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 American Journal of  
Food Science and Technology (AJFST)

Optimization of  the Proximate Composition and Functional Properties of  a Composite 
Flour Formulated from Malted Sorghum, Sprouted Mung Bean and Date Fruit Using 

Response Surface Methodology
Ntukidem, Victor Edet1*, Edima-Nyah, Anne Peter1, Bello, Florence Abolaji2, Enidiok, Sunday Edet1

Volume 4 Issue 2, Year 2025
ISSN: 2834-0086 (Online)

DOI: https://doi.org/10.54536/ajfst.v4i2.5552
https://journals.e-palli.com/home/index.php/ajfst

Article Information ABSTRACT

Received: July 10, 2025

Accepted: August 11, 2025

Published: September 27, 2025

This study evaluated the effects of  varying proportions of  malted sorghum flour (MSF), 
sprouted mung bean flour (SMF), and date fruit powder (DFP) on the functional and 
nutritional properties of  composite flour blends. A D-optimal mixture design was used to 
generate fourteen formulations, varying MSF (60–80%), SMF (10–30%), and DFP (5–10%). 
The blends were assessed for functional attributes including bulk density, foaming capacity, 
wettability, gelatinization temperature, water and oil absorption capacities, and swelling 
capacity as well as proximate composition (moisture, protein, fat, ash, fiber, carbohydrate, 
and energy). Significant differences (p < 0.05) were observed across samples, reflecting 
the influence of  blend ratios on product characteristics. Increased levels of  SMF and 
DFP significantly improved nutritional quality and functional properties, including protein 
content, foaming ability, and fiber enrichment. Response surface plots revealed that higher 
proportions of  SMF and DFP enhanced most quality attributes. Regression models (linear 
to quartic) were statistically significant (p < 0.05) for the majority of  responses, though 
gelatinization temperature and water absorption capacity did not fit well. Model performance 
metrics including high R², adjusted R², predicted R², low lack-of-fit, and adequate precision 
validated model reliability. Numerical optimization using Response Surface Methodology 
(RSM) identified an optimal formulation of  69.93% MSF, 21.38% SMF, and 8.69% DFP, 
with a composite desirability of  0.620. The optimized blend demonstrated desirable shelf  
stability, nutritional density, and functional performance, making it suitable for health-
oriented foods such as snack bars and other bakery products. This research highlights the 
potential of  underutilized, climate-resilient crops in developing nutrient-rich, functional 
food systems for improved dietary diversity and food security.

Keywords

Date Fruit Powder, Malted 
Sorghum, Optimization, Snack 
Bars,Sprouted Mung Bean

1 Department of  Food Science and Technology, University of  Uyo, Uyo, Nigeria
2 Department of  Food Science and Technology, University of  Calabar, Calabar, Nigeria
* Corresponding author’s e-mail: vicksonybless@gmail.com

INTRODUCTION
The rising demand for health-promoting, sustainable, 
and gluten-free food products has intensified interest in 
nutrient-rich composite flours, which serve as versatile 
functional ingredients across various food systems. 
Composite flours, typically combining cereals, legumes, 
and fruits, offer a promising strategy to improve the 
nutritional, functional, and sensory properties of  food 
while promoting food security and dietary diversity 
especially in regions relying on underutilized crops (Ubbor 
& Akobundu, 2022; Ezeama et al., 2023; Edima-Nyah  et 
al., 2023; Ntukidem et al., 2025. Sorghum (Sorghum bicolor), 
a resilient, gluten-free cereal, is valued for its dietary fiber, 
phenolic content, and slowly digestible starch. Malting 
enhances its nutritional and functional attributes by 
increasing enzyme activity, reducing antinutritional factors, 
and improving starch gelatinization and fermentation 
potential (Agu et al., 2017; Musa et al., 2022). Mung 
bean (Vigna radiata), a protein-rich legume, gains further 
nutritional and functional benefits through sprouting, 
which improves vitamin content, bioavailability of  
nutrients, and reduces antinutrients. Sprouted mung bean 
flour also exhibits enhanced foaming, water absorption, 
and emulsifying capacities (Saini et al., 2021; Olagunju et 

al., 2023). Date fruit (Phoenix dactylifera) contributes natural 
sugars, fiber, minerals, and antioxidants. Its addition 
improves the energy value, taste, and consumer appeal of  
food products while promoting gut health and glycemic 
control (Al-Hooti et al., 2020; El Sohaimy & Hafez, 
2021; Khan et al., 2022). The combination of  malted 
sorghum, sprouted mung bean, and date fruit flours 
offers synergistic advantages enhancing protein, fiber, 
and functional properties like bulk density, absorption 
capacity, and emulsification. However, to achieve optimal 
formulation, a statistical approach such as Response 
Surface Methodology (RSM) is essential. RSM, through 
designs like D-optimal and Central Composite Design, 
enables the modeling of  complex interactions between 
ingredients while minimizing experimental runs (Myers 
et al., 2016; Adebo & Oyedeji, 2021; Ifesan et al., 2024). 
Therefore, this study aims to optimize the proximate and 
functional properties of  this composite flour using RSM, 
contributing to the development of  high-quality, gluten-
free functional food ingredients.

MATERIAL AND METHODS 
Source of  Raw Materials
Sorghum grains improved variety (KSV-15) was obtained 



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from the Seed Production Unit of  the Institute of  
Agricultural Research (I.A.R), Ahmadu Bello University, 
Samaru, Zaria, Kaduna State, Nigeria. Mung bean seeds 
were obtained, identified, and authenticated at the 
Department of  Agronomy, Michael Okpara University 
of  Agriculture, Umudike, Abia State, Nigeria, as Vigna 
radiata L. Wilczek species (NM 94 Variety). Dried Date 
Palm Fruit was purchased from Nassarawa Market, Mbak 
Itam III, Akwa Ibom State, Nigeria, and was identified 
and authenticated as Phoenix dactylifera L. species (Dabinoin 
Hausa Variety) under the Voucher Number: UUPH 
8(h) at University of  Uyo Pharmacy Herbarium. Baking 
ingredients were bought from Etaha Itam Market in Itu 
Local Government Area. Akwa Ibom State, Nigeria. All 
the reagents used throughout the study were of  analytical 
grade. 

Processing of  Malted Sorghum Flour
The method of  Bello et al. (2020) was used for malted 
sorghum flour production. Five (5) kg of  sorghum grains 
were sorted to remove foreign matter and soaked for 
12 h in portable water (w/v; 1:2). Soaked grains were 
drained and sprouted by spreading out on a covered 
jute bag in a germination box. Water was sprinkled on 
it daily until sprouting began. After 48 h of  sprouting, 
sprouted sorghum was in an oven (NAAFCO BS, OVH 
– 102, China) at 65˚C for 6 h, sprouts were removed by 
rubbing through palms. The dried malted sorghum was 
milled using a laboratory hammer mill (Cu – 600 Glufex 
Medicals and scientific, UK), and sieved through a 425 
µm mesh sieve, the flour was cooled and packaged in a 
polyethylene bag for further use.

Processing of  sprouted Mung Bean Flour
Sprouted mung bean flour was carried out using the 
method described by Offia-Olua and Akubuo, (2019). 
Three (3) kg of  mung bean seeds were sorted, cleaned, 
steeped in a portable water for 12 hours. The steeped 
beans were spread on a moistened muslin cloth and 
sprinkled with water daily while allowed to sprout for 

48 hours. The water sprinkled on the mung bean seeds 
contained a small amount of  sodium hypochlorite to 
destroy or discourage the growth of  microorganisms 
while the seeds were allowed to germinate at 30oC in the 
germination box. After 48 h of  sprouting, the sprouted 
seeds were kilned in an oven (NAAFCO BS, OVH – 102, 
China) at 650C for 4 h to terminate germination, sprouts 
were removed on palm by abrasion and winnowing. The 
dried malted mung bean seeds were milled using using 
hammer mill (Cu – 600 Glufex Medicals and scientific, 
UK), sieved through a sieve-shaker, cooled and packaged 
in an air-tight container for further use.

