Process Optimisation of Egg Replacer in Sponge Cake Baking

Process Optimisation of Egg Replacer in Sponge Cake Baking
Levan Mai a , Tom Norton b , Weili Li a , Brijesh Tiwari a , Charles Brennan a
a Department of Food, Manchester Metropolitan University, Hollings Faculty, Manchester, UK
b Department of Engineering, Harper-Adams University College, Shropshire, UK
INTRODUCTION
Heath risk associated with the consumption of eggs [1] and consumer preference for vegan diet
had lead researchers to investigate for egg replacers. The partial or total substitution of egg in
cake formulation appears interesting for people who suffer from cholesterol-diseases. The
replacement of egg in bakery products such as cake is a challenging task. Presence of egg
white proteins plays a significant role in foam formation by allowing the incorporation of large
volumes of air into the batter. Subsequent baking allows trapped air bubbles to expand leading
to an increase in the volume of cake after the coagulation of egg proteins during baking [2].
Response surface methodology has previously been used to optimise the processing variables
in partial or complete replacement of egg in cakes. For example, Arozarena et al., [3] employed
central composite design to investigate the effect of several ingredients on physicochemical
characteristics of lupine. The objective of this study was to optimise the baking process
parameters such as mixing time, baking time and temperature using Box-Benhken design.
MATERIALS & METHODS
Cakes were prepared using a standard recipe as outlined by AACC. Cakes samples were
analysed for texture, colour values (L*,a*,b*), specific volume, specific gravity, symmetry of
cake samples as per AACC. The effects of the three independent processing parameters on
quality parameters were investigated using Box-Behnken designs. The independent variables
were; X 1 (4 – 10 min), X 2 (160 – 200 o C) and X 3 (10 – 30 min). Experimental data from the
Box-Behnken design was analysed and fitted to a second-order polynomial model.
3
3
2
Y X X X X
[1]
0 i i
ii i
ij
i1
i1
i ji1
where Y is the predicted response, β 0 , β i , β ii and β ij are the intercept, linear, quadratic and cross
product coefficients. X i and X j are independent variables.
i
j
RESULTS & DISCUSSION
SG, texture, L*, a*, b* and Sym responses fluctuated between 0.74 to 0.64, 194.06 to 300.12,
50.03 to 77.30, 4.04 to 15.60, 16.86 to 33.64 and 0.15 to 1.80 respectively. The models
presented showed high regression coefficients (R 2 > 0.80) for SG and colour values (L*, a*,b*)
whereas low regression coefficients (R 2 = 0.47) laws observed for Sym of the cakes. The
predicted models were found to be significant with p values

a) b)
200
0.68
0.68
0.67
0.70
190
180
0.71
0.68
170
Baking temperature ( o C)
200
190
180
170
221
213
213
229
245
0.67
0.66
160
10
12
0.69
14
16
18
20
Figure 1. Contour plots showing the effect of baking temperature ( o C) and baking time (min) at mixing
time of 7 min on specific gravity (a), texture (b) of cakes.
160
10
12
205
14
16
221
18
237
20
Both linear and quadratic models were significant (p