Abstract-- Pumpkin (Cucurbita moschata) is a fruit that contains a large amount of dietary fiber. In this study, noodles were produced by substituting a part of wheat flour with pumpkin powder at two concentrations (5% and 10%). Sensory, physicochemical, microstructure, and cooking analyzes were perform-ed on the resulting noodles. The addition of pumpkin powder caused a significant increase in ash, dietary fiber, Mg, K and Zn content, cooking loss, water absorption capacity and adhesiveness values, and a significant decrease in the protein, fat and carbohydrate content and energy value. The cohesiveness, resilience, gumminess, springiness, and chewiness values also decreased significantly. It was determined from microstructure images that the addition of pumpkin powder to the noodle formulation led to an interruption in the gluten-starch matrix. The color analysis revealed the control sample to have significantly lower a* and b* values and higher L* values than the enriched samples. Finally, the noodles made with pumpkin powder received significantly higher sensory scor-es in terms of overall acceptability, flavor and color.
Keywords-- Pumpkin Powder, Enrichment, Noodle, Dietary Fiber
I. INTRODUCTION
Pumpkins, which belong to the Cucurbitaceae family, come in four main types: Cucurbita. moschata, C. mixta, C. maxima and C. pepo (Rakcejeva et al., 2011). Pumpkins are an excellent source of dietary fiber (DF) (Norfezah et al., 2011), which are usually grouped into two classes based on their water solubility: insoluble dietary fibers (IDF), including lignin, some hemicelluloses and celluloses; and soluble dietary fibers (SDF), including mucilages, gums, pectins, β- glucans and some resistant starches (Kulaitiene et al., 2014; Soliman, 2019). The two groups of dietary fibers (SDF and IDF) perform different functions in the human body. SDF has physiological functions, such as lowering cholesterol levels and enhancing glucose tolerance. In addition, SDF plays a critical role in the regulation of metabolic function, while IDF can promote intestinal peristalsis and increase the volume of feces, thus prevent diarrhea, constipation and bowel cancer (Li et al., 2019). The recommended daily intake (RDI) of DF is 36 and 28 g/day for adult males and females, respectively (Anderson et al., 2009). Sufficient DF intake reduces the progress of some diseases, such as obesity, diabetes, certain gastrointestinal disorders, hypertension, stroke and coronary heart disease. Furthermore, DF can modify the sensorial, rheological and textural properties of enriched foods. A rich DF content can contribute to the hydration features of food. The hydroxyl groups in the fiber structure permit more water interactions through hydrogen bonding (Aydin and Gocmen, 2015; Anderson et al., 2009; Rosell et al., 2009). In pumpkin, the DF is primarily lignin, pectin, hemicellulose and cellulose, although the DF content of pumpkins is dependent on the cultivar (De Escalada Pla et al., 2007; Cerniauskiene et al., 2014; Mirhosseini et al., 2015).
Pumpkins are also rich in carotenoids, and some minerals (K, P, Fe, Mg) and vitamins (K, E, C, B6, B2, B1, A) (Ahmed et al., 2014; Cerniauskiene et al., 2014; Seremet et al., 2015). Carotenoids, especially b-carotene, contribute to the color of pumpkins and to the formation of the attractive yellowish color in enriched foods. They are an excellent source of vitamin A (Noor Aziah and Komathi, 2009). Minerals play a significant role in the human body, affecting the usage of vitamins, and are fundamental components of nerve cells, blood, muscles, soft tissues, teeth and bones (Kulaitiene et al., 2014).
Their rich nutrient content makes pumpkins important resources for food enrichment. Generally, pumpkin in puree and powder forms is used for the production of such foods as desserts, sauces, bread, pasta, biscuits and noodles (Ahmed et al., 2014; Kulkarni and Joshi, 2013).
Noodle is one of the most popular traditional foods, and is produced mainly from three ingredients: flour, salt and water (Kong et al., 2012; Fu, 2008). Noodles have gained popularity due to their flavor, low cost and facilitation of preparation and transportation, although they are often deficient in such fundamental nutritional components as DF (Pu et al., 2017; Koca et al., 2018). Nowadays, consumers are considering secondary properties of food, such as their functional and nutritional aspects. As a result of the growing health concerns and the expansion of the marketing of functional foods, noodles have been enriched with such ingredients as black rice bran, apple fiber, beetroot and banana flour, aiming to take advantage of their secondary benefits (Kong et al., 2012; Yuksel and Gurbuz, 2019; Chhikara et al., 2019; Choo and Aziz, 2010).
