Development and evaluation of some physicochemical qualities, antioxidant properties, and sensory attributes of functional cookies from breadnut seeds flour supplemented with maize and pineapple pomace flours

Abstract

The usage of underutilized and available fruit by-products is a recent trend in food product development. The study investigated the effect of yellow maize flour (YMF) and pineapple pomace flour (PPF) on some physicochemical qualities, antioxidant properties, and sensory attributes of breadnut seeds flour (BSF)-based cookies. The three flours (BSF, YMF, and PPF) were blended, and sixteen runs were generated to develop the functional cookies (FC). These FCs were evaluated for proximate analysis. Three cookie samples: R4 (80.63% BSF; 18.12% YMF; 1.25% PPF), R12 (97.50% BSF; 0.00% YMF; 2.50% PPF) and R13 (95.00% BSF; 0.00% YMF; 5.00% PPF) were selected. The selected samples with control (100% whole wheat flour cookies) were evaluated for some physicochemical, antioxidant properties, and sensory attributes. The ash and fiber contents were significantly higher than the control. Increase in Vit. B₂ and Vit. C was observed as the addition of PPF was higher, while the K was found to be the highest mineral in all the samples. Insoluble dietary fiber was higher than insoluble fiber. The addition of different proportions of PPF to the flour blends significantly (p < 0.05) reduced the in vitro protein digestibility and increased the in vitro starch digestibility of FC. The phenol and DPPH contents increased with a higher proportion of PPF. The color properties showed an increase in L* and b* values due to YMF, while the addition of PPF caused an increase in a* values. The sensory score of the R12 was favorable when compared with the control.

Keywords:

• food product development
• nutrition
• food analysis

PUBLIC INTEREST STATEMENT

Breadnut seeds are indigenous-underutilized vegetable seeds solely used to make soup at home but are rich in fiber and minerals. Yellow maize is gluten-free, contains antioxidant and other health benefits. The utilization of fruit and vegetable by-products in food fortification is a recent trend. Fruit juice companies largely waste pineapple pomace; however, it contains dietary fiber and antioxidants that are good for one’s health. The incorporation of pineapple pomace flour is a potential option for increasing the value of this by-product, encouraging total reliance on natural ingredients from indigenous crops, and producing intriguing functional foods. Each of these flours plays a part in developing a new product (cookies), adding to its chemical and physical characteristics. The nutrient composition, in vitro protein and starch digestibility, and antioxidant properties of breadnut seed-based cookies fortified with yellow maize and pineapple pomace flours were all improved in this study.

1. Introduction

Fruit by-products are widely produced around the world and have been found to be high in phytochemicals that can be exploited to make functional foods (Jiang et al., 2022; Kırbaş et al., 2019). Functional foods have been recognised to be industrially processed or natural foods that have the potential to improve health beyond basic nutrition (Ruiz Rodríguez et al., 2020). Pineapple pomace, a by-product of pineapple juice extraction which is usually discarded, has been recognized for its biological activity as a powerful antioxidant (Chareonthaikij et al., 2016). Fresh pineapple pomace contains 2.84% ash, 0.93% fat, 1.98% protein, and 58.36% total dietary fiber (Montalvo-González et al., 2018). Dietary fiber enhances gastrointestinal and physiological functioning and provides a number of health benefits to humans such as healthy weight, lowering cholesterol, and controlling blood sugar levels. Previous research in this area have shown that pineapple pomace flour has the potential to be used in baked foods such as bread and extruded products (Chareonthaikij et al., 2016; Montalvo-González et al., 2018; Raleng et al., 2019). Cookies, among bakery products, are great for fortification due to their palatability, long shelf life, and universal appeal, making them a good vehicle for delivering a fiber-rich product (Sahni & Shere, 2016).

Cookies are starchy processed foods made out of wheat flour, sugar, and fat that are extensively consumed. The gluten content and higher calorie of wheat flour have prompted researchers to examine the use of indigenous underutilized flours as substitutes for wheat flour such as pearl millet flour supplemented with mung bean and orange-fleshed sweet potato flours in the production of cookies (Bello et al., 2022), or yellow yam, unripe plantain, and pumpkin seed flour blends in biscuit production (Bello et al., 2018). The solution to addressing the nutrient imbalance in cookies is to use natural, cheap, and readily available ingredients containing nutrients such as breadnut seeds, yellow maize, and pineapple pomace (Bello et al., 2021). Breadnut (Artocarpus camansi) seeds have been mostly overlooked, underutilized, and underdeveloped, with its main use being a vegetable stew. Their underutilization is attributed to cultural belief as food for slaves and the poor in Nigeria and other parts of the world, along with their short shelf life after harvest due to a high moisture content of 35–66% (Adeleke & Abiodun, 2010; Rabeta & Syafiqah, 2016).

Although breadnut seeds have been neglected, they have untapped potential which needs to be harnessed. It contains an appreciable amount of macro-mineral, a moderate in essential amino acids, 6.16% protein, and 75% carbohydrates (Alcon et al., 2021). The fat content was reported to be 3.48% and that of ash was 3.43% (Adeleke & Abiodun, 2010). In the Caribbean, immature breadnut seeds are prepared as a unique meal with rice, coconut milk, and even meat (Mohammed & Wickham, 2011). When roasted, preserved in brine, or made into breadnut butter, paste, or oil, can be sold commercially. Additionally, breadnut seeds that have been boiled could be turned into high-value products like a ground paste that can be baked or fried and used to produce palatable high-protein baby foods that are appropriate for use in conventional cuisine and child feeding practices (Nelson-Quartey et al., 2007). It can be preserved using a variety of processing techniques (boiling, roasting, germination, and fermentation). These procedures improve food’s flavor, nutritional content, and other desirable aspects related to feeding, quality, and digestibility. Furthermore, breadnut seeds can be dried, processed into flour, and utilized in the preparation of foods. The potential of breadnut seed flour in the production of cookies has been documented (Go et al., 2015).

Maize (Zea mays) has already been reported to be useful in the production of cookies by Adeyeye and Akingbala (2016), and Paesani et al. (2020). It is a common food source in several regions around the world, thereby contributing in a variety of ways to global agri-food systems and the security of food and nutrition (Grote et al., 2021; Poole et al., 2021). The main chemical component of maize is carbohydrates, particularly starch. This is followed by 6.36% protein, which is the second-most abundant component, along with 4.67% fat and 1.12% ash (Bello & Udo, 2018).

