Quality Assessment of Biscuits Made from Blend of Wheat and Baobab Leaf Powder
Adegbola
O Dauda*, Rowland M.O Kayode, Khadijat O Salami
Department of Home
Economics and Food Science, University of Ilorin, Kwara State
*Corresponding author: Adegbola O Dauda, Department of Home
Economics and Food Science, University of Ilorin, P.M.B. 1515, Tanke Road,
Ilorin, Kwara State. Tel: +2347086382585; Email: adegboladauda@yahoo.com
Biscuit is a nutritive snack produced from
unpalatable batter transformed into appetizing product by oven heat. Wheat
flour, the major raw material for biscuit production, is deficient in lysine,
an essential amino acid. Baobab leaf is rich nutritionally and high in
antioxidant properties. Baobab leaf flower was blended with wheat flour to
produce biscuits rich in nutrients. Wheat and Baobab flours were respectively
blended thus: A (100:0); B (98:2); C (96:4); D (94:6); E (92:8); F (90:10), and
mixed with other ingredients for production at 175-180oC for 15-20 minutes,
cooled and packaged. The functional properties of the flour, proximate
composition, colour, microbial and sensory evaluation were determined using
standard methods. Result showed baobab leaf flour to be highly functional,
while the Protein, Moisture-Content, Ash, Crude-Fat, Crude-Fibre and
Carbohydrate respectively ranged thus:(10.50-12.11%), (2.51-3.28%),
(1.38-2.96%), (10.31-12.27%), (1.07-2.16%), and (67.99-73.46%). Addition of
baobab leaf flour at 10% levels lightly affected the biscuit colour, but the
microbial load of the samples with baobab leaf flour was low probably due to
the antiviral and antibacterial properties of the leaf. The sensory panelists
accepted the samples with baobab leaf flour. Incorporating baobab leaf flour
into biscuits production improved nutritional content, quality and prevent
malnutrition among consumers.
1. Introduction
Biscuit, as it is known in the United Kingdom, but more
generally referred to as “cookies” in USA, is regarded as a confection-food
with low moisture content [1]. They are nutritive snacks obtained from single
or composite dough, which has been transformed into digestible and more
appetizing products through the action of heat in the oven [2]. Bakery products
are fast foods loved by every age-group for their ease of transportation,
taste, cholesterol-free, containing digestive and dietary principles of vital
importance, low cost and more convenient with longer shelf-life [3, 4]. It
should be noted that nutrient improvement to biscuits is not the sole thing,
but shelf life extension could also work on [5]. They are normally classified
based on ingredient composition and processing techniques [1]. Wheat flour,
because of its high gluten protein, is the basic ingredient for biscuit
production [6]. Gluten protein forms elastic dough during baking and gives high
organoleptic quality to products [7]. Whole grain generally is rich in macro
and micronutrients than refined ones, which has mostly starch [8]. High energy
and gluten in wheat flour combines strength and elasticity in the production of
floury products with desirable texture and flavour [9]. African baobab (AdansoniadigitataL.,
Malvaceae) is an important indigenous fruit tree species for food security,
nutrition and income generation by the rural populace in Africa [10]. The
edible parts of baobab (leaves, seeds, and fruit pulp) are consumed mostly by
rural communities who also sell them in local markets, while the non-food parts
(timber, fodder, and fibers) are mainly used for income generation in sub-Saharan
Africa [11]. A. digitata originated in Madagascar, but was
introduced to the rest of African countries by long distance dispersal [12],
and in Nigeria, it is found in all the ecological zones, as it is widely
distributed in the arid, semi-arid zones and savannah regions; the north west
and east regions, where it is called Kuka tree [13, 14]. In the southern part
of Nigeria, the Yorubas called it Osetree, Nupe (Muchi), Edo (Usi) [13]. The
tree which is normally used in parkland agro-forestry system in Nigeria grows
undistributed and survives until their natural death.
