The wild type of Aspergillus niger was obtained from the Biology Laboratory, Department of Biological Sciences, Covenant University, Ota Nigeria. Pineapples wastes were collected from the Cafeteria of Covenant University, Ota, Nigeria.

Pineapple peels were air dried for about 8 hours and further dried in a convention oven for 2 h at 60 °C and then screened to fractional sizes. Screened particle sizes of 2 mm were used for this study. The spore suspension used for the A. niger was 0.5% of the standard McFarland solution (a chemical solution of 1%BaCl₂ (0.05 mL) and 1%H₂SO₄ (9.95 mL) to a bacterial suspension of 1.5 x 10⁸/mL. The turbidity of the McFarland solution was compared to the bacterial suspension. Process variables studied were glucose concentration, pH, temperature, methanol concentration and fermentation time. Based on these selected variables, CCD of the STATISTICA software generated 27 different experimental runs (Table 1). The pH was adjusted using 0.1 N HCl or 0.1 N NaOH as the case may be.

The fermentation process involved the initial preparation of media, inoculation, and incubation for the specified period as stated in the experimental design. The amount of citric acid produced was determined titrimetrically.

The inoculation of the fermentation media was prepared by mixing 1.5 g substrate in 250 ml Erlenmeyer flasks with the volume raised to 50 mL with distilled water. The whole mass was autoclaved for 15 min at 121 °C prior to the fermentation process. Thereafter, it was cooled to room temperature. A. niger was used to inoculate each medium with the addition of methanol (0–5%) to the flasks. During the fermentation, the operational set point parameters were kept as specified in the design. The fermentation process of the inoculum media was conducted in duplicate in an orbital incubator at 180 revolutions per minute at specified operational temperature.

In order to determine the citric acid produced after fermentation, 0.1 M NaOH was titrated against the extract (juice) using phenolphthalein as an indicator [25]. The equivalent number of moles of NaOH required to neutralize citric acid, C₃H₅O (COOH)₃, the content of the pineapple juice was determined based on the concentration and volume of NaOH solution used during titration (Eq. (1)).

The amount in moles of citric acid, C₃H₅O (COOH)₃, in the titrated sample was determined according to Equation(2):

(2)

The concentration (molarity) of citric acid produced was calculated by Eq. (3)

(3)

The concentration of C₃H₅O (COOH)₃ in g/L was determined by Eq. (4) and (5)

(4)

The experimental data as presented (Table 1 ) were used to generate a second-degree polynomial model (Eq. (6)) that relates citric acid response to the five operational parameters considered in this study.

(6)

Where Y is the yield of citric acid generated, α_o to α₄₅ are the model coefficients, A, B, C, D and E are linear coefficients, A², B², C², D², and E² are quadratic coefficients while AB, AC, AD, AE, BC, BE, CD, CE and DE represent the interactions between individual parameters on citric acid production. The model coefficients were obtained using the least square estimation method and the most suitable model was selected based on the mean square error (MSE) value. The accuracy of the model fitness was evaluated by the analysis of variance (ANOVA).

The results of the experiments are presented in Table 1. The highest yield of citric acid (15. 51 g/L) was observed in experimental run 17 at the prevailing conditions of 30 ^oC, 40 h, pH of 5, methanol concentration of 72 g/L and glucose concentration of 4 g/L. Looking closely,the citric acid yield was much lower compared to our previous study [2]. In the study [2], better yields of citric acid (with the maximum value of 59.00 g/L) were obtained when the carbon sources were apple pomace and corn steep liquor and at very reduced methanol concentration, reduced pH of 4.5, and temperature of 38 ^oC. These highlight the sensitivity of the operating variables in the citric acid fermentation process which conform to previous studies [26, 27]. Sugar or carbon sources utilization and citric acid yields appear to be a closely related. The more the carbon source is utilized, the more the citric acid yield.

The regression model which explains the influence of the operating variables on citric acid produced is presented in Equation 7. The model statistical significance was evaluated using the analysis of variance (ANOVA). ANOVA together with tools like R², the sum of squares values, and the P (probability) values validate the model results. R² value close to unity means that the reliability of the model is very high. A very high F-value and low P (probability) value indicate the validity of operating parameters on the dependent variable (citric acid yield). The statistical validation further shows how individual, quadratic, and interactive factors (independent variables) are significant on citric acid yield. In other words, statistical validation reveals which of the operating parameters will actually greatly influence the production of citric acid from pineapple waste. The model generated for the effective prediction of citric acid production from pineapple waste using Aspergillus niger is given as follows:

(7)

Where citric acid yield (Y) is the dependent variable; A(temperature), B(fermentation time), C(pH), D(methanol concentration) and E(glucose concentration) are the independent parameters investigated on citric acid yield.

Furthermore, from the ANOVA (Table 2), the sum of squares (SS) values indicate minimal variability in the data set. SS is the square of the difference between the individual measurements and the mean of all measurements. It measures the amount of data variability and how far the individual measurements are from the mean. A high SS would indicate a lot of variability in the data.

