INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue VI, June 2026

Cooking Quality, Fasting Blood Glucose, Glycemic Index and Load of

High–Fiber Noodles Made from Wheat, Tiger Nut Residue and Cassava

Flour Blends

^*12Elemuo, G. K., ²Obasi, N. E., ²Onwuka, G. I., ¹Odeyemi, T. A., ³Ezenwa, C. J., ⁴Emetole, J. M. and

⁵Okoroafor, C. N.

¹Department of Food Science and Technology, Federal University of Technology Owerri, Imo State,

Nigeria

²Department of Food Science and Technology, Michael Okpara University of Agriculture, Umudike,

Abia State, Nigeria

³Department of Public Health, Federal University of Technology, Owerri, Imo State, Nigeria

⁴Product Development Programme, National Root Crops Research Institute, Umudike, Abia State,

Nigeria

⁵Department of Human Nutrition and Dietetics, Ambrose Alli University, Ekpoma, Edo State,

Nigeria

*Corresponding Author

DOI: https://doi.org/10.51583/IJLTEMAS.2026.150600003

Received: 12 June 2026; Accepted: 17 June 2026; Published: 02 July 2026

ABSTRACT

High-fiber composite noodles were made from the combination of wheat, tiger nut residue and cassava flour

blends. High fiber inclusion (up to 20 %) was achieved presenting an excellent option for formulating healthier

noodles. The cooking quality and fasting blood glucose of the noodles were evaluated and the data generated

were subjected to analysis of variance (ANOVA) and means were separated using Duncan multiple range test

(DMRT) to establish the significant difference (p <0.05). Available carbohydrate, glycemic index and load were

also determined. The result of the cooking quality of the noodles generated include; cooking time (38–40 min.),

cooking loss (0.22–0.82 g), water uptake (0.14–0.17 %), and bulk density (0.26–0.53 g/ml). Fasting blood

glucose (85.85–110.37 mg/dL), glycemic index (36.14–49.17), glycemic load (9.36–14.93) and available

carbohydrate (25.90–30.37 g/100g) values for noodles remained lower than wheat controls, confirming reduced

postprandial glycemic response and overall functional suitability. The composite noodles performed favourably

when compared with the control (100 % wheat flour).

Keywords: Cooking quality, fasting blood glucose, glycemic index, glycemic load, high-fiber noodles

INTRODUCTION

In recent decades, there has been an increasing shift towards the consumption of high-fiber foods as opposed to

carbohydrate-dense diets. The consumption of dietary fiber is associated with improved digestion, enhanced

nutrient absorption, and better blood sugar control, especially for individuals with metabolic disorders such as

type 2 diabetes. Sources of dietary fiber include whole grains, fruits, vegetables, legumes, nuts, and seeds

(Slavin, 2019).

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Noodles, a staple food in many regions, is often made from wheat, which is known for its relatively high

glycemic index. Hence, the search for alternative food sources with lower glycemic indices and improved

nutritional profiles has gained significant importance (Agbaje et al., 2023).

The blending of flours from various sources, such as wheat, tiger nut residue, and cassava, offers a unique

opportunity to develop noodle products with enhanced nutritional benefits. Tiger nut residue, a rich source of

dietary fiber, and cassava flour, known for its gluten-free properties, present excellent options for formulating

healthier alternatives (Asogwa et al. (2024). The aim of this study is to evaluate the cooking quality of high-

fiber noodles made from wheat, tiger nut residue and cassava flour blends.

MATERIALS AND METHODS

Wheat and yellow tiger nuts healthy seeds were purchased from a Relief market in Owerri, Imo state of Nigeria

while the cassava tubers were sourced from National Root Crops Research Institute, Umudike, Abia State,

Nigeria for uniformity and proper identification.

