EGG-FREE LOW-FAT MAYONNAISE FROM VIRGIN COCONUT OIL
Рубрики: RESEARCH ARTICLE
Аннотация и ключевые слова
Аннотация (русский):
Introduction. Mayonnaise is a widely consumed product all over the world. Nowadays, the number of vegetarians, egg allergy cases, and heart diseases are increasing. This makes manufacturers develop alternatives. The research objective was to select the optimal concentration of emulsifiers for egg-free mayonnaise made from virgin coconut oil. Study objects and methods. We produced 20 egg-free mayonnaise samples with different amounts of emulsifiers. We also determined physicochemical properties of the samples, as well as performed proximate and statistical analyses. Results and discussion. The response surface methodology made it possible to define such parameters as viscosity, stability, and firmness as affected by the following concentrations: cashew nut protein isolates – 5–15%, xanthan gum – 0–1%, and modified starch – 0–0.5%. The optimal values of emulsifiers were obtained as follows: cashew nut protein isolates – 13 g, xanthan gum – 1.0 g, and modified starch – 0.4 g. The optimized mayonnaise had the following parameters: viscosity – 120.2 mPa·s, stability – 98.7%, and firmness – 25 g. The study revealed no significant differences (P > 0.05) between the actual and predicted data, which confirmed the efficiency of the suggested models. Conclusion. The obtained low-fat egg-free mayonnaise was relatively similar to the traditional commercial products. However, virgin coconut oil should be emulsified with a combination of cashew nut protein isolates, modified starch, and xanthan gum.

Ключевые слова:
Mayonnaise, emulsion, egg yolk, emulsifier, protein isolates, cashew nut, virgin coconut oil
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INTRODUCTION
Mayonnaise is an emulsion of oil in water. Therefore,
dietary mayonnaise has a smaller dispersed step
and larger water content [1–3]. Mayonnaise consists
of 60–80% fat [4]. Conventionally, it contains egg
yolk, oil, lemon juice or vinegar, and seasonings, e.g.
salt, mustard, paprika, sweeteners, etc. Three main
components in mayonnaise perform as different phases
in the formulation: oil is the dispersed phase, water is the
continuous phase, and egg yolk is the emulsifier [5, 6].
Mayonnaise is fat-free if its fat level is at least 50%
lower than that of standard mayonnaise; mayonnaise
is considered light if its fat level is 25% lower than
standard [7].
Eggs are a common mayonnaise emulsifier
because their emulsifying properties are perfect for
mayonnaise production. However, the growing rates
of vegetarianism, egg allergy, heart diseases, and
production costs make producers look for egg-free
formulation variants.
Furthermore, plant-based diets have gained
popularity not only due to the health benefits they
promise but as a way to reduce environmental
footprint [8]. Therefore, new egg substitutes and eggfree
products are of great importance in vegetarian
food supplies [9]. In general, protein acts as a surfactant
to reduce the surface tension between hydrophilic
and lipophilic materials in food systems and stabilize
emulsions. Cashew nut protein isolates can serve as
an egg alternative and a fat replacer agent due to their
excellent emulsifying property [10]. However, cashew
nuts are a much less popular plant protein, despite their
excellent sensory and nutritional benefits [11].
Copyright © 2022, Mohammed et al. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International
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Foods and Raw Materials, 2022, vol. 10, no. 1
E-ISSN 2310-9599
ISSN 2308-4057
77
Mohammed N. et al. Foods and Raw Materials, 2022, vol. 10, no. 1, pp. 76–85
Several studies have evaluated plant-based
emulsifiers as potential substitutes for eggs. Chetana
et al. reported egg-free mayonnaise of rice bran oil and
sesame oil produced by replacing egg with xanthan
gum [14]. Gaikwad et al. managed to replace
egg yolk with skim milk powder [15]. In another
study, wheat germ protein isolate and xanthan gum
substituted egg yolk to produce low-cholesterol
mayonnaise with acceptable characteristics [16].
Modified starch can also serve as an alternative
to fat and eggs in low-fat mayonnaise [17].
Among vegetable oils, coconut oil obtained from
coconut kernel (Cocos nucifera L.) was reported to have
antibacterial and antioxidant biological activities [18].
Virgin coconut oil is widely used in other vegetable oils
since it has many health benefits. Virgin coconut oil
decreases total cholesterol, triglycerides, phospholipids
and low-density lipoprotein (LDL) cholesterol, while
increasing high-density lipoprotein (HDL) cholesterol in
the blood [19].
Although many studies reported this or that kind of
egg-free mayonnaise produced from various oils and
emulsifiers, none of them featured the combination of
cashew nut protein isolates, xanthan gum, and modified
starch. Consequently, the current study aims at selecting
the optimal concentration of emulsifiers of cashew nut
protein isolates, xanthan gum, and modified starch to
produce egg-free virgin coconut oil mayonnaise and
compare its properties with commercial mayonnaise
products.
