiesel production. J Clean Prod 192:390–395. https://doi.org/10.1016/j.jclepro.2018.04.242 Veljković VB, Biberdžić MO, Banković-Ilić IB, Djalović IG, Tasić MB, Nježić ZB, Stamenković OS (2018) Biodiesel production from corn oil: A review. Renew Sustain Energy Rev 91:531–548. https://doi.org/10.1016/j.rser.2018.04.024 AOCS (2017) Official Methods and Recommended Practices of the American Oil Chemists' Society, 7th vol edn. AOCS Press Champaign, IL Tuntiwiwattanapun N, Monono E, Wiesenborn D, Tongcumpou C (2017) In-situ transesterification process for biodiesel production using spent coffee grounds from the instant coffee industry. Ind Crop Prod 102:23–31. https://doi.org/10.1016/j.indcrop.2017.03.019 Karademir C, Karademir E (2015) Efficiency of Biodiesel Production from Soybean, Corn, and Canola Oil. Paper presented at the International Mesopotamia Agriculture Congress, Diyarbakir, Turkey, 22–25 September 2014. https://doi.org/10.13140/RG.2.1.4533.2000 Knothe G (2006) Analyzing biodiesel: standards and other methods. J Am Oil Chem ' Soc 83(10):823–833. https://doi.org/10.1007/s11746-006-5033-y Mata TM, Sousa IR, Vieira SS, Caetano NS (2012) Biodiesel production from corn oil via enzymatic catalysis with ethanol. Energy Fuels 26(5):3034–3041. https://doi.org/10.1021/ef300319f Moser BR, Vaughn SF (2012) Biodiesel from corn distillers dried grains with solubles: preparation, evaluation, and properties. Bioenrg Res 5(2):439–449. https://doi.org/10.1007/s12155-011-9168-9 Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3136748","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":217613322,"identity":"93ab578d-bf65-4e8d-abce-79841eb7b90a","order_by":0,"name":"Md Sanaul Huda","email":"","orcid":"","institution":"North Dakota State University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Md","middleName":"Sanaul","lastName":"Huda","suffix":""},{"id":217613323,"identity":"aca263de-25c8-4922-a726-24ebc8bc67a2","order_by":1,"name":"Michael Odegaard","email":"","orcid":"","institution":"North Dakota State University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Odegaard","suffix":""},{"id":217613324,"identity":"8f3f2ebe-3d32-4e16-8d0f-a3e5536b14a9","order_by":2,"name":"Niloy Sarker","email":"","orcid":"","institution":"North Dakota State University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Niloy","middleName":"","lastName":"Sarker","suffix":""},{"id":217613325,"identity":"c1e5aebb-2a1f-4fec-b814-377fd6717343","order_by":3,"name":"Dean Webster","email":"","orcid":"","institution":"North Dakota State University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dean","middleName":"","lastName":"Webster","suffix":""},{"id":217613326,"identity":"825b1546-e6b4-4f4b-8791-3b456c96a358","order_by":4,"name":"Ewumbua Monono","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYJACZiS2DQPDARDNRryWNNK1HCashV8ix3RzYZsdg25778HHBRXn8/hupD9g+FB2GKcWyRk5ZrdntiUzmJ05l2w848ztYskbOQaMM87h1mJwG6iFt42ZwexGjpk0b9vtxA03chiYedtwa7GHaKmHaTkH1JL+gPkvHi0G0mAth2FaDgC1JBgwM+LRInH/WdntGeeO85idOWNszHMmOXHmmTcGB3vOpePUwt9zeNvtgrJqObPjPYaPeSrsEvuOpz988KPMGqcWGOBB4R0gqH4UjIJRMApGAV4AAO7gWP9IwakiAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-2460-0487","institution":"North Dakota State University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ewumbua","middleName":"","lastName":"Monono","suffix":""}],"badges":[],"createdAt":"2023-07-03 19:43:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3136748/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3136748/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":40045750,"identity":"2ed79d1b-e81e-4643-8dd5-003c60773ed8","added_by":"auto","created_at":"2023-07-14 15:26:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":346097,"visible":true,"origin":"","legend":"\u003cp\u003eDifference between separation of glycerol from methyl ester of vegetable oil (left) and corn oil (right)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3136748/v1/21abd8249963926efb1caf4d.png"},{"id":40043837,"identity":"1675f30f-2d6f-4913-bcff-54837f13817b","added_by":"auto","created_at":"2023-07-14 15:18:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":16106,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of neutralization on methyl ester yield of different oils (response is methyl ester yield and different letters indicate significant differences at α = 0.05)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3136748/v1/2f7a92617d288d159390860c.png"},{"id":40043839,"identity":"98626041-e35d-4765-9747-8c7dc08dc607","added_by":"auto","created_at":"2023-07-14 15:18:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":57432,"visible":true,"origin":"","legend":"\u003cp\u003ePareto chart of the standardized effects of reaction time and acid amount (response is methyl ester yield, α = 0.05)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3136748/v1/03354ef04cfbaf4e95d7b5e6.png"},{"id":40043838,"identity":"0b951035-8961-44e6-ad5b-83cc8d406c1c","added_by":"auto","created_at":"2023-07-14 15:18:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":71437,"visible":true,"origin":"","legend":"\u003cp\u003eMain effects plot for methyl ester yield (different letters indicate significant differences (at α = 0.05) between time and acid amount main effects)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3136748/v1/b7a66d599b7d04e177b42dfb.png"},{"id":40043841,"identity":"505db5f7-a139-4007-9a42-03b474d4950c","added_by":"auto","created_at":"2023-07-14 15:18:05","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":149074,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction plot for methyl ester yield\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3136748/v1/c78fd9eb00f9be77f7c0b61f.png"},{"id":41035989,"identity":"b3313d94-0b86-41b2-be53-e983a75a9efe","added_by":"auto","created_at":"2023-08-03 20:08:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":977269,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3136748/v1/2aa8ad75-804e-4bda-91e9-930234a98ff5.pdf"}],"financialInterests":"","formattedTitle":"Optimizing the Process Conditions of Corn Oil Methyl Ester for Bioresin Production","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEpoxy resins can be synthesized from plant-based oils. Most of the commercially available epoxy resins are derived from petroleum sources and have many environmental and sustainability concerns. Vegetable oils can compete with petroleum sources because they are readily biodegradable and grown in a sustainable manner [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Vegetable oils with higher amount of unsaturated fatty acids can be converted into epoxidized oils. The best compositions of unsaturated fatty acids for use in the production of epoxy fatty acid are oleic, linoleic and linolenic groups [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These fatty acids are plentiful in linseed oil, rapeseed oil, soybean oil, corn oil, and sunflower oil [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e Epoxidized sucrose esters of fatty acid (ESEFA) are novel bio-based resins pioneered at North Dakota State University from different vegetable oils, including soybean oil, for over a decade [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and the produced ESEFA and their derivatives have been used in a number of coatings and thermoset materials applications. Corn oil has a similar degree of unsaturation as soybean oil; hence, it can be another potential source for producing ESEFA resins. Corn oil is usually produced from corn germ by combining expelling in continuous screw presses with solvent extraction of the press cake. The corn germ extraction methods can be classified as dry and wet methods. The ethanol industry mainly uses the dry method, and the oil from the wet process is primarily intended for human consumption. In 2021, 3.52 MT (million tons) of corn oil was produced worldwide, representing about 2% of the total worldwide vegetable oil production [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The United States is the largest corn oil producer in the world with 1.9 MT (million tons) of production per year which is half of the world's corn oil production per year. Compared with the worldwide production of other vegetable oils, corn oil ranks tenth [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] and corn oil is less expensive than most other types of vegetable oils. According to National Weekly Ag Energy Round-Up-2022 (on second week of June, 2022), the average US wholesale price for crude corn oil was \u003cspan\u003e$\u003c/span\u003e0.80 per pound whereas crude soybean oil is priced at \u003cspan\u003e$\u003c/span\u003e0.92 per pound [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe production of ESEFA from corn oil requires highly purified corn methyl ester. Transesterification of vegetable oils is the most effective process for transforming the triglyceride molecules into molecules of fatty acid methyl or ethyl esters. As a renewable resource, corn oil (usually rich in oleic and linoleic acids) can be epoxidized using hydrogen peroxide in the presence of either acetic acid or formic acid. The same reaction principle can be applied to corn oil methyl ester after it has been esterified with sucrose to produce a bio-based resin. Some specific quality of the methyl ester influences the production of ESEFA. Glycerol and water content of the methyl ester are important, because transesterification separates the glycerol from the fatty acid, and moisture content can impact the efficiency of the catalyst used in the esterification reaction to produce sucrose ester.\u003c/p\u003e \u003cp\u003eSeveral published reports showed corn oil methyl ester yield in the range of 85\u0026ndash;95% [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, most of these yields were based on the conversion rate of triglycerides, which does not provide the actual amount of ester produced during transesterification. KOH and NaOH are commonly used catalysts in the transesterification of vegetable oils, due to their low cost, high efficiency, and ease of availability [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The homogeneously catalyzed reaction is commonly known as a one-step process in the presence of base catalysts. According to previous studies, base catalysts initiate the saponification reaction, which reduces the yield of methyl esters and makes separation of methyl esters from the glycerol phase difficult [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. V\u0026aacute;vra et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], stated that the transesterification reaction is reversible and has to be stopped before the methanol is removed. During the methanol removal process from the entire reaction mixture in the presence of the base catalyst, reverse transesterification to raw materials occurred [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], leading to the low yield of methyl ester.\u003c/p\u003e \u003cp\u003eTo increase methyl ester yield by reducing saponification and reverse transesterification, some acid can be added to neutralize the catalytically active methoxide ions and to stop the transesterification process [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In some previous studies, the problem associated with phase separation between glycerol and methyl ester was reported [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and the neutralization step after the reaction by adding acid can minimize this problem [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, this catalyst neutralization step is usually used in kinetics studies during methyl ester production and to recover quality glycerol as a valuable by-product of transesterification. Some critical parameters of transesterification reaction, such as temperature, alcohol to oil molar ratio, and catalyst concentration, have been studied for methyl ester yield from corn oil. Veljković et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], reviewed these conditions and concluded that higher corn oil triacylglycerol conversion (\u0026gt;\u0026thinsp;90%) was achieved using NaOH catalyst at a concentration of 1.25% at 60 \u0026ordm;C and 6:1 methanol to oil molar ratio. However, there is little available information about stopping the transesterification reaction after corn oil was transesterified. El Boulifi et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], reduced the pH of the system by washing with distilled water during separation. Moreover, various reports mentioned different reaction times for corn oil transesterification, ranging from 0.5\u0026ndash;1.5 h [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In this context, it is necessary to optimize the corn oil methyl ester yield in terms of stopping the reaction with different amounts of acid added after different reaction times. It is also essential to compare if the neutralization affects the yield and quality of corn oil methyl ester compared to other commonly used vegetable oils such as soybean and canola oils.\u003c/p\u003e \u003cp\u003eIn this study, the objective was to optimize the yield and quality of corn methyl ester for the production of epoxidized sucrose esters of fatty acid and also to illustrate the effect of using acid at the end of the base-catalyzed transesterification of different vegetable oil in terms of methyl ester yield.