To our knowledge, there is no information on the impact of pineapple pomace flour on breadnut seeds flour and yellow maize flour-based cookies. As a result, the total substitution of wheat flour with these local flour blends in the baking industry can help to ensure food security, boost the use of underutilized crops, reduce postharvest losses, benefit celiac disease patients due to the use of gluten-free ingredients, and surely assist to reduce the cost and importation of wheat in Nigeria. The present study aims to assess the effect of maize and pineapple pomace flours on some physicochemical qualities, antioxidant properties, and sensory attributes of breadnut seeds flour-based cookies.

2. Materials and methods

2.1. Sample collection

The breadnut fruits were collected from a farm located in Ibiono Ibom Local Government Area in Akwa Ibom State. Yellow maize, pineapple fruits, and wheat grains were bought from Itam market, Uyo, Akwa Ibom State alongside additional ingredients used in cookie production (margarine, sugar, egg, milk, baking powder, and salt). Analytical grade reagents were used. These raw materials were chosen because they were readily available, relatively affordable, underutilized, and could produce a sustainable product (cookies).

2.2. Preparation of breadnut seeds flour, yellow maize flour, pineapple pomace flour, and whole wheat flour

The breadnut fruits were fermented in a basin at room temperature so that the seeds could be extracted easily. The seeds were removed, cleaned with potable water, boiled for 1 h, cooled, and dehulled (Noah & Oluwafemi, 2017). The yellow maize grains were manually cleaned by sorting and winnowing to remove husks, stones, cobs, broken grains, and then washed. The mature pineapple fruits were thoroughly cleaned before being peeled using a sterile knife. The peeled pineapples were sliced into small pieces for an easier juice extraction. The juice was extracted with a juice extractor (Model JE-580, Binatone, Hong Kong), and the pomace was collected as described by Sadal et al. (2018). The wheat grains were cleaned by removing dirt such as stones and sticks, and washed in potable water. The dehulled breadnut seeds, cleaned yellow maize, collected pineapple pomace, and cleaned whole wheat grains were dried in a blast air oven (Model K× 350A, Kenxin International Co., LTD, Guangzhou, China) at 60 °C for 24 h, milled in a hammer mill and sieved through a 75 µm mesh sieve. The flours were packaged in airtight bags, labeled, and stored at 4 °C for subsequent use.

2.2.1. Experimental design and treatment combination

A D-optimal mixture of response surface methodology (RSM) (Design expert software version 12.0.3.0 Stat-Ease, version 12) was used to generate the experimental design. Composite flours were formulated by combining the flours in the following range of proportions based on the preliminary study: breadnut seed flour (BSF) (75–100%), yellow maize flour (YMF) (0–25%), and pineapple pomace flour (PPF) (0–5%). Sixteen treatment combinations were developed as presented in Table 1.

Table 1. Experimental design used to produce flour blends (%)

Samples	BSF	YMF	PPF
R1	100.00	0.00	0.00
R2	86.25	11.25	2.50
R3	87.50	12.50	0.00
R4	80.63	18.12	1.25
R5	95.00	0.00	5.00
R6	75.00	22.50	2.50
R7	75.00	20.00	5.00
R8	100.00	0.00	0.00
R9	75.00	25.00	0.00
R10	75.00	20.00	5.00
R11	87.50	12.50	0.00
R12	97.50	0.00	2.50
R13	95.00	0.00	5.00
R14	75.00	25.00	0.00
R15	80.63	15.62	3.75
R16	93.13	5.62	1.25

Note: BSF = breadnut seeds flour; YMF = yellow maize flour; PPF = pineapple pomace flour.

2.2.2. Production of functional cookies and control

The functional cookies and control (100% whole wheat flour cookies) were produced using a modified method as described by Man et al. (2014) by reducing the baking temperature and increasing the time. The margarine (41.25 g) and sugar (25 g) were beaten until light and fluffy. The mixed ingredients (100 g of composite flour, 25 mL of egg, 10 g of powdered milk, 0.9 g of sodium bicarbonate, and 0.5 g of salt) were added to the sweetened margarine and mixed well to form a homogenous dough. Then the dough was kneaded and flattened to a regular thickness before being cut into a uniform shape. Cookie doughs were left to rest for 30 min to allow for optimal development before baking for 45 min at 170 °C. The baked cookies were spread on trays to cool to ambient temperature before being packaged in airtight bags and labeled.

2.3. Chemical composition analyses of functional cookies and control

2.3.1. Proximate composition analysis and total energy values

The moisture, crude protein, crude fat, ash, and crude fiber of the functional cookies and control were determined by following the procedure of Association of Official Analytical Chemists (2006). The difference between 100 and the total content of moisture, crude protein, crude fat, ash, and crude fiber was used to calculate total carbohydrate (CHO) content. Total energy values were calculated as follows:

$\%\text{Total}\text{energy=}(\%\text{protien}\times \text{4})\text{+}(\%\text{fat}\times \text{9})\text{+}(\%\text{cho}\times \text{4})$

2.3.2. Mineral and vitamin composition analyses

The mineral and vitamin analyses were carried out following the procedures of Association of Official Analytical Chemists (2006). The standard flame emission photometer (PFP7 Flame photometer JENWAY, model 410, Staffordshire, UK) was used to determine sodium (Na) and potassium (K). Using an atomic absorption spectrophotometer (AAS Model SP9, Pye UNICAM Ltd., Cambridge, UK), calcium (Ca), manganese (Mn), and iron (Fe) were determined. The fluorimeter was set to excitation wavelength and emission wavelength of 470 nm and 525 nm, respectively, to analyze vitamin B₂ (riboflavin). The 2,6-dichlorophenolindophenol technique was used to determine vitamin C (ascorbic acid).

2.3.3. Determination of dietary fiber, in vitro protein and starch digestibility

The standard gravimetric dietary fiber technique was used to determine the total dietary fiber (Association of Official Analytical Chemists, 2000). In this approach, enzymatic treatment was used to remove carbohydrates and protein and then determined the soluble and insoluble dietary fiber. The method of Alka et al. (2012) was adopted for the determination of in vitro starch digestibility where 50 mg of each of the samples was mixed with 1 mL of 0.2 M phosphate buffer (pH 6.9). A 0.5 mL of pancreatic alpha-amylase (100 unit/mg) was added to the sample and incubated at 37 °C for 2 h. After incubation, 2 mL of 3, 5-DNS reagent was added immediately. The mixture was heated for 5–15 min in a boiling water bath. After heating, 1.0 mL of 40% K-Na tartarate solution was added in the test tubes and allowed to cool. The solution was made up to 25 mL with distilled water and filtered prior to measurement of the absorbance using a spectrophotometer (Model 6305, Dunmow, UK) at 550 nm. The in vitro protein digestibility (IVPD) of the samples was determined by the enzymatic method of Shastry and John (1991). One (1) g of each of the samples was digested with 1 mg pepsin in 15 mL of 0.1 M HCl at 37 °C for 2 h. The reaction was stopped by the addition of 15 mL of 10% trichloroacetic acid (TCA). The mixture was filtered quantitatively through Whatman No. 1 filter paper. The TCA soluble fraction was assayed for nitrogen using the micro-Kjeldahl method, and the protein digestibility of the sample was calculated.