STUDY OBJECTS AND METHODS
Materials. Table 1 shows the ingredients of eggfree
Lady’s Choice mayonnaise (Bangi, Selangor) used
as a reference sample. Xanthan gum, cashew nut protein
isolates, and modified starch (maize) were purchased
from Sigma-Aldrich Co. (St. Louis, MO, USA).
Experimental design. The methods of response
surface methodology and central composite design were
used with three independent variables of emulsifiers,
namely cashew nut protein isolates (5–15%) (Xc),
xanthan gum (0–1%) (Xx), and modified starch (0–0.5%)
(Xm) (Table 2). Viscosity (Y1), stability (Y2), and firmness
(Y3) served as response variables.
Preparation of egg-free virgin coconut oil
mayonnaise. The low-fat and egg-free mayonnaise-like
emulsion gel was prepared according to Mozafari et al.
with some modifications [20]. Briefly, a fixed amount
of distilled water, lemon juice, mustard, sugar, acetic
acid, and salt (Table 1) were mixed in a blender 8010S
(Waring Commercial Torrington, USA), at medium
speed for 3 min to achieve a smooth and creamy coarsephase
emulsion. Virgin coconut oil was then gradually
added to the coarse-phase emulsion, followed by
emulsifiers, i.e. cashew nut protein isolates, modified
starch, and xanthan gum (Table 2). The mix (500 mL)
was further homogenized at high speed for 2 min until
smooth and creamy. All mayonnaise samples were
transferred into 500-mL sterilized glass jars, capped,
tightly sealed, and kept at room temperature (25 ± 2°C)
prior further analysis.
Physicochemical properties. Physicochemical
properties are given for the optimized formulation only.
Viscosity. The viscosity measurement followed
the method developed by Makeri et al. [21]. It involved
a rheometer HAAKE RheoStress RS600 (Thermo
Electron Corporation, Karlsruhe, Germany) and a
parallel stainless-steel plate with a 25-mm diameter
at a 1-mm distance at 25°C. A sample of 10 mL was
loaded onto the plate with extreme carefulness to
prevent emulsion softening. The excess sample was
carefully trimmed from the sensor edge with a thin
blade [22]. The flow characteristics were determined at
a temperature of 25°C and a shear rate of 1–100 s–1. Each
viscosity measurement was performed in triplicate, and
mean ± SD values were plotted.
Texture. The texture of the egg-free virgin coconut
oil mayonnaise was determined using a texture analyser
(XT2i, Surrey, UK) following the method described
in [23] with slight modifications. A total of 100 mg for
each sample was placed in round plastic containers at
a depth of 30 mm. The texture was determined using a
P/35-cylinder probe (Stable Micro System, Surrey, UK).
The force was measured in compression mode at fixed
75% strain at room temperature (25 ± 2°C). The test
conditions included 10 mm penetration, 1 mm/s pre-test
speed, as well as 1 and 10 mm/s test speed. The tests
were performed in triplicate, and the mean values were
tabulated.
Stability. The mayonnaise emulsion stability test was
based on the amount of oil removed from the emulsion
after centrifugation [24]. Briefly, 1.5 g of the sample
was placed in a 25-mL centrifuge tube (Refrigerated
centrifuge SIGMA 3-18K, Goettingen, Germany) and
weighed (initial weight, F0). The sample was heated
for 30 min at 80°C in a shaking water bath at 120 rpm
to form emulsion. After heating, the emulsions were
centrifuged in a Thermo Sorvall Legend Micro 17
micro-centrifuge (Thermo Science, Waltham, MA) for
Table 1 Formulation for egg-free virgin coconut oil
mayonnaise
Ingredients Amount
Distilled water, mL 32.20
Virgin coconut oil, mL 32.20
Lemon juice, mL 16.10
Mustard, g 3.35
Sugar, g 2.68
Acetic acid, mL 2.68
Salt, g 0.13 g
Cashew nut protein isolates, Xc, %* 5–15
Xanthan gum, Xx, %* 0–0.1
Modified starch, Xm, %* 0–0.5
* % varies according to formulations generated using response
surface methodology experimental design
78
Mohammed N. et al. Foods and Raw Materials, 2022, vol. 10, no. 1, pp. 76–85
5 min at 5000 rpm, and the top oil layer was extracted
with a long-needle syringe. The precipitated fraction
(F1) was weighed, and the stability of the emulsions was
estimated using the equation below:
Percentage of emulsion stability (%) = 𝐹𝐹1
𝐹𝐹0 × 100 Wet − weight percentage (%) = (𝐴𝐴−𝐵𝐵)
𝐴𝐴 × 100 Protein content ( g
100g) = Fat content (
g
100g
) =
𝑊𝑊1 − 𝑊𝑊2
𝑊𝑊1
× 100 Ash percentage (%) =
(a + b) − b
c
× 100
(1)
where F0 is the Initial weight; F1 is the weight of the
precipitated fraction.