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eMaterials\u003c/p\u003e \u003cp\u003eCommercial edible grade (brand name: Our Family) corn oil, soybean oil and canola oil were bought from the local supermarket. Methanol of 99.8% purity was supplied from VWR (PA, USA). Sodium hydroxide (NaOH) pellets (reagent grade, \u0026ge;\u0026thinsp;98%, anhydrous) purchased from Sigma-Aldrich. Magnesium sulfate (MgSO\u003csub\u003e4\u003c/sub\u003e), anhydrous\u0026thinsp;\u0026ge;\u0026thinsp;99%, powder was purchased from J.T. Baker (PA, USA). A working solution of 6M HCl was prepared from ACS grade HCl solution (supplied from EMD Millipore, Germany). All the chemicals were used without any further purification.\u003c/p\u003e \u003cp\u003eMethyl Ester Production\u003c/p\u003e \u003cp\u003eThe methyl esters were produced via a transesterification process in which NaOH was used as a catalyst. 100 g of different oil samples (corn, canola and soybean) were heated to 50\u0026deg;C in a 250-mL Erlenmeyer flask. The heating helped to decrease the viscosity of the oil and thus facilitated the activity for methanol. Sodium methoxide solution was prepared separately by dissolving 1.25 g of NaOH in 22-mL of methanol using a magnetic hotplate stirrer. The methanol amount for the sodium methoxide solution was based on the molar ratio of the methanol and corn oil at 6:1. Prepared sodium methoxide solution was poured into the reaction flask when the corn oil reached 50\u0026deg;C. Heating continued and was maintained at 60\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C, below the boiling point of methanol (63\u0026deg;C). The temperature of the reactant was monitored using Graphtec mini data logger (Model GL220). Stirring on the hot plate was done using a magnetic stirrer at 600 rpm. The reaction was timed as soon as the methanol/catalyst mixture was added. The total reaction time was 1 h for the neutralization experiment when different vegetable oils were used for methyl ester production. In the methyl ester yield optimization study with corn oil the reaction time was varied from 0.5\u0026ndash;1.5 h (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). After completion of the reaction time mentioned, a fixed amount of acid (5.2 mL) was added in the neutralization experiment and different acid amounts (0-5.2 mL) were used for the optimization study with corn oil (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) to produce methyl ester. Neutralization was done by using 6M HCl and the amounts were calculated based on the stoichiometry between HCl and NaOH used. The neutralized reaction mixture was transferred into a 500-mL separatory funnel and left overnight for cooling and separation of the phases of glycerol and corn oil methyl ester. Dark glycerol phase was discarded followed by the phase separation and the methyl esters phase was washed and purified with distilled water.\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\u003eExperimental matrix with corn oil and their results\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\" colname=\"c1\"\u003e \u003cp\u003eRun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eYield of corn oil methyl ester (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReaction time (h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAcid amount (mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNeutralization (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExperimental*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePredicted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRelative error (%)**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6 \u003csub\u003ec\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1 \u003csub\u003ec\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9 \u003csub\u003eb\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1\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\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.5\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\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1\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\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.4\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\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.5\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\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 \u003csub\u003ea\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.4\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\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9 \u003csub\u003eab\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e*different letters indicate significant differences (at α\u0026thinsp;=\u0026thinsp;0.05);\u003c/p\u003e \u003cp\u003e**Relative error (%) = [abs value of (Experimental-Predicted)/Experimental]\u0026times;100\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\u003eFirstly, the excess methanol from the methyl esters phase was removed by evaporation under vacuum. This was done by heating the washed methyl ester under 85\u0026ndash;100 kPa vacuum pressure at 65\u0026deg;C for 30 min. The methyl esters were further purified by gentle washing with distilled water to remove residual catalyst, glycerol and soaps (aqueous phase). The mixture was allowed to settle for 20 min followed by each washing for complete removal of the aqueous phase. After three successive washes with distilled water (25 mL in each wash), the aqueous phase became clear. Afterwards, the resulting solution was dried overnight using anhydrous MgSO\u003csub\u003e4\u003c/sub\u003e. Finally, the produced methyl ester was filtered under vacuum to remove the hydrated MgSO\u003csub\u003e4\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eNeutralization Experiment using Three Different Vegetable Oils\u003c/p\u003e \u003cp\u003eTo investigate the effect of neutralization on yield, methyl ester was produced from corn oil, soybean oil, and canola oil. Two different reaction conditions, each with three replicates were used in this experiment. The first reaction condition was to produce methyl ester without adding any acid, and the other was to add 5.2 mL of 6M HCl to stop the reaction before separation. The reaction ran for 60 min, and other parameters were the same as described in the previous section. The yield of the produced methyl ester was determined using Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\text{Yield (%)=}\\frac{\\text{Weight of refined methyl ester}}{\\text{Theoretical weight of methyl ester}}\\text{\u0026times; 100}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere the theoretical weight of the methyl ester was calculated by multiplying the weight of oil used with a conversion factor of 0.96.