Processing of wheat seeds, tiger nut and cassava tubers into flour and residues

The processing method outlined by Jaya et al. (2021) was adopted in processing the tiger nut residue with slight

modification on the fiber obtaining method. The tiger nut was sorted to remove stones, debris, and spoiled nuts.

It was then washed under a running water. After that, the tiger nuts were thoroughly washed again with 0.1 %

sodium hydroxide solution to eliminate microorganisms, remaining dirt and impurities. The washed tiger nut

was grated and sieved using muslin sac to separate the milk and the residue, the final residue obtained was

sparged with hot water to separate more extractives and the dried in an oven (model LBN-DO161, Labnic, USA-

based Supplier) at 60°C for 12 hours to reduce moisture content. After drying, it was grounded into fine powder

using a hammer mill (model 9FQ40 Hammer mill, Honest Industrial, China).

The method described by Adebayo et al. (2020) was adopted in processing the cassava tuber into flour with a

slight modification on the method of drying. The peeled cassava tubers were grated into small particles. The

grated cassava mash is soaked for 12 hours and then spray dried in a spray drier. The dried cassava mash was

then milled into flour using a hammer mill (model 9FQ40 Hammer mill, Honest Industrial, China).

The processing method described Olatunji et al. (2021) was adopted in manufacturing of wheat flour. The wheat

grains were sorted, cleaned, and washed with a clean water to get rid of any remaining contaminants. Following

an overnight soak in clean water, the cleaned grains were poured through a plastic sieve. The grains were hammer

milled (model 9FQ40 Hammer mill, Honest Industrial, China) and then re-milled after being oven (model LBN-

DO161, Labnic, USA-based Supplier) dried for 12 hours at 60°C.

Formulation of the processed flours

Flour blends were prepared using different ratios of wheat, tiger nut residue, and cassava flour. The following

blending ratios were used: WTC1: 74.30 % wheat flour, 20 % tiger nut residue, 5.70 % cassava flour, WTC2:

75 % wheat flour, 20 % tiger nut residue, 5 % cassava flour, WTC3: 71.80 % wheat flour, 18.10 % tiger nut

residue, 10.10 % cassava flour, WTC4: 100 % wheat flour (control). Each blend was mixed thoroughly using a

mechanical mixer for 10 minutes to ensure homogeneity.

Production of high-fiber composite noodles

The procedure for producing the high-fiber outlined by Fernandez et al. (2022) were modified and used as shown

in Figure 1. The ingredients were combined with a consistent number of composite flours (76% w/w), egg, salt

(11% w/w), and water (13% w/w) to make fresh noodles. Both the liquid and solid components were weighed

and combined; the liquids were added to the solid raw materials at an average speed for 45 seconds, after which

the liquids were added at a low speed for 15 seconds. The final mixes were kneaded in two stages, each lasting

ten minutes (interspersed with ten minutes of rest time). To facilitate sample relaxing, the resultant doughs were

placed inside a plastic bag and let to stand at 40 °C for 20 minutes. Next, a manual extruding machine, was used

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to produce the freshly noodle rolled sheets, and subsequently yielding the final noodle form. The noodle was

steamed at 100 ⁰C for 3 min then tray dried at 39 ⁰C for 5 h.

Determination of the cooking quality composite noodles

The cooking time was determined following the method described by AACC (2000), cooking loss was assessed

using the method described by Kim et al. (2018), water uptake was determined using the method outlined by Fu

(2008) and bulk density was determined using the method described by Rosell et al. (2007).

Determination of glycemic index and load of high-fiber composite noodles

The glycemic index (GI) was carried out and calculated using the method described by Brand – Miller et al.