2.3.4. Determination of total phenolic, total flavonoid, and antioxidant activity

The determination of the total phenolic content of the cookie samples was carried out following the procedure outlined by Singleton et al. (1999). Five (5) mL of distilled water was measured into the volumetric flask and 0.1 mL of acidified methanolic extract of ground cookie samples was added and mixed thoroughly. 2.5 mL solution of Folin-Ciocalteu’s reagent solution and 7.5 mL of 15% sodium carbonate solution were added to the mixture, diluted with distilled water to 50 mL, and then left for 30 min for the proper reaction of the whole mixture. The absorbance of the reaction mixture was determined at 760 nm in a spectrophotometer (Jenway 7415B UV/Vis, UK). The total phenolic content was calculated using Gallic acid as standard.

The procedure described by Zhishen et al. (1999) was used to determine the total flavonoid in cookie samples. 4.9 mL of distilled water was added to 0.1 mL of cookie extract followed by 0.3 mL NaNO₂ and all was mixed. After 5 min 0.3 mL AlCl₃ was added to the mixture followed by 2 mL of 1 M NaOH after 6 min. A dilution was made with distilled water to 10 mL, the entire mixture was mixed well, and the absorbance was measured at 510 nm. The total flavonoid content was calculated using quercetin as standard.

The 1,1-diphenyl-2-picrylhydrazyl was determined according to the method of De Ancos et al. (2002). 90 μL of distilled water was added to 10 μL of the cookie acidified methanolic extract followed by 3.9 mL 0.1 M DPPH solution. The mixture was mixed well, left in the dark for 30 min, and its absorbance was measured at 515 nm. The DPPH free radical scavenging ability was calculated with respect to the reference (which contains all the reagents without test samples). Free radical scavenging ability was expressed as percentage (%) inhibition.

2.4. Amino acid analysis

The amino acid profile was determined following the method described by Yang et al. (2011). A 0.2 mg of the sample was made into a fine paste with 7 mL 6 N HCl and then filtered by using Whatman No. 1 filter paper. The protein hydrolysis was done by putting the flask containing the filtrate in a heated mantle at 110 °C for 22 h. After hydrolysis, the solution was put in an evaporating dish to evaporate HCl in a water bath. It was then filtered into a 25 mL volumetric flask and the solution served as stock solution. A 0.45 µm syringe filter was used to filter the stock solution once more. The stock and standard solution were then run through the amino acid analyzer (Model 120A, Applied Biosystems PTH Ltd., Foster City, CA, USA).

2.5. Physical properties determination of functional cookies and control

2.5.1. Determination of some physical characteristics

The diameter of the functional cookies and control were determined by arranging six edge-to-edges horizontally and rotating at a 90° angle. The thickness was carried out by stacking six cookies on top of one another, then recording three replicates reading by shuffling cookies. A digital weighing balance (BA-W113P, Bioevopeak, Inc., Shandong, China) was used to determine the weight of the cookies, and the mean value was calculated. The spread ratio was determined through calculation as follows:

$\text{Spread}\text{ratio=}\frac{\text{Diameter}}{\text{Thickness}}$

2.5.2. Determination of color

A colorimeter (PCE-CSM2 Deutschland GmbH, Meschede, Germany) coupled to CQCS3 software was used to determine the color of functional cookies and of the control. Hunter L*, a*, and b* parameters were determined using a spectrophotometer with a color difference meter. Before taking the reading, the spectrophotometer was calibrated against a white plate. The spectrophotometer’s aperture was placed above the cookie, and measurements were taken. The hue (H)* and chroma (C)* are calculated as follows:

$\begin{array}{c}{\mathrm{H}}^{\ast }={tan}^{-1}\left[\frac{{\mathrm{b}}^{\ast }}{{\mathrm{a}}^{\ast }}\right]\\ C^{\ast }=squarerootof\left[a^{2\ast }+b^{2\ast }\right]\end{array}$

2.6. Sensory evaluation

A 20-judge panel integrated by postgraduate students of the Food Science and Technology Department, University of Uyo, Uyo, Nigeria, evaluated the sensory attributes of the functional and control cookies. They were briefed on the procedure before it began. Appearance, aroma, taste, texture, aftertaste, and overall acceptability were the attributes evaluated. The panelists were given the coded samples along with water to rinse their mouths between determinations, hiding the sensory characteristics of the prior determination. A 9-point Hedonic scale was used to measure cookie attributes, with 1 representing extreme dislike and 9 representing extreme liking (Iheokoronye & Ngoddy, 1985).

2.7. Statistical analysis

Data obtained were analysed through one-way analysis of variance (ANOVA) by using Statistical Package for Social Sciences (SPSS version 20). The means were separated by using Duncan’s new multiple range test at p < 0.05.

3. Results and discussion

3.1. Proximate composition and energy value of functional cookies and control

The proximate composition and energy value of all the functional cookies and control are presented in Table 2. The moisture content of a food product has a direct relationship with its shelf life. Food with a high moisture content has a shorter shelf life, and vice versa. The highest moisture content (5.08%) was recorded in functional cookies R12 and the lowest (3.41%) in R10. The R12 value was higher than the ranges (4.51–4.90%) reported by Obasi and Ifediba (2018) for cookies made with African breadfruit, maize, and coconut flour blends but lower than 22.70% reported for cookies made with 60% whole wheat flour and 40% date palm fruit flour (Peter et al., 2017). The crude protein content significantly (p < 0.05) ranged from 7.00% (R5) to 10.72% (R4) but compared to the control (13.30%) the amount of crude protein in the functional cookies was lower. The addition of YMF increased the protein content in the formulated cookies. In 2018, Akaffou et al. and Trehan et al., respectively, reported that YMF had protein contents of 8.85% and 8.44%, compared to the 6.16% in BSF (Alcon et al., 2021). The crude protein content obtained in most of the cookie samples were higher than those (7.23–7.63%) reported by Sadal et al. (2018) only in samples R5, and R13 the protein content was 7.00% and 7.02%, respectively. The crude fat content ranged from 23.47% (R3) to 25.88% (R4) with the lowest value (22.39%) observed in the control. As low-fat values for YMF (4.27%) and BSF (3.48%) were previously reported by Adeleke and Abiodun (2010) and Trehan et al. (2018), respectively, the higher fat content could be due to the use of margarine and milk in the production of the functional cookies. Fat, in addition to carbohydrates, also serves as an energy source in the diet. A higher fat content is a sign that there is more overall available energy. The findings are similar to those of Go et al. (2015), who reported values of 22.10% for breadnut seed cookies, which is higher compared to the crude lipid content of 9.01–13.01% reported by Obasi and Ifediba (2018) for high-fiber rich cookies made from blends of African breadfruit, maize, and coconut flour.

