VCO Introduction

Introduction

Coconut oil is well accepted by the consumer as a functional food oil, and the demand for this oil in baking industries, processed foods, infant formulae, pharmaceuticals, and cosmetics continues to increase [1,2,3]. Recently, the trend towards producing coconut oil is no longer through a dry process, that is refining bleaching and deodorizing process (RBD process), but rather through a wet process, which coconut oil was extracted from coconut milk [4,5]. This process appears more desirable due to the free usage of chemical solvents, thus environmental friendly than the solvent extraction. The coconut oil resulting through a wet process is called Virgin Coconut Oil (VCO). VCO is more beneficial since the mode of extraction retains more biologically active components such as vitamin E and polyphenols [6,7].

VCO contains more than 90% of saturated fatty acids, and more than 70% are medium chain triglyceride (MCT), which is MCT more rapidly absorbed and hydrolyzed in the body [8]. These properties make MCT preferred carrier for flavors, vitamins, essences, and colors and can be further processed into emulsifier and biodiesel [6,9]. VCO with more than 50% lauric acid has been proved that the body could convert it into monolaurin. Monolaurin is antimicrobial and antiviral activity. Moreover, it is used as anti obesity treatment [10,11,12].

VCO manufacturing technology through a wet process is diverse, namely enzymatic, fermentation and centrifugation [1,3,4]. Some are considered as an inferior quality product, which indicated by high moisture and free fatty acid content [13]. This product is easy to be rancid, turned brown and exhibited relatively short lifetime. Fermentation process has more beneficial and safety effect rather than other wet process methods [14,15]. Coconut milk fermentation process using minimal energy produces VCO with low rancidity, longer shelf life, bright color and the aromatic is typical of coconut oil [2,10].

Saccharomyces cerevisiae is a potential microbial starter for extracting VCO through fermentation system. S. cerevisiae is mold and able to separate the layers of fermented in a short time [16]. During the fermentation process, the microbe produces enzymes protease and lipase. This enzyme acts as a breaker of molecules contained in coconut milk to produce coconut oil [6].

Fermented coconut milk has been affected by several parametric factors namely pH, temperature, stirring speed, inoculum concentration, fermentation time, and types of bacteria [2,4,5,15]. So far, the effect of each variable on the yield of VCO produced has been reported widely. However, the effect of the interaction of parametric factors simultaneously to yield VCO is still limited.

This study is aimed to observe the impact of three major factors affecting the fermentation of coconut milk; they are the stirring speed, the concentration of inoculum added to the process, and fermentation time. The methods of observations were carried out simultaneously to obtain the effect of the interaction of parametric factors and the optimum conditions that could be achieved [17,18]. Optimization is one of the most important engineering tools for creating a process that is economical, safe, and environmentally benign throughout the whole lifetime of the plant [19,20].

Interaction effects were observed using RSM with the Box-Behnken design. RSM is a sequential procedure with an initial objective to lead the experiments rapidly and efficiently to the general vicinity of the optimum. RSM is preferred because of its

responsible high efficiency, and it can simultaneously consider several factors at many different levels and corresponding interactions among these factors using a small number of observations [16,21]. Through these methods, the effect of interactions on every two factors to response variable (the percentage of oil recovery) is observed.

Bearing the explanation above, the objectives of the study reported in this paper are to develop a response surface method using Box-Behnken design and to evaluate the interaction effect of three dominant parametric factors that can be increased VCO production in the fermentation process using Saccharomyces cerevisiae.

Materials and Methods

Materials

Uniformly sized of a 12 (twelve) month old (matured) nuts were collected from the local market where the study was carried out. Yeast (Saccharomyces cerevisiae) was a commercial yeast namely Le Saffre^® from PT. Saf Indonusa, Indonesia. All chemicals and solvent used were of analytical grades.