Large numbers of people suffer from hidden hunger, a condition
caused not by lack of sufficient food, but lack of essential nutrients. Hidden
hunger is defined as a nutritional deficiency caused by the lack of balance in
an otherwise full die t [15]. People who suffer from hidden hunger are
receiving enough calories, but lack micronutrients, which sustain life, and
baobab leaves are rich in several minerals; such as calcium, iron, potassium,
magnesium, to name a few among which calcium and iron are found to be
predominant, as well as vitamins and superior to that of fruit of the tree
[16]. Most families in the rural areas use either the fresh and/or dried leaves
as food to supply essential nutrients [17], and when compared to fruits, the
leaves contain more essential amino acids, minerals and vitamin A. [18] who
worked on the antiviral activity of A. digitata leaves by
extracting with them with water, dimethyl sulfoxide and methanol
reported that the leaf extract exhibited a promising activity against influenza
virus and herpes simplex virus. As a result of the numerous benefits and
qualities of A. digitata, this research work, apart from preventing
its extinction, tended to increase its utilization by eliminating micronutrient
deficiencies among young children in particular by incorporation into products
such asbiscuit.
2. Materials and Methods
2.1. Materials
The wheat flour used for the research work was purchased at
Tanke area, Ilorin, Kwara State, while fresh baobab leaves was sourced from the
teak plantation, University of Ilorin permanent site. Other ingredients used
were equally sourced from Tanke area, Ilorin, Kwara State. The Oven, milling
machine, stirrer, chopping board, rolling pin, weighing balance were sourced
from the laboratory.
2.1.1. Preparation of Baobab Leaf Flour and Blends
Fresh baobab leaves harvested were carefully rinsed with water
to remove dust, drained and oven dried at 50oC and milled into
flour. The wheat flour was blended with 2% to 10% baobab leaf flour and labeled
as samples A, B, C, D, E and F respectively, with sample Aserving as the
control sample (Table 1).
2.1.2. Biscuit Formulation and Production
The method of [19] was adopted for the biscuit production (Figure
1). The recipe for the biscuit include 200 grammes composite flour, 3 teaspoon
of milk, 60 grammes margarine, 0.2 grammes salt, 80 grammes sugar, 2 medium
sized eggs and 2 grammes baking powder etc.
2.1.3. Proximate Composition Flour and Biscuit
Samples
The proximate composition of the flour and biscuit samples was determined
by the method of American Association of Cereal Chemists [20] with number
44.15A.
2.1.4. Functional Properties of Flour samples
Water and oil absorption capacities, bulk density and
dispersibility were determined by the methods of [21, 22] respectively.
2.1.5. Sensory Analysis of Biscuit Samples
The taste, appearance, texture, aroma and overall acceptability
of the biscuit samples were assessed by a 50-member panelist (untrained but
regular consumers of biscuits). They were properly instructed in both written
and verbal formats as described by [23]. Each panelist compares the six samples
using a nine 9-point hedonic scale with 9 representing-like extremely, and 1
representing dislike extremely.
2.1.6. Colour Determination
The flour colour was measured with a Minolta CR-310 (Minolta
camera Co. Ltd, Osaka, Japan) tristimulus colorimeter, recording L, “a” and “b”
values. L represented lightness (with 0=blackness,100= brightness); a,
corresponds to the extent of green colour (from negative= green to positive =
redness); b represents blue from negative=blue to positive=yellow. The
colorimeter was calibrated against a standard white reference tile. Samples
were placed in clear glass Petri dish (10 replicates), and measurements done in
triplicate.
2.1.7. Mineral Analysis of Biscuit Samples
Digestion and determination of Biscuit Samples for Mineral
Analysis. Two-grammes each of the biscuit samples were weighed into a
125ml Erlenmeyer flask earlier washed with acid and distilled water. About 4ml
perchloric acid, 25ml of conc. HNO3 and 2ml conc. H2S04 were added under a fume hood. The contents
were mixed and heated gently at low heat on a hot plate until dense white fumes
appeared, heated strongly for another 30 seconds and cooled. About 40-50ml
distilled water was added and the solution boiled for 30 seconds on the same
plate at medium heat. The solution that emerged was cooled and filtered
completely into a 100ml Pyrex volumetric flask before making-up to mark with
distilled water and later filtered with Whatman No 42 filter paper (9cm) [24]. Selected
minerals were determined with “Buck scientific Atomic Absorption
Spectrophotometer Model 210A”. Standard solutions with optimum range for each
element were prepared and strictly followed.
2.1.8. Microbiological Analysis of Biscuit Samples
The microbial (bacteria and fungi) counts of the biscuit samples
were determined by the compendium of methods for the microbiological
examination of foods [25].
