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 American Journal of  
Food Science and Technology (AJFST)

Proximate Composition and Functional Properties of  Soyabeans (Glycine Max) Enriched 
Carbohydrate Diets

Otokpa Emmanuel Ihotu1*, Etim Esin Etim2

Volume 3 Issue 2, Year 2024
ISSN: 2834-0086 (Online)

DOI: https://doi.org/10.54536/ajfst.v3i2.3443
https://journals.e-palli.com/home/index.php/ajfst

Article Information ABSTRACT

Received: August 10, 2024

Accepted: September 04,  2024

Published: September 07,  2024

This study explored enhancing the nutritional value and functional properties of  
carbohydrate-rich diets by incorporating soybeans into millet, cassava, and yam. Soybeans, 
known for their high protein, unsaturated fats, and micronutrients, were used to fortify these 
staple foods. Proximate analysis assessed the macronutrient content of  both the original 
and soybean-enriched samples, while functional properties such as water and oil absorption 
capacities, swelling index, bulk density, and gelation capacity were evaluated. Results showed 
significant increases in protein content, particularly in the millet-soybean mixture (29.81%), 
with relatively low levels of  fat and ash. Functional assessments indicated millet’s highest 
gelation capacity and cassava’s superior water absorption. These findings suggest that 
soybean fortification can improve carbohydrate-rich diets’ nutritional quality and versatility. 
Further research is recommended to assess the impact of  these dietary modifications on 
human health and consumer acceptance. 

Keywords

Cassava, Functional Properties, 
Proximate Composition, 
Soybeans, Yam

1 Department of  Biotechnology, I.M. Sechenov First Moscow State Medical University, Moscow. Russia. 
2 Department of  Biochemistry, Joseph Sarwuan Tarka University, Makurdi, Benue State, Nigeria
* Corresponding author’s e-mail: otokpaemmanuelihotu@gmail.com

INTRODUCTION
Our diets are mostly composed of  foods high in 
carbohydrates, which account for more than half  of  
our daily caloric intake. This is in line with the DRIs’ 
recommendations, which indicate that 45–65% of  our 
calories come from carbohydrates (Marriott et al., 2020). 
This macronutrient is particularly crucial in economically 
disadvantaged populations, where carbohydrate-rich 
staples are often the most accessible food sources. 
While carbohydrates provide essential energy, the type 
of  carbohydrate consumed significantly impacts health 
outcomes. In recent decades, there has been growing 
concern over the excessive intake of  added sugars. The 
World Health Organization (WHO, 2015) and other 
health authorities have issued guidelines recommending 
a substantial reduction in free sugar consumption to 
mitigate the risks of  obesity, dental caries, and type 
2 diabetes. This has prompted a global shift towards 
healthier carbohydrate choices, emphasizing whole 
grains, legumes, and other minimally processed options. 
To address the dual challenges of  reducing sugar intake 
and promoting nutrient-rich diets, innovative food 
formulations are required. One promising approach 
involves fortifying carbohydrate-based foods with protein 
sources, such as soybeans. 
Soybeans contain isoflavones, proteins, carbohydrates, 
and lipids, and have been shown to significantly impact 
the management of  metabolic disorders like obesity and 
hyperglycemia (Chatterjee et al., 2018 and Basson et al., 
2021). Soy protein, which makes up 35-40% of  soybeans, 
is the only complete plant-based protein, providing 
all the essential amino acids found in animal proteins 
(Chatterjee et al., 2018). Additionally, soybean extracts 
have been associated with inhibiting key enzymes linked 

to type 2 diabetes and hypertension, as well as exhibiting 
anti-inflammatory and antioxidant properties (Ademiluyi 
and Oboh, 2013).
Millets are excellent sources of  micronutrients, especially 
iron and zinc, in addition to vitamins and other minerals 
(Dias-Martins et al., 2018; Kaur et al., 2014; United 
States Department of  Agriculture (USDA), 2016). 
They are affordable and readily available food crops 
that are attracting industry attention due to their natural 
antioxidants and other vital bioactive phytochemicals and 
minerals (Kaur et al., 2019). Cassava (Manihot esculenta) is 
widely acknowledged as one of  the most important tuber 
crops grown in tropical and subtropical areas, serving as 
a major food source for over 800 million people globally 
(McCallum et al., 2017). It is a staple ingredient in the 
diets of  many developing countries and was identified 
by the FAO in 2003 as Africa’s most vital root crop and 
a significant source of  nutritional calories (Nassar and 
Ortiz, 2007). Yam (Dioscorea spp.), prevalent in West 
Africa, Asia, and the Caribbean, is rich in carbohydrates, 
dietary fiber, vitamins, and essential minerals like 
potassium, manganese, and iron, and is associated with 
improved digestive health and blood sugar regulation 
(Bhandari & Kawabata, 2004).
Analyzing the proximate composition of  food 
components such as moisture, ash, protein, fat, fiber, 
and carbohydrates is vital for assessing their nutritional 
value and suitability for dietary needs. This analysis is 
particularly important for optimizing the use of  soybeans, 
millet, cassava, and yam in food formulations to ensure 
nutritional adequacy. Additionally, understanding the 
functional properties of  these foods, including water 
and oil absorption capacity, foaming capacity, and 
emulsification properties, is essential. These properties 