Processing of  Date Palm Fruit Powder 
Three (3) kg of  dried date fruits were cleaned, pitted and 
then cut in small pieces and dried in the oven (NAAFSCO 
BS, OVH – 102, China) at 650C for 4 h to obtain constant 
weight and then milled in a grinder (M-20, KA – Werke, 
GMBH and Co. KG, Staufen Germany) to obtain date 
powder. The date powder was packaged in an air-tight 
container for further use, as described by Oraby et al. (2021).

Experimental Design for the Preparation of  the 
Flour Blends 
D-optimal mixture design of  Response Surface 
Methodology (Design- Expert Software Version 
12.0.3.0., Stat- Ease Inc., Minneapolis, USA) was used 
for the formulation of  the flour blends from malted 
sorghum flour, sprouted mung bean flour and date fruit 
powder. The proportion of  each flour was expressed as 
a fraction of  the blend form to make the sum of  the 
component ratio as 100%. The independent variables 
and their constraints limits were malted sorghum flour 
(60 - 80%), sprouted mung bean flour (10 - 30%) and 
date fruit powder (5 - 10%). The responses were (physical 
properties - weight, diameter, thickness, width and spread 
ratio). The range obtained here were selected based on 
information obtained from literature and preliminary 
experiments. Table 1. shows the formulated mixture runs 
generated from the design.

Table 1: Composite Flour Formulation of  Malted Sorghum, Sprouted Mung Bean and Date Fruit Powder Blends 
using D-Optimal Mixture Design
Experimental 
runs

Samples Malted Sorghum 
flour (%)

Sprouted Mung bean 
flour (%)

Date fruit powder 
(%)

1 MSD 1 70.00 20.00 10.00
2. MSD 2 80.00 10.00 10.00
3 MSD 3 80.00 15.00 5.00
4 MSD 4 65.00 30.00 5.00
5 MSD 5 80.00 10.00 10.00
6 MSD 6 65.63 25.62 8.75
7 MSD 7 75.63 15.63 8.75
8 MSD 8 62.50 30.00 7.50
9 MSD 9 75.63 18.13 6.25
10 MSD 10 65.00 30.00 5.00



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11 MSD11 60.00 30.00 10.00
12 MSD 12 60.00 30.00 10.00
13 MSD13 80.00 15.00 5.00
14 MSD 14 72.50 22.50 5.00

MSD 1-14 = Malted Sorghum, Sprouted Mung Bean and Date Fruits

Functional properties determinations 
Bull density, foaming capacity, wettability, gelatinization 
temperature, water absorption capacity, oil absorption 
capacity and swelling capacity were performed following 
the methods of  AOAC, (2010). The experiment was done 
in triplicate.

Proximate composition determinations 
Moisture, ash, crude fiber, crude protein, crude fat was 
performed following the methods of  AOAC, (2010) 
carbohydrate calculated by difference. The experiment 
was done in triplicate.
Statistical Analysis 
Analysis of  data was performed using IBM SPSS (version 
23 software). One-way Analysis of  Variance (ANOVA) 
was used to determine significant (p<0.05) differences 
between means which were separated using New Duncan 
multiple range test (NDMRT) to perform multiple 
comparism between means at P < 0.05. All statistical 
analysis, mixture design, generation of  response surfaces, 
desirability functional analysis, and optimization were 
accomplished using Design-Expert (12.0.3.0) software 
(Stat-Ease, Minneapolis, United States) software, 
significant at p < 0.05. 

RESULTS AND DISCUSSION 
Effect of  Mixture Component On the functional 
properties of  flour blends from Malted Sorghum, 
Sprouted Mung Bean and Date Fruit 
Bulk density is an essential functional property in flour-
based food systems, influencing texture, packaging 
efficiency, and transportation costs. In this study, bulk 
density values of  the composite flour blends ranged from 
0.83 to 0.86 g/mL. The highest values (0.86 g/mL) were 
recorded in formulations such as MSD 2, MSD 4, MSD 
5, MSD 6, MSD 7, MSD 9, and MSD 14, all containing 
at least 65% malted sorghum flour (MSF). This suggests 
that MSF enhances bulk density due to its fine particle size 
and high starch content, which facilitate tighter packing. 
In contrast, MSD 8 had the lowest bulk density (0.83 g/
mL), attributed to its higher sprouted mung bean flour 
(SMF) content and lower MSF inclusion. Germination 
increases SMF porosity, reducing particle compaction. 
Additionally, the presence of  date fruit powder (DFP), 
though nutritionally beneficial, may reduce cohesiveness 
due to its hygroscopic nature. These observations align 
with findings that cereal-based flours tend to have greater 
compactness compared to legume or fruit-derived flours 
(Adebowale et al., 2020). The bulk density data fit well 
to a special quartic response surface model, which was 

statistically significant (F = 14.97, p < 0.05) and exhibited 
a high R² value (0.9599). However, the predicted R² 
(0.5025) was considerably lower than the adjusted R² 
(0.8958), suggesting the model may not generalize well 
to new data. Despite this, the low coefficient of  variation 
(0.3764%) and high adequate precision (11.96) support 
model reliability. A non-significant lack-of-fit (F = 
0.1215) further validated model adequacy. Among the 
components, DFP had the most substantial positive effect 
on bulk density (+1.98), followed by SMF (+0.8599) 
and MSF (+0.8451). Negative binary interactions and 
synergistic higher-order effects (e.g., A²BC, AB²C) were 
also observed. The 3D surface plot effectively visualized 
these interactions, aiding formulation optimization 
(Njapndounke et al., 2023).
Bulk density = + 0.8451A + 0.8599B + 1.98C-0.0506AB - 
1.44AC - 1.55BC + 4.57A²BC + 4.04AB²C - 11.50ABC²  
             ....(1)
Where, A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Foaming capacity is a vital functional attribute in 
flour blends, particularly for baked goods where air 
incorporation and gas retention are crucial for structure and 
texture. In this study, foaming capacity varied significantly 
among the formulations, ranging from 5.66% to 7.68% 
(p < 0.05). The highest values were observed in MSD 10, 
MSD 3, MSD 4, and MSD 13, which contained 15%–30% 
sprouted mung bean flour (SMF). The improved foaming 
in these samples is likely due to enzymatic hydrolysis of  
storage proteins during germination, which enhances 
protein solubility and surface activity two key factors in 
foam formation and stability (Saini et al., 2021; Olagunju 
et al., 2023). In contrast, lower foaming capacities were 
recorded in samples such as MSD 1, MSD 2, and MSD 5, 
each with malted sorghum flour (MSF) levels ≥70%. This 
can be attributed to the presence of  kafirins hydrophobic, 
tightly packed proteins in sorghum that are less effective 
at stabilizing foams (Musa et al., 2022). Although 
malting improves sorghum’s enzymatic activity, it has 
limited impact on enhancing foaming potential (Agu et 
al., 2017). While date fruit powder (DFP) contributes 
minimal protein, its presence may modify viscosity and 
dispersion characteristics, subtly supporting foaming in 
mixed systems. Statistical modeling using a special quartic 
response surface model confirmed a strong fit (F = 
16.75, p < 0.05), explaining 91.28% of  the variation in 
foaming capacity (R² = 0.9128). The adjusted R² (0.8583) 
and predicted R² (0.7281) were well-aligned, indicating 
strong model performance (Abasiekong et al., 2023; 
Anchang and Okafor, 2022). The model’s robustness was 