(2003). The glycemic index was determined by feeding 10 individuals with The sample of high fiber food

(Noodles) and their blood sugar level were taken at intervals. This process was repeated for 0, 30, 60, 90 and

120 min with different samples. The feeding process were used until the samples were tested on the individuals

for 4 days appointment. The GI was expressed thus:

퐼퐴푈퐶 표푓 푡푒푠푡 푓표표푑

100

1

GI =

푥

퐼퐴푈퐶 표푓 푠푡푎푛푑푎푟푑 푓표표푑

ꢀꢁꢂꢃ ꢄꢅ ꢆꢇꢈꢉꢊꢈꢋꢊ ꢅꢄꢄꢊ (퐺푙푢푐ꢄꢆꢌ) = 2500

[

(

)

]

[

(

)

]

ꢀꢁꢂꢃ ꢄꢅ ꢇꢌꢆꢇ ꢅꢄꢄꢊ = 0.5 푥 ꢃ₁+ ꢃ₂푥 30 + 0.5 푥 ꢃ₂+ ꢃ₃푥 30 +

[

(

)

]

[

(

)

]

0.5 푥 ꢃ₃+ ꢃ₄푥 30 + 0.5 푥 ꢃ₄푥 30

Simplifying,

(

)

(

)

(

)

ꢀꢁꢂꢃ ꢄꢅ ꢇꢌꢆꢇ ꢅꢄꢄꢊ = 15 푥 + [ꢃ₁+ 2 푥 ꢃ₂+ 2 푥 ꢃ₃+ 2 푥 ꢃ₄]

Where:

C₁− C₄: Feeding interval values

30: Fasting intervals (min)

0.5: Trapezoidal constant

IAUC: Incremental area under curve

Therefore, Glycemic load (GL) can be calculated as:

퐺ꢀ 푥 ꢁ푣ꢈ푖푙ꢈ푏푙ꢌ 푐ꢈꢋ푏ꢄℎ푦ꢊꢋꢈꢇꢌ 푝ꢌꢋ ꢆꢌꢋ푣푖ꢉ푔 (푔)

퐺퐿 =

100

Experimental design and statistical analysis

The experimental design used in this study is completely randomized design (CRD). Statistical Package for

Service Solution (SPSS) version 25 was used for statistical analysis. Data generated from the study were

subjected to descriptive analysis and the means were treated with One – way ANOVA and means separation was

done using Duncan Multiple Range Test (DMRT) to determine significant differences (p < 0.05)

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Figure 1: Production of high-fiber noodles

RESULTS AND DISCUSSIONS

Cooking quality of the noodles

The cooking qualities of noodles, including cooking time, cooking loss, water uptake, and bulk density, are

presented in Table 1. These properties influence texture, structure, and the retention of nutrients, particularly in

composite flour formulations that modify the physical characteristics of traditional wheat-based noodles.

Cooking time

Cooking time is an essential parameter for evaluating noodle quality, as it influences texture, digestibility, and

consumer convenience. The results showed that the cooking time of the composite noodles (WTC1, WTC2, and

WTC3) was 40 minutes, whereas the control sample (WTC4) had a slightly shorter cooking time of 38 minutes.

The longer cooking time in the composite noodles can be attributed to the increased fiber content from tiger nut

and cassava flour, which affects water absorption and starch gelatinization (Adegbanke et al., 2020). Similar

trends were observed by Bai et al. (2019), who reported that high-fiber wheat-based noodles required up to 42

minutes for full hydration and starch gelatinization, compared to 35–38 minutes for conventional wheat noodles.

This prolonged cooking time is beneficial in slowing starch hydrolysis, which may contribute to a lower

glycemic index.

Cooking loss

Cooking loss refers to the amount of solid matter leached into cooking water during boiling, which directly

affects the integrity of the noodle strands. The results showed that WTC3 had the highest cooking loss (0.82 g),

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while WTC4 (control) had the lowest (0.22 g). The higher cooking loss in composite noodles aligns with findings

from Ayo et al. (2021), who observed a cooking loss of 0.75–0.90 g in fiber-enriched noodles. Increased cooking

loss in composite noodles is likely due to reduced gluten content, which weakens the structural network, leading

to increased solubilization of starch and protein components into the cooking water (Osundahunsi et al., 2021).