Water activity. The water activity test followed
the calibration procedure. The sample cup was filled
halfway with 3 g of mayonnaise sample using an
AquaLab water activity meter (Model 3TE, Decagon
Devices, USA). The sample chamber lid was sealed to
reach vapor equilibrium. The dew point/temperature
was later translated into water activity (Aw) reading.
pH measurement. The pH values were assessed by
using a pH meter (S210 Seven compact, Mettler-Toledo
Instrument Co., Ltd., Shanghai, China) at 25°C. The pH
meter was adjusted at pH 7.01, 4.01, and 10.01 buffer
solutions. The pH values were presented as a mean of
three readings for one sample.
Proximate analysis. Moisture content. The
moisture content was determined using the method
developed by the Association of Official Analytical
Chemists (AOAC) [25]. A sample of 5 g was put into a
covered crucible and placed into a Memmert 800 oven
(Schwabach, Germany). There it stayed for at least 7 h
at 105°C; the temperature of the oven was constant.
The crucible and its cover were set on the balance and
weighed quickly and accurately. The weighing process
was repeated to obtain constant weight. The moisture
content was calculated based on the percentage of wetweight:
Percentage of emulsion stability (%) = 𝐹𝐹1
𝐹𝐹0 × 100 Wet − weight percentage (%) = (𝐴𝐴−𝐵𝐵)
𝐴𝐴 × 100 Protein content Fat content (
g
100g
) =
𝑊𝑊1 − 𝑊𝑊2
𝑊𝑊1
× 100 Ash percentage (%) =
(a + b) − c
(2)
where A is the weight of sample before oven drying, g; B
is the weight of dried sample after oven drying, g.
Protein content. This crude protein analysis method
was designed by AOAC: it is based on the nitrogen (N)
determination according to the Kjeldahl method in a
Kjeltec 2100 Distillation Unit (Foss Tecator, Hoganas,
Sweden) [25]. The protein content was calculated using
the following formula:
stability (%) = 𝐹𝐹1
𝐹𝐹0 × 100 Wet − weight percentage (%) = (𝐴𝐴−𝐵𝐵)
𝐴𝐴 × 100 Protein content ( g
100g) = Nitrogen content × 𝐹𝐹
Fat content (
g
100g
) =
𝑊𝑊1 − 𝑊𝑊2
𝑊𝑊1
× 100 Ash percentage (%) =
(a + b) − b
c
× 100
(3)
where F is the protein factor (6.25, depends on the
sample).
Fat content. The fat content was measured according
to another AOAC method by petroleum ether extraction
using a Soxtec System (2055 Soxtec Avanti; Foss
Tecator, Höganäs, Sweden) [25]. The fat content was
calculated by using the following formula:
Percentage of emulsion stability (%) = 𝐹𝐹1
𝐹𝐹0 × 100 Wet − weight percentage (%) = (𝐴𝐴−𝐵𝐵)
𝐴𝐴 × 100 Fat content (
g
100g
) =
𝑊𝑊1 − 𝑊𝑊2
𝑊𝑊1
× 100 Ash percentage Percentage of emulsion stability (%) = 𝐹𝐹1
𝐹𝐹0 × 100 Wet − weight percentage (%) = (𝐴𝐴−𝐵𝐵)
𝐴𝐴 × 100 Protein content Fat content (
g
100g
𝑊𝑊1 − 𝑊𝑊2
𝑊𝑊1
× 100 Ash percentage (%) =
(a + b) c
Percentage of emulsion stability (%) = 𝐹𝐹1
𝐹𝐹0 × 100 Wet − weight percentage (%) = (𝐴𝐴−𝐵𝐵)
𝐴𝐴 × 100 Protein Fat content (
g
100g
) =
𝑊𝑊1 − 𝑊𝑊2
𝑊𝑊1
× 100 Ash percentage (%) 10              (4) where W1 is the sample weight, g; W2 is the plain
aluminum weight, g; W3 is the aluminum with sample
weight, g.
Ash content. The ash content was measured
according to AOAC method: 10 g of the sample were
placed into the crucible [25]. After recording the weight,
it was put into a muffle furnace at 550°C. The sample
burned for at least 2 h to obtain permanent weight,
until no black particles. Next, the crucible and ash
were cooled in the desiccators. Finally, the crucible was
weighed together with the ash.
Percentage of emulsion stability (%) = 𝐹𝐹1
𝐹𝐹0 × 100 Wet − weight percentage (%) = (𝐴𝐴−𝐵𝐵)
𝐴𝐴 × 100 Protein content ( g
100g) = Nitrogen content × Fat content (
g
100g
) =
𝑊𝑊1 − 𝑊𝑊2
𝑊𝑊1
× 100 Ash percentage (%) =
(a + b) − b
c
× 100 ( 5 )
where a is the weight of ash; b is the weight of crucible;
c is the weight of sample.
Carbohydrates content. The carbohydrate content
was determined by extracting the protein, fat, moisture,
and ash amount from 100%.