The aim of this research was evaluated the nutritional potential of noodles supplemented with pumpkin powder. For this, the maximum substitution level of pumpkin powder leading to the improvement in nutritional properties was investigated, along with the influence of the enrichment on the sensory, cooking, textural and microstructural qualities.
Table 1. Formulations of Noodle Samples
|
Noodle samples* |
Ingredients (%) |
|||
|
Wheat flour |
Pumpkin Powder |
Salt |
Water |
|
|
C |
100 |
0 |
1 |
40 |
|
PP5 |
95 |
5 |
1 |
42 |
|
PP10 |
90 |
10 |
1 |
45 |
*C: Control, PP5: 5% of wheat flour was substituted with pumpkin powder, PP10: 10% of wheat flour was substituted with pumpkin powder
II. METHODS
A. Materials
Pumpkins (Cucurbita moschata), wheat flour (WF) and salt were acquired from local markets in Denizli (Turkey).
The pumpkins were cut into 0.5 cm slices and dried in a hot air dryer (Yucebas Machine Analytical Equipment Industry, Turkey) at 50±2°C until a ˂15% moisture content was achieved. The airflow rate in the dryer was 0.2 m/s and the relative humidity of the air was in the range of 19–21%. After drying, the pumpkins were ground to powder of a ˂500 µm particle size.
B. Noodle Preparation
Pumpkin powder (PP) was substituted at rates of 5% and 10% to the WF. The optimum amount of water for each formulation was detected in preliminary tests, and the formulations of the noodles are given in Table 1. The PP, WF, salt and water were mixed in a dough mixer (Kitchen Aid Professional 600, Ml, USA) for 10 min. The thickness of the dough was reduced to 1 mm using reduction rollers that were used to shape the dough. The noodles were dried at room temperature until a ˂10% moisture content was reached.
C. Proximate Composition Analysis
The crude protein (N%×5.7), ash, moisture and fat content of the PP, WF and noodles were analyzed using AOAC (1990) methods. The IDF and SDF content were determined with a total dietary fiber (TDF) assay kit (Megazyme Inc., Ireland) in accordance with the AOAC (1995) 991.43 and AACC (1995) 32-07 methods. The carbohydrate content was calculated by difference [100-(protein+moisture+ash+fat+TDF)]. Energy value (EV) was calculated using the following eq.1 (Souci et al., 2000):
D. Mineral Matter Content
The mineral matter content (P, K, Mg, Zn, Fe) of the raw materials and noodles were determined through Inductively Coupled Plasma Optical Emission Spectrometry (Optima 8000, Perkin Elmer, USA) and the method described by Isik and Topkaya (2016).
E. Microstructure Analysis
The raw noodles were freeze dried in a Savant Modulyod-230 freeze dryer (Thermo Electron Co., USA), and then coated with gold in a Quorum Q150R ES model high vacuum sputter-coating machine for 120 s (Quorum Tech., UK). The external microstructures of the noodles were analyzed using a Zeiss Supra 40 VP model Field Emission Scanning Electron Microscope (Carl Zeiss GmbH, Germany).
F. Cooking Quality
The optimum cooking time (OCT), Cooking loss (CL), Swelling index (SI) and Water absorption capacity (WAC) of the noodle samples were evaluated according to the AACC (2000), Piwinska et al. (2016), Ozgoren and Yapar (2019) and Marti et al. (2013), respectively.
E. Texture Analysis
A CT3 model texture analyzer (Brookfield Eng. Lab. Inc., USA) was equipped with a 25.4 mm diameter cylindrical probe (TA 3/100) for a measured texture profile analysis (TPA) of the cooked noodle. Accordingly, three strands of cooked noodle were placed perpendicularly to the probe and compressed twice at a constant rate of deformation (1 mm/s) to 70% of the initial noodle thickness. TPA curve was using for the calculating hardness, chewiness, cohesiveness, resilience, gumminess, springiness and adhesiveness (Epstein et al., 2002).