\u003c/p\u003e \u003cp\u003eThis conversion factor was based on the average molecular weight of the corn oil triglyceride and its fatty acid methyl esters, and the stoichiometry of the transesterification reaction. The percent yield in Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) is the recovered yield indicating how much methyl ester can be isolated from the reaction mixture, and the theoretical weight of the methyl ester is the reaction yield which means how much oil is converted to methyl ester. The fatty acid profile of corn oil (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) was used to calculate the average molecular weight of the triglyceride in corn oil (869 g/mol) and its fatty acid methyl ester (277.5 g/mol). For soybean oil, the average molecular weight of the triglyceride and its fatty acid methyl ester was 870.5 g/mol and 278 g/mol, respectively. For canola oil it was 900.23 g/mol and 287.4 g/mol, respectively.\u003c/p\u003e \u003cp\u003eExperimental Design to Optimize Corn Oil Methyl Ester\u003c/p\u003e \u003cp\u003eA full factorial design with two factors was designed to optimize the methyl ester production from corn oil. The two selected factors were the reaction time (A) and the acid amounts used to stop the reaction (B). Factor A had three levels (0.5, 1 and 1.5 h) and factor B had five levels (0, 1.3, 2.6, 3.9 and 5.2 mL). The experimental matrix was tabulated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 15 treatment combinations were obtained and each treatment was conducted in triplicate. The response variable was the yield of methyl ester. Following the completed experiments, the response variable (methyl ester yield) was fitted into a second order polynomial model in order to correlate the response variable to the independent variable. The general form of the model equation was as follows in Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e):\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\text{Y}= {\\text{b}}_{0}+ \\sum {\\text{b}}_{\\text{i }}{\\text{X}}_{\\text{i}}+\\sum {\\text{b}}_{\\text{ii }}{{\\text{X}}_{\\text{i}}}^{2}+\\sum {\\text{b}}_{\\text{ij }}{\\text{X}}_{\\text{i}}{\\text{ X}}_{\\text{j}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere Y is the yield of methyl ester, X\u003csub\u003ei\u003c/sub\u003e and X\u003csub\u003eij\u003c/sub\u003e are the factors/independent variables, b\u003csub\u003e0\u003c/sub\u003e is the constant regression coefficient, b\u003csub\u003ei\u003c/sub\u003e, b\u003csub\u003eii\u003c/sub\u003e and b\u003csub\u003eij\u003c/sub\u003e (i,j\u0026thinsp;=\u0026thinsp;1,2) are linear, quadratic and two-way regression coefficients, respectively.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using Minitab 21 (State College, PA) at a 0.05 significance level. In addition, One-way analysis of variance (ANOVA) was also computed to evaluate the statistical significance and validity of the model. The influence of the process factors on methyl ester yield was analyzed using main effect and interaction effect. The optimal condition providing the maximum methyl ester content was determined by solving the model equation.\u003c/p\u003e \u003cp\u003eAnalytical Methods\u003c/p\u003e \u003cp\u003eThe Official American Oil Chemists' Society [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] methods were used to determine the fatty acid composition (Ce 1e-62), acid value (Cd 3a-63) and saponification value (Cd 3a-94) of the oils. The quality of the produced methyl ester was analyzed in terms of viscosity (ASTM D445), acid value (ASTM D664), cloud and pour point (ASTM D2500) using the methods according to ASTM standards. The water content of the methyl ester was determined using Karl Fischer titration. The total glycerin was calculated using the SafTest\u0026trade; total glycerin kit [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This glycerin kit was brought from MP biomedical; Solon, OH, USA. A total glycerin reagent which is a lipase enzyme was used to convert bound glycerin into free glycerin of the sample. Then a SafTest\u0026trade; analyzer which is a spectrophotometer at 570 nm was used to quantify the total free glycerin content. The obtained characteristics of methyl ester were then compared with the standards such as American Society for Testing and Materials (ASTM D6751) and previously published literature.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003eEffect of Neutralization on Yield of Corn Oil Methyl Ester Compared to Other Vegetable Oils\u003c/p\u003e \u003cp\u003eThis research started by producing corn oil methyl ester using homogeneous base catalyst (NaOH pellets) in lab-scale. However, the recovered yield of the corn methyl ester was very low (\u0026lt;\u0026thinsp;50%) because it was difficult to separate the methyl ester from the glycerol phase (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There was no distinct separation phase for the corn methyl ester compared to that of vegetable (soybean) oil methyl ester as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The corn methyl ester had significant soap formation and was mixed in the aqueous phase. It was important to investigate the best way to address the poor separation of corn methyl ester.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePoor separation of corn oil methyl ester can be explained by looking at some properties of the different oils tabulated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Corn oil has the highest saponification value and ester value among three oils (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A low saponification value usually indicates easy soap formation at a higher temperature. Canola oil had the lowest saponification value (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) causing more soap formation during transesterification reaction. The soap increases the methyl ester solubility in glycerol and results in emulsification of the ester and glycerol, which causes difficulties in the separation of the esters, thus reduces the recovered yield.\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\u003eThe iodine, acid and saponification value of corn, canola and soybean oils including distribution of fatty acids\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOils\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSaponification value\u003c/p\u003e \u003cp\u003e(mg KOH g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEster value (mg KOH g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c8\" namest=\"c4\"\u003e \u003cp\u003eDistribution of Fatty acid, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePalmitic (16:0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStearic (18:0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOleic (18:1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLinoleic (18:2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLinolenic (18:3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e193.