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further supported by a low coefficient of  variation (CV 
= 5.09%) and high adequate precision (10.53). However, 
a significant lack-of-fit (F = 34.82) suggests that higher-
order interactions were not fully captured (Elochukwu 
et al., 2019). Linear effects showed DFP (C) had the 
strongest positive influence (+34.91), while binary 
interactions (AB, AC, BC) were antagonistic. These 
relationships were clearly visualized in the 3D response 
surface plots (Njapndounke et al., 2023).
Foam capacity = + 5.91A + 5.85B + 34.91C - 1.89AB - 
29.26AC - 30.63BC            ....(2)
Where, A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Wettability is a crucial functional property that affects how 
quickly flour particles absorb water and disperse, directly 
influencing the preparation ease and consumer acceptance 
of  instant foods. In this study, wettability times ranged 
from 70.33 to 77.33 seconds, with significant differences 
among samples (p < 0.05). The shortest wetting times 
were observed in MSD 7, MSD 8, and MSD 10 (70.33 
s), which had higher levels of  sprouted mung bean flour 
(SMF ≥ 15%) and lower levels of  malted sorghum flour 
(MSF < 75%). The enhanced wettability in these samples 
is linked to the enzymatic modifications from sprouting, 
which increase flour porosity and hydrophilicity through 
the breakdown of  cell walls and proteins (Saini et al., 
2021; Olagunju et al., 2023). Conversely, samples MSD 
11 and MSD 12 both containing 10% date fruit powder 
(DFP) exhibited the longest wetting times (77.33 and 
75.66 s, respectively). This reduced wettability may be 
due to DFP’s high sugar and fiber content, which can 
create a sticky, hygroscopic surface layer that delays water 
absorption (El Sohaimy and Hafez, 2021). These results 
emphasize the importance of  ingredient balance in instant 
flour blends (Adebowale et al., 2020). The quadratic model 
fitted to the data was statistically significant (F = 24.00, p 
< 0.05), explaining 93.75% of  the variation in wettability 
(R² = 0.9375). The adjusted R² (0.8984) and predicted R² 
(0.8084) were closely aligned, indicating good predictive 
reliability (Anchang and Okafor, 2022; Abasiekong et 
al., 2023). The low coefficient of  variation (0.94%) and 
high adequate precision (13.99) further confirmed model 
precision. The non-significant lack-of-fit (F = 0.5740) 
supports its validity (Elochukwu et al., 2019). Coefficient 
estimates revealed that DFP (C) had the strongest 
positive effect on wettability (+207.59), followed by MSF 
(+76.41) and SMF (+72.14), though DFP interactions 
(AC, BC) negatively influenced rehydration—highlighting 
its dual role in water absorption.
Wettability = + 76.41A + 72.14B + 207.59C + 1.53AB - 
205.37AC - 180.12BC              ....(3)
Where A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Gelatinization temperature (GT) is a critical functional 
property reflecting the heat required for starch granules 
to absorb water, swell, and rupture key processes 
influencing texture, consistency, and processing behavior 
in flour-based products. In this study, GT values of  the 

composite flour blends ranged from 80.00°C to 84.66°C, 
with statistically significant differences observed across 
samples (p < 0.05). The highest GT (84.66°C) occurred 
in MSD 3, which contained 80% malted sorghum flour 
(MSF), 15% sprouted mung bean flour (SMF), and 5% 
date fruit powder (DFP). This result is attributed to 
the dominance of  MSF, whose partially malted starches 
retain crystalline integrity, making them more resistant 
to thermal disruption. Additionally, SMF may contribute 
through resistant starch and protein-starch interactions 
formed during germination (Saini et al., 2021; Musa et al., 
2022). Conversely, samples like MSD 4 through MSD 7 
with higher SMF (≥30%) and DFP (7.5–10%) recorded 
lower GTs (80.33–80.66°C). The enzymatic breakdown 
of  starches in SMF and the presence of  sugars and fibers 
in DFP likely disrupted starch–water interactions, thereby 
reducing gelatinization energy requirements (Olagunju et 
al., 2023; El-Sohaimy and Hafez, 2021). The quadratic 
model for GT had limited explanatory power, with an 
F-value of  2.38 (p = 0.1325) and R² = 0.5976. Adjusted 
and predicted R² values (0.3461 and −0.2513, respectively) 
indicated weak predictive reliability (Abasiekong et al., 
2023). Despite this, the model’s precision (4.51) and 
low coefficient of  variation (1.27%) suggest acceptable 
experimental consistency (Elochukwu et al., 2019). Among 
factors, DFP had the strongest positive effect (+95.28), 
followed by MSF (+81.83) and SMF (+80.83). However, 
interactions such as AC (–25.36) and BC (–5.12) reduced 
GT, highlighting the complex interplay of  components. 
A 3D response plot was not generated due to the model’s 
low statistical significance.
Gelatinization Tempt: + 81.83A + 80.83B + 95.28 - 
1.25AB - 25.36AB - 5.12BC             ....(4)
Where A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Water absorption capacity (WAC) is a vital functional 
property of  flour blends, influencing dough handling, 
product texture, and shelf  life. In this study, WAC 
values of  the composite flours ranged from 1.70 to 2.33 
mL/g, though differences among the samples were not 
statistically significant (p > 0.05), as indicated by shared 
superscripts. Despite this, clear formulation trends 
emerged. The highest WAC (2.33 mL/g) was observed 
in samples such as MSD 1, MSD 2, MSD 4, MSD 9, 
and MSD 10, all of  which had ≥70% malted sorghum 
flour (MSF). The enhanced WAC in these samples likely 
stems from MSF’s partially degraded starches and fibrous 
structure developed during malting, which increases 
water-binding capacity (Musa et al., 2022; Agu et al., 
2017). In contrast, lower WAC values (1.70–1.79 mL/g) 
were recorded in samples with higher levels of  sprouted 
mung bean flour (SMF) and/or date fruit powder (DFP), 
such as MSD 3, MSD 6, MSD 7, MSD 8, and MSD 14. 
Germination of  SMF may decrease WAC by breaking 
down macromolecules, while DFP’s high sugar and 
fiber content may reduce hydration by limiting water 
accessibility (Olagunju et al., 2023; El-Sohaimy and Hafez, 
2021). The cubic model used to describe WAC variation 



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was not statistically significant (F = 3.24, p = 0.1348), 
suggesting limited predictive reliability. While the R² 
value was relatively high (0.8794), the wide discrepancy 
between adjusted R² (0.6080) and predicted R² (−0.3421) 
indicates potential overfitting (Abasiekong et al., 2023). 
Nonetheless, model diagnostics revealed acceptable 
experimental consistency, with a coefficient of  variation 
of  8.71% and an adequate precision of  4.32. Coefficient 
analysis showed that DFP (C) had the strongest linear 
positive effect (+2.10), followed by MSF (A, +1.83), 
while SMF (B) had a strong negative effect (−378.84), 
possibly due to scaling issues. Positive interactions were 
observed in AB (+1.47) and AB(A–B) (+3.17), although 
model limitations precluded generation of  a response 
surface plot.
WAC = + 1.83A + 2.10B -378.84C + 1.47 AB + 662.41 
AC - 582.43 ABC + 3.17 AB(A-B) - 304.36 AC(A-C) - 
262.30 BC(B-C)              ....(5)
Where, A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Oil absorption capacity (OAC) is a key functional 
property influencing flavor retention, mouthfeel, and 
texture in low-moisture food products such as snack bars. 
In this study, OAC values of  the composite flours varied 
significantly (p < 0.05), ranging from 0.83 to 1.23 mL/g, 
depending on the formulation. The highest OAC (1.23 
mL/g) was recorded in MSD 1, MSD 4, and MSD 12, 
which contained higher proportions of  sprouted mung 
bean flour (SMF) and/or date fruit powder (DFP). These 
ingredients are rich in proteins, fibers, and sugars with 
polar side chains and hydrophilic structures, enhancing 
oil retention (Adebowale et al., 2012; Mohammed et al., 
2022). Conversely, the lowest OAC (0.83 mL/g) in MSD 8 
may be attributed to its limited DFP content, despite high 
SMF levels. Samples like MSD 3, MSD 5, and MSD 14 also 
exhibited low OAC, likely due to a reduced presence of  
oil-binding components. The results reflect the differing 
oil-holding capacities of  the ingredients: malted sorghum 
flour (MSF), being starch-rich, tends to have lower OAC, 
while legumes like mung bean improve lipid interaction 
through protein structures (Kaur and Singh, 2005; Aremu 
et al., 2020). ANOVA revealed that the data fitted well to 
a special quartic model (F = 4.83, p = 0.0367), explaining 
84.93% of  the variation (R² = 0.8493). However, a large 
gap between adjusted R² (0.6736) and predicted R² 
(0.1020) indicated limited predictive strength, possibly 
due to overfitting or weak correlation among variables. 
Despite this, the model showed good reproducibility with 
a low coefficient of  variation (6.73%) and strong signal-
to-noise ratio (adequate precision = 7.21). The non-
significant lack-of-fit (F = 0.26) confirmed the model’s 
suitability (Elochukwu et al., 2019). Coefficient analysis 
identified DFP (Factor C) as the most impactful on OAC 
(+17.60), while interactions like AB²C (+42.70) were 
synergistic, and AC and BC showed antagonistic effects.
OAC = + 1.18A + 0.9746B + 17.60C + 0.5577AB - 
21.98AC - 22.05BC + 42.70 AB²C - 88.39 ABC²      ....(6)
Where, A = malted sorghum flour, B = sprouted mung 