F. Color Measurement
The colors (L*, a*, b*) of the noodles and raw materials were measured using a colorimeter (Miniscan XE, Hunter Assoc. Lab., Reston, Virginia, USA).
G. Sensory Analysis
The noodles were cooked for the OCT and drained, and 48 semi-trained panelists from the Pamukkale University, Department of Food Engineering (27 females, 21 males, aged 20–50 years) were participated in the sensory analysis. The samples were evaluated for overall acceptability, texture, flavor, odor and color on a seven-point hedonic rating scale, in which a score of 7 denoted like extremely, and 1 denoted disliked extremely. The noodles were numbered with arbitrarily selected three-digit numerical codes, and the final scores of the different samples were the average of the 48 scores.
H. Statistical Analysis
All tests were performed in triplicate. Experimental data was statistically analyzed using IBM SPSS Statistics, Version 22.0 (IBM Corp., Armonk, NY, USA). Tukey’s multiple range test was performed, and any differences among the values were considered significant at p˂0.05.
III. RESULTS
A. Raw Materials (WF and PP)
Table 2 shows the moisture, protein, fat, ash, TDF, SDF, IDF, carbohydrate, P, Mg, K, Zn and Fe content, energy value and hunter color values (L*, a*, b*) of the WF and PP. As can be seen from the results, PP contains higher contents of P, Mg, K, Zn, Fe, ash, IDF, SDF than WF, but lower energy values and carbohydrate, fat and protein content. The color measurement showed PP to have higher a* and b* values and lower L* values than WF.
It has been reported in previous studies that PP has a
12.57–44.6% total dietary fiber, 0.89–7.70% ash content, 0.07–3.74% fat
content, 1.41–9.63% protein content and 55.30–79.57% carbohydrate content in
dry basis (Pong-
Table 2. Chemical and physical properties of WF and PP
|
|
WF |
PP |
|
Moisture (%) |
9.30±0.20 |
11.51±0.17 |
|
Protein (%)1 |
9.95±0.01 |
8.29±0.18 |
|
Fat (%)1 |
1.32±0.06 |
0.67±0.03 |
|
Ash (%)1 |
0.90±0.03 |
6.38±0.24 |
|
TDF(%)1 |
2.89±0.05 |
28.40±1.13 |
|
SDF (%)1 |
1.36±0.08 |
6.60±0.14 |
|
IDF (%)1 |
1.53±0.04 |
21.80±0.99 |
|
Carb(%)a1 |
75.65±0.08 |
44.76±1.05 |
|
Energy Value (kcal/100g) 1 |
354.26±0.76 |
218.19±4.67 |
|
P (ppm) |
2322.00±116.00 |
2745.00±120.20 |
|
Mg (ppm) |
827.00±26.90 |
1782.00±53.70 |
|
K (ppm) |
3325.00±106.10 |
24383.00±739.60 |
|
Zn (ppm) |
18.80±1.70 |
59.30±2.70 |
|
Fe (ppm) |
30.7±2.3 |
57.9±3.1 |
|
Hunter color values |
|
|
|
L* |
85.91±0.05 |
67.95±1.06 |
|
a* |
0.09±0.02 |
26.19±0.46 |
|
b* |
18.52±0.05 |
44.14±0.20 |
1: In wet basis a: Carbohydrates except dietary fibers
janta et al., 2006; Noor Aziah and Komathi, 2009; Saeleaw and Schleining, 2011; Jacobo-Valenzuela et al., 2011; Mirhosseini et al., 2015; Minarovicova et al., 2017; de Escalada Pla et al., 2007). The total dietary fiber, ash, fat, and protein content recorded in the present study were 32.09%, 7.21%, 0.76% and 9.37% in a dry basis, respectively, which are similar to the results of the previous studies noted above. In contrast, the carbohydrate content was 50.58% in dry basis, which is lower than in the previous studies.
The mineral matter composition of PP has been investigated in earlier studies. Jacobo-Valenzuela et al. (2011) reported the content of P, Mg, K, Zn and Fe to be 3040.48 ppm, 1590.40 ppm, 42194.00 ppm, 23.88 ppm and 31.69 ppm, respectively, in winter pumpkin pulp. The mineral composition results in the present study partially agree with the findings of Jacobo-Valenzuela et al. (2011). The mineral matter content of food may change as a result of several factors, including food variety, climatic conditions and the mineral matter properties of the soil (Pinto et al., 2014).