Experimental Design

RSM with Box-Behnken design was used to analyze the interaction effect between the variable of fermentation of coconut milk. The Minitab 17^® trial version software (Minitab Inc. USA) was used for design and regression analysis of the experimental data. The experimental design was carried out by three independent parameters with three levels (-1, 0, +1) as shown in Table 1. The independent parameters were as follows: stirring speed (rpm), inoculum concentration (% w/v), and fermentation time (h). The response (dependent parameter) was oil recovery (%). A Box-Behnken design and three replications at the center point (leading to a total number of 15 experiments) were employed for optimization of fermentation condition. The experimental data were analyzed by RSM to fit the second-order polynomial equations [22].

Fermentation of Coconut Milk

The endosperm of mature coconut was made into a viscous slurry and squeezed through cheese cloth to obtain fresh coconut milk. Fresh coconut milk was added to distilled water with the ratio of 1:1 and then it was extracted for 30 minutes in a separation funnel to produce two layers. The bottom layer was water (skimmed), and the upper layer was coconut milk. Both layers were then separated. In the coconut oil, the acetate acid was added to increase pH 4. Then, the coconut oil was stirred at 100-300 rpm for 20 minutes. At the time of stirring, the S. cerevisiae 0.1-0.3% (w/v) was added. The mixture was then left to stand for 8-24 h at room temperature. As the layers of oil and water became separated, the upper oil layer was directly decanted. The acquired oil was prepared in duplicate and kept refrigerated until further use. This procedure was modified from the method of Prapun et al. [4] and Mansor et al. [10].

Oil Recovery

The determination of oil recovery was calculated according to the initial oil content in the coconut milk to the oil extracted [10]. The official AOAC Soxhlet method [23] and Gerber method using Gerber butyrometer [24] were applied to ascertain the oil content in the coconut milk. The oil recovery was determined by the following equation [4,10].

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Fatty Acids Analysis

Fatty acid composition in VCO was analyzed by Gas Chromatography instrument (HP6890) equipped with a flame ionization detector (FID) and a high-temperature 190-200^oC, flow rate 1.0 cm/s, fused silica capillary column (3 m length), and volume of sample injection was 4 (four) μL [5]. Fatty acids were identified by comparing their retentions times with those of individually purified standards.

Statistical Analysis

The experimental data in Table 1 were analyzed by response surface regression procedures of Minitab 17^® trial version software to fit the following second-order polynomial equation of the form:

where Y = oil recovery (%) ; X₁= stirring speed (rpm); X₂= inoculum concentration (% w/v); X₃= fermentation time (h); b₀ = intercept (constant); b_i = linear coefficient; b_ii = quadratic coefficients; b_ij =cross product coefficient [20]. The regression analysis, statistical significance and response surfaces were done using Minitab 17^® trial version software package.

Results and Discussion

The production of VCO from coconut milk using S. cerevisiae was performed. These microbes are expected to separate the layers of fermented in short time. During the fermentation process, S. cerevisiae would produce the enzymes protease and lipase, which would break down the protein molecules surrounding the oil in coconut milk [3,10]. In this period the oil phase would be separated to the liquid phase.

Optimization of VCO Production by Regression Analysis

Acquisition of coconut oil through a fermentation process is generally low [14]. Hence, it is important to improve the acquisition by studying the relationship between the parameters, in which significantly influence the fermentation process.

In the present study, the levels of parameters (stirring speed, inoculum concentration and fermentation time) and the effect of interaction on fermentation process are determined by the Box-Behnken design of RSM. Table 1 shows the independent parameters, levels, and factorial design in term of coded and actual and the experimental values as well. Out of total 15 experiments, the treatment number 12 (stirring speed 200 rpm, inoculum concentration 0.3% (w/v), and fermentation time 24 h) provides the greatest yield (92.73%). Whereas the treatment number 5 (stirring speed 100 rpm, inoculum concentration 0.2% (w/v), and fermentation time eight h gives the lowest yield (30.58%).

Table 1: The independent variables, levels, and factorial design in term of coded and actual, together with the experimental values

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