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Am. J. Food. Sci. Technol. 3(2) 53-59, 2024

affect the processing behavior and the texture, flavor, and 
overall acceptability of  food products.
This study aims to analyze the proximate composition 
and functional properties of  soybeans, millet, cassava, 
and yam, providing a comprehensive understanding of  
their nutritional profiles and potential applications in food 
systems. This information will be valuable for developing 
nutritionally balanced diets and enhancing the utilization 
of  these important food resources.

MATERIALS AND METHODS
Food Samples 
Soybeans, millet, cassava, and yam were sourced from 
North Bank Market in Makurdi, Benue State, Nigeria. 
Grains were washed with tap water and sun-dried. Milling 
was performed at the Food Science and Technology 
Laboratory of  the University of  Agriculture Makurdi, 
Benue State, Nigeria using a Brook Crompton Hammer 
mill (Huddersfield, England). The resulting flours were 
packed into polyethylene sacs and stored in airtight 
containers until further use.

Chemical Analysis
Proximate analysis was conducted to measure the 
moisture, protein, fat, fiber, ash, and carbohydrate content 
in all three flour samples (Table 1). The food samples 
were analyzed for moisture, protein, fat, ash, and crude 
fiber content using the methods specified in the AOAC 
(2012) publication. The total carbohydrate content was 
calculated by subtracting the combined percentages of  
fat, moisture, ash, crude fiber, and protein from 100.

Dry Matter Determination
An empty crucible was weighed, and 0.5-2 g of  the 
thoroughly mixed sample was transferred into the 
crucible. The crucible was then placed in a hot air oven 
and dried at 100°C for 2 hours. After drying, the crucible 
and sample were cooled in a desiccator, and the weight of  
the crucible with the dry sample was recorded.

Calculation
% DM = (W2-W1)/W  X 100 
where W2 = Weight of  the crucible and dry sample, W1 
= Weight of  the empty crucible, and W= Weight of  the 
sample/ 

Ash Determination
The weight of  an empty crucible was recorded. 0.5-2 g 
of  the thoroughly mixed sample was transferred into the 
crucible and placed in a furnace at 550°C for 3 hours. 
After ashing, the crucible and its contents were cooled in 
a desiccator, and the final weight was noted.

Calculation
% Ash = (W2-W1)/W  X 100
where W2 = Weight of  the crucible and ash, W1 = Weight 
of  the empty crucible, and W = Weight of  the sample. 

Fat and Oil Determination 
2 g of  the sample was weighed, placed in a filter paper, 
and then into an extraction thimble. The weight of  the 
receiver flask was recorded, and 200 ml of  petroleum 
ether was added. The apparatus was assembled and 
heated for 8 hours. After extraction, the solvent was 
evaporated from the flask. The flask containing the fat 
was dried at 100°C for 1 hour, cooled in a desiccator, 
and weighed.

Calculation
% DM = (W2-W1 )/W  X 100
where W2 = Weight of  the crucible and dry sample, W1 
= Weight of  the empty crucible, and W = Weight of  the 
sample

Crude Fiber Determination
2 g of  the fat/oil-free sample was weighed. The sample 
was boiled with 100 ml of  sulfuric acid solution for 30 
minutes, rinsed with boiling water, and then boiled with 
100 ml of  sodium hydroxide solution for another 30 
minutes. After rinsing, the residue was dried at 100°C 
for 24 hours, cooled, and weighed. The residue was then 
incinerated at 550°C for 3 hours, cooled, and reweighed.

Calculation
% Crude Fiber = (W2-W1)/W   X 100
where W2 = Weight of  the crucible and sample before 
ashing, W1 = Weight of  the crucible and ash, and W = 
Weight of  the sample. 