Statistical analysis. Minitab 17.0 (Minitab, Inc,
State College Pennsylvania, USA) was used for
optimization. The software programmed a face-centered
composite design with three independent variables,
namely cashew nut protein isolates (Xc), xanthan gum
(Xx), and modified starch (Xm) at three coded levels (–1,
0, +1). The experiment involved six replicates at the
center stage, with a total design of 20 experimental runs
per sample. As a result, the effect of the two independent
variables on the response surface was obtained as 3-D
graphs of response. The polynomial regression model
equation was used to define the performance of the
response surface. The generalized response surface
model looked as follows:
Table 2 Response surface methodology experimental design
of the three independent variables in egg-free mayonnaise
formulations
Run
order
Block Cashew nut
protein isolate
Xanthan
gum
Modified
starch
(Xc) (Xx) (Xm)
1(c) 3 10(0) 0.5(0) 0.25(0)
2(c) 3 10(0) 0.5(0) 0.25(0)
3 3 15(1) 0.5(0) 0.25(0)
4 3 15(1) 1(1) 0.5(1)
5 3 5(–1) 0(–1) 0(–1)
6(c) 3 10(0) 0.5(0) 0.25(0)
7 3 5(–1) 0(–1) 0.5(1)
8 3 15(1) 1(1) 0(–1)
9(c) 1 10(0) 0.5(0) 0.25(0)
10 1 10(0) 0.5(0) 0.5(1)
11 1 10(0) 0.5(0) 0(–1)
12(c) 1 10(0) 0.5(0) 0.25(0)
13 1 5(–1) 1(1) 0.5(1)
14 1 15(1) 0(–1) 0.5(1)
15 2 10(0) 0(–1) 0.25(0)
16(c) 2 10(0) 0.5(0) 0.25(0)
17 2 5(–1) 1(1) 0(–1)
18 2 10(0 1(1) 0.25(0)
19 2 5(–1) 0.5(0) 0.25(0)
20 2 15 (1) 0(–1) 0(–1)
c is center point
79
Mohammed N. et al. Foods and Raw Materials, 2022, vol. 10, no. 1, pp. 76–85
y= ß0 + ß1x1 + ß2 x2 + ß11 x1
2 + ß22 x2
2 + ß12 x1 x2 (6)
where y is the response calculated by the model; ß0 is
the constant regression; ßi, ßii, ß1j are the linear, squared,
and interaction coefficients, respectively; x1, x2 are the
independent variables.
The responses were evaluated by multiple
regressions and the square least method. A t-test was
performed to compare the properties of both mayonnaise
samples.
To validate the model, the experimental data were
compared to the predicted values using the t-test at
P-value = 1 and F-ratio = 0 for each response. Therefore,
the model was declared suitable when no statistically
significant difference was observed between the
experimental and predicted values.
RESULTS AND DISCUSSION
Response surface methodology. The goal of
the optimization was to obtain target values for
responses, viscosity, and firmness, as well as to
maximize the stability of the emulsion. The initial
step was to decide on the experimental ranges for the
independent variables. The levels of variation were
selected according to a preliminary study. A uniform
precision type central-composite design consisted of
three variables, namely cashew nut protein isolates,
xanthan gum, and modified starch. It had a threelevel
pattern with 20 runs and was prepared using
the response surface methodology. The experimental
design contained six cube center points, where six out of
twenty runs were replications of the central points of all
the factors. Twenty samples of egg-free virgin coconut
oil mayonnaise were prepared based on the emulsifier
quantity proposed in the experimental design. Other
ingredients remained constant.
All twenty samples were measured for viscosity,
stability, and firmness. Table 3 displays the variables,
levels, and results obtained for all the responses.
The analysis of variance was used to determine the
significance of the linear, quadratic, and interaction
effects, as well as the lack of fit value against the
responses in the variables. The models fit well for all the
response variables because they had acceptable levels of
R2 of more than 80%.
Table 4 illustrates the summary of R2, %, P-value,
and multiple regression equation of response for reduced
regression equation model in the decoded units. The
best model was the one with the highest R2, lowest
P-value (model), and the highest number of significant
factors. The emulsifiers were optimized by identifying
the desired response. The anticipated responses were
designated based on the viscosity, stability, and firmness
of commercial mayonnaise. These properties are known
to be accepted by consumers. The reference mayonnaise
underwent an analysis to obtain the desired response.
The lack-of-fit in all the models had a P-value ≥ 0.05,
i.e. the models were acceptable. The next step involved
the P-value of individual factors of the quadratic and
interaction effect against response. The factors with
insignificant effects were removed to obtain a fitted
reduced model equation.