Table 2. Proximate composition (%) and energy value (Kcal) of functional cookies from the flour blends of breadnut seeds, yellow maize, and pineapple pomace

Samples	Moisture	Crude protein	Crude fat	Ash	Crude fiber	Carbohydrate	Energy
R1	4.12^ef ± 0.02	8.40^cd ± 0.74	24.89^ab ± 1.50	4.32^a ± 0.67	1.56^d ± 0.40	56.71^ab ± 2.14	484.45^ab ± 1.68
R2	4.22^cde ± 0.03	8.40^cd ± 0.49	25.59^a ± 0.10	3.71^b ± 0.53	2.30^b ± 0.00	55.78^ab ± 1.15	487.03^ab ± 1.70
R3	3.82^g ± 0.08	8.45^cd ± 0.26	23.47^b ± 0.94	3.97^ab ± 0.88	2.18^bcd ± 0.58	58.11^a ± 2.58	477.47^bc ± 0.84
R4	4.19^de f ± 0.00	10.72^b ± 0.83	25.88^a ± 1.97	3.31^b ± 0.00	2.27^bc ± 0.04	53.63^b ± 2.86	490.32^a ± 0.70
R5	4.31^c ± 0.01	7.00^d ± 0.74	24.90^ab ± 1.81	3.63^b ± 0.04	2.61^ab ± 0.07	57.55^a ± 2.43	482.30^b ± 0.59
R6	3.75^gh ± 0.03	8.75^c ± 0.49	25.38^a ± 1.64	3.08^bc ± 1.15	2.38^b ± 0.77	56.66^ab ± 0.82	490.06^a ± 1.61
R7	3.43^i ± 0.01	8.75^c ± 0.24	25.67^a ± 0.81	3.38^b ± 1.04	2.75^a ± 0.56	56.02^ab ± 1.65	490.11^a ± 0.28
R8	4.11^f ± 0.02	8.36^cd ± 0.72	25.73^a ± 1.23	4.24^a ± 0.39	1.54^d ± 0.39	56.02^ab ± 0.26	489.09^ab ± 0.23
R9	5.04^a ± 0.02	10.13^b ± 0.24	24.78^ab ± 1.30	2.99^c ± 0.91	2.20^bc ± 0.13	54.86^b ± 2.62	482.98^b ± 2.26
R10	3.41^i ± 0.01	8.72^c ± 0.08	25.66^a ± 0.76	3.43^b ± 0.26	2.73^a ± 0.02	56.05^ab ± 0.37	490.02^a ± 5.03
R11	3.71^h ± 0.01	8.46^cd ± 0.28	23.96^b ± 0.19	4.01^a ± 0.01	2.20^bc ± 0.08	57.66^a ± 0.31	480.12^b ± 0.65
R12	5.08^a ± 0.01	7.70^d ± 0.71	24.52^ab ± 3.70	3.42^b ± 0.16	2.28^bc ± 0.12	57.00^a ± 7.53	479.48^bc ± 1.07
R13	4.32^c ± 0.00	7.02^d ± 0.71	24.80^ab ± 0.05	3.66^b ± 0.02	2.58^ab ± 0.01	57.62^a ± 0.01	481.76^b ± 0.33
R14	5.02^a ± 0.02	10.15^b ± 0.28	25.69^a ± 0.33	2.96^c ± 0.04	2.20^bc ± 0.02	53.98^b ± 0.62	487.73^ab ± 1.69
R15	4.80^b ± 0.05	8.40^cd ± 0.12	25.24^a ± 0.33	3.00^bc ± 0.70	2.42^b ± 0.07	56.14^ab ± 0.94	485.32^b ± 1.18
R16	4.26^cd ± 0.02	8.86^c ± 0.56	25.01^a ± 2.50	3.43^b ± 0.07	2.27^bc ± 0.04	56.17^ab ± 3.17	485.21^b ± 1.09
Control	3.43^i ± 0.00	13.30^a ± 0.72	22.39^a ± 0.97	2.59^c ± 0.21	1.77^d ± 0.01	56.52^ab ± 1.71	480.79^b ± 4.73

Note: Values are means ± standard deviation of three replicates determinations. Means differently superscripted within the columns are significantly different (p <0.05). Control = 100% wheat flour cookies.

The ash content of functional cookies ranged between 2.96% and 4.32% for R14 and R1, respectively. Significant higher amount of ash content was observed in all the functional cookies compared to the lowest value (2.59%) found in the control. The ash content in a food indicates if it is a good source of minerals. R1 and R8 had the highest ash content of all the cookie samples, which could be provided by BSF. A high ash content of 5.01% has been reported for BSF (Alcon et al., 2021). The value was higher than the 2.04% reported for cookies produced with flour blends of 50% breadnut seeds flour and 50% wheat flour (Go et al., 2015). The crude fiber content ranged from 1.54% (R8) to 2.75% (R7) and was 1.77% in the control. The highest percentages of crude fiber were quantified in functional cookies R7 (2.75%), R10 (2.73%), R5 (2.61%), and R13 (2.58%) which had the highest PPF percentage (5%) in the formulation of their dough. This can be attributed to the high fiber content of PPF as reported by Sadal et al. (2018). In their work, the crude fiber content of biscuit samples increased from 2.16% to 3.13% at different percentages of addition (5–15%) of pineapple pomace flour. Fiber is regarded as the fraction of plant foods that cannot be digested, and its significance in diets has been widely recognised. High-fiber foods are believed to help support a healthy digestive tract, regulate bowel movements, lower cholesterol and triglycerides, and strengthen colon walls in addition to helping to avoid cancer, heart disease, kidney stones, and obesity. Eating too little fiber can make defecation more difficult (Akinjayeju et al., 2019). The results of the current study are consistent with those of Bello et al. (2022), who found that adding tigernut pomace flour to their flour blends enhanced their crude fiber content. Carbohydrate content ranged between 53.63% (R4) and 58.11% (R3). The high level of carbohydrate content in this study could possibly be due to the contribution of each of the food composition found in the cookie samples. The present findings are lower than the report of Go et al. (2015) who found a higher carbohydrate value of (67.60%) in wheat flour cookies with 50% BSF substitution. The energy content ranged from 477.47 to 490.32 kcal in R3 and R4, respectively. The highest value found in R4 was not significantly (p < 0.05) different from R6 (490.06 kcal), R7 (490.11 kcal) and R10 (490.02 kcal). The composition of food (percentage of carbohydrates, proteins, and fats) directly affects its energy value. The energy value obtained in the present study was enhanced due to the percentages of YMF, PPF, and BSF.