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e182.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanola\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e186.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoybean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.8\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\u003eSaponification values include the neutral fatty acids and free fatty acid content present in the oil. On the other hand, the ester value represents the amount of neutral fat in the oil, which is directly associated with acid and saponification values. A high ester value indicates a high amount of ester with a low molecular weight fatty acid indicates the availability of short-chain fatty acid. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that the ester value is higher in corn oil than in other oils, and it may hinder the separation of glycerol and ester. Saponification is a side reaction happening along with transesterification. Saponification occurs when the free hydroxide of a catalyst breaks the ester bonds between fatty acids and glycerol in a triglyceride, resulting in more free fatty acids and glycerol. The ester bond is more prone to break down with short chain fatty acid. The sodium used for a catalyst is then bound with the fatty acid and unusable, thus complicating the separation and recovery of esters.\u003c/p\u003e \u003cp\u003eThe soybean oil had a similar saponification value to the corn oil and a similar ester value to the canola oil (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Nevertheless, it is already evident from Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e that the soybean oil had less soap formation during reaction, when compared to the corn oil resulting in better methyl ester yield. Soybean oil had the lowest amount of oleic acid among others, and free fatty acid is often expressed as percent oleic acid. The presence of low oleic acid could be the reason for less soap formation during saponification towards transesterification of soybean oil.\u003c/p\u003e \u003cp\u003eTo improve the recovered yield, the effect of stopping or neutralizing the reaction of the different corn, canola, and soybean methyl esters was studied. These are commonly used oils in the US and the expectation is that the yield of methyl ester production will be similar since the refining steps are also similar. The results illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e revealed that neutralization has a positive effect on the yield of methyl ester. The recovered yield increased with the use of acid to stop the reaction. The methyl ester yield was 52\u0026ndash;55% for corn and canola oil samples that were not neutralized. This yield significantly increased to 75% when the reaction was neutralized using acid. However, it was also visible that soybean methyl ester yield in reaction with no neutralization was around 72%, which was not significantly different with corn and canola methyl ester yield neutralized with acid. Neutralizing the reaction of soybean methyl ester significantly increased the yield to 88%. and was comparable to the maximum expected theoretical yield of 90%. The small variation might be an indication of some esters were washed during washing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis finding is interesting because the recovered yield is dependent on how well the organic phase separated from the aqueous phase and also the formation of soap that usually dissolves in the aqueous phase. The higher recovered yield seen with soybean oil is likely due to less soap formation. Moreover, the added HCl is more strongly attracted to the metal ion on the sodium soap than the fatty acid chain. So, the metal ion combines with the Cl from the HCl to produce NaCl, and the hydrogen freed from the HCl converts the fatty acid chain to free fatty acid. In this way, the soap formation was reduced, and an increasing recovered yield was observed when acid was added after the transesterification reaction.\u003c/p\u003e \u003cp\u003eMost previous studies on the transesterification of these three mentioned oils were mainly focused on the property of methyl ester from different oils and their combustion performance. The findings of this present study is quite similar to Karademir and Karademir [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] who measured the efficiency of biodiesel production from soybean, corn and canola oil. Their result also showed a better ester conversion rate in soybean compared to corn or canola. But their yield measurement was based on total ester rate and the percent of linoleic acid conversion through gas chromatography instrument rather than the recovered yield. Moreover, the previous studies did not use any neutralization step during their experiment. The neutralization step of stopping transesterification reaction and the recovered yield on the basis of weight differentiates the present study from previous studies. Overall, the differences observed with the recovered yield of methyl ester justified why optimizing the process steps for each type of vegetable oil used is important. Hence, it was essential to optimize the process for corn oil which was the focus of this research.\u003c/p\u003e \u003cp\u003eModelling the Factors Influence the Yield of Corn Oil Methyl Ester\u003c/p\u003e \u003cp\u003eWith the finding of the importance of neutralization towards increasing the yield during transesterification, it was important to identify the amount of acid needed and its interaction with the total reaction time. The experimental runs corresponding to the factorial design along with the values of the yield for each run are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, where the predicted value is based on the statistical model. The model to predict the yield of methyl ester was first developed by considering both the linear and quadratic terms in Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. For developing a quadratic model, the present experimental design was expanded to a central composite design by the addition of three new runs (at time 1 h and stopping the reaction with 2.6 mL HCl). A statistical analysis was carried out on these experimental values, and the main effects and interaction effects of the factors were determined. Initially, both time (A) and square of time (A\u003csup\u003e2\u003c/sup\u003e) in the model were not statistically significant at p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Therefore, a reduced model was developed using forward selection method as seen in Eq.