In this study, Xc, Xx, and Xm were coded values for
independent variables in the experiment, i.e. cashew
Table 3 Viscosity, stability, and firmness of egg-free virgin coconut oil mayonnaise produced with different percentages of cashew
nut protein isolate, xanthan gum, and modified starch
Run Order Cashew nut protein isolate Xanthan gum Modified starch Viscosity, mPa·s Stability, % Firmness, g
(Xc) (Xx) (Xm) (Yv) (Ys) (Yf)
1 10 0.5 0.3 104.2 ± 11.4 95.2 ± 2.2 24.6 ± 3.7
2 10 0.5 0.3 98.2 ± 4.9 89.3 ± 0.6 25.8 ± 1.6
3 15 0.5 0.3 101.6 ± 6.9 92.9 ± 1.0 22.3 ± 3.0
4 15 1 0.5 120.3 ± 22.8 100.0 ± 0.0 21.1 ± 2.0
5 5 0 0 47.8 ± 5.7 81.8 ± 0.7 9.2 ± 2.2
6 10 0.5 0.3 100.3 ± 15.6 93.9 ± 1.4 30.0 ± 2.0
7 5 0 0.5 88.2 ± 3.9 93.4 ± 1.8 17.3 ± 1.5
8 15 1 0 92.1 ± 3.6 96.4 ± 0.1 10.8 ± 1.4
9 10 0.5 0.3 106.8 ± 6.5 94.3 ± 0.9 22.3 ± 2.2
10 10 0.5 0.5 127.8 ± 19.4 95.8 ± 0.2 30.8 ± 3.1
11 10 0.5 0 84.0 ± 6.8 93.1 ± 1.6 17.5 ± 1.6
12 10 0.5 0.3 107.9 ± 9.0 93.9 ± 0.4 21.1 ± 1.8
13 5 1 0.5 122.8 ± 14.3 100.0 ± 0.0 16.6 ± 1.7
14 15 0 0.5 97.8 ± 4.8 94.2 ± 2.0 19.3 ± 5.1
15 10 0 0.3 72.8 ± 7.3 87.2 ± 1.3 19.4 ± 2.0
16 10 0.5 0.3 103.4 ± 14.4 94.9 ± 1.6 27.6 ± 2.7
17 5 1 0 93.4 ± 3.6 97.4 ± 1.2 6.7 ± 1.2
18 10 1 0.3 123.0 ± 6.5 95.2 ± 0.2 27.7 ± 1.8
19 5 0.5 0.3 98.1 ± 7.6 89.8 ± 3.1 18.0 ± 1.5
20 15 0 0 44.1 ± 3.1 79.2 ± 0.9 13.1 ± 2.1
80
Mohammed N. et al. Foods and Raw Materials, 2022, vol. 10, no. 1, pp. 76–85
nut protein isolates, xanthan gum and modified starch,
respectively. Likewise, Yv, Ys, and Yf were coded values
for viscosity, stability, and firmness dependent variables.
All the initial and reduced model multiple regression
equations used the code above.
Effect of independent variables on viscosity (Yv).
Viscosity measurement is essential to characterize the
structure and stability of the food emulsion products,
such as mayonnaise. Figure 1a shows that both the linear
and square effects were significant for viscosity, while
the overall model P-value was < 0.05 for both. The
interaction effect of cashew nut protein isolates with
xanthan gum and modified starch was not significant,
with a P-value of 0.472 and 0.372, respectively.
The analysis of regression coefficient showed that
viscosity experienced significant impact (P < 0.05)
from the linear effect of cashew nut protein isolates (Xc),
xanthan gum (Xx), modified starch (Xm), quadratic effect
cashew nut – cashew nut (Xc·Xc), xanthan gum – xanthan
gum (Xx·Xx), and interaction effect xanthan gum –
modified starch (Xx·Xm). The increased amount of these
Table 4 Summary of reduced model equation for all responses
Response R2, % P-value Reduced model equation
Viscosity, mPa·s 97.5 0.00 Yv = 22.76 + 5.64 Xc + 84.9 Xx + 96.48 Xm – 0.2760 Xc·Xc – 35.56 Xx·Xx – 36.5 Xg·Xm
Stability, % 88.7 0.00 Ys = 81.89 – 0.033 Xc + 15.74 Xx + 24.42 Xm – 20.40 Xx·Xm
Firmness, g 80.9 0.00 Yf = –21.18 + 7.74 Xc + 0.97 Xx + 19.10 Xm – 0.3683 Xc·Xc
80
5
10
100
120
1.0
0.5
0.0
15
Viscosity
XG
CN
80
100
5
10
120
0.2
0.0
15
0.4
Viscosity
MS
CN
50
75
100
0.0
0.5
125
0.4
0.2
0.0
1.0
Viscosity
MS
XG
Surface Plots of Viscosity
80
5
10
100
120
1.0
0.5
0.0
15
Viscosity
XG
CN
80
100
5
10
120
0.2
0.0
15
0.4
Viscosity
MS
CN
50
75
100
0.0
0.5
125
0.4
0.2
0.0
1.0
Viscosity
MS
XG
Surface Plots of Viscosity
80
100
5
10
120
1.0
0.5
0.0
15
Viscosity
XG
CN
80
100
5
10
120
0.2
0.0
15
0.4
Viscosity
MS
CN
50
75
100
0.0
0.5
125
0.4
0.2
0.0
1.0
Viscosity
MS
XG
Surface Plots of Viscosity
а
90
95
5
10
100
0.5
0.0
15
1.0
Stability
XG
CN
90
92
94
5
10
96
0.2
0.0
15
0.4
Stability
MS
CN
85
90
0.0
0.5
95
100
0.4
0.2
0.0
1.0
Stability
MS
XG
Surface Plots of Stability
90
95
5
10
100
0.5
0.0
15
1.0
Stability
XG
CN
90
92
94
5
10
96
0.2
0.0
15
0.4
Stability
MS
CN
85
90
0.0
0.5
95
100
0.4
0.2
0.0
1.0
Stability
MS
XG