2.1.9. Statistical Analysis of Biscuit Samples
The sensory evaluation data was statistically analysed using the
analysis of variance (ANOVA) and the Duncan Multiple range test with
significance level at p<0.05 [7].
3. Results and Discussion
The functional properties of the flour samples are as shown in
Table 2. According to [26], functional property of food is the physic-chemical
property/characteristic of the food component, which determines their
usefulness and success. The Water Absorption Capacity (WAC) of baobab and wheat
flour was 48.11% and 14.91% respectively. The WAC of baobab leaf flour was
higher than that of wheat flour, and could be due to the high protein and
mucilage contents reported in baobab leaf flour [27]. This was reflected in the
dough formation with increasing proportion of baobab leaf flour given hardness
to the dough. According to [28], it was stated that WAC enables bakers to
quantify the quantity of water added to dough in order to improve its handling
characteristics and freshness of the baked products. WAC is the maximum water
added to food material to retain formulation condition or relates to dryness
and porosity of the material [29]. It could also be the ability of protein in a
product to associate and retain water, thus increasing the water absorption and
protein content [28]. The Oil Absorption Capacity (OAC) of the baobab leaf and
wheat flour was 19.50% and 10.95% respectively. Good OAC of flour in baking
improves handling characteristics of products [30], and equally improves
biscuit quality by contributing to the soft texture [31].
The Bulk Density (BD) of baobab leaf and wheat flour was
2.08g/cm3 and 0.89g/cm3 respectively. The particle size and density of the flour
generally affect the BD and important in determining the packaging requirement,
raw material handling and application in wet processing in the food industry
[32]. The lower the BD, the higher the amount of flour particles that can bind
together leading to higher energy values [33]. Low BD of the flours was
reported to be useful for food formulation, and such products tended to have
less retrogradation. It also measures the heaviness of a flour sample [34].
Dispersibility of baobab leaf and wheat flour was 3.48% and 1.34% respectively.
In Table 3, the proximate composition of the flour sample baobab
leaf to be rich in protein (13.75%), crude lipids (6.45%) and ash content
(7.73%). The high mineral content recorded made it suitable for combating
micronutrient deficiency. The crude fibre was 3.68% and was known to reduce the
risk of some prevalent diseases like obesity, diabetes, high blood cholesterol,
cardiovascular disease, and numerous gastrointestinal disorders [35]. Lowered
blood cholesterol level helps slows the process of absorption of glucose and
its control. It also ensures smooth bowel movements, which helps in the ease of
flushing out of waste products from the body, increasing satiety and hence
impacts some degree of weight management. The protein content was similar to
that reported by [36, 37] (between 13-15 %), and that of [17] for protein,
carbohydrate and crude lipids; 13-15%, 60-70% and 4-10% respectively.
In Table 4, significant differences were recorded for the
proximate composition of the biscuit samples. The protein, ash, fat, fibre and
vitamins of the samples increased with increasing addition of baobab leaf flour
except for moisture and carbohydrate. The decrease in the moisture content of
the biscuits with increasing proportion of baobab leaf flour may be due to the
higher oil and water absorption capacities of baobab leaf flour. The ash content
of the biscuit samples varied from 1.38 to 3.31%, with the control sample
having the least value. Higher ash contents depicted higher mineral content.
From Table 5, mineral contents increased with increasing
quantities of added baobab leaf. Sample F had the highest mineral content,
though not significantly different, but the value of zinc and iron was the most
abundant in the samples. Highest value of iron (0.58mg/g) was recorded in
sample F, showing the rich mineral contents of baobab leaf.
The L*, a*, b* values of the biscuit samples are shown in Table
6. Statistically, there were significant differences between the mean values of
the colour measurements (at p≤ 0.05). Lightness (L* values) for the samples was
in the range of 46.54 to 55.94. L* value (lightness) decreased with increasing
content of baobab leaf flour. The a* values were between -2.41 and 2.25. Though
samples A and B had positive values, the biscuit appears greenish with
increasing addition of baobab leaf flour. However, the a* values of sample F
and A were 2.25 and -1.36 respectively. In terms of the degree of yellowness
(b*), incorporation of baobab leaf flour to wheat flour decreased the
yellowness.