\u0026nbsp;(\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and the ANOVA results of the developed model are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\text{Yield (%) = 73.45-16.77A+0.31B-0.003}{\\text{B}}^{\\text{2}}\\text{+0.22 AB}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\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 results for the reduced quadratic 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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of variation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDegree of freedom\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted Sum of squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted Mean 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 \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=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3421.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e855.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLinear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2432.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1216.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime (A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253.7 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e253.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcid amount (B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2179.2 (51.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2179.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcid Amount\u0026times; Acid Amount (B\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e539.2 (12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e539.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteractions (A\u0026times;B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e449.8 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eError\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e792.2 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.8\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack-of-Fit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e339.6 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.042\u003c/p\u003e \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=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e452.6 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.1\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4214.1\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 \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to the ANOVA result (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), the reaction time (A), the acid amounts used to stop the reaction (B), square term of acid amount (B\u003csup\u003e2\u003c/sup\u003e) and interaction term (A\u0026times;B) significantly affected the yield at 95% confident level. The p-values (\u0026lt;\u0026thinsp;0.0001) indicate that all of the factors were important in modeling the transesterification reaction. The ANOVA table shows that almost 82% of the source of variation (SOV) in the process was due to variation in the levels of the selected factors. Acid amount (B) contributed more than 50% to the variation in the model. Both the squared term of acid amount (B\u003csup\u003e2\u003c/sup\u003e) and interaction term (A\u0026times;B) had similar contribution to predict the yield of methyl ester (12.8% and 10.7%, respectively). Time (A) had contributed only 6% in the variation of the developed model. The source of variation for each factor is represented in the Pareto chart in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. to present the magnitude and the importance of the effects. On the Pareto chart, bars that cross the reference line are statistically significant.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHowever, the lack of fit was slightly significant at p-value\u0026thinsp;=\u0026thinsp;0.042 in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, which was very close to being insignificant at p-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05. The significant error term was probably due to the elimination of square term of time (A\u003csup\u003e2\u003c/sup\u003e) from the initial model and higher relative deviation (greater than 5%) occurred in experimental run 1 to 6 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The developed model indicates that for the reactions with no acid addition, the separation between methyl ester and glycerol becomes more difficult, as the reaction time increases.\u003c/p\u003e \u003cp\u003eThe significance of each coefficient in Eq.\u0026nbsp;(\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) was evaluated by the p-value shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The smaller the magnitude of the P-value, the more significant is the corresponding coefficient. From Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, it can be seen that all terms in the model were found to be statistically significant. The acid amount (B) term had the most significant effect, followed by the square of acid amount (B\u003csup\u003e2\u003c/sup\u003e) and interaction (AB) term. The reaction time (A) had the least impact and a similar trend is also seen at 5% significance level with the Pareto chart at Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\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\u003eRegression coefficients of the predicted model\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\u003eTerm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime (A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcid Amount (B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcid Amount \u0026times; Acid Amount (B\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-8.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime \u0026times; Acid Amount (AB)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\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\u003eReaction time (A), amount of acid (B), and time-acid amount interaction effects (AB) were fitted by multiple regression analysis to develop a linear model. This linear model was developed to improve on the quadratic models. The adequacy of all the statistical models (linear, quadratic, quadratic with forward selection) was compared by model summary statistics (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The linear model maximizes the value of R\u003csup\u003e2\u003c/sup\u003e and R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e and minimizes the standard deviation compared to the other quadratic models. The high R\u003csup\u003e2\u003c/sup\u003e value refers to the acceptable goodness of fit of the linear model. The R\u003csup\u003e2\u003c/sup\u003e value 0.893 of the linear model revealed that 89.3% of the variation in the response was due to the difference observed in the factors. The linear model to predict methyl ester yield (response function) for the significant main effects and interactions is in Eq.