Plots of Stability
90
95
5
10
100
0.5
0.0
15
1.0
Stability
XG
CN
90
92
94
5
96
Stability
85
90
0.0
0.5
95
100
0.4
0.2
0.0
1.0
Stability
MS
XG
Surface Plots of Stability
b
15
20
5 10
25
1.0
0.5
0.0
15
Firmness
XG
CN
10
20
5 10
30
0.4
0.2
0.0
15
Firmness
MS
CN
20
25
0.0 0.5
30
0.2
0.0
1.0
0.4
Firmness
MS
XG
Surface Plots of Firmness
15
20
5 10
25
1.0
0.5
0.0
15
Firmness
XG
CN
10
20
5 10
30
0.4
0.2
0.0
15
Firmness
MS
CN
20
25
0.0 0.5
30
0.2
0.0
0.4
Firmness
MS
Surface Plots of Firmness
15
20
5 10
25
1.0
0.5
0.0
15
Firmness
XG
CN
10
20
5 30
Firmness
20
25
0.0 0.5
30
0.2
0.0
1.0
0.4
Firmness
MS
XG
Surface Plots of Firmness
c
Figure 1 Surface plots of viscosity (a), solubility (b), and firmness (c) changes in low-fat egg-free mayonnaise by formulation
parameters
variables resulted in increased viscosity. The reduced
model equation for viscosity was predicted as below:
Yv = 22.76 + 5.64 Xc + 84.9 Xx + 96.48 Xm –
– 0.2760 Xc·Xc – 35.56 Xx·Xx – 36.5 Xx·Xm (7)
The equation above was fitted using a seconddegree
polynomial model for independent variable
effects of cashew nut protein isolates, xanthan gum,
and modified starch on apparent viscosity response. The
modified value (R2 = 97.5) proved that more than 97%
of the experimental points were adequate independent
variables.
The highest viscosity reading obtained was
127.8 ± 19.4 mPa·s, and the lowest was 44.1 ± 3.1 mPa·s.
Among all three factors, xanthan gum had the most
significant effect on viscosity. This finding was similar
to the results obtained by Mozafari et al., who found that
xanthan affected the viscosity of low-fat low-cholesterol
mayonnaise [20].
Also, Kumar et al. illustrated that xanthan gum
significantly impacted the viscosity of egg-free
81
Mohammed N. et al. Foods and Raw Materials, 2022, vol. 10, no. 1, pp. 76–85
mayonnaise produced by ultrasonication [26]. The
experimental outcomes and contour plots showed that
a larger amount of xanthan gum followed by modified
starch improved the viscosity of mayonnaise samples.
For standard oil, the viscosity and flow behavior in water
emulsion was captivated by the dispersed phase and
controlled by the hydrophilic additives, such as sugar,
salt, and polymeric thickener [27].
Effect of independent variables on stability (Ys).
Egg-free virgin coconut oil mayonnaise samples proved
moderate to high stability, depending on the emulsifier
used in the formulation. The linear effect of cashew nut
protein isolates (Xc), xanthan gum (Xx), modified starch
(Xm), and a combination of xanthan gum and modified
starch (Xx·Xm) had significant effects on the stability of
egg-free virgin coconut oil mayonnaise. The remaining
factors proved insignificant (P-value > 0.05) and were
removed. A reduced model equation for stability was
predicted as below:
YS = 81.89 – 0.033 Xc + 15.74 Xx +
+ 24.42 Xm – 20.40 Xx·Xm (8)
The stability of samples was 100% for formulations
4 and 13, which had the maximal amount of emulsifier.
This result was similar to the findings obtained by
Mozafari et al., who achieved a good stability of low-fat
low-cholesterol mayonnaise with the maximal amount
of xanthan gum and Zodo gum as emulsifiers [20]. In
this study, the formulations of egg-free virgin coconut
oil mayonnaise with xanthan gum and modified starch
had higher emulsion stability than the control samples.
Lee et al. reported similar findings in their study of lowfat
mayonnaise with gelatinized rice starch and xanthan
gum [24].
Two formulations demonstrated a much lower
stability, namely formulation 5 (cashew nut protein
isolates (Xc) – 5, Xanthan gum (Xx) – 0, Modified
starch (Xm) – 0) and formulation 20 (cashew nut protein
isolates (Xc) – 15, Xanthan gum (Xx) – 0, Modified starch
(Xm) – 0). The stability was 81.8 ± 0.7 and 79.2 ± 0.9%,
respectively.