B. Proximate composition of noodle samples
Proximate compositions(energy values and fat, protein, moisture, ash, TDF and carbohydrate content) of the noodle samples are presented in Table 3.
The moisture content of the noodle samples was statistically similar (p˃0.05), and while the carbohydrate, fat and protein content and energy values were decreased, the ash, IDF and SDF content increased as the substitution ratio of PP increased.
The results reveal the PP10 sample to have nearly 2.6
and 1.8 times the IDF and SDF content of the C sample, respectively. DF is
necessary for good health (Cerniaus-kiene et al., 2014), playing an
important role in the prevention of colon cancer, heart disease, obesity and
diabetes. Sufficient dietary fiber intake is vitally important for a healthy
life (Kulaitiene et al., 2014). The RDI of DF is 28–36 g/day for adults
(Anderson et al., 2009). Assuming
Table 3. Proximate composition of noodle samples*
|
Parameters |
C |
PP5 |
PP10 |
|
Moisture1 |
7.85±0.09a |
7.88±0.05a |
7.71±0.06a |
|
Protein1 |
9.60±0.01a |
9.31±0.01b |
9.27±0.01c |
|
Fat 1 |
1.29±0.05a |
0.96±0.05b |
0.89±0.01b |
|
Ash1 |
1.06±0.02c |
1.56±0.01b |
2.33±0.09a |
|
TDF1 |
3.08±0.06c |
5.51±0.04b |
6.91±0.11a |
|
SDF1 |
1.43±0.14b |
2.10±0.03a |
2.64±0.22a |
|
IDF1 |
1.65±0.08c |
3.41±0.01b |
4.28±0.33a |
|
Carba,1 |
77.15±0.13a |
74.80±0.01b |
72.91±0.05c |
|
Energy Value2 |
358.53±0.95a |
345.04±0.33b |
336.69±0.10c |
*Different superscript letters (a, b,…) in row are significantly different (p < 0.05)
a Carbohydrates except dietary fibers 1In wet basis(%) 2kcal/100g
Table 4. Mineral matter contents of noodle samplesa
|
Mineral (ppm) |
C |
PP5 |
PP10 |
|
P |
2597.0±141.4a |
2605.0±70.7a |
2743.0±155.6a |
|
Mg |
828.0±31.1b |
868.0±14.1ab |
954.0±22.6a |
|
K |
3433.0±117.4c |
4735.0±108.9b |
5909.0±213.5a |
|
Zn |
18.6±1.1b |
27.7±2.7ab |
36.7±4.1a |
|
Fe |
33.6±3.7a |
35.5±3.5a |
38.4±2.7a |
aDifferent superscript letters (a, b,…) in row are significantly different (p < 0.05)
an individual should have a daily DF intake of 32 g/day, a portion (100 g) of the PP10 sample provides nearly 21.6% of this requirement for an adult.
The ash content of the enriched samples was 2.2 (PP10) and 1.5 (PP5) times higher than that of the C sample, which can be attributed to the rich ash content of PP (Table 2).
C. Mineral Matter Content
The mineral matter contents of the noodles are presented in Table 4. The Mg, K and Zn contents increased with the supplementation of PP (p<0.05), which can most likely be attributed to the higher mineral matter content of PP than WF (Table 2).
Minerals are inorganic substances that are found naturally in a variety of foods, and that play key roles in the functioning of the human body and in a healthy and long life. The presence of certain minerals can not only lead to the development of particular hormones but can also regulate the standard heartbeat. They are also involved in bone health, enzyme activation, oxidative phosphorylation, oxygen transport and nerve impulse conduction (Gharibzahedi and Jafari, 2017; Isik and Yapar, 2017).
The RDI of P, Mg, K, Zn and Fe are 1250 mg, 420 mg, 4700 mg, 11 mg and 18 mg, respectively, for adults (FDA, 2020). The consumption of the one portion (100 g) of the C noodle provides nearly 20.8%, 19.7%, 7.3%, 16.9% and 18.66% of the RDI of P, Mg, K, Zn and Fe, respectively. The addition of PP to the formulation were increase the percentages of meeting the mineral daily needs. One portion of PP10 noodle provided nearly 21.9% of the P, 22.7% of Mg, 12.6% of K, 33.4% of Zn and 21.3% of Fe of the RDI of an adult.
