Fruit-based vegan ice cream-type frozen dessert with aquafaba: effect of fruit types on quality parameters

Abstract

"Aquafaba", defined as legume cooking water, has a feature that can be used in various formulations as an egg and milk alternative in vegan products and improves functional properties such as foaming, emulsifying and gelling. In this study, it was aimed to investigate the usability of aquafaba in ice cream type frozen desserts containing different fruit purees (strawberry, nectarine and banana) by using its foaming capacity. Rheological properties, microstructure, overrun, melting characteristics, color measurement, dry matter, and sensory properties were investigated in different fruit-based frozen dessert samples. The brix value, density, protein content, foaming capacity (FC) and foaming stability (FS), flow behavior index, consistency coefficient, and overrun of aquafaba were determined as 7.1 ± 0°Bx, 1.022 ± 0.011 g/ml, 1.51 ± 0.41%, 85 ± 0% FC and 81 ± 0.23% FS, between 0.28 and 0.64, between 8.68 and 41.30 Pa·sn, between 116.75 and 395.93%, respectively. The dry matter content of the strawberry, nectarine, and banana-based dessert samples ranged between 17 and 48%, 20–49%, 25–50%, and the first dropping times were determined between 348 and 1538 s, 369–1689 s and 435–1985 s, respectively. As a result, cooking liquid leftover aquafaba can be used as a suitable raw material in the production of an alternative ice cream type frozen dessert for individuals with milk allergy, lactose intolerance or who prefer a vegan diet.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-023-05885-y.

Introduction

Ice cream is a food item that is widely consumed by people of all ages around the world and has dozens of varieties. Although it is very rich in nutritional components, many people who have a vegan diet and are lactose intolerant cannot consume these products due to the milk content. Apart from that, milk contains more than 20 proteins that can cause a clinically abnormal immunological allergic reaction for humans (El-Agamy 2007). In today's world, health-conscious consumers have increasingly shifted their focus towards foods that both fulfill the body's specific nutritional requirements and possess disease-fighting properties. For these reasons, non-dairy plant-based alternatives are being studied to increase the variety of products that can be consumed by people who follow a vegan diet and have special food needs (Marrone et al. 2021).

Food waste and loss occur at each stage of the food supply chain such as harvest, manufacturing, transportation, delivery, retail, and food service from the field to consumers. The Food and Agriculture Organization (FAO) has reported that about a third (approximately 1.3 billion tons) of the food produced for human consumption is lost or wasted per year. Over recent years, the global production of legumes has reached 90 million tons, with approximately 12 million tons of chickpeas, representing 14% of this total output (Ray et al. 2023). Among the diverse types of legumes in all around the world, chickpea (Cicer arietinum L.) is third, widely grown legume, especially for Afro-Asian countries (Glusac et al. 2020). The preferred method for cooking chickpeas, according to Damian et al. (2018), generally involves soaking them first, followed by cooking with a 1:1.75 ratio of dry matter to water. At the end of the cooking process, this large amount of water remains as waste water which is called as Aquafaba. Aquafaba combines two Latin words, aqua for water and faba for the family Fabaceae. The Aquafaba obtained from legume cooking water is often discarded without being used. Legume cooking water is rich in carbohydrates, proteins, phytochemicals, vitamins, and minerals. There is a growing awareness of this issue worldwide (Eren et al. 2021).

Soaking, boiling, steaming, and canning generally applied to legumes are the most common methods that result in the loss of most nutritional components. In terms of food processing technology, protein isolates and concentrates from legumes contribute to binding and thickening, partly due to their starch and fiber content (Meurer et al. 2020). These components are also effective in providing water binding ability, freeze–thaw stability, that is, crystallization control. When the literature information is examined, it shows that aquafaba is a valuable ingredient that can be used as an egg and milk alternative in various formulations of vegan products, providing functional properties such as foaming, emulsifying and gelling (Stantiall et al. 2018). In short, aquafaba obtained from chickpeas has technological properties such as water and oil holding capacity, emulsion stabilizer, foaming, gelling and thickening. Aquafaba could be used as a vegan, gluten-free, and cholesterol-free additive in a variety of food items such as egg-free mayonnaise, meringue, mousse, whipped cream, ice cream, emulsified dressings, cocktails, and baking products. Moreover, different commercial products have been produced, such as the instant form of aquafaba and vegan mayonnaises with aquafaba (He et al. 2021). Mustafa et al. (2018) used aquafaba as a replacer of egg white in sponge cake white in sponge cake production. According to the results, the physical and foaming properties of aquafaba are similar to the egg white in sponge cake showing that aquafaba can be used replacer of egg white in sponge cake formulation and other baked confectionaries. Stantiall et al. (2018) proposed that the proteins and saponins in pulse cooking waters (PCW) help to create foam and gel, they examined the physicochemical properties of PCW and their effects on product quality by using PCW in the meringue formulation.