Therefore, cashew nut protein isolates had an almost
negligible effect as natural emulsifiers on the stability
of the emulsion. In addition, the percentage of virgin
coconut oil used in this formulation was approximately
only 30–31%. This indicates that emulsion stability
was affected by the biopolymers used in the system.
According to Lee et al., a lower amount of oil resulted
in a significant decline in mayonnaise stability [24].
Therefore, such biopolymers as starches and gums
have to be combined with such fat-reduced formulation
products as stabilizers.
Effect of independent variables on firmness (Yf).
According to Khor et al., firmness is the product’s
ability to resist deformation or breaking and increases
with the force required for penetration [28]. Higher
firmness of emulsion makes it difficult for the mouth to
break the sample and swallow. The interactions between
proteins and oils in a network structure are known to
increase mayonnaise firmness [29].
Based on the P-value, all linear (Xc, Xx, and Xm) and
quadratic effects of cashew nut protein isolates (Xc·Xc)
had a significant impact (P < 0.05) on the firmness. The
best reduced model equation for predicting firmness was
as follows:
Yf = –21.18 + 7.74 Xc + 0.97 Xx +
+ 19.10 Xm – 0.3683 Xc·Xc (9)
In this study, fat content in egg-free virgin coconut
oil mayonnaise was 30%, which was lower than that
in whole fat mayonnaise (70%). Such reduction of fat
content caused a lower droplet density, which affected
the emulsion stability by weakening the interactions
between droplets. However, such lower oil content
increased the aqueous phase and decreased the dispersed
phase, which reduced the firmness and viscosity of the
emulsion [30]. Singla et al. reported similar findings: a
higher amount of xanthan gum with maltodextrin as
thickener increased firmness and stickiness values [31].
Response optimization and model validation. A
graphical optimization (Fig. 2) was performed using
Minitab 16 package to optimize the percentage of
Figure 2 Response optimization
Cur
High
0.89643 Low
D
Optimal
d = 0.98947
Targ: 120.0
Viscosit
y = 120.1579
d = 0.72917
Maximum
Stabilit
y = 98.6458
d = 0.99842
Targ: 25.0
Firmness
y = 24.9778
0.89643
Desirability
Composite
0.0
0.50
0.0
1.0
5.0
15.0
CN XG MS
[13.0266] [1.0] [0.3586]
Table 5 Optimal values of emulsifiers (factors) derived
through response surface methodology
Factor Optimized
value, g
Percentage in
formulation, %
Cashew nut protein isolates 13.0 12.6
Xanthan Gum 1.0 1.0
Modified Starch 0.4 0.4
82
Mohammed N. et al. Foods and Raw Materials, 2022, vol. 10, no. 1, pp. 76–85
emulsifier. The optimal values of emulsifiers were 13.0 g
for cashew nut protein isolates, 1.0 g for xanthan gum,
and 0.36 g for modified starch (Table 5). The desired
response required the highest amount of xanthan gum.
Table 6 illustrates the predicted optimal and
experimental values of response, viscosity, stability, and
firmness. Based on the two-sample t-test, the P-value
for all responses was > 0.05. Statistically, there was no
significant difference between the experimental and
predicted values. Thus, the model and the reduced model
equations were validated and accepted.
Proximate analysis and physicochemical
properties. Table 7 shows the proximate analysis and
physicochemical properties of the optimal formulation
of egg-free virgin coconut oil mayonnaise and reference
samples. They demonstrated a significant difference
(P < 0.05) in fat content, protein content, water activity,
and consistency. In the egg-free virgin coconut oil
mayonnaise, fat content, water activity, and consistency
were significantly lower, whereas the protein content
was higher compared to the reference product. However,
the comparative analysis showed no significant
difference in terms of viscosity, stability, firmness,
cohesiveness, pH, moisture content, ash content, and
carbohydrate content.
Singla et al. compared the firmness of the standard
and the egg-free mayonnaise samples, and the egg-free
mayonnaise showed a higher firmness [31]. However, the
high-fat content in the standard mayonnaise caused an
increment in textural firmness and stickiness by keeping
the neighboring oil droplets flocculated to form a thin
gel network.
In this study, thickeners enhanced the firmness
and stickiness values in the egg-free virgin coconut oil
mayonnaise compared with the egg-containing sample.
Generally, the texture of mayonnaise depends on the
ingredient selection and the effect of thickening agents
used in the system.
The pH of the egg-free virgin coconut oil
mayonnaise was acidic, and pH 4 was similar to that
of the reference mayonnaise. The acidic emulsion is
formed when adding lemon juice or vinegar. Acidic
state extends the shelf life of the product and ensures its
microbiological stability [28].