3.1.1. Selection of the best samples of functional cookies

The three best functional cookie samples were selected based on their higher fiber and low crude fat content i.e. R4 (80.63% BSF, 18.12% YMF, and 1.25% PPF); R12 (97.50% BSF, 0.00% YMF, and 2.50% PPF); and R13 (95.00% BSF, 0.00% YMF, and 5.00% PPF). Furthermore, the three selected functional cookies were compared with the control for the remaining analyses.

3.2. Vitamins and mineral composition, dietary fiber, antioxidant properties, and in vitro digestibility of functional cookies and control

Table 3 shows the composition of selected vitamins and minerals, dietary fiber, antioxidant properties, and in vitro digestibility of control and selected functional cookies. The content of vitamins B₂ and C substantially varied between the selected samples. The highest content of Vit. B₂ (2.55 mg/100 g) was quantified in R13. The value attributed to R13 was a result of higher percentages of PPF in the functional cookie as pineapple has been reported to contain 0.03 mg/100 g Vit. B₂ (ANSES, 2020). The higher values recorded for the cookie samples may also be attributed to the other ingredients (milk and egg) used in the production of functional cookie. The cookie samples had vitamin C contents ranging from 0.65 mg/g (R12) to 1.72 mg/g (R13). The baking temperature, which led to its significant loss, is responsible for the low values that were reported (Bello et al., 2022). However, the significant (p < 0.05) increase observed in vitamin C might be due to the higher level of PPF which is similar to the outcome shown in Vit. B₂ in the present study. The vit. C content of 37.73 mg/100 g has been quantified in PPF (Jose et al., 2022).

Table 3. Vitamins and mineral composition, dietary fiber, antioxidant properties, and in vitro digestibility of functional cookies

	R4	R12	R13	Control
Vit. & Mineral (mg/100 g)
Vit. B2	1.28^d ± 0.00	2.16^b ± 0.00	2.55^a ± 0.00	2.08^c ± 0.00
Vit. C	0.65^d ± 0.00	1.29^b ± 0.00	1.72^a ± 0.00	1.06^c ± 0.00
K	970.90^a ± 2.11	965.00^b ± 4.05	965.70^b ± 2.41	878.0^c ± 0.00
Na	98.54^c ± 0.18	125.02^a ± 0.67	102.81^b ± 0.22	6.24^d ± 0.04
Ca	15.86^c ± 0.08	22.01^a ± 0.17	18.74^b ± 0.12	4.32^d ± 0.02
Mn	3.10^c ± 0.14	3.94^b ± 0.07	3.08^c ± 0.11	11.01^a ± 0.01
Fe	7.73^d ± 0.37	14.51^b ± 0.72	13.14^c ± 0.19	29.09^a ± 1.50
Dietary fiber (%)
Soluble fiber	42.31^a ± 0.90	29.79^b ± 0.93	15.41^c ± 1.19	16.08^c ±  1.15
Insoluble fiber	54.18^c ± 1.21	69.20^b ± 1.93	81.09^a ± 1.19	82.42^a ± 1.85
Total dietary fiber	96.49^b ± 0.43	98.99^a ± 0.28	96.50^c ± 0.65	98.50^b ± 0.50
In vitro digestibility
IVPD (%)	30.88^a ± 0.15	28.13^b ± 0.16	28.29^b ± 0.21	20.04^c ± 0.17
IVSD (%)	37.53^c ± 0.05	40.88^b ± 0.18	43.93^a ± 0.05	29.06^d ± 0.15
Antioxidant properties
Phenol (mg GAE/100 g)	0.38^b ± 0.00	0.41^b ± 0.02	0.69^a ± 0.00	0.17^c ± 0.00
Flavonoid (mg QE/100 g)	0.18^a ± 0.00	0.14^b ± 0.00	0.14^b ± 0.00	0.03^c ± 0.00
DPPH scavenging (%)	3.54^c ± 0.03	3.35^d ± 0.00	4.01^a ± 0.00	3.84^b ± 0.00

Note: Values are means ± standard deviation of three replicates determination. Means differently superscripted within the rows are significantly different (p < 0.05). R4 = 80.63% A, 18.12% B, 1.25% C; R12 = 97.50% A, 0.00% B, 2.50% C; R13 = 95.00% A, 0.00% B, 5.00% C. A = breadnut seeds flour; B = yellow maize flour; C = pineapple pomace flour; control = 100% wheat flour cookies. IVPD = In vitro protein digestibility; IVSD = In vitro starch digestibility.

Minerals are necessary elements that the body needs to support the healthy function of several organs (Twum et al., 2015). The minerals K (970.90 mg/100 g) and Na (125.02 mg/100 g) were found in the highest concentrations in R4 and R12, respectively. The higher K content found in R4 is explained by the fact that BSF and YMF have been identified as K-rich sources (Adeleke & Abiodun, 2010; Akaffou et al., 2018; Williams & Badrie, 2005). Compared to the control, the concentration of K in functional cookies is higher and falls within the range values (77.00–1160.00 mg/100 g) reported for African breadfruit, corn, and soybean flour blends (Nwabueze & Enoch, 2008). K is known to protect against arterial hypertension, and it is also necessary for maintaining the osmotic balance of body fluids, pH, regulating the irritability of muscles, and enhancing normal protein retention during growth (Wardlaw, 2004). According to Park et al. (2016), consuming Na is seen as a substantial risk factor, making it a target for health policies aimed at reducing the prevalence of hypertension. The selected functional cookies may be suitable for consumption by hypertensive people due to its low Na content (Grillo et al., 2019). The calcium content (15.86–22.01 mg/100 g) in the selected functional cookie samples was significantly (p < 0.05) higher than in the control (4.32 mg/100 g). The BSF and PPF contributed to the increase in the calcium content of R12 as it was previously reported that both flours contain an appreciable amount of calcium (Devi et al., 2015; Williams & Badrie, 2005). According to Bolarinwa et al. (2015), calcium is a crucial mineral for the development of strong bones and teeth, blood coagulation, control of blood pressure, and body development All the selected functional cookies contained significantly low manganese concentrations ranging between 3.08 and 3.94 mg/100 g for (R13) and (R12), respectively, compared to the control (11.01 mg/100 g). All of the flour samples used in the production of the functional cookies are poor sources of manganese (Adeleke & Abiodun, 2010; Williams & Badrie, 2005), which contributed to the low Mn content of the functional cookies. However, the level of Mn in the functional cookies was greater than the reported (0.45–1.82 mg/100 g) in extruded African breadfruit-corn-soybean blends (Nwabueze & Enoch, 2008). The Fe content of the functional cookies ranged between 7.73 mg/100 g (R4) to 14.51 mg/100 g (R12) which were significantly lower than the control (29.09 mg/100 g). According to Akaffou et al. (2018) and Nagarajaiah and Prakash (2016), low Fe contents had been reported for YMF (2.21 mg/100 g) and PPF (5.86 mg/100 g), respectively, while an appreciable amount of Fe (22.25 mg/100 g) was found in raw breadnut seed (Amadi et al., 2019).