Although this may affect firmness and texture, it also suggests that composite noodles have higher starch

leaching, which could contribute to a lower glycemic response post-consumption.

Water uptake

Water uptake is a critical functional property that affects the texture and mouthfeel of cooked noodles. The

results showed that water uptake was relatively similar across all samples, ranging from 0.14 to 0.17%. WTC1,

WTC3, and WTC4 exhibited higher water uptake (0.17 %), while WTC2 had the lowest (0.14%). The variation

in water uptake may be due to differences in fiber content and starch composition. Olatunde et al. (2022) reported

that noodles containing up to 20 % tiger nut residue and cassava flour exhibited water uptake levels between

0.15 and 0.18 %, which aligns with the findings of this study. Higher water uptake typically results in a softer

texture, whereas lower water uptake can lead to firmer noodles with increased chewiness, which some consumers

may prefer.

Table 1: Cooking quality of the high-fiber noodles made from wheat, tiger nut residue and cassava flour blends

Sample

Cooking loss

(g)

Water uptake

(%)

Cooking time

(min)

Bulk density

(g/ml)

WTC1

WTC2

WTC3

40.00^a±1.41

40.00^a±0.00

0.43^b±0.01

0.47^b±0.01

0.82^a±0.02

0.17^a±0.01

0.14^a±0.01

0.16^a±0.01

0.26^c±0.01

0.48^b±0.01

0.53^a±0.01

WTC4

LSD

38.00^a±1.41

3.400

0.22^c±0.01

0.044

0.17^a±0.00

0.044

0.49^b±0.00

0.044

Values are means of replicate determinations ± standard deviation. Mean values on the same column with

different superscripts (a, b, c…) are significantly different at p<0.05

WTC1: Noodles made with wheat flour (74.3 %), tiger nut residue (20 %), cassava flour (5.7 %)

WTC2: Noodles made with wheat flour (75 %), tiger nut residue (20 %), cassava flour (5 %)

WTC3: Noodles made with wheat flour (71.86 %), tiger nut residue (18.14 %), cassava flour (10 %)

WTC4: Noodles made with 100 % wheat flour (control)

Bulk density

Bulk density is an important quality parameter affecting packaging, processing, and sensory characteristics of

noodle products. The results showed that bulk density was highest in WTC3 (0.53 g/ml), followed by WTC4

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(0.49 g/ml), WTC2 (0.48 g/ml), and WTC1 (0.26 g/ml). The significantly lower bulk density in WTC1 suggests

that the presence of tiger nut and cassava flour reduced the compactness of the noodle structure, leading to

increased porosity. This finding aligns with the study by Ogunlade et al. (2020), which reported a decrease in

bulk density (0.25–0.30 g/ml) in composite flour noodles due to the incorporation of high-fiber and low-gluten

ingredients. Lower bulk density is desirable for producing light-textured noodles, which may appeal to

consumers looking for softer noodle variants.

Blood glucose responses of high – fiber noodles made from blends of wheat, tiger nut residue and cassava

flours

The blood glucose response to food consumption is a critical indicator of glycemic control, particularly for

individuals with diabetes and metabolic disorders. The postprandial blood glucose response of participants after

consuming noodle samples made from wheat-tiger nut residue-cassava composite flour was recorded. The results

(Table 2) demonstrate that composite flour formulations significantly reduced blood glucose spikes compared

to the control samples (WTC4, made entirely from wheat flour).