D. Microstructure Analysis
SEM images of the surface microstructures of raw noodles are presented in Fig 1.
|
|
|
|
|
|
Fig. 1. Surface SEM images of a. Control, b. PP5, c. PP10
SEM images demonstrate the arrangement of the starch and gluten network in the noodle (Rajeswari et al., 2013). Starch and gluten play a critical role in supporting the protein network responsible for stability (Sun et al., 2019). A homogeneous structure was observed in the control sample image, in which the protein-starch matrix can be seen to be well-formed. The numerous starch granules, which appear to vary in both size and shape, were monitored in the micrograph of the freeze-dried control sample (Fig. 1.a), as observed also by Alireza Sadeghi and Bhagya (2008). When semolina was replaced by PP, the noodle samples showed a more irregular and rougher surface. The addition of PP to the formulation appeared to disrupt the protein–starch matrix (Fig. 1.b, 1.c), and this phenomenon also supported the change in the hardness value.
Previous studies have reported similar effects on noodle microstructures (Aravind et al., 2012; Tudorica et al., 2002; Manthey and Schorno, 2002).
E. Cooking Quality
Cooking quality parameters such as OCT, CL, SI and WAC have a major influence on the overall quality assessment of noodles (Panghal et al., 2019). The cooking quality parameters of the noodles are presented in Table 5.
Table 5. Cooking quality parameters of noodle samplesa
|
Samples |
C |
PP5 |
PP10 |
|
OCT (min) |
7.00±0.71a |
6.75±1.06a |
6.25±0.35a |
|
CL (%) |
5.10±0.23c |
6.51±0.15b |
7.95±0.42a |
|
SI |
1.77±0.02a |
1.81±0.09a |
1.97±0.01a |
|
WAC (%) |
131.25±1.21b |
134.89±2.09b |
141.63±0.76a |
aDifferent superscript letters (a, b,…) in row are significantly different (p < 0.05).
The OCT is related to the starch gelatinization and water penetration rate (Liu et al., 2016), and ranged from 7.00 to 6.25 min. in the present study. Although the OCT of the PP-added samples was lower than those of the C sample, the values were not significantly different (p>0.05). Similar changes observed by Minarovicova et al. (2017) who reported that the addition of 10% pumpkin powder to the pasta formulation decreased the OCT by nearly 15%.
CL refers to the amount of solids that diffuse out from the noodle samples into the boiling water during cooking (Espinosa-Solis et al., 2019). For the C sample, CL value was 5.10%, whereas for PP10 the value was 7.95%. When compared to the C sample, CL was significantly higher in the PP-added samples, although it was found that all of the CL values of the noodles were below the acceptable limit of 9% (AACC, 2000). An increase in the proportion of PP in the formulation results in a decrease in the amount of WF-based components, such as gluten, in noodles, which leads to a weakening of the gluten network (Ozgoren and Yapar, 2019). Similar results were reported previously by Minarovicova et al. (2017), Aydin and Gocmen (2011) and Ovando-Martinez et al. (2009), all of whom reported that samples supplemented with pumpkin powder, oat flour and banana flour had higher CL values than the control sample.
SI and WAC are related to the tolerance of the noodle to cooking and the degree of hydration (Pasqualone et al., 2016). The SI ranged from 1.77 to 1.97, although there was no significant difference (p>0.05) in the values among the samples. The WAC values of the samples ranged between 131.25% and 141.63%, and increasing the PP ratio in the noodle formulation was found to increase the WAC of the samples (p˂0.05), which can be attributed to the hydrophilic properties of PP. In previous studies, the increases in SI and WAC were explained by the greater capacity of DF to absorb and retain water within the protein-starch-polysaccharide network than the C sample (Foschia et al., 2015).
F. Texture Analysis
The textural properties of noodles are affected by the matrix network of fibers, proteins, glutens, starches and other ingredients (Kong et al., 2012). The textural properties of the noodles are presented in Table 6.