PPF did not have a significant effect (p > 0.05) on the soluble dietary fiber, which ranged between 15.41% (R13) and 42.31% (R4), while the addition of YMF in functional cookie (R4) explains this increase. A significance (p < 0.05) increase was observed in the insoluble dietary fiber content varying from 54.18 (R4) to 81.09% (R13). This increase was due to the higher PPF percentage in samples R12 and R13 which were the samples that had 2.5 and 5.0% PPF, respectively. The high fiber content in pineapple pomace, which is largely insoluble fiber (hemicellulose and cellulose), accounts for this increase. Adult men and women consume 38 and 25 g of dietary fiber daily, respectively; hence, functional cookies will help consumers meet their daily dietary fiber needs (Neha & Ramesh, 2012). In snack bars made with the African breadfruit seeds, maize, and coconut flour blends, Edima-Nyah et al. (2019) found reduced soluble and insoluble dietary fiber contents of 2.87–5.18% and 7.25–14.76%, respectively.

Research has demonstrated that in vitro (starch and protein) digestibility tests are necessary since the nutritional composition of food alone is insufficient to predict nutrient bioavailability (Anuonye et al., 2007). An increase in in vitro protein digestibility (IVPD) and in vitro starch digestibility (IVSD) levels was observed in the selected functional cookies, and they were significantly (p < 0.05) higher than in the control. The IVPD percentage in the selected samples increased from 28.13 (R12) to 30.88% (R4) as the proportion of YMF was augmented. The samples with different PPF percentages showed a reduction in the IVPD concentration. The observed decrease in IVPD of R12 and R13 May be as a result of their percentage insoluble dietary fiber. The rate of starch digestion in foods is influenced by the extent of starch damage or gelatinization, size of the starch granules, composition, and structure. The IVSD percentage ranged from 37.53 (R4) to 43.93% (R13) and increased as the PPF percentage was higher. The higher insoluble dietary fiber content of PPF recorded in the present study could be the reason for the cookies’ increased starch digestibility. Soluble dietary fiber interacted with the starch, enveloping the starch and thereby limiting the interaction between starch and enzymes resulting to low starch digestibility in food products, which was evident in functional cookie R4 (Giuberti et al., 2018).

The antioxidant properties of the functional cookies selected samples varied significantly (p < 0.05). The lowest phenol content (0.17 mg/100 g) was in the control, while in the functional cookies samples it varied from 0.38 (R4) to 0.69 mg GAE/100 g (R13). The phenol content in the functional cookies was higher as the percentage of PPF increased, this could be due to the synthesis of phenolic compounds during baking (Mashau et al., 2020). The current study is in line with Azuan et al. (2020) findings (0.76–1.44 mg/100 g) for cookies fortified with various coffee ground extracts, but it is lower than the range values (23.98–48.08 mg GAE/100 g) reported for wheat-grape pomace flour blend cookies (Karnopp et al., 2015). This could be due to the proportion of PPF added to the blends, which has been recognized for its biological activity as powerful antioxidant (Selani et al., 2014). The abundance of phenolic compounds in both the PPF and the YMF has been documented by previous researchers (Montalvo-González et al., 2018; Nayak et al., 2015). The highest flavonoid level (0.18 mg QE/100 g) was found in R4 probably due to the use of YMF. The higher flavonoid level (35.41 mg/100 g) has been reported by Akaffou et al. (2018) in yellow maize. Flavonoids are major polyphenolic components of foods that exhibit anti-allergic, anti-inflammatory, and anti-cancer properties (Awolu & Olabiran, 2019). DPPH ranged from 3.35 (R12) to 4.01% (R13), and in the control was 3.84%. The result obtained in this research falls within the range (2.6–7.8%) of Azuan et al. (2020) producing cookies supplemented with different levels of spent coffee ground extract. The inclusion of PPF and YMF justifies itself by improving antioxidant capabilities through an increase in DPPH scavenging activities. This demonstrates that the polyphenolic content of the functional cookies and its DPPH radical scavenging actions are connected.

3.3. Amino acid profile of the functional cookies and control

The results of essential and non-essential amino acids are presented in Table 4. There was a significant (p < 0.05) difference among the functional cookies for all amino acids except for lysine. The presence and availability of essential amino acids, which are necessary for the growth, reproduction, and maintenance of the human body, are crucial factors in determining the protein quality of a diet. Since essential amino acids play a crucial role in achieving these functions, they are frequently used as indicators of the protein quality of food. The most abundant essential amino acids in the selected functional cookies were leucine, lysine, and phenylalanine, with contents ranging from 5.52 to 6.48 g/100 g, 4.47 to 4.83 g/100 g, and 3.90 to 4.52 g/100 g, respectively. Leucine is recognized as a significant dietary amino acid capable of promoting the synthesis of muscle protein and is said to play a significant therapeutic function in stress-related illnesses like trauma and sepsis (FAO/WHO/UNU, 2007). The control had the highest value for these amino acids, followed by R12, with the exception of lysine, whose highest concentration was quantified in R12. The low values recorded in the functional cookies are not surprising, since the raw materials used to make them have a high protein content. R12 was unusually high in lysine, which is a limiting amino acid in most cereals. This increase could be attributable to the incorporation of BSF in the dough blends since a high lysine content (5.19 g/100 g) has been reported in BSF and low (0.24 g/100 g) in YMF (Amadi et al., 2019; Daji et al., 2023). Lysine is important for children because it aids in bone formation, hormone production, and decreases serum triglyceride levels (Gersten, 2013). Tryptophan, methionine, and histidine were the essential amino acids with the lowest concentration in the functional cookies ranging from 0.78–0.91 g/100 g, 1.30–1.49 g/100 g, 1.82–2.24 g/100 g, respectively. The concentration of some amino acids agrees with the finding of Wabali et al. (2020) for wheat, African breadfruit and moringa seed flour blend biscuits ranging from 5.31–6.48 g/100 g (leucine) and 4.14–5.86 g/100 g (lysine). The concentration of valine in the present study varied from 3.66 (R13) to 3.95 (R12) g/100 g, so the range is lower than that reported by Wabali et al. (2020), and in the case of glutamate, the concentration in this study varied from 12.49 (R4) to 14.12 (R12) g/100 g so the range is higher than that reported by Wabali et al. (2020).