\u0026nbsp;(\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\text{Y}\\text{i}\\text{e}\\text{l}\\text{d} \\left(\\text{%}\\right) = 70.66-2.91\\text{A}+9.84\\text{B}+5.48 \\text{A}\\text{B}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\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\u003eModel summary statistics of different model\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003epred\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLinear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.758\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuadratic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.751\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuadratic with forward selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.763\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\u003eMain Effect and Interaction Effect on Corn Oil Methyl Ester Yield\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrate the main effects and interaction effects of the treatment combinations on the yield of corn oil methyl ester. The model results indicate that both the main effects\u0026rsquo; such as reaction time and acid amounts were statistically significant. Moreover, the interaction between the reaction time and amount of acid added was also significant. In the main effects plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), reaction time at 0.5 h and 1 h were associated with the highest mean yield. The methyl ester yield at 1.5 h was significantly different than the yield at 0.5 h and 1 h. The decreasing trend of the yields with increasing time was also evident in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The negative coefficient of factor time (A) in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e indicates a reduction in methyl ester yield with the increasing reaction time.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHighest yield was achieved by stopping the transesterification reaction with 5.2 mL of 6 M HCl. However, the highest yield was not statistically different for 2.6 mL and 3.9 mL of acid addition to the reaction. Lowest yield of methyl ester was found when no acid was added. Even with a little acid added to stop the reaction, the yield increases significantly (from 55.9% with no acid to 69.4% with 1.3 mL of acid). The positive coefficient of factor acid amount (B) in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e indicates an increasing trend of methyl ester yield with the increasing acid amount. The negative coefficient of the square of acid amount (B\u003csup\u003e2\u003c/sup\u003e) indicates a concave curvature relationship with yield (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the interaction plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), the highest yield (79.1%) of methyl ester was achieved with the treatment condition of 1 h reaction time and 5.2 mL acid amounts used to stop the reaction. The significant differences of means were not illustrated here in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, but it was already presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. From Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, it was evident that the methyl ester yield of corn oil depends both on reaction time and the amount of acid added to stop the reaction. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e exhibited a trend of increasing yield with the increasing time and acid amount. The only exception happened when no acid was added to stop the reaction. When no acid was used, the yield of methyl ester reduced significantly from 69.6% at 0.5 h to 52.3% and 45.9% at 1.0 h and 1.5 h, respectively. From practical observation, the separation between glycerol and methyl ester became very difficult when no acid was added. Moreover, the interaction effect only occurs between 0.5-1 h. As the reaction time extended beyond 1 h, the interaction was not seen, and methyl ester yield was also slightly reduced.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eQuality of Methyl Ester\u003c/p\u003e \u003cp\u003eCharacteristics of the produced methyl ester from the experimental runs were tabulated and compared with standard methyl ester values and other previous studies as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The selected characteristics were water content, viscosity, total glycerin content, acid value, cloud point, and pour point. For sucrose esters of fatty acid (bioresin) production using methyl esters, water content of the methyl ester is considered to be the most important parameter. This is because high water content slows down the catalysts by not only participating in the formation of emulsions but also causing hydrolysis or hydrolytic oxidation during the esterification reaction [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The water content of the produced corn oil methyl ester was well below the limit of ASTM D6751 (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Some of the previous studies have reported a very high water content of the methyl ester and might be an indication of using a different drying agent (diatomaceous earth) than that used in present study [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Both diatomaceous earth and MgSO\u003csub\u003e4\u003c/sub\u003e have been reported to be good drying agents for oil but maybe the vacuum drying may have helped lower the moisture content. The amount of drying agent can also impact the water content in the final product. The kinematic viscosity and total glycerin content were also found to be within the limits of ASTM standards and comparable to the previous studies as well (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The low total glycerin content indicated that the conversion was good and very little impurity was present. The acid value found in this study was very similar to [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The low acid value may be due to the difference of acid value in the corn oil used.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacterization of corn oil methyl ester\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eASTM D6751\u003c/p\u003e \u003cp\u003e(limit)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorn oil methyl ester (present study)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eEl Boulifi et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMoser and Vaughn [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMata et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater content, ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242.05\u0026thinsp;\u0026plusmn;\u0026thinsp;42.