Table 2: Blood glucose responses of high – fiber noodles made from blends of wheat, tiger nut residue and

cassava flours

0 min

30 min

60 min

90 min

120 min

(mg/dL)

Sample

(mg/dL)

(mg/d L)

WTC1

WTC2

WTC3

WTC4

LSD

85.85^c±1.10

88.05^c±1.19

92.52^b±3.27

99.12^a±3.91

2.42

95.73^d±1.32

100.98^c±1.44

105.88^b±1.49

111.03^a±0.65

1.15

100.81^d±1.39

105.99^c±1.52

110.37^b±1.79

120.45^a±0.51

1.26

95.9^d±1.50

100.52^c±1.82

106.02^b±1.47

113.72^a±0.69

1.30

86.02^d±1.09

88.38^c±1.10

95.63^b±1.34

101.48^a±0.45

0.95

Values are means of replicate determination ± standard deviation. Mean values on the same column with

different superscripts (a, b, c…) are significantly different at p<0.05

WTC1: Noodles made with wheat flour (74.3 %), tiger nut residue (20 %), cassava flour (5.7 %)

WTC2: Noodles made with wheat flour (75 %), tiger nut residue (20 %), cassava flour (5 %)

WTC3: Noodles made with wheat flour (71.86 %), tiger nut residue (18.14 %), cassava flour (10 %)

WTC4: Noodles made with 100 % wheat flour (control)

The results indicate that WTC1 (74.3% wheat flour, 20% tiger nut residue, 5.7% cassava flour) elicited the

lowest postprandial glucose response at all-time intervals, with blood glucose values increasing from 85.85

mg/dL (0 min) to a peak of 100.81 mg/dL (60 min), before decreasing to 86.02 mg/dL (120 min). This was

followed by WTC2 (75% wheat, 20% tiger nut, 5% cassava), which peaked at 105.99 mg/dL at 60 min and

dropped to 88.38 mg/dL at 120 min (Table 2).

The noodle samples followed a trend with WTC1 (74.3% wheat flour, 20% tiger nut residue, 5.7% cassava flour)

eliciting the lowest glucose response, peaking at 100.81 mg/dL at 60 min before declining to 86.02 mg/dL at

120 min. WTC2 and WTC3 showed moderate glucose responses, with peak values of 105.99 mg/dL and 110.37

mg/dL at 60 min, respectively. The highest glucose response was recorded in WTC4 (wheat-only control), where

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blood glucose levels surged to 120.45 mg/dL at 60 min and remained elevated (113.72 mg/dL) at 90 min, until

its decline at 101.48 mg/dL at 120 min confirming that wheat-based noodles have a high glycemic impact.

The significantly lower blood glucose response in WTC1 compared to WTC4 is consistent with findings by

Olatunde et al. (2022), who reported that fiber-enriched noodles exhibited peak glucose values of 100–110

mg/dL, whereas refined wheat noodles reached 140 mg/dL. The higher fiber content (up to 5.21%) in composite

flour noodles likely slowed glucose absorption and gastric emptying, contributing to better blood sugar

regulation (Ogunlade et al., 2020).

Notably, the control noodle (WTC4) demonstrated a more pronounced and prolonged glycemic response

compared to control waffle cone (WTC4). This aligns with research by Osundahunsi et al. (2021), who found

that wheat noodles tend to have a higher glycemic impact than pastries like waffle cones due to faster starch

gelatinization and greater digestibility. The greater surface area of noodles increases starch exposure to digestive

enzymes, leading to a more rapid glucose release (Nwosu et al., 2021).

Glycemic index and glycemic load of high – fiber noodles made from blends of wheat, tiger nut residue

and cassava flour blends

The glycemic index (GI) and glycemic load (GL) of the high – fiber noodles are shown in Tables 3. GI is a

measure of how quickly carbohydrates in food raise blood glucose levels, while the glycemic load (GL) considers

both the GI and the carbohydrate content per serving, providing a more accurate assessment of a food’s impact

on blood sugar (Jenkins et al., 2019). Foods with a low GI (≤55) are digested and absorbed slowly, leading to

gradual increases in blood glucose levels, while those with a medium GI (56 – 69) and high GI (≥70) cause more

rapid glucose spikes. Lower GI and GL foods are beneficial for individuals managing diabetes, obesity, and

other metabolic disorders (Bolarinwa et al., 2019).