The bacterial and fungal loads of the samples stored for 8 weeks
at ambient temperature are shown in Tables 7,8. There was an increase in the
total plate counts. The bacterial count of 18×102CFU (Colony forming unit) per gram and fungal count of 3×101CFU per gram were the highest over the period. These values may
be due to increase in moisture content of the biscuit leading to increase in
its water activity, which may have favoured microbial growth. Of all the
samples, control sample (A) had higher load for both bacteria and fungi. Low
values recorded for the samples with baobab leaf flour may be due to antiviral
and antibacterial properties of the baobab leaf. Ray & Bhunia 2007 [38]
reported a maximum bacteria (aerobic) count of 5.30 X 104cfu/g and 5.0 X 103cfu/g for cookie
sample. The results obtained even after six weeks was lower than that recorded
by Ray & Bhunia (2007) [38] for cookie, hence, better shelf life.
The sensory evaluation carried out on the samples (Table 9)
showed significant differences (at p<0.05) among the samples. Sample A had
the highest score (7.98) for appearance, while sample F had the lowest score
(4.54). The appearance, which was visual, revealed that the panelists showed
preference for the light colour of sample A. The browning appearance of the
biscuit could have been due to Maillard-type reactions [8], a reaction between
reducing sugars, proteins and amino acids or caramelization, severe heating
during processing [39]. The acceptance level of the biscuit appearance
decreased with increasing quantities of baobab leaf flour. It was reported by
[40] stated that when colour of a new product differs significantly from the
existing one, consumers see it as a sign of spoilage and sometimes reject them.
Appearance plays vital role in raw material’s suitability for baked goods,
provides information about the formulation and quality of the product [41].
The aroma of the biscuits ranged from 5.68 to 7.06. Addition of
baobab leaf flour increased the aroma. There was no significant difference
(p≤0.05) in aroma of the samples containing baobab leaf flour, but were
significant from the control sample. The results obtained showed that the
inclusion of baobab leaf flour had impact on aroma of the biscuits. It was
reported by [42] that flavour enhancement could contribute to non-enzymatic
browning reactions or development of new flavour complex molecules. Flavours
affect the senses of taste and smell and affect aroma [43]. The crunchiness of
the biscuits was liked slightly and was significant (p≤0.05) in all the
samples. Biscuit sample with 10% baobab leaf was rated higher in terms of
crunchiness. Inclusion of baobab leaf flour to the biscuit had varying effect
on the crunchiness. Crunchiness is a desired characteristic that makes
customers purchase any biscuit [44]. These attributes are perceived by sounds
or noises produced during mastication. A report by [45] showed crisp and crunch
demonstrates evidence of a crunchy sound. The disparity is that crispiness has
a higher pitch and louder than that from crunchiness [46].
The texture values ranged from 5.48 to 7.56, and there was
significant difference (p≤0.05) between the texture of the control and treated
samples. Product texture is an essential attribute in consumer’s examination
and buying judgment and [47] says texture is a "sensory expression for
product structure in terms of reaction to stress by the kinesthetic sense.
Samples A, B and Chad the best taste. Taste of foods is affected more by
formulation than processing, and biscuit taste is mainly affected by
composition than baking parameters [48]. The score for overall acceptability of
the biscuit samples varies between 8.08 (sample A) and 6.92 (sample F). The
least accepted of the samples was liked moderately (approximately 7.0). The
result was an indication that baobab leaf enriched biscuit samples were
accepted by the panelists. This result agrees with the report of [49] for
cookies enriched with 5% dried Moringa leaves.
4. Conclusion
The research work was able to reveal the improved nutritional
composition of the biscuit produced from the blends, that is, biscuits with
superior nutritional composition in terms of macro and micronutrients. The
macronutrients increased with increase in the addition of baobab leaf flour
except for carbohydrate and moisture contents that decreased. Inclusion of the
baobab leaf flour improves the crunchiness of the biscuit because of its fibre
content, though the colour depreciated slightly. Biscuit with baobab leaf flour
had higher WAC, OAC, BD and dispersibility, which rubbed on the nutritional
qualities, functional properties and enhanced consumers’ acceptability. With
the high macro and micro nutrients in the biscuit, it could be adopted in the
fight against children protein malnutrition through the snack eating by children,
most especially, in the third world countries. Addition of baobab leaf reduces
carbohydrate content and enhanced availability of desirable minerals, which was
safe for human consumption due to their low microbial content. As a result,
incorporating baobab leaf flour into biscuit production would improve
nutritional content, prevent malnutrition among children and reduce the cost of
production.