Hardness is detected instrumentally as the peak force
of compression. A good quality noodle should have a high degree of hardness
(Udachan and Sahoo, 2017). In the present study, the hardness values of samples
decreased as the PP ratio increased, although no significant (p>0.05)
difference was detected between the three kinds
Table 6. Textural properties of noodle samplesa
|
Textural Properties |
C |
PP5 |
PP10 |
|
Hardness (N) |
2.45±0.16a |
2.31±0.14a |
2.20±0.07a |
|
Resilience |
0.38±0.04a |
0.32±0.04ab |
0.28±0.06b |
|
Cohesiveness |
0.76±0.02a |
0.65±0.07b |
0.60±0.02b |
|
Gumminess (N) |
2.06±0.13a |
1.79±0.20ab |
1.67±0.12b |
|
Springiness (mm) |
0.37±0.02a |
0.33±0.02b |
0.32±0.02b |
|
Chewiness (mJ) |
0.77±0.05a |
0.57±0.09b |
0.53±0.06b |
|
Adhesiveness (mJ) |
0.05±0.03b |
0.08±0.03ab |
0.12±0.02a |
aDifferent superscript letters (a, b,…) in row are significantly different (p < 0.05)
Table 7. Color values of noodle samplesa
|
Samples |
|
L* |
a* |
b* |
|
C |
Raw Noodle |
75.02±0.28a |
3.09±0.05c |
22.00±0.31b |
|
PP5 |
73.14±0.08b |
12.27±0.01b |
39.10±0.04a |
|
|
PP10 |
70.03±0.62c |
18.31±0.21a |
39.16±0.76a |
|
|
C |
Cooked Noodle |
72.24±0.53a |
0.56±0.08c |
22.31±0.09b |
|
PP5 |
64.57± 0.11b |
10.80± 0.91b |
38.41±0.71a |
|
|
PP10 |
60.85±1.20c |
15.61±0.64a |
38.14±0.76a |
aDifferent superscript letters (a, b,…) in column are significantly different (p < 0.05)
of noodles. This result is similar with the research of Espinosa-Solis et al. (2019), who reported no statistical difference between the hardness values of their oat bran-added sample and a control sample.
Resiliency is the ratio of recoverable energy after the initial compression is relieved (Epstein et al., 2002), while cohesiveness, is defined as the ability of a material to stick to itself, and is related to the force of the internal bonds holding the noodle structure together (Pasqualone et al., 2016; Epstein et al., 2002). The resilience and cohesiveness values of the noodle samples were in the ranges of 0.28–0.38 and 0.60–0.76, respectively (Table 6). Resilience and cohesiveness decreased as the supplementation ratio of PP increased (p˂0.05). Sozer et al. (2007) reported that the addition of bran to a spaghetti formulation decreased cohesiveness due to the diluting effect on the gluten network.
Gumminess is calculated by multiplying hardness by cohesiveness (Epstein et al., 2002). The addition of PP decreased (p˂0.05) the gumminess of the noodles in the present study, and similar results were reported by Kong et al. (2012), who found that the supplementation of black rice bran to a noodle formulation decreased the gumminess values of the enriched samples.
Springiness is related to the protein-starch matrix. The supplementation of PP significantly decreased (p˂0.05) the springiness of the noodles, which may be due to the decreased gluten in the noodle formulation. Bustos et al. (2011) investigated the effect of different types of DF on some textural properties of pasta, and determined that the springiness values decreased with the addition of inulin and oat bran to the pasta formulation.
Chewiness is correlated with the elastic strength of the protein matrix (Sozer et al., 2007). Chewiness values decreased from 0.77 mJ (C sample) to 0.53 mJ after the addition of 10% PP in the present study. Pasqualone et al. (2016) determined that pasta samples enriched with bran oleoresin had lower chewiness values than their control sample.
Adhesiveness is associated with the amount of starch
and the level of starch gelatinization (Sozer et al., 2007).