Fruits are a source of dietary fibers, vitamins, and phenolic compounds linked to health outcomes such as a lower ratio of chronic diseases. In this study, fruit-based vegan ice cream-type frozen desserts were made with strawberry, banana, and nectarine fruits, resulting in a functional, non-dairy, and vegan ice cream substitute. This study investigated the usability of aquafaba in a new fruit-based ice cream type frozen dessert using its strong foaming property.

Materials and methods

Materials

Chickpea seeds of Kabuli type which are a large seeded type suitable to different climates, fresh banana and nectarine, frozen strawberries, and sugar were purchased from local growers (Istanbul, Turkey). The chemicals used were of analytical purity and all of these chemicals were obtained from Sigma Aldrich (St. Louis, MO, USA) or Merck (Darmstadt, Germany).

Aquafaba production

Before the cooking process, chickpea seeds were soaked with distilled water (1:2.5 dry matter:water) for 16 h (Haileslassie et al. 2019). Chickpea samples were washed and filtered with stainless steel laboratory strainer (mesh 4 mm, size: 25 cm diameter). Cooking in boiling water (1:3.5 dry matter:water) was continued for 1–2 h and the process was continued until the samples softened. The process was carried out in a 5L stainless steel pressure cooker. At the end of the cooking process, the grains are kept in the pot without opening the lid until they reach room temperature and the grains are filtered with stainless steel laboratory strainer (mesh 4 mm, size: 25 cm diameter). Then Aquafaba was separated by using a strainer. It was stored in a freezer at − 18 °C until the time of use (Arçelik 2031 MB, Turkey).

Quality analysis of aquafaba

Density, brix and protein concentration value of aquafaba

Quality analysis such as density, brix and protein content were made using chickpea cooking water. The density of aquafaba was obtained by dividing its mass by its volume (g/ml). The brix value of the Aquafaba sample was measured with the binoculars of the hand refractometer and the result was taken as brix value. Kjeldahl nitrogen determination method was used for determination of % protein content of aquafaba. Protein content was calculated as the nitrogen content (N) multiplied by a conversion factor of 6.25 (AOAC 2011.11) (Shim et al. 2018).

Foaming capacity and foaming stability

According to Mustafa et al. (2018) aquafaba (V_sample = 20 ml) was whipped for 6 min at the highest level of the mixer (Fakir Sierra 425 W, Turkey). The volume of foam obtained was measured at time 0 (V_F0). After 30 min, the volume of foam was determined again (V_F30) and both foaming capacity (FC) and foaming stability (FS) were calculated following Eqs. (1) and (2), respectively.

$$\text{FC}\left(\%\right)={\text{V}}_{\text{F}0}/{\text{V}}_{\text{sample}}\times 100$$ 1

$$\text{FS}\left(\%\right)={\text{V}}_{\text{F3}0}/{\text{V}}_{\text{F}0}\times 100$$ 2

Fruit puree production

Banana, strawberry, and nectarine fruits were used to obtain fruit puree. After washing the banana and nectarine with water, they were frozen with their peels in the deep freezer. Frozen bananas were mashed after removing the skin, and nectarines were mashed without removing the skin. The frozen strawberries were mashed directly. Food mixer device (Philips Hr2291/41 3000, Holand) with a rotating blade was used for the crushing process.

Production of fruit-based ice cream-type frozen dessert with aquafaba

Fruit puree was added to the prepared Aquafaba ice cream-type frozen dessert according to Table 1. They were mixed with a hand mixer (Fakir Sierra 425 W, Turkey) until the whipped ice cream-type frozen dessert mix had a homogeneous appearance for nearly 2 min. Whipped dessert mix was placed in the plastic ice cream container with lid. Frozen-desserts were preserved at − 18 °C. The stages were repeated separately for 21 fruit-based frozen dessert samples (Attachment 1) belonging to 3 different fruit varieties. While the abbreviations S, N, B, C, A represent Strawberry, Nectarine, Banana, Powdered Sugar and Aquafaba, respectively, the numbers represent the percentages in the mixture.

Table 1.