bean flour, and C = date fruit powder 
Swelling capacity is a crucial functional property that 
reflects the ability of  flour particles to absorb water 
and expand, influencing texture and hydration in food 
applications. In this study, swelling capacity values ranged 
significantly (p < 0.05) from 48.80% to 59.98% across the 
composite flour formulations. The highest values were 
observed in MSD 3 (59.98%), MSD 12 (59.92%), and 
MSD 11 (59.70%), which contained moderate levels of  
sprouted mung bean flour (SMF) and higher proportions 
of  date fruit powder (DFP). These combinations enhance 
water uptake and volumetric expansion due to improved 
hydration and matrix structure (Ojo et al., 2021). Malted 
sorghum flour (MSF), rich in partially hydrolyzed starch, 
facilitates water absorption and granule swelling. SMF 
contributes solubilized proteins and disrupted cell walls, 
improving hydration (Eneche et al., 2020; Ocheme et al., 
2022). However, excessive SMF, as seen in MSD 10 and 
MSD 4, reduced swelling capacity (48.80–49.90%), likely 
due to denser protein matrices that bind water without 
expansion. Similarly, high MSF content in MSD 2 (80%) 
led to lower swelling (50.93%). DFP, known for its soluble 
sugars and fiber, positively influenced swelling through 
enhanced gelation and water retention (Gbadamosi et al., 
2019). ANOVA confirmed a highly significant special 
quartic model (F = 71.48, p = 0.0001), with an excellent 
fit (R² = 0.9913, adjusted R² = 0.9775, predicted R² = 
0.8122). The low coefficient of  variation (1.20%) and 
adequate precision (20.01) demonstrated strong reliability 
and signal strength. The non-significant lack-of-fit (F 
= 0.2636) validated the model’s accuracy. DFP (C) had 
the strongest positive effect on swelling (+95.68), while 
MSF (A) and SMF (B) followed. Significant interactions 
included synergistic AB (+10.42) and A²BC (+372.88), 
while AC, BC, AB²C, and ABC² had antagonistic 
effects. These findings emphasize the critical role of  
DFP and optimal blend balance in maximizing swelling 
performance (Njapndounke et al., 2023).
Swelling Capacity = + 59.83A + 51.56B + 95.68C + 
10.42AB - 103.72AC - 16.52BC + 372.88 A²BC - 387.39 
AB²C - 611.23 ABC²              ....(7)
Where, A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder.

Effect of  Mixture Component On the proximate 
composition of  flour blends from Malted Sorghum, 
Sprouted Mung Bean and Date Fruit Powder
The proximate composition analysis of  the composite 
flour samples offers valuable insights into their nutritional 
quality and suitability for developing health-enhancing 
snack bars. 
Moisture content is a vital quality attribute in snack 
formulations due to its influence on shelf-life, microbial 
stability, and sensory characteristics such as texture and 
mouthfeel. In this study, moisture levels in composite 
flour blends of  malted sorghum, sprouted mung bean, and 
date fruit powder ranged from 8.58% to 9.52%, remaining 
within the safe storage threshold (<10%) recommended 



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for ready-to-eat cereal-based snacks (Nwanekezi et al., 
2023). The lower moisture in MSD 2 indicates reduced 
spoilage risk, while the slightly higher value in MSD 4 is 
likely due to the water-binding capacity of  sprouted mung 
bean flour, which is rich in fiber and protein (Fekadu et 
al., 2022). Analysis of  variance (ANOVA) for the special 
cubic model confirmed statistical significance (F = 
12.34, p = 0.0020), suggesting that the model effectively 
explains moisture variability. Significant linear effects of  
malted sorghum (A), sprouted mung bean (B), and date 
fruit powder (C), along with the AB interaction, were 
identified (p < 0.05), while AC, BC, and ABC interactions 

were non-significant. The model showed good fit (non-
significant lack of  fit: F = 0.08, p = 0.9701), with strong 
performance metrics (R² = 0.9136, adj. R² = 0.8396, pred. 
R² = 0.6730). High adequate precision (10.853) and low 
coefficient of  variation (1.21%) confirm its robustness. 
Date fruit powder (C) had the greatest positive influence 
on moisture (+10.73), followed by malted sorghum (A) 
and sprouted mung bean (B). However, high variance 
inflation factors (VIF > 200) for AC and BC suggest 
potential multicollinearity, warranting caution. A 3D 
surface plot visualized the interaction effects, especially 
between A and B, supporting the model’s predictive 

Table 2: Functional properties of  composite flours

Sa
m

pl
es

M
SF

 (%
)

SM
F 

(%
)

D
FP

 (%
)

B
ul

k 
de

ns
ity

 (g
/

m
L)

Fo
am

in
g 

ca
pa

ci
ty

 
(%

)

W
et

ta
bi

lit
y 

(S
ec

.)

G
el

. T
em

pe
ra

tu
re

 
(c

0 )

W
A

C
 (m

L/
g)

O
A

C
 (m

L/
g)

Sw
el

lin
g 

C
ap

ac
ity

 
(%

)

M
SD

 1

70
.0

0

20
.0

0

10
.0

0

0.
84

cd
±

0.
01

5.
66

f ±
0.

01

74
.3

3bc
±

0.
57

81
.6

6bc
±

0.
57

2.
33

a ±
0.

57

1.
23

a ±
0.

05

58
.3

5c ±
0.

04

M
SD

 2

80
.0

0

10
.0

0

10
.0

0

0.
86

a ±
0.

00

5.
77

de
f ±

0.
11

72
.3

3de
±

0.
57

81
.3

3bc
d ±

0.
57

2.
33

a ±
0.

57

1.
03

ab
c ±

0.
05

50
.9

3e ±
0.

73

M
SD

 3

80
.0

0

15
.0

0

5.
00

0.
85

ab
c ±

0.
00

7.
64

a ±
0.

03

72
.6

6cd
±

1.
15

84
.6

6a ±
05

7

1.
70

a ±
0.

01

0.
93

bc
±

0.
05

59
.9

8a ±
0.

03

M
SD

 4

65
.0

0

30
.0

0

5.
00

0.
86

ab
±

0.
00

7.
61

a ±
0.

02

70
.6

6ef
±

0.
57

80
.0

0d ±
0.

00

2.
33

a ±
0.

57

1.
23

a ±
0.

05

49
.9

0ef
±

0.
08

M
SD

 5

80
.0

0

10
.0

0

10
.0

0

0.
86

a ±
0.

01

5.
85

de
±

0.
06

72
.3

3de
±

0.
57

80
.3

3cd
±

0.
57

1.
86

a ±
0.

05

0.
93

bc
±

0.
05

52
.2

6d ±
0.

32

M
SD

 6

65
.6

3

25
.6

2

8.
75

0.
86

ab
±

0.
01

5.
85

d ±
0.

02

72
.3

3de
±

0.
57

81
.3

3bc
d ±

0.
57

1.
79

a ±
0.

01

1.
01

ab
c ±

0.
02

58
.5

4bc
±

0.
05

M
SD

 7

75
.6

3

15
.6

3

8.
75

0.
86

a ±
0.

01

5.
67

ef
±

0.
01

70
.3

3f ±
0.

57

80
.3

3cd
±

0.
57

1.
79

a ±
0.

00

1.
06

ab
c ±

0.
11

53
.0

3d ±
0.

25



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M
SD

 8

62
.5

0

30
.0

0

7.
50

0.
83

d ±
0.

01

6.
68

c ±
0.

02

70
.3

3f ±
0.