Table 4. Amino acid profile (g/100 g) of selected functional cookies from the flour blends of breadnut seeds, yellow maize, and pineapple pomace

	R4	R12	R13	Control
Essentials
Leucine	5.52^d ± 0.03	6.48^b ± 0.00	5.87^c ± 0.04	6.89^a ± 0.00
Lysine	4.47^a ± 0.05	4.83^a ± 1.39	4.64^a ± 0.04	4.71^a ± 0.02
Isoleucine	3.37^c ± 0.04	3.93^a ± 0.00	3.75^b ± 0.02	4.06^a ±  0.09
Phenylalanine	3.90^d ± 0.00	4.39^b ± 0.05	3.99^c ± 0.00	4.52^a ± 0.00
Tryptophan	0.78^c ± 0.02	0.91^b ± 0.02	0.80^c ± 0.01	0.99^a ±  0.02
Valine	3.71^c ± 0.04	3.95^b ± 0.12	3.66^c ± 0.03	4.26^a ± 0.02
Methionine	1.30^d ± 0.02	1.49^b ± 0.02	1.41^c ± 0.02	1.67^a ± 0.02
Histidine	1.82^d ± 0.04	2.24^b ± 0.00	2.11^c ± 0.09	2.31^a ± 0.72
Threonine	2.36^d ± 0.04	3.04^b ± 0.05	2.64^c ± 0.03	3.21^a ± 0.12
Non-essential
Proline	3.86^b ± 0.00	4.72^ab ± 0.07	3.96^b ± 0.68	5.03^a ± 0.07
Alanine	3.76^d ± 0.04	4.21^b ± 0.05	3.98^c ± 0.05	4.44^a ± 0.05
Aspartic acid	7.35^d ± 0.04	8.37^b ± 0.08	7.72^c ± 0.04	8.73^a ± 0.11
Glutamate	12.49^d ±  0.32	14.12^b ± 0.15	13.10^c ± 0.10	15.15^a ± 0.20
Glycine	3.18^c ± 0.00	3.59^b ± 0.35	3.40^c ± 0.00	4.20^a ± 0.02
Serine	3.40^b ± 0.04	3.54^b ± 0.03	3.22^c ± 0.03	3.79^a ± 0.07
Tyrosine	3.10^c ± 0.00	3.70^a ± 0.12	3.44^b ± 0.00	3.79^a ± 0.00
Cysteine	0.94^c ± 0.04	1.21^b ± 0.00	1.00^c ± 0.04	1.36^a ± 0.04

Note: Values are means ± standard deviation of three replicates determination. Means differently superscripted within the rows are significantly different (p < 0.05). R4 = 80.63% A, 18.12% B, 1.25% C; R12 = 97.50% A, 0.00% B, 2.50% C = R13: 95.00% A, 0.00% B, 5.00% C. A = breadnut seeds flour; B = yellow maize flour; C = pineapple pomace flour; control = 100% wheat flour cookies.

The three selected functional cookies had non-essential amino acid levels that were considerably (p < 0.05) lower than the control. Glutamate was quantified to have the highest values ranging between 12.49 g/100 g (R4) to 14.12 g/100 g (R12). This amino acid plays a crucial function in transamination reactions and is essential for the production of important molecules like glutathione, which is needed for the elimination of extremely hazardous peroxides, and polyglutamate folate cofactor (Jiddere & Filli, 2015). Aspartic acid had the second-highest value of non-essential amino acids in the selected cookie samples, with values of 7.35, 7.72, and 8.37 g/100 g for samples R4, R13, and R12, respectively. R12 had the highest concentration of the majority of non-essential amino acids from all functional cookies, but it was lower than the one present in the control. The same trend was also observed in essential amino acids with R12 having a higher percentage of BSF in its flour blend than R13 and R4.

3.4. Physical characteristics of the functional cookies and control

Table 5 presents the physical properties of the selected functional cookies and the control. The selected functional cookies had diameters that ranged from 3.09 cm (R12) to 3.30 cm (R13), while the control had 3.32 cm. The diameters of the cookie samples were significantly (p < 0.05) different. Olagunju and Ifesan (2013) found a diameter range of 3.8–4.33 cm for cookies prepared from wheat and sesame seed flour, which is close to the results obtained in the present study. The thickness (0.25 cm and 0.23 cm) of R4 and control, respectively, were not significantly different and their weights (18.99 g and 21.91 g) were higher than those of R12 and R13. This could be the result of the presence of bran in wheat and maize flour which gave bulkiness to the cookies. The spread ratio in R12 (14.71), however, was significantly (p < 0.05) higher than in the control (14.43). This could be because the functional cookies contained less insoluble dietary fiber than the control (whole-wheat flour), which had more. Mancebo et al. (2018) reported that adding insoluble fibers caused the spread ratio to significantly decrease. However, it has been claimed that flour or any other component that absorbs water while mixing the dough will reduce the spread ratio.