5. Conflict of Interest Statement
Figure 1: Flowchart for Production of Biscuits.Source: [19].
Composite Flour |
Wheat Flour(WF)
(%) |
Baobab LeafFlour
(BLF) (%) |
A |
100 |
0 |
B |
98 |
2 |
C |
96 |
4 |
D |
94 |
6 |
E |
92 |
8 |
F |
90 |
10 |
Table 1: Formulation of Wheat and Baobab Flour.
Samples |
WAC (%) |
OAC (%) |
Bulk density(g/cm3) |
Dispersibility(%) |
Baobableaf flour |
48.11a±1.80 |
19.50a±0.99 |
2.08a±0.08 |
3.48a±0.07 |
Wheat flour |
14.91b±0.09 |
10.95b±0.09 |
0.89b±0.01 |
1.34b±0.04 |
*Data are mean values of triplicate determination ±
standard deviation |
Table 2: Functional Properties of Wheat and Baobab Leaf Flour.
Samples |
Moisture (%) |
Ash (%) |
Carbohydrate (%) |
Total protein (%) |
Crude fibre (%) |
Crude lipids (%) |
leaf flour |
8.16±0.29b |
7.73±0.62a |
60.23±0.99b |
13.75±0.26a |
3.68±0.31a |
6.45±0.40a |
Wheat flour |
11.10±0.21a |
1.23±0.08b |
70.86±0.15a |
11.62±0.19b |
1.87±0.04b |
3.32±0.12b |
*Data are mean values of triplicate determination ±
standard deviation. |
Table 3: Proximate Composition of Wheat and Baobab Leaf Flour.
Samples |
Moisture (%) |
Ash (%) |
Carbohydrate (%) |
Total protein (%) |
Crude fibre (%) |
Crude lipids (%) |
A |
3.28±0.05a |
1.38±0.04f |
73.46±0.09a |
10.50±0.07e |
1.07±0.03f |
10.31±0.04f |
B |
3.10±0.05b |
1.56±0.06e |
72.76±0.16b |
10.73±0.04d |
1.23±0.07e |
10.52±0.03e |
C |
2.98±0.10b |
2.37±0.07d |
70.78±0.01c |
11.41±0.08c |
1.43±0.09d |
11.03±0.02d |
D |
2.69±0.03c |
2.65±0.06c |
69.97±0.13d |
11.44±0.11c |
1.760.05c |
11.49±0.09c |
E |
2.51±0.12d |
2.96±0.12b |
67.99±0.38e |
12.11±0.06b |
2.16±0.07b |
12.27±0.07b |
F |
2.39±0.15d |
3.31±0.72a |
66.92±0.28f |
12.33±0.04a |
2.43±0.05a |
12.60±0.05a |
*Data are mean values of triplicate determination ±
standard deviation. Mean value with different subscript in the same column
are significantly different (P<0.05). Legend as in Table 1. |
Table 4: Proximate Composition of Biscuit Samples.
Samples |
P(mg/g) |
Na(mg/g) |
Ca(mg/g) |
Mg(mg/g) |
Fe(mg/g) |
Zn(mg/g) |
||||
A |
0.012±0.0b |
0.005±0.0e |
0.12±0.0d |
0.12±0.0e |
0.27±0.0d |
0.02±0.0a |
||||
B |
0.012±0.0b |
0.008±0.0d |
0.15±0.0c |
0.16±0.0d |
0.31±0.0d |
0.021±0.0a |
||||
C |
0.012±0.0b |
0.010±0.0d |
0.15±0.0c |
0.17±0.0d |
0.39±0.0c |
0.023±0.0a |
||||
D |
0.016±0.0a |
0.014±0.0c |
0.18±0.0c |
0.19±0.0c |
0.46±0.01b |
0.024±0.0a |
||||
E |
0.017±0.0a |
0.017±0.0b |
0.22±0.0b |
0.30±0.0b |
0.54±0.0a |
0.025±0.0a |
||||
F |
0.017±0.0a |
0.20±0.0a |
0.25±0.0a |
0.33±0.0a |
0.58±0.0a |
0.028±0.0a |
||||
*Data are mean values of duplicate determination ±
standard deviation. Mean value with different subscript in the same column
are significantly different (P<0.05). Legend as in Table 1. |
Table 5: Mineral Composition of Biscuit Samples.