Table 3: Available carbohydrates, glycemic index and glycemic loads of high – fiber noodles made from

optimum blends of wheat, tiger nut residue and cassava flours

Samples Available Carbohydrates (g/ 100g) Glycemic index Glycemic load

WTC 1

WTC 2

WTC 3

WTC 4

25.90

26.20

30.37

35.72

36.14

44.65

49.17

53.09

9.36

11.70

14.93

18.96

WTC1: Noodles made with wheat flour (74.3 %), tiger nut residue (20 %), cassava flour (5.7 %)

WTC2: Noodles made with wheat flour (75 %), tiger nut residue (20 %), cassava flour (5 %)

WTC3: Noodles made with wheat flour (71.86 %), tiger nut residue (18.14 %), cassava flour (10 %)

WTC4: Noodles made with 100 % wheat flour (control)

The GI and GL values of the noodle samples followed a similar trend with composite flour formulations, showing

significantly lower glycemic responses compared to the wheat-based control (WTC4). The GI of the noodle

samples ranged from 36.14 (WTC1) to 53.09 (WTC4), while the GL varied from 9.36 (WTC1) to 18.96 (WTC4)

with corresponding available carbohydrates of 25.90 g/ 100g (WTC1) to 35.72 g/ 100g (WTC4) per serving

(Table 3). WTC1 had the lowest GI (36.14) and GL (9.36), making it a low-GI food. This suggests that

incorporating 20% tiger nut and 5.7% cassava flour into wheat-based noodles significantly slows glucose release,

similar to findings by Olatunde et al. (2022), who reported that tiger nut-enriched noodles had a GI of 34.50.

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The reduction in glycemic response is attributed to the high insoluble fiber and resistant starch content in tiger

nut and cassava flour, which delay carbohydrate digestion and absorption (Ogunlade et al., 2020).

WTC2 and WTC3 also exhibited low GI values (38.61 and 48.23, respectively), suggesting that even lower

proportions of tiger nut and cassava flour can still offer glycemic benefits. These values are similar to commercial

whole-grain pasta, which has a GI of 50–55 (Osundahunsi et al., 2021). Comparably, WTC4 (control) still had

a low GI (53.09) and medium GL (18.96), categorizing it as a low-GI food with medium GL. The GI in WTC4

was higher than WTC1 – WTC3 due to rapid starch gelatinization during cooking which makes wheat-based

noodles highly digestible, leading to quick glucose release into the bloodstream (Nwosu et al., 2021). The

practical implication of these findings is that replacing part of the whole wheat flour with tiger nut and cassava

flour significantly improves the glycemic properties of noodles, making them more suitable for individuals with

diabetes or those seeking better blood sugar control. Additionally, low-GI noodles contribute to prolonged satiety

and steady energy release, which can be beneficial for athletes and individuals looking for sustained energy

throughout the day (Bai et al., 2019).

CONCLUSION

This study evaluated the cooking quality, fasting blood glucose, glycemic index and load of high-fiber noodles

made from wheat, tiger nut residue and cassava flour blends. High fiber inclusion, up to 20 % was achieved

presenting an excellent option for formulating healthier noodles. The cooking quality of noodles, such as bulk

density, cooking time, and water uptake, were influenced by the flour composition, indicating that slight

modifications could enhance further, the texture and cooking performance. The glycemic index and load of the

products showed a clear nutritional advantage of the composite formulations over the wheat control formulation

making them more suitable for individuals managing diabetes, obesity, and other related metabolic disorders.

Declarations

Funding Declaration

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest Statement

The authors declare no conflict of interest.

Consent to Publish Declaration

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable

request.

Transparency statement

The lead author Godswill Kodili Elemuo affirms that this manuscript is an honest, accurate, and transparent

account of the study being reported; that no important aspects of the study have been omitted; and that any

discrepancies from the study as planned (and, if relevant) have been explained.

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