Table 5. Physical properties of selected functional cookies from the flour blends of breadnut seeds, yellow maize, and pineapple pomace

					Color
Sample	Diameter (cm)	Thickness (cm)	Weight (g)	Spread ratio	L*	a*	b*	c*	h^o
R4	3.25^b ± 0.00	0.25^b ± 0.01	18.99^b ± 0.03	13.00^b ± 0.13	62.02^b ± 2.30	12.93^b ± 1.82	22.88^a ± 0.27	27.83^a ± 1.68	59.08^a ± 1.41
R12	3.09^c ± 0.02	0.21^c ± 0.00	18.01^c ± 0.02	14.71^a ± 0.15	48.95^c ± 1.93	13.76^a ± 0.80	16.07^b ± 0.42	21.89^b ± 1.76	44.94^b ± 2.82
R13	3.30^a ± 0.03	0.29^a ± 0.00	18.47^c ± 0.01	11.38^c ± 0.17	48.63^c ± 1.26	13.83^a ± 1.53	15.90^b ± 1.01	20.24^b ± 2.95	39.45^c ± 1.72
Control	3.32^a ± 0.02	0.23^b ± 0.01	21.91^a ± 0.02	14.43^a ± 0.02	71.02^a ± 2.01	3.25^c ± 0.12	13.87^c ± 0.92	17.67^c ± 0.01	37.68^d ± 2.52

Note: Values are means ±  standard deviation of three replicates determination. Means differently superscripted within the columns are significantly different (p < 0.05). R4 = 80.63% A, 18.12% B, 1.25% C; R12 = 97.50% A, 0.00% B, 2.50% C; R13 = 95.00% A, 0.00% B, 5.00% C. A = breadnut seeds flour; B = yellow maize flour; C = pineapple pomace flour; control = 100% wheat flour cookies. L* = lightness; a* = red; b* = yellow; c* = chroma; h = hue.

L* (brightness), a* (reddish), and b* (yellowish) describe the color composition of the selected cookies. Among the cookies with the highest L* value, the control was the brightest (71.02). The lowest L* value (48.63) was found in R13, indicating that it was the darkest cookie. Chareonthaikij et al. (2016) made the same observation for wheat bread supplemented with PPF. The dark color of R13 is due to the baking temperature as well as the addition of a high percentage (5%) of PPF, which darkens as a result of enzymatic oxidation of pineapple pomace after juice extraction, as to the color change of breadnut seed during its peeling. When the proportion of crude fiber in the cookies was increased as a result of PPF incorporation, the lightness of the cookies decreased. The a* values in the selected functional cookies ranged from 12.93 (R4) to 13.83 (R13) and were higher than in the control (3.25), which is explained by the low content of red components in the control. With an increase in PPF, the a* values also increased. The b* values were between 15.90 and 22.88 in R13 and R4, respectively. The highest b* values were found in R4 which could be a result of the yellow color in the maize flour. The calculated c* and h* values ranged from 20.24–27.83 and 39.45–59.08, respectively. The color of baked products is important for their initial acceptability, but the intensity of browning may affect the flavor of the final product.

3.5. Sensory properties of the functional cookies and control

The sensory attributes of the selected functional cookies and control are displayed in a radar plot (Figure 1). The taste of the cookies was significantly (p < 0.05) influenced by all three flours. The taste score ranged from 5.00 to 7.10 on a scale of one to nine. For taste, the control got the highest score, followed by R12 and R13. This could be related to the panelist’s familiarity with the taste of wheat flour cookies. The taste score value improved as BSF and PPF increased. Similarly, R12 received the highest appearance score rated between 6.00 and 7.45. The proportion of 2.50% PPF and an increase in BSF had a positive effect on appearance. The appearance of the control and R13 did not differ significantly (p > 0.05). BSF and PPF had a greater impact on the cookies’ aroma, ranging from 5.32 to 6.72. The texture and overall acceptability of the cookies improved with each of the three flours. Overall acceptance values ranged from 5.70 to 7.55, with R12 receiving the highest overall acceptability score. The findings of this study coincide with those by Go et al. (2015) for breadnut seed-wheat flour blend cookies, who found that an increase in the % of BSF improved the aroma, flavor, and crispiness ratings of the cookies. R12 (97.50% BSF and 2.50% PPF) was the most preferred sample by the panelists and was not significantly (p > 0.05) different from the control. All of the scores were greater than 5.00, which is the minimum admissible value on a nine-point hedonic scale.

Figure 1. Sensory scores of functional cookies from breadnut seeds, yellow maize and pineapple pomace flour blends. R4 = 80.63% A, 18.12% B, 1.25% C; R12 = 97.50% A, 0.00% B, 2.50% C; R13 = 95.00% A, 0.00% B, 5.00% C. A = breadnut seeds flour; B = yellow maize flour; C = pineapple pomace flour; control = 100% wheat flour cookies.

4. Conclusion

In this study, the effect of replacing wheat flour with different BS-YM-PP flour blends was successfully done and evaluated. The crude fiber, insoluble dietary fiber, Vit. B₂, and Vit. C contents of the selected functional cookies improved after they were fortified with 5.00% PPF and 95% BSF (R13). Ca, Na, Mn, Fe, and amino acid contents were also enhanced at the inclusion of 2.50% PPF and 97.5% BSF (R12). The addition of YMF to the cookies also resulted in a significant increase in K and soluble dietary fiber contents. The cookies exhibited a more balanced amino acid profile and contained a significant amount of eight important amino acids. In vitro protein and starch digestibility was higher in the selected functional cookies than in the control. The antioxidant content of the cookies was enhanced by adding PPF. Moreover, the panelists preferred cookies with 2.50% PPF and 97.5% BSF (R12), which were not significantly different from the control. Thus, the study demonstrated that the use of breadnut seed, maize, and pineapple pomace flours in baking would reduce the risk of malnutrition by providing a cheap source of nutrients, reducing postharvest loss of the perishable crops, and encouraging the wider use of underutilized crops. It is important that further research be conducted to ascertain the shelf life of cookie samples and the pasting properties should be carried out to help identify other food uses of the flour blends.

Acknowledgments

The authors appreciate the effort of the Technologist (Mr. Udeme Offiong and Mr. Paul Johnson) of the Department of Food Science & Technology, University of Uyo, Uyo for assisting during sample preparation.

Disclosure statement

The authors declare no conflict of interest.

Supplemental material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/23311932.2023.2284232

Additional information

Notes on contributors

Margaret O. Edet

Margaret O. Edet graduated from the Department of Food Science and Technology, University of Uyo, Nigeria. She is passionate about using underutilized indigenous crops, and discovering new and efficient techniques that improve food processing and quality.

Florence A. Bello

Florence A. Bello is a senior lecturer and researcher in the Department of Food Science and Technology, University of Uyo, Nigeria, and is currently on a Sabbatical appointment at the University of Calabar, Nigeria. Her research focuses on applying improved postharvest handling and processing technologies to reduce food losses and waste, and valorization of food processing by-products for food product development.

Babatunde S. Oladeji

Babatunde S. Oladeji is a senior lecturer and an acting Head of the Department of Food Science and Technology, University of Calabar, Nigeria. He is a dedicated researcher and consultant with a passion for quality research in the development of novel food products capable of alleviating the problem of protein energy malnutrition.