Based on [32, 33], mayonnaise producers favor
higher acidity because it improves the microbial
stability, emulsion stability, and viscoelasticity
properties. Moisture content is a significant factor as it
affects stability and shelf life. The moisture content in
the sample produced by applying the optimal conditions
was 34.7 ± 2.9%, while for the commercial sample it was
35.8 ± 4.3%, which indicated no significant differences.
This result could be due to the similar content of
solid materials used to formulate the egg-free virgin
coconut oil mayonnaise. The water activity of the eggfree
virgin coconut oil mayonnaise was significantly
lower compared to reference sample. Even though the
percentage of water was higher in this formulation, a
higher amount of emulsifier was expected to bind all
the molecules to obtain properties similar to standard
mayonnaise.
Ash content was 3.3 ± 0.5% for the egg-free
virgin coconut oil mayonnaise and 3.6 ± 1.1% for the
commercial sample. The differences between these
results might be due to the different ingredients applied
for the production.
The protein content of the egg-free virgin coconut
oil mayonnaise was 2.6 ± 0.2 g, which was higher than
the labeled value of commercial sample (1.4 g). This
is primarily because of the protein-based emulsifiers
used in the formulation. The carbohydrate content
of the egg-free virgin coconut oil mayonnaise was
14.0 ± 3.7 g, which was higher than in the labeled value
of commercial sample (9.2 g). This result also could be
due to the differences in the formulations.
The fat content of the egg-free virgin coconut oil
mayonnaise was 27.5 ± 3.6 g/100 g, whereas for the
reference mayonnaise it was 66.2 g/100 g. This result
was expected because the experimental low-fat eggless
mayonnaise contained 30% of fat, while the commercial
sample was a whole-fat mayonnaise. Standard
mayonnaise formulation includes 60–80% of fat,
depending on the composition and type of oil [33, 34].
Table 6 Predicted optimal value and experimental values
of response
Response Experimental
value
Predicted
value
P-value
Viscosity, mPa·s 102.4 120.2 0.1
Stability, % 99.5 98.7 0.1
Firmness, g 21.8 25.0 0.2
* P-values < 0.05 are significant differences using Tukey Method test
between experimental value and predicted value
Table 7 Proximate analysis and physicochemical properties
of optimal formulation of egg-free virgin coconut oil
mayonnaise and reference sample
Analysis Egg-free virgin
coconut oil
mayonnaise
Reference
mayonnaise
P-value
Viscosity, mPa·s 102.4 ± 4.1a 121.1 ± 16.0b 0.2
Stability, % 99.5 ± 0.3a 99.7 ± 0.2a 0.2
Firmness, g 21.8 ± 1.5a 25.3 ± 5.1a 0.3
Water activity 1.0 ± 0.0a 1.0 ± 0.0a 0.0
pH 4.0 ± 0.0a 4.0 ± 0.0b 0.2
Moisture content, % 34.7 ± 2.9a 35.8 ± 4.3a 1.0
Ash content, % 3.3 ± 0.5a 3.6 ± 1.1b 1.0
Protein content,
g/100 g
2.6 ± 0.2 1.4* 0.0
Carbohydrate
content, g/100 g
14.0 ± 3.7 9.2* 0.1
Fat content, g/100 g 27.5± 3.6 66.2* 0.0
*Values obtained from product nutritional information
83
Mohammed N. et al. Foods and Raw Materials, 2022, vol. 10, no. 1, pp. 76–85
Therefore, a lower amount of oil in the formulation
resulted in a lower fat content.
CONCLUSION
The research objective was to improve the
application of egg replacers in low-fat virgin coconut oil
mayonnaise using response surface methodology. The
optimal combination of three independent variables was
as follows: cashew nut protein isolates – 12.6%, xanthan
gum – 1.0%, and modified starch – 0.3%. We produced
a high-quality egg-free virgin coconut oil mayonnaise
with optimal viscosity, stability, and firmness. The
predicted response values under the defined optimal
levels were generally in accordance with the model. The
proximate analysis and physicochemical properties of
the egg-free virgin coconut oil mayonnaise had a lower
fat content, water activity, and consistency, as well as a
higher protein content compared to the reference sample.
Therefore, a mix of cashew nut protein isolates,
xanthan gum, and modified starch at optimal levels
could be used as a plant-based substitute to improve
the viscosity, texture characteristics, and stability of
mayonnaise. More investigations are required to assess
the sensory properties and storage stability of the eggfree
virgin coconut oil mayonnaise, which could be a
good product for vegan consumers.
CONTRIBUTION
Nameer Khairullah Mohammed performed the
experiments, drafted the manuscript, and proofread
the article. Hemala Ragavan developed the research
concept, performed the formal analysis, worked with the
software, and drafted the article. Nurul Hawa Ahmad
performed the data validation, wrote the review, and
edited the manuscript. Anis Shobirin Meor Hussin
supervised the project, developed the methodology, and
acquired the funding. The manuscript was checked and
approved by all the authors. All authors have read and
agreed to the published version of the manuscript.
CONFLICT OF INTEREST
The authors declare no conflict of interests regarding
the publication of this article.

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