Table 8. Sensory properties of noodle samplesa
|
Sensory properties |
C |
PP5 |
PP10 |
|
Color |
4.21±0.01b |
4.52±0.08a |
4.65±0.09a |
|
Odor |
4.56±0.03a |
4.61±0.09a |
4.83±0.35a |
|
Flavor |
4.17±0.18b |
4.36±0.04ab |
4.64±0.01a |
|
Texture |
4.59±0.23a |
4.60±0.11a |
4.56±0.03a |
|
Overall acceptability |
4.30±0.07b |
4.52±0.03ab |
4.61±0.09a |
aDifferent superscript letters (a, b,…) in columns indicate statistical differences (p < 0.05)
The adhesiveness values of noodles increased 1.6- and 2.4-fold with the supplementation of 5% and 10% PP to the formulation, respectively. The higher WAC values of the enriched samples than that of the control may have led to the increase in adhesiveness (Simonato et al., 2019). Tudorica et al. (2002) reported inulin-added pasta to have higher adhesiveness values than their control sample.
G. Color Measurement
Noodle color is an important quality factor in consumer preference, with a bright yellow color generally being preferred by consumers (Choy et al., 2013; Petitot et al., 2010). The color properties of the noodles are reported in Table 7.
The color values indicate that the PP-added samples have more redness (a*) and more yellowness (b*), but less lightness (L*) values than the control sample. The color changes were found to be related to the original color of the raw materials (PP and WF) (Table 2). These results were similar to those of Pongjanta et al. (2006), who used pumpkin powder to enrich different bakery products, and found that all enriched products (cookies, chiffon cake, butter cake, sweet bread and sandwich bread) had higher a* and b* values and lower L* values than the control samples.
The color differential index (ΔE) defines the color changes between the control sample and the enriched samples (Ozgoren and Yapar, 2019). The ΔE values of noodles increased with increasing supplementation levels of PP. The color differential indexes of the cooked and raw noodles were in the range of 20.56–24.64 and 19.49–23.47 respectively. According to the Handbook of Colour Science (Yamauchi, 1989), all of the enriched samples (raw and cooked) were classified as “another color group”. Similar results were observed by Desai et al. (2018), who reported that the fortification of noodles with fish powder increased ΔE values.
H. Sensory Analysis
Sensory analyses are applied for the definition and scientific measurement of the attributes of a product perceived by the senses: touch, taste, smell and sight (Carpenter et al., 2000). Ingredients added during enrichment should not cause any undesirable change in the sensory properties of food (Kruger, 1996). The noodles in the present study were evaluated for overall acceptability, texture, flavor, odor and color by a team of panelists. The results are presented in Table 8.
No difference (p>0.05) was reported in the odor and textural properties of the noodle samples, while PP10 sample scored significantly higher (p<0.05) in terms of overall acceptability, color and flavor compared with the control sample. The highest scores were determined in the 10% PP-added noodle sample, which was identified as the most desirable noodle. These results are similar to those of Minarovicova et al. (2017), who also reported 10% PP-added pasta to be the most acceptable. In another study, cookies, chiffon cake, butter cake, sweet bread and sandwich bread enriched with PP, and it was reported that substituting a proportion of WF with PP in cookies, sandwich bread and sweet bread were acceptable at a 10% level, and at a 20% level in chiffon cake and butter cakes (Pongjanta et al., 2006).
IV. CONCLUSIONS
Food enrichment studies have increased significantly with the improvement in consumer knowledge and healthy eating awareness in recent years. PP can be added to several foods and is an excellent source of DF. The present research has demonstrated the potential use of PP in noodles. It was observed that enrichment with PP enhanced the dietary fiber, Mg, K and Zn content of the noodles, with a portion of 10% PP-added noodles providing nearly 21.6% of dietary fiber, 22.7% of Mg, 12.6% of K and 33.4% of Zn of the recommended daily intake for adults. Besides nutritional enrichment, a desirable bright yellow color was also obtained by the addition of PP. The sensory analysis revealed that scores of overall acceptability, flavor and color were increased significantly with the addition PP to the formulation, and significant changes were also determined in the cooking quality. Increasing the PP ratio in the noodle formulation was found to increase the WAC and CL of the noodle samples, although all CL values of the noodle samples were found to be below the acceptable limit of 9%.
Consequently, it can be concluded that PP can be added in quantities of up to 10% to noodle formulations, leading to improved nutritional and sensory properties without adversely affecting the cooking properties of the noodles.
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Received: August 2, 2021
Sent to Subject Editor: September 16, 2021
Accepted: February 27, 2022
Recommended by Subject Editor Sebastián Collins