Samples |
L* |
a* |
b* |
A |
55.94±2.61a |
2.25±0.82a |
33.25±1.24a |
B |
52.29±3.01b |
0.79±0.24ab |
29.84±1.72b |
C |
49.49±1.20bc |
-0.61±1.31bc |
28.68±0.12bc |
D |
47.61±0.34c |
-2.41±0.35d |
26.76±0.29cd |
E |
48.33±1.49bc |
-0.91±0.57cd |
27.51±0.94cd |
F |
46.54±1.47c |
-1.39±1.43cd |
26.54±1.20d |
*Data are mean values of triplicate determination ±
standard deviation. Mean value with different subscript in the same column
are significantly different (P<0.05). Legend as in Table 1. |
Table 6: Result of Colour Determination of the Biscuit Samples.
Samples |
0 day |
2weeks |
4weeks |
6weeks |
8weeks |
A |
0.0±0.0a |
2.00±1.00b |
8.00±1.00a |
9.33±1.53a |
18.00±2.65a |
B |
0.33±0.58a |
2.33±0.58ab |
5.33±1.53bc |
8.33±0.58ab |
12.67±2.57ab |
C |
0.33±0.58a |
2.33±0.58ab |
5.00±1.00bc |
7.00±1.00b |
12.33±2.52b |
D |
0.33±0.58a |
2.33±0.58ab |
4.33±0.58c |
6.67±1.16b |
13.32±3.06ab |
E |
0.0±0.0a |
1.67±0.58b |
6.67±1.16ab |
8.00±1.00ab |
14.00±3.61ab |
F |
0.33±0.58a |
3.67±1.16b |
5.67±1.16bc |
8.67±1.16ab |
11.00±2.65b |
*Data are mean values of triplicate determination ±
standard deviation. Mean value with different subscript in the same column
are significantly different (P<0.05). Legend as in Table 1. |
Table 7: Bacteria Load of Biscuit Samples (cfu×102).
Samples |
0day |
2weeks |
4weeks |
6weeks |
8weeks |
A |
0.00±0.0 |
0.33±0.12a |
0.67±0.22a |
1.33±0.21a |
3.00±1.73a |
B |
0.00±0.0 |
0.30±0.28a |
0.33±0.58a |
1.33±0.21a |
1.67±0.31b |
C |
0.00±0.0 |
0.33±0.12a |
0.33±0.58a |
0.67±0.42ab |
1.33±0.33b |
D |
0.00±0.0 |
0.00±0.0a |
0.28±0.51a |
0.00±0.0b |
0.67±0.58b |
E |
0.00±0.0 |
0.33±0.12a |
0.00±0.0a |
0.67±0.42ab |
1.33±0.33b |
F |
0.00±0.0 |
0.00±0.0a |
0.33±0.58a |
0.33±0.58ab |
1.00±0.0b |
*Data are mean values of triplicate determination ±
standard deviation. Mean value with different subscript in the same column
are significantly different (P<0.05). Legend as in Table 1 |
Table 8: Fungi Load of Biscuit Samples (cfu×101).
Samples |
Appearance |
Aroma |
Crunchiness |
Texture |
Taste |
Overall
Acceptability |
A |
7.98±0.81a |
5.68±0.79b |
5.90±0.61c |
7.56±0.76a |
7.70±0.58a |
8.08±0.60a |
B |
7.74±0.80a |
7.00±0.81a |
6.56±0.58b |
7.22±0.65b |
7.58±0.50ab |
7.38±0.73b |
C |
6.24±0.87b |
7.02±0.62a |
6.84±0.84ab |
6.32±0.94c |
7.50±0.51ab |
7.22±0.42bc |
D |
5.46±0.76c |
7.06±0.91a |
6.90±1.30ab |
5.68±0.68d |
7.44±0.58b |
7.22±0.51bc |
E |
4.80±0.88d |
7.00±0.83a |
6.88±0.87ab |
5.76±0.89d |
7.42±0.58b |
7.06±0.59cd |
F |
4.54±0.86d |
6.98±0.59a |
7.06±0.84a |
5.48±0.89d |
7.34±0.56b |
6.92±0.60d |
Mean value with different subscript in the same column
are significantly different (P<0.05). Legend as in Table 1. |
Table 9: Sensory Evaluation of Biscuit Samples.
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