Nitrogen and Crude Protein Determination
0.5-2 g of  the sample was weighed and placed in a 
digestion flask. Copper sulfate (10 g) and sodium sulfate 
(50 ml) were added, followed by 25 ml of  concentrated 
sulfuric acid. The flask was heated until the mixture 
turned clear and light blue-green. After cooling, the 
mixture was diluted to 250 ml. A 10 ml aliquot was used 
for distillation. Sodium hydroxide (10 ml, 40%) was 
added, and the ammonia was distilled into 20 ml of  2% 
boric acid. The ammonia absorbed was titrated with 0.02 
M hydrochloric acid.

Calculation
% N2 = (14.02 ×Concentration of  acid ×Volume made 
×Titre ×100)/(10 ×1000 ×Sample weight)
where Crude protein = N2 x 6.25 (General factor), N2 x 
6.30 (milk), N2 x 5.70 (Flour), and N2 x 5.55 (Gelatin). 

Carbohydrate
The carbohydrate content was calculated by subtracting 
the percentages of  crude protein, fat/oil, ash, moisture, 
and crude fiber from 100%.

Calculation
% Carbohydrate = 100 - (Crude protein + Fat/Oil + Ash 
+ Moisture + Crude fiber)



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Am. J. Food. Sci. Technol. 3(2) 53-59, 2024

The food samples were mixed in a 70:30 ratio 
(carbohydrate to soybeans), and proximate analysis was 
performed to determine the moisture, protein, fat, fiber, 

ash, and carbohydrate content in all three flour samples, 
as shown in Table 2.

Table 1: Proximate composition of  flours on dry weight bases (g/100g)
Foods Components

Protein (%) Fat/Oil (%) Ash (%) Moisture (%) Crude Fiber (%) Carbohydrate (%)
Millet 7.00 3.80 1.28 9.71 1.82 76.39
Cassava 2.63 0.56 1.84 9.88 1.33 83.76
Yam 7.00 0.36 2.35 12.37 1.53 76.39

Table 2: Proximate composition of  flours mixed with Soya beans in the ratio of  70:30 on dry weight bases (g/100g)
Foods Components

Protein (%) Fat/Oil 
(%)

Ash (%) Moisture 
(%)

Crude Fiber 
(%)

Carbohydrate 
(%)

Millet 70% + Soybean 30% 29.81 7.99 2.43 12.98 8.66 38.13
Cassava 70% + Soybean 30% 19.38 7.87 1.75 12.72 5.96 52.32
Yam 70% + Soybean 30% 21.13 6.20 2.89 13.00 4.06 52.72

Functional Properties 
Functional Analysis was also performed to determine 
Bulk density, Gelation capacity, Swelling Index, Oil and 
Water absorption capacity. 

Bulk Density 
Was measured using the method described by Onwuka 
(2005). A 10 ml graduated cylinder was filled with the 
flour sample, tapped until no further settling occurred, 
and then weighed to determine the bulk density. Bulk 
density was expressed as:
Bulkdensity (g/ml)=(weight of  sample (g))/(volume of  
sample (ml))

Water and Oil Absorption Capacities
Were assessed following the procedure outlined by 
Onwuka (2005). For water absorption, 1 g of  flour was 
mixed with 10 ml of  distilled water, allowed to stand for 

30 minutes, and then centrifuged to measure the volume 
of  water absorbed. Oil absorption was determined using 
a similar method with olive oil.

Swelling Index 
was determined according to Alobo (2003) and Onwuka 
(2005). One gram of  flour was added to a 10 ml measuring 
cylinder, filled with water, and the volume change after 45 
minutes was recorded to calculate the swelling index. The 
ratio of  the initial volume to the final volume gave the 
swelling index.

Least Gelation Capacity 
was evaluated using the method described by Onwuka 
(2005). Flour suspensions at concentrations from 2% 
to 15% (W/V) were heated, cooled, and assessed for 
gelation by observing the lowest concentration at which 
the gel remained intact upon inversion of  the test tube.

Table 3: Functional analysis of  the various food samples
Foods Components

Swelling Index Bulk Density (g/mL) Oil Absorption 
Capacity (mL)

Water Absorption 
Capacity (mL)

Gelation 
Capacity (%)

Millet 1.33 0.65 1.70 2.3 10%
Cassava 1.25 0.53 1.70 2.5 6%
Yam 1.24 0.61 1.20 3.5 8%

RESULTS AND DISCUSSION
The proximate composition and functional properties 
of  the food samples reveal important insights into their 
nutritional content and potential applications in food 
processing.