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eViscosity, mm\u003csup\u003e2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.9\u0026ndash;6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e4.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal glycerin, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcid value, mg KOH g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCloud point, \u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePour point, \u0026deg;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.41\u0026thinsp;\u0026plusmn;\u0026thinsp;2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e*\u003c/sup\u003en\u0026thinsp;=\u0026thinsp;30 (15 sample with two replicates) displayed as average\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, nd: not determined\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\u003eCloud point and pour point was a main indicator of cold flow properties of methyl esters. However, ASTM D6751 requires that cloud point and pour point be reported. The observed cloud point and pour point values for the present study were \u0026minus;\u0026thinsp;1.96\u0026deg;C and \u0026minus;\u0026thinsp;4.41\u0026deg;C, respectively. Other studies have reported lower cloud point and pour point for their methyl esters, indicating good cold flow properties (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). In our study, this characteristic has less attention as it was mainly related with fuel properties. Overall, it was evident that despite having a low yield in some of the experimental runs, the quality was still within acceptable limits.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe production of methyl ester from commercial corn oil via transesterification was optimized using a full factorial design. Results indicated that the acid amount used to stop the reaction (both linear and quadratic terms), the reaction time (only linear term), and their two-way interaction were statistically significant at 0.05 significance level. The developed quadratic model adequately described the transesterification process. After 1.5 hours of reaction time and complete neutralization of the NaOH catalyst included in the experiment, a maximum corn oil methyl ester yield of 78.9% was predicted. The acid amount factor and its quadratic terms had the most influence on the transesterification reaction. Compared to the treatment with the least amount of acid, the yield was much lower when no acid was added. The characteristics of the corn oil methyl ester generated in this research complemented those of existing standards and prior reports. Present findings of this study will pave the way to synthesize quality bioresin (epoxidized sucrose esters) from corn oil. Future studies will be looking at how the properties of corn oil methyl ester influence the production of sucrose ester.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the North Dakota Corn Utilization Council (FAR0032322) for funding this research study. Additional support comes from North Dakota Agricultural Experiment Station and USDA-NIFA Hatch multistate ND01491.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by\u0026nbsp;Md. Sanaul Huda,\u0026nbsp;Michael Odegaard\u0026nbsp;,\u0026nbsp;Niloy Chandra Sarker, Dean Webster\u0026nbsp;and\u0026nbsp;Ewumbua Monono. The first draft of the manuscript was written by\u0026nbsp;Md. Sanaul Huda, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are very grateful to Dr. Brent Hulke from USDA, Sunflower and Plant Biology Research in Fargo, ND for providing the fatty acid analysis of different oils used in the experiment. The authors also would like to acknowledge Andrew Taylor of the North Dakota State University Graduate Center for Writers for his writing consultation to prepare the manuscript. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlam M, Akram D, Sharmin E, Zafar F, Ahmad S (2014) Vegetable oil based eco-friendly coating materials: A review article. 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Bioenrg Res 5(2):439\u0026ndash;449. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12155-011-9168-9\u003c/span\u003e\u003cspan address=\"10.1007/s12155-011-9168-9\" 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":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Biodiesel, Transesterification, Reaction time, Neutralization","lastPublishedDoi":"10.21203/rs.3.rs-3136748/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3136748/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe conversion of corn oil into quality methyl ester through the transesterification process is an age-old concept. Because of its higher degree of unsaturation, similar to soybean oil, transesterified corn oil has promising properties to produce bio-based resin. Replicating published methods did not result in desired quantity and quality of corn methyl ester needed for bio-resin production, which requires further investigation. This research investigated the effect of different reaction conditions on the yield and quality of methyl ester produced from corn oil. The reaction was conducted at 60\u0026deg;C with a methanol-oil ratio of 6:1 and NaOH as a catalyst. Hypothesized recovered yield (\u0026gt;\u0026thinsp;70%) of corn methyl ester was achieved after stopping the reaction with HCl. The process was conducted at different reaction times (0.5, 1, and 1.5 h) and acid amounts (0, 1.3, 2.6, 3.9, and 5.2 mL). The methyl ester yield ranged from 45\u0026ndash;79%. A statistical model was obtained with linear and quadratic terms, and the recovered yield varied significantly with the acid amount, reaction time, and their interactions. The addition of 2.6 mL acid after the transesterification process resulted in a 15\u0026ndash;25% increased yield compared to no acid treatment. On the other hand, the yield was reduced 18\u0026ndash;24% with increasing time when no acid was added. All the measured characteristics of the produced corn methyl ester sample were found within the limits of ASTM D6751 pure methyl ester. Overall, the optimization of the transesterification process showed promise in increasing the yield of quality methyl ester from corn oil.\u003c/p\u003e","manuscriptTitle":"Optimizing the Process Conditions of Corn Oil Methyl Ester for Bioresin Production","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-14 15:18:00","doi":"10.21203/rs.3.rs-3136748/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"898171fc-4a02-4a6d-a0f6-0a4631c701d1","owner":[],"postedDate":"July 14th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-08-03T20:00:44+00:00","versionOfRecord":[],"versionCreatedAt":"2023-07-14 15:18:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3136748","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3136748","identity":"rs-3136748","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}