57

80
.6

6cd
±

0.
57

1.
73

a ±
0.

05

0.
83

c ±
0.

05

52
.9

4d ±
0.

12

M
SD

 9

75
.6

3

18
.1

3

6.
25

0.
86

a ±
0.

0

5.
77

de
f ±

0.
01

70
.6

6ef
±

0.
57

82
.6

6b ±
0.

57

2.
33

a ±
0.

57

1.
10

ab
c ±

0.
17

50
.6

9e ±
0.

06

M
SD

 1
0

65
.0

0

30
.0

0

5.
00

0.
86

ab
±

0.
01

7.
68

a ±
0.

00

70
.3

3f ±
0.

57

81
.3

3bc
d ±

0.
57

2.
33

a ±
0.

57

1.
10

ab
c ±

0.
17

48
.8

0f ±
0.

07

M
SD

11

60
.0

0

30
.0

0

10
.0

0

0.
85

ab
c ±

0.
01

5.
82

de
f ±

0.
01

77
.3

3a ±
0.

57

80
.6

6cd
±

0.
57

1.
83

a ±
0.

01

1.
13

ab
±

0.
05

59
.7

0ab
±

0.
26

M
SD

 1
2

60
.0

0

30
.0

0

10
.0

0

0.
84

bc
d ±

0.
01

5.
67

ef
±

0.
01

75
.6

6ab
±

0.
57

82
.6

6b ±
0.

57

1.
83

a ±
0.

05

1.
23

a ±
0.

05

59
.9

2a ±
0.

08

M
SD

13

80
.0

0

15
.0

0

5.
00

0.
85

ab
c ±

0.
00

7.
52

a ±
0.

02

71
.3

3de
f ±

0.
57

82
.6

6b ±
0.

57

1.
83

a ±
0.

06

1.
06

ab
c ±

0.
11

58
.9

9ab
c ±

1.
07

M
SD

 1
4

72
.5

0

22
.5

0

5.
00

0.
86

ab
±

0.
01

7.
19

b ±
0.

20

72
.3

3de
±

0.
57

80
.6

6cd
±

0.
57

1.
70

a ±
0.

01

0.
93

bc
±

0.
05

50
.2

3e ±
0.

33
Values are means of  the triplicate determination ± standard deviation. Means with different superscript in the same column are significantly 
(p<0.05) different. MSF = Malted Sorghum flour, SMF = Sprouted Mung Bean Flour, DFP = Date Fruit Powder, MSD = Malted 
Sorghum, Sprouted Mung Bean and Date Fruits, OAC = Oil Abasorption Capacity, WAC = Water Absorption Capacity

Table 3: Diagnostic parameters for the fitted model of  the functional properties of  the composite flours

Pa
ra

m
et

er
s

m
od

el

R
-s

qu
ar

ed

A
dj

us
te

d 
R

-s
qu

ar
ed

Pr
ed

. 
R

-S
qu

ar
ed

La
ck

 o
f 

fit

PR
E

SS

A
de

qu
at

e 
Pr

ec
is

io
n

p-
 v

al
ue

Bulk density 
(g/mL)

Special 
quartic

0.9599 0.8958 0.5025 0.7450 0.0006 11.9688 0.0043*

Foam capacity 
(%)

 Quadratic 0.9128 0.8583 0.7281 0.0023 2.69 10.5341 0.0005*

Wettability 
(Sec)

Quadratic 0.9375 0.8984 0.8084 0.6980 11.26 11.1315 0.0001*

Gelatinization 
temperature 
(o C)

Quadratic 0.5976 0.3461 -0.2513 0.6907 26.58 4.5056 0.1325NS



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Figure 1: Response surface plot for the effects of  mixture components on the bulk density of  malted sorghum-
sprouted mung bean-date flour.

Figure 2: Response surface plot for the effects of  mixture components on the foam capacity of  malted sorghum-
sprouted mung bean-date flour.

WAC (mL/g) Cubic 0.8794 0.6080 - - NA 4.3236 0.1348NS
OAC (mL/g) Reduced 

Special 
Quartic 

0.8493 0.6736 0.1020 0.7838 0.1811 7.2130 0.0367*

swelling 
capacity (%)

 Special 
Quartic 

0.9913 0.9775 0.8122 0.6347 46.27 20.0075 0.0001*

*: Means in the same row are significantly different at p<0.05, respectively. NS: Means in the same row are not significantly (p>0.05) 
different



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Figure 3: Response surface plot for the effects of  mixture components on the wettability of  malted sorghum-
sprouted mung bean-date flour.

Figure 4: Response surface plot for the effects of  mixture components on the swelling capacity of  malted sorghum-
sprouted mung bean-date flour.

Figure 5: Response surface plot for the effects of  mixture components on the oil absorption capacity of  malted 
sorghum-sprouted mung bean-date.



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strength.
Moisture  = +8.93A+8.61B+10.73C+1.19AB+0.3578AC-
1.79BC              ....(8)
Where A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Protein content, a critical macronutrient essential for 
growth, maintenance, and repair, varied significantly 
(p<0.05) across the composite flour samples, ranging 
from 12.38% in MSD 2 to 21.92% in MSD 11 and MSD 
12. The notable increase in protein content was primarily 
linked to the inclusion of  sprouted mung bean flour 
(SMF), which is known to enhance protein digestibility 
and bioavailability through enzymatic modification during 
sprouting (Nkhata et al., 2018; Onuorah et al., 2024). 
Additionally, sprouting improves lysine levels a limiting 
amino acid in cereals like sorghum thereby boosting the 
overall protein quality of  the blends (FAO, 2023). This 
improvement holds relevance for combating protein-
energy malnutrition, particularly in low-resource regions. 
ANOVA results for the special cubic model used to 
evaluate protein content demonstrated a highly significant 
fit (F = 2070.16, p < 0.0001), with an exceptionally low 
probability of  results arising from random variation. The 
linear terms for malted sorghum (A), sprouted mung 
bean (B), and date fruit powder (C), along with the binary 
interactions AB, AC, and BC, were significant (p < 0.05), 
while the ternary interaction (ABC) was not. The model’s 
robustness was confirmed by high R² (0.9994), adjusted 
R² (0.9990), and predicted R² (0.9956), all within the 
acceptable deviation range (<0.2). A low coefficient of  
variation (0.64%) and high adequate precision (118.25) 
further reinforced the model’s precision and predictive 
power (Mehmood et al., 2018). Among the ingredients, 
date fruit powder (C) had the strongest positive effect on 
protein content (+36.98), followed by malted sorghum 
(A: +21.94) and sprouted mung bean (B: +12.41). AB 
had a synergistic effect, while AC and BC interactions 
were antagonistic (–23.00 and –19.61). High VIFs (>230) 
for AC and BC suggest multicollinearity, requiring careful 
interpretation. A 3D surface plot highlighted the AB 
interaction as critical in protein optimization.
Protein Content = + 21.94A + 12.41B + 36.98C + 
1.53AB - 23.00AC - 19.61BC + 7.01ABC              ....(9)
Where A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Fat content, a key determinant of  energy density, 
mouthfeel, and oxidative stability, ranged from 1.67% 
to 2.85% across the composite flour samples. The lower 
fat levels observed in MSD 10 and MSD 4 are desirable 
for extending shelf  life and aligning with growing 
consumer preferences for low-fat, health-conscious 
snacks. Conversely, the highest fat content in MSD 13 is 
likely due to the inclusion of  date fruit powder, which 
contributes minor lipid quantities alongside natural 
sugars (Al-Farsi and Lee, 2022). While reduced-fat 
formulations are beneficial for cardiovascular health, 
moderate fat levels remain important for flavor and 
caloric adequacy (Obinna-Echem et al., 2024). The 