Proximate Composition
From Figure 1, it is evident that the carbohydrate content 

is highest in Cassava (83.76%), followed by Millet and 
Yam, both with 76.39%. The inclusion of  Soya beans 
significantly alters the nutritional profile. For instance, the 
crude protein content increases drastically in all samples 
with the inclusion of  Soya beans, with Millet-Soya mixture 
showing the highest protein content (29.81%), followed 
by Yam-Soya (21.13%) and Cassava-Soya (19.38%). 
This indicates that Soya beans are an excellent source of  



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protein and can significantly enhance the protein content 
of  carbohydrate-rich foods. Additionally, the reduction in 
carbohydrate content when mixed with Soya beans can be 

beneficial in creating more balanced nutrient profiles in 
these foods.

Figure 1: Proximate composition of  flours on dry weight basis (g/100g) compared with proximate composition of  
flours mixed with Soya beans in the ratio of  70:30 on dry weight basis (g/100g)

Functional Properties
The data in Table 3 provides a comprehensive overview 
of  the functional properties of  Millet, Cassava, and 
Yam, which are further illustrated in Figures 2, 3, 4, 5, 
and 6 through bar charts. These functional properties 
are crucial for determining the usability of  these food 
samples in various food applications. The swelling index, 
bulk density, oil absorption capacity, and water absorption 
capacity are critical parameters that influence the texture, 

shelf-life, and consumer acceptability of  food products. 
Millet has the highest gelation capacity (10%), making 
it suitable for products requiring thickening. The food 
samples exhibit high water absorption capacity, indicating 
their potential use in products where moisture retention 
is important. The close range in swelling index and bulk 
density among the samples suggests they can be used 
interchangeably in various food applications depending 
on the desired texture and consistency.

Figure 2: Swelling Index for various food samples.



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Figure 3: Bulk Density for various food samples

Figure 4: Oil Absorption Capacity for various food samples. 

Figure 5: Water Absorption Capacity for various food samples. 



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Plant foods are generally processed before consumption, 
involving methods such as cooking (boiling, roasting, 
frying, steaming, baking, autoclaving), drying, mashing, 
grinding into flour, and fermentation. In this study, the 
test foods were primarily obtained from North Bank 
Market, Makurdi, Benue State, and processed by drying, 
milling into flour, sieving, and reconstituting to paste 
with hot water. These processes reduce particle sizes 
and retrograde starch to varying extents, potentially 
influencing their functional properties and nutritional 
benefits.
The nutritional responses in human subjects and animals 
for different foods and among the same group of  food 
may vary due to factors such as chemical composition, 
nature of  the carbohydrates, dietary fiber, method of  
food processing, and the presence of  substances acting 
as inhibitors of  enzymatic digestion (Tovar et al., 1992; 
Bjorck et al., 1994; Behall et al., 1999; Darabi et al., 2000; 
Thannoun and Al-Kubati, 2005a and 2005b).

CONCLUSION 
The proximate composition and functional properties 
assessment showed significant differences in the 
carbohydrate, protein, fat, and other nutrient contents 
when the food samples were mixed with Soya beans. 
These differences highlight the nutritional benefits of  
incorporating Soya beans into carbohydrate-rich foods, 
thereby enhancing their protein content and other 
nutritional qualities. The functional properties also 
indicate potential applications of  these food mixtures in 
various food products. Understanding these properties 
can guide food processing techniques and dietary 
planning, promoting healthier food choices.
Further research into the proximate composition and 
functional properties of  locally consumed foods is 
recommended to generate comprehensive data that can 

aid in dietary planning and food processing. Additional 
studies could help food manufacturers develop a broader 
range of  processed foods from African farm produce, 
utilizing the nutritional benefits of  Soya beans. The 
findings have significant implications in formulating 
rational dietary and therapeutic goals for diabetic 
patients and others with clinical conditions necessitating 
carbohydrate restriction. Moreover, such research can 
assist food manufacturers and processors in developing a 
greater range of  low-GI processed foods, enhancing the 
health profiles of  traditional diets and supporting public 
health objectives.

Acknowledgement
The Food Science and Technology Laboratory at the 
University of  Agriculture Makurdi, Benue State, Nigeria 
for their expertise in milling the samples using the Brook 
Crompton Hammer mill.

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