Maximum production of citric acid through the process of fermentation by Aspergillus niger is rested on the availability of sufficient carbon sources [28, 29]. Many other factors such as temperature, pH, and methanol concentration have been reported to also have different effects on the yield of citric acid [13]. The type and concentration of sugar have effects on citric acid production [23]. There should be minimum and maximum levels of sugar dosages in order to maximize citric acid production. High-level sugar in medium introduces intracellular compounds, may cause mycelium overgrowth which increases viscosity in the medium causing reduction in citric acid production [30]. For media having less than 2.5%, minimal level of citric acid production is achieved [23]. In understanding the interactive effects of experimental factors on citric acid yield in this study, response surface and contour plots (Figs. 1 to 4) were utilized. Understanding the interactions of the operating parameters and conditions with citric acid production through the help of the surface and contour plots guide the decisions to be made in predicting the ranges of citric acid optimization.

Fig. (1) illustrates the interaction between temperature and methanol concentration and citric acid yield. The response surface plot shows that maximum citric acid production should be achieved at low methanol concentrations (not greater than 3 g/L) and temperature ranges between 20–30 ^oC (Fig. 1). The results obtained in this study are consistent with the literature, mesophilic temperatures (25-35 °C) have been reported as favorable for optimum yield of citric acid [31].

A high pH often results in the deactivation of the enzyme necessary for citric acid production. During fermentation, the pH of the medium is important because a low pH reduces the risk of contamination of the fermentation process [13]. A low pH of the fermentation medium inhibits and removes unwanted organic acids (oxalic acid and gluconic acid) thereby increasing the production of citric acid [23]. In addition, glucose oxidase may be activated reducing citric acid production [32]. Increasing pH beyond 4.5 during the production process reduces the final yield of citric acid [23]. It should be noted that the type of carbon substrate for the fermentation process also contribute to either increasing or decreasing the pH of the medium [2]. Fig. (2) shows that increasing the time for fermentation increases the pH of the medium. Though it appears from the response plot that more of the citric acid was produced, the optimum production points cannot be achieved in relation to other parameters as temperature, methanol concentration, and glucose loading. Looking closely in Fig. (2), the optimum conditions should be located between pH 3-5 and fermentation time ranges of 4-8 h.

Temperature and pH of fermentation medium are essential parts for maximizing the production of citric acid by Aspergillus niger. Fig. (3) shows that maximum production of citric acid can be achieved for pH range 2.0-6.0 and a temperature range of 24-38 ^oC. Maximum production of 15.51 g/L citric acid was achieved at a pH of 3 and 30 ^oC fermentation temperature (Table 1). This guided our judgement for the optimization process. Increased citric acid production may be attributed to high enzymatic activity at increasing temperatures. This agrees with other relevant studies as reported in the literature [33].

Fig. (1). Response surface and contour plot showing the effect of Methanol concentration and Temperature on citric acid yield.

Fig. (2). Response surface and contour plot showing the effect of pH and fermentation Time on citric acid yield.

Fig. (3). Response surface and contour plot showing the effect of Temperature and pH on citric acid yield.

The interactive effect of fermentation time and temperature on citric acid yield is as shown in Fig. (4). A shorter production time is of great importance. This reduces the cost of production.

Eq. (7) was solved by the method of Myers and Montgomery [34] to obtain the optimum parameters required for the generation of citric acid. The surface responses, as well as the ANOVA results, were used to predict the optimum conditions of citric acid generated. Responses predicted for citric acid production were evaluated using Eq. (7). These results showed that methanol concentration above 2% (v/v) is suitable for citric acid production. The ANOVA analysis of the methanol concentration factor provided a low probability value of 0.0266 on the linear term (Table 2). Table 2 shows the analysis of the developed model using ANOVA.

Furthermore, Table 2 shows that the linear effects of the temperature, time, pH, and methanol concentration to be significant on citric acid production. The quadratic terms of temperature, glucose concentration, the interactive effect of temperature-time, and the interactive effect of time and methanol concentration are marginally significant on citric acid production. These evaluations follow the trends as shown through the response surface plots (Figs. 1 to 4). From the regression model (Eq. 7), the coefficient of determination (R²) of 0.895 was obtained by comparing the experimental with the predicted values.

This indicates that 89.5% of the observed data can be demonstrated by the model while only 10.5% cannot be accounted for by the model. ANOVA shows a developed model to be marginally significant with a probability value of 0.060. The observed (experimental) and predicted values were compared and noted to be in close agreements (Fig. 5), further validating the model. The differences between the experimental and predicted values, that is, the residuals (Table 1), were also within the allowable ranges. Predicted optimum conditions for citric acid production were 41 g/L glucose concentration, 5.5%(v/v) methanol, 45 h fermentation time, pH of 5.4, and temperature of 34 ^oC given a yield of 13.5 g/L citric acid.

Optimal conditions were validated by carrying out another duplicated set of an experiment which gave the optimum conditions as 38 g/L of glucose concentration, 3% (v/v) of methanol, 50 h of fermentation time, pH of 4.3 and temperature of 30 ^oC which yielded 15.51 g/L citric acid.

Fig. (4). Response surface and contour plot showing the effect of Temperature and Time on citric acid yield.

Fig. (5). Predicted values versus Experimental values of citric acid production.