ANOVA for the reduced cubic model applied to fat 
content yielded a highly significant fit (F = 404.98, p 
< 0.0001), confirming the model’s strong explanatory 
power. Significant contributors included the linear effects 
of  malted sorghum (A), sprouted mung bean (B), and 
date fruit powder (C), along with interaction terms AB, 
ABC, and AB(A–B). Although AC and BC were not 
statistically significant (p > 0.05), they were retained to 
preserve model hierarchy. The model exhibited excellent 
performance metrics: R² = 0.9979, adjusted R² = 0.9954, 
and predicted R² = 0.9849. A low coefficient of  variation 
(1.27%) and high adequate precision (55.576) confirm the 
model’s precision and reliability (Mehmood et al., 2018; 
Abasiekong et al., 2023). Among the ingredients, date fruit 
powder had the greatest positive effect on fat content 
(+3.23), followed by sprouted mung bean (+2.56) and 
malted sorghum (+1.88). Notably, AB(A–B) enhanced 
fat content (+1.79), while AB and ABC had negative 
effects (−0.6165 and −7.54). High variance inflation 
factors (>240) for AC and BC indicate multicollinearity, 
warranting cautious interpretation.
Fat = + 1.88A + 2.56B + 3.23C - 0.6165AB - 2.85AC + 
0.5283BC - 7.54ABC + 1.79AB(A - B)         ....(10)
Where, A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Ash content, which represents the total mineral 
composition of  food products, varied significantly across 
the snack bar formulations. The highest ash content was 
observed in MSD 11 and MSD 12 (3.67%), while the 
lowest was found in MSD 5 (2.49%). Elevated ash levels 
suggest higher mineral content, largely contributed by 
sprouted mung bean flour (SMF) and date fruit powder 
(DFP), both rich in essential minerals such as calcium, 
magnesium, potassium, and iron (Ocheme et al., 2020). 
The inclusion of  legumes like mung bean enhances the 
micronutrient density of  composite flours, supporting 
dietary adequacy and helping to address micronutrient 
deficiencies in vulnerable populations (Afolayan et al., 
2023). The ANOVA for the special quartic model revealed 
a highly significant fit (F = 620.59, p < 0.0001), indicating 
strong explanatory power for ash content variability. Key 
significant terms included the linear effects of  malted 
sorghum (A), sprouted mung bean (B), and date fruit 
powder (C), along with higher-order interactions AC, BC, 
AB²C, and ABC². The A²BC term was nearly significant 
(p = 0.0556), while AB showed no significant impact. A 
non-significant lack of  fit (F = 0.24, p = 0.6488) indicated 
that model errors were mostly due to random variation 
(Elochukwu et al., 2019; Kumari et al., 2022). Model 
performance was excellent, with R² = 0.9990, adjusted R² 
= 0.9974, and predicted R² = 0.9796. A low coefficient 
of  variation (0.65%) and high adequate precision 
(71.67) confirmed strong precision and signal strength 
(Mehmood et al., 2018). While DFP had the most positive 
effect on ash content (+19.30), its interactions with A 
and B were strongly negative (−21.80 and −21.00). The 
AB²C term increased ash content (+34.89), but ABC² 
significantly decreased it (−67.04). High VIFs (>1000) 



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Am. J. Food. Sci. Technol. 4(2) 65-84, 2025

for some terms indicate multicollinearity, warranting 
cautious interpretation.
Ash = + 3.67A + 2.52B + 19.30C - 0.0050AB - 21.80AC - 
21.00BC + 10.23 A²BC + 34.89AB²C - 67.04 ABC² ....(11)
Where, A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Crude fiber content across the composite snack 
formulations ranged from 4.01% to 8.66%, with 
the highest values recorded in samples with greater 
proportions of  date fruit powder (DFP) and sprouted 
mung bean flour (SMF). Dietary fiber plays an essential 
role in digestive health, regulating blood glucose, 
supporting cholesterol reduction, and promoting regular 
bowel movements (Wolever, 2023). The elevated fiber 
content in samples such as MSD 5 and MSD 1 suggests 
their potential utility as functional foods, especially for 
managing non-communicable diseases like diabetes 
and obesity. Furthermore, the integration of  cereal-
legume-fruit components may enhance the solubility 
and fermentability of  dietary fiber, improving prebiotic 
potential and gut health benefits (Chinma et al., 2022), in 
line with WHO (2022) recommendations on increasing 
fiber intake for chronic disease prevention. The quadratic 
model used to analyze fiber content in the blends 
demonstrated a statistically significant fit (F = 10.38, p 
= 0.0024), indicating reliable model performance. Linear 
terms for malted sorghum (A) and sprouted mung bean 
(B) were both significant (p < 0.05), underscoring their 
individual contributions to fiber content. Interaction 
terms AB, AC, and BC were not significant but retained 
to preserve model hierarchy. The non-significant lack of  
fit (F = 0.31, p = 0.8594) confirmed model adequacy 
(Elochukwu et al., 2019; Kumari et al., 2022). The model’s 
R² (0.8664), adjusted R² (0.7829), and predicted R² 
(0.5915) reflect acceptable reliability, as the difference 
between adjusted and predicted R² remains within 0.2 
(Abasiekong et al., 2023). Adequate precision (8.82) and 
a CV of  11.82% further support model robustness. 
DFP had the most substantial positive influence on fiber 
(+19.29), though its high VIF (511.04) and those of  AC 
and BC (>228) suggest multicollinearity. Future modeling 
should address this to improve parameter stability 
(Mehmood et al., 2018).
Crude fibre = + 7.72A + 8.44B + 19.29C - 0.5515AB - 
35.01AC - 27.68BC           ....(12)
Where A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder
Carbohydrate content, calculated by difference, varied 
inversely with the levels of  protein and fiber across 
the composite flour blends. Samples MSD 3 and MSD 
2 recorded the highest carbohydrate contents 65.82% 
and 65.62%, respectively which correlates with their 
lower inclusion of  sprouted mung bean flour (SMF), a 
component known for its high protein and fiber content. 
Carbohydrates are essential in snack formulations, serving 
as a primary energy source and contributing to texture, 
flavor, and satiety. The natural sugars in date fruit powder 
(DFP) offer a healthier alternative to refined sugars, 

enhancing sweetness while aligning with global dietary 
trends aimed at reducing added sugar intake, particularly 
in products targeted at children and adolescents (Al-Farsi 
et al., 2022). The ANOVA results for the quadratic model 
assessing carbohydrate content demonstrated a highly 
significant model fit, with an F-value of  48.41 and a 
p-value < 0.0001. This signifies that the model reliably 
explains the variation in carbohydrate content with 
only a 0.01% chance of  the results occurring randomly. 
Significant linear terms included malted sorghum (A) and 
sprouted mung bean (B) (p < 0.0001), while interaction 
terms AB, AC, and BC were not statistically significant 
(p > 0.05). These were retained to preserve the model 
hierarchy, as recommended in mixture design analysis 
(Elochukwu et al., 2019; Kumari et al., 2022). The model’s 
adequacy was further confirmed by a non-significant lack 
of  fit (F = 0.39, p = 0.8064) and strong performance 
metrics: R² = 0.9680, adjusted R² = 0.9480, and predicted 
R² = 0.9008. A minimal difference between adjusted and 
predicted R² (<0.2) indicates strong predictive capability 
(Abasiekong et al., 2023). Adequate precision (18.99) and 
a low coefficient of  variation (1.26%) highlight excellent 
model precision and reliability (Mehmood et al., 2018). 
Coefficient estimates showed sprouted mung bean (B) 
had the highest impact on carbohydrate content (+65.46), 
followed by malted sorghum (A, +55.84). Date fruit 
powder (C) had the lowest effect (+13.68), with a high VIF 
(511.04), indicating multicollinearity, also seen in AC and 
BC terms. These findings underscore the dominant role 
of  individual components in determining carbohydrate 
content, consistent with prior studies (Njapndounke et 
al., 2023; Ukoha et al., 2022).
Carbohydrate = + 55.84A + 65.46B + 13.68C - 1.59AB 
+ 78.32AC + 65.44BC           ....(13)
Where A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder 
Energy content, calculated using Atwater factors, ranged 
from 328.28 to 348.16 KCal/100g, with the highest value 
recorded in MSD 3, likely due to its elevated carbohydrate 
and fat composition. These energy values fall within 
the recommended range for nutrient-dense snack bars 
targeted at children, athletes, and individuals facing 
undernutrition. Such formulations are suitable for school 
feeding programs and emergency nutrition responses, 
offering a portable and cost-effective source of  calories 
(FAO, 2023). The blend of  energy-yielding macronutrients 
carbohydrates, fats, and proteins alongside fiber-induced 
satiety and plant-based protein quality, supports the 
development of  functional snacks that can address both 
undernutrition and emerging lifestyle-related diseases. 
The ANOVA for the quadratic model evaluating energy 
values in blends of  malted sorghum (A), sprouted mung 
bean (B), and date fruit powder (C) revealed a statistically 
significant model fit (F = 8.21, p = 0.0052). This suggests 
that the model adequately explains variation in energy 
content, with only a 0.52% chance of  random influence. 
Linear terms A, B, and C were significant (p < 0.05), while 
interactions AB, AC, and BC were not but were retained 



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Am. J. Food. Sci. Technol. 4(2) 65-84, 2025

for structural integrity (Elochukwu et al., 2019; Kumari 
et al., 2022). The model’s lack of  fit was non-significant 
(F = 0.23, p = 0.9079), affirming its validity. Model 
performance was moderate, with R² = 0.8369, adjusted 
R² = 0.7350, and predicted R² = 0.5192. The >0.2 
difference between adjusted and predicted R² suggests 
issues like high variability or outliers, implying that model 
refinement may be necessary (Mehmood et al., 2018; 
Abasiekong et al., 2023). Despite this, the model showed 
strong experimental consistency, with a low coefficient 
of  variation (CV = 0.86%) and adequate precision 
(7.36). Among the components, sprouted mung bean 
(B) contributed most to energy (+335.05 kcal/100g), 
followed by malted sorghum (A, +329.01) and date 
fruit powder (C, +317.64). However, the estimate for 
C had a high standard error and VIF (>511), indicating 
multicollinearity. Similar caution applies to AC and BC 
terms. These results support prior findings on energy-
enhancing properties of  cereal-legume-fruit blends 
(Njapndounke et al., 2023; Ukoha et al., 2022).
Energy = + 329.01A + 335.05B + 317.64C - 11.22AB + 
80.71AC + 65.43BC          ....(14)
Where, A = malted sorghum flour, B = sprouted mung 
bean flour, and C = date fruit powder.
Optimization of  Numerical values
Optimization of  Numerical values of  independent 
variables and simultaneous optimization of  the multiple 
responses with significant models were carried out by 
choosing the desired goals for each variable and response 
by using Design Expert software (Design- Expert 
Software Version 12.0.3.0., Stat- Ease Inc., Minneapolis, 

USA). The ingredients (Malted sorghum flour, sprouted 
mung bean flour and Date fruit powder) were set in 
ranges. The relative importance of  “3” was assigned to all 
the parameters. The optimization goal of  for the design 
specifications are presented in Table 6.
Optimization formulation for the functional 
properties and proximate composition of  Composite 
flour from malted sorghum flour, sprouted mung 
bean flour and date powder
Stat-Ease Inc (2023) showed that the response optimizer 
of  the software generated six (6) solutions in the ingredient 
value with desirability of  0.178 to 0.620 and their respective 
responses values as shown in Tables 7 and Table 8. 
Optimization solutions presented in in Tables 7 and Table 
8, suggested that Composite flour made with 69.925 % 
Malted sorghum flour, 21.382 % sprouted mung bean flour 
and 8.693 % Date fruit powder was selected as the best 
solution for this combination of  variables with a desirability 
of  0.620 which is 62 % for all the responses evaluated.
CONCLUSION 
This study demonstrated the significant influence of  
varying proportions of  malted sorghum flour (MSF), 
sprouted mung bean flour (SMF), and date fruit powder 
(DFP) on the nutritional and functional characteristics 
of  composite flour blends. Using a mixture design with 
fourteen formulations, the research revealed notable 
differences (p < 0.05) across key properties such as bulk 
density, foaming capacity, swelling, wettability, oil and 
water absorption capacities, gelatinization temperature, 
and proximate composition (moisture, protein, fat, 
ash, fiber, carbohydrate, and energy). Response Surface 

Table 4:  Proximate analysis on the composite flour samples

Sa
m

pl
es

M
SF

 (%
)

SM
F 

(%
)

D
FP

 (%
)

M
oi

st
ur

e 
co

nt
en

t (
%

)

Pr
ot

ei
n 

(%
)

Fa
t (

%
)

A
sh

 (%
)

Fi
br

e 
(%

)

C
ar

bo
hy

dr
at

e 
(%

)

E
ne

rg
y 

(K
C

al
/1

00
g)

M
SD

1

70
.0

0

20
.0

0

10
.0

0

9.
07

ab
cd

e ±
0.

05

17
.6

4e ±
0.

14

2.
08

c ±
0.

02

3.
09

d ±
0.

00

8.
25

b ±
0.

11

59
.8

7e ±
0.

10

32
8.

76
f ±

0.
78

M
SD

 2

80
.0

0

10
.0

0

10
.0

0

8.
58

e ±
0.

02

12
.3

8h ±
0.

57

2.
59

b ±
0.

06

2.
54

g ±
0.

08

8.
29

b ±
0.

23

65
.6

2b ±
0.

00

33
6.

11
d ±

0.
82

M
SD

 3

80
.0

0

15
.0

0

5.
00

8.
85

cd
e ±

0.
08

14
.8

8g ±
0.

04

2.
80

a ±
0.

05

2.
79

f ±
0.

92

4.
86

h ±
0.

10

65
.8

2a ±
0.

06

34
8.

16
a ±

0.
53

M
SD

4

65
.0

0

30
.0

0

5.
00

9.
52

a ±
0.

08

21
.4

5b ±
0.

19

1.
69

f ±
0.

07

3.
48

b ±
0.

46

4.
01

i ±
0.

02

59
.8

5e ±
0.

29

34
0.

41
b ±

0.
30



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Am. J. Food. Sci. Technol. 4(2) 65-84, 2025

M
SD

5

80
.0

0

10
.0

0

10
.0

0

8.
64

de
±

0.
04

12
.4

5h ±
0.

08

2.
53

b ±
0.

04

2.
49

g ±
0.

70

8.
66

a ±
0.

08

65
.2

3b ±
0.

25

33
3.

49
d ±

1.
03

M
SD

6

65
.6

3

25
.6

2

8.
75

9.
10

ab
cd

±
0.

63

19
.7

0c ±
0.

01

1.
95

d ±
0.

06

3.
23

c ±
0.

03

7.
07

d±
0.

02

58
.9

5f
±

0.
12

33
2.

15
e ±

0.
06

M
SD

7

75
.6

3

15
.6

3

8.
75

8.
88

cd
e ±

0.
09

15
.0

9g ±
0.

98

2.
11

c ±
0.

02

2.
81

ef
±

0.
23

6.
69

e ±
0.

09

64
.4

2c ±
0.

09

33
7.

03
d ±

0.
55

M
SD

8

62
.5

0

30
.0

0

7.
50

9.
17

ab
c ±

1.
44

21
.4

7b ±
0.

15

1.
76

ef
±

0.
01

3.
24

c ±
0.

00

5.
64

f ±
0.

02

58
.7

9f ±
0.

28

33
6.

88
d ±

0.
10

M
SD

9

75
.6

3

18
.1

3

6.
25

8.
99

bc
de

±
0.

04

16
.2

8f ±
0.

08

2.
13

c ±
0.

04

2.
93

e ±
0.

02

5.
28

g ±
0.

06

64
.3

9c ±
0.

03

33
7.

10
d ±

0.
73

M
SD

10

65
.0

0

30
.0

0

5.
00

9.
40

ab
±

0.
01

21
.2

3b ±
0.

19

1.
67

f ±
0.

03

3.
50

b ±
0.

01

4.
02

i ±
0.

01

60
.1

8g ±
0.

19

34
1.

85
b ±

0.
13

M
SD

11

60
.0

0

30
.0

0

10
.0

0

8.
76

cd
e ±

0.
57

21
.9

2a ±
0.

01

1.
88

de
±

0.
00

3.
67

a ±
0.

02

7.
50

c ±
0.

02

56
.2

7g ±
0.

05

32
9.

68
f ±

0.
33

M
SD

12

60
.0

0

30
.0

0

10
.0

0

9.
12

ab
cd

±
0.

04

21
.9

2a ±
0.

01

1.
88

de
±

0.
00

3.
67

a ±
0.

23

7.
49

c ±
0.

00

55
.9

2g ±
0.

05

32
8.

28
f ±

0.
24

M
SD

13

80
.0

0

15
.0

0

5.
00

8.
75

cd
e ±

0.
00

14
.8

8g ±
0.

04

2.
85

a ±
0.

03

2.
76

f ±
0.

04
1

7.
49

c ±
0.

00

63
.2

7a ±
0.

05

33
8.

25
c ±

0.
23

M
SD

14

72
.5

0

22
.5

0

5.
00

9.
11

ab
cd

±
0.

11

18
.6

8d ±
0.

20

1.
91

d ±
0.

00

3.
14

cd
±

0.
02

4.
74

h ±
0.

05

62
.4

2d ±
0.

08

34
1.

59
b ±

0.
40

Values are means of  the triplicate determination ± standard deviation. Means with different superscript in the same column are significantly 
(p<0.05) different. MSF = Malted Sorghum flour, SMF = Sprouted Mung Bean Flour, DFP = Date Fruit Powder, MSD = Malted 
Sorghum, Sprouted Mung Bean and Date Fruits



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Table 5: Diagnostic parameters for the fitted model of  the proximate composition of  the composite flour from 
malted sorghum flour, sprouted mung bean flour and date fruit powder

Pa
ra

m
et

er
s

m
od

el

R
-s

qu
ar

ed

A
dj

us
te

d 
R

-s
qu

ar
ed

Pr
ed

. 
R

-S
qu

ar
ed

La
ck

 o
f 

fit

PR
E

SS

A
de

qu
at

e 
Pr

ec
is

io
n

p-
 v

al
ue

Moisture (%) Special cubic 0.9136 0.8396 0.6730 0.9701 0.0006 10.8530 0.0020*
Protein (%) Special cubic 0.9994 0.9990 0.9956 0.1441 0.7042 118.2537 0.0001*
Fat (%) reduced cubic 0.9979 0.9954 0.9849 0.5422 0.0315 55.5756 0.0001*
Ash (%) Special quartic 0.9990 0.9974 0.9796 0.6488 0.0408 71.6652 0.0001*
Crude fibre (%) Quadratic 0.8664 0.7829 0.5915 0.8594 14.11 8.8206 0.0024*
Carbohydrate (%) Quadratic 0.9680 0.9480 0.9008 0.8064 14.86 18.9924 0.0001*
Energy Value (%)  Quadratic 0.8369 0.7350 0.5192 0.9079 197.92 7.3591 0.0052*

*: Means in the same row are significantly different at p<0.05, respectively. NS: Means in the same row are not significantly (p>0.05) 
different

Figure 6: Response surface plot for the effects of  mixture components on the moisture content of  malted sorghum-
sprouted mung bean-date flour.

Figure 7: Response surface plot for the effects of  mixture components on the protein content of  malted sorghum-
sprouted mung bean-date flour.



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Figure 8: Response surface plot for the effects of  mixture components on the fat content of  malted sorghum-
sprouted mung bean-date flour.

Figure 9: Response surface plot for the effects of  mixture components on the ash content of  malted sorghum-
sprouted mung bean-date flour.

Figure 10: Response surface plot for the effects of  mixture components on the fibre content of  malted sorghum-
sprouted mung bean-date.



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Figure 11: Response surface plot for the effects of  mixture components on the carbohydrate of  malted sorghum-
sprouted mung bean-date.

Figure 12: Response surface plot for the effects of  mixture components on the energy value of  malted sorghum-
sprouted mung bean-date.

Methodology (RSM) effectively guided the optimization 
process, resulting in a gluten-free, nutrient-dense flour 
blend with improved functional performance. MSF 
contributed to higher bulk density and energy value, SMF 
enhanced foaming and wettability due to its modified 
protein structure from germination, while DFP increased 

fiber and sugar content, promoting energy availability and 
digestive benefits. The optimized formulation comprising 
69.93% MSF, 21.38% SMF, and 8.69% DFP achieved a 
composite desirability score of  0.620, meeting criteria for 
nutritional adequacy and shelf  stability. These findings 
support the use of  underutilized, climate-resilient 

Table 6: Optimization constraints for the functional properties, nutrient content and caloric value of  malted sorghum-
sprouted mung bean-date flour
Name Goal Lower Limit Upper 

Limit
Lower 
Weight

Upper 
Weight

Importance

A: Malted sorghum flour Is in range 60 80 1 1 3
B: Sprouted mung bean flour Is in range 10 30 1 1 3
C: Date fruit powder Is in range 5 10 1 1 3
Bulk density Maximize 0.83 0.86 1 1 3
Foam capacity Minimize 5.66 7.68 1 1 3



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Table 7: Optimization solutions for the functional properties of  malted sorghum-sprouted mung bean-date flour blends.

N
um

be
r

M
al

te
d 

so
rg

hu
m

 
flo

ur

Sp
ro

ut
ed

 
m

un
g 

be
an

 
flo

ur

D
at

e 
fr

ui
t 

po
w

de
r

B
ul

k 
de

ns
ity

Fo
am

 
ca

pa
ci

ty

W
et

ta
bi

lit
y

O
A

C

Sw
el

lin
g 

ca
pa

ci
ty

D
es

ira
bi

lit
y

1 69.925 21.382 8.693 0.871 5.545 71.641 1.121 56.720 0.620 Selected
2 60.350 30.000 9.650 0.840 5.918 75.172 1.092 58.673 0.535
3 74.085 15.915 10.000 0.845 5.476 73.722 1.152 56.176 0.501
4 78.277 16.556 5.167 0.850 7.184 71.796 1.105 53.432 0.491
5 64.507 29.551 5.942 0.847 7.023 69.856 0.903 51.272 0.368
6 65.000 30.000 5.000 0.860 7.675 70.697 1.164 49.344 0.178

ingredients in functional food development, especially 
for health-targeted products like snack bars and other 
baked products. The statistical models showed strong 
predictive accuracy (R² values > 0.80), and 3D surface 

plots effectively visualized ingredient interactions, 
underscoring the strength of  RSM in food formulation 
optimization.

Wettability Minimize 70.33 77.33 1 1 3
OAC Maximize 0.83 1.23 1 1 3
Swelling capacity Maximize 48.8 59.98 1 1 3
Moisture Minimize 8.58 9.52 1 1 3
Protein Maximize 12.38 21.92 1 1 3
Fat Is in range 1.67 2.85 1 1 3
Ash Maximize 2.49 3.67 1 1 3
Fibre Maximize 4.01 8.66 1 1 3
Carbohydrate Is in range 55.92 65.82 1 1 3
Energy Maximize 328.28 348.16 1 1 3

Table 8: Optimization solutions for the Proximate composition and caloric value of  malted sorghum-sprouted mung 
bean-date flour blends  

N
um

be
r

M
al

te
d 

so
rg

hu
m

 
flo

ur

Sp
ro

ut
ed

 
m

un
g 

be
an

 
flo

ur

D
at

e 
fr

ui
t 

po
w

de
r

M
oi

st
ur

e

Pr
ot

ei
n

Fa
t

A
sh

Fi
br

e

C
ar

bo
hy

dr
at

e

E
ne

rg
y

D
es

ira
bi

lit
y

1 69.925 21.382 8.693 9.069 17.939 1.971 3.108 6.735 61.308 332.934 0.620 Selected
2 60.350 30.000 9.650 8.970 21.810 1.857 3.568 7.325 56.447 330.196 0.535
3 74.085 15.915 10.000 8.955 15.547 2.078 2.856 8.111 62.286 330.926 0.501
4 78.277 16.556 5.167 8.876 15.689 2.487 2.920 5.740 64.289 341.980 0.491
5 64.507 29.551 5.942 9.343 21.126 1.712 3.276 4.448 60.082 339.626 0.368
6 65.000 30.000 5.000 9.449 21.388 1.686 3.490 4.051 59.984 341.300 0.178

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