Ingredient ratios used in fruit-based ice cream-type frozen dessert with Aquafaba

Sample Codes according to fruit-based type			Percentage weight ratio in ice cream (%w/w)
Strawberry (S)	Nectarine (N)	Banana (B)	Fruit	Sugar (C)	Aquafaba (A)
S0.33C0.33A0.33	N0.33C0.33A0.33	B0.33C0.33A0.33	33.33	33.33	33.33
S0.36C0.27A0.36	N0.36C0.27A0.36	B0.36C0.27A0.36	36.36	27.27	36.36
S0.40C0.20A0.40	N0.40C0.20A0.40	B0.40C0.20A0.40	40.00	20.00	40.00
S0.44C0.11A0.44	N0.44C0.11A0.44	B0.44C0.11A0.44	44.44	11.11	44.44
S0.27C0.36A0.36	N0.27C0.36A0.36	B0.27C0.36A0.36	27.27	36.36	36.36
S0.20C0.40A0.40	N0.20C0.40A0.40	B0.20C0.40A0.40	20.00	40.00	40.00
S0.11C0.44A0.44	N0.11C0.44A0.44	B0.11C0.44A0.44	11.11	44.44	44.44

Quality analysis of fruit based ice cream-type frozen dessert with aquafaba

Rheological properties of fruit based ice cream-type frozen dessert

Rheological measurements were performed by Anton Paar (MCR 302, Austria) rheometer (PP50, gap 2 mm). The flow behavior (shear stress and shear viscosity) was examined by steady shear test at shear rates ranging from 0.1 to 100 s⁻¹. All samples were taken at + 4 °C and analysis were carried in triplicate (Rossa et al. 2012). Yield stress (τ0), consistency index (K), and behavior index (n) were determined and interpreted using the Herschel-Bulkley model (Chen et al. 2019).

Microstructure investigation of fruit-based ice cream-type frozen dessert

The microstructure of whipped ice cream-type frozen dessert mixes was investigated by polarized light microscopy (PLM, Zeiss Axio imager A2, Carl Zwiss, Germany). After whipping of ice cream-type frozen dessert mix according to the production method, the mix was applied to the depression slide, covered with the cover slip for observation at + 4 °C from a 40 × objective.

Overrun (%)

The overrun of the ice cream-type frozen dessert was measured depending on the foaming capacity of Aquafaba. The required ingredients for the samples were placed in the cylinder measure to determine the mix volume (V_mix). The volume of the whipped ice cream-type frozen dessert mix (V_ice-cream) was determined in a volumetric beaker after the required ingredients for the mix were prepared in accordance with the ice cream-type frozen dessert samples production method. Overrun (%) was calculated according to the formula number (4).

$$\text{Overrun}\left(\%\right)=\left({\text{V}}_{\text{ice}-\text{cream}}-{\text{V}}_{\text{mix}}\right)/{\text{V}}_{\text{mix}}\times 100$$ 3

Dry matter (%)

Ice cream-type frozen dessert samples were weighed between 1 and 2 g in a tared container which was kept in the oven with a fan at 100 °C for 3.5 h. Afterwards, the ice cream samples kept in the desiccator were allowed to cool, weighed, and the dry matter % was calculated by determining the weight differences. Dry matter content (%) was calculated from the following formulas (4) (where m and E are the dry weight of the test sample and the initial weight of the test sample, respectively, expressed in grams):

$$\text{Dry matter content}\left(\%\right)=\text{m}/\text{E}\times 100$$ 4

Melting characteristics

The frozen (− 18 °C) dessert sample (20 g) was placed on a wire filter fixed in a graduated glass cylinder. The time when the ice cream frozen dessert samples were first dropped (sec) was taken as the time when they were first dropped, and the time when they were completely melted (sec) was taken as the full melting time (Cottrell et al. 1979).

Color measurement

For color measurements, Hunter Lab (Color Quest XE, UK) device with D65/10 standard light source according to the CIE system was used. The L* (lightness: 0 = black, 100 = white), a* (greenness (−), redness ( +)), and b* (blueness (−), yellowness ( +)) values of the samples were measured for each sample from 3 points.

Sensory properties

Sensory analysis was carried out with 9 panelists trained and experienced in sensory evaluation consisting of undergraduate and graduate students in Food Engineering. Sensory analysis of frozen dessert samples was performed using a hedonic scale (5: best, 1: worst score). The purpose of the study was explained to the panelists in an informative article. Sensory evaluation parameters were determined as intensity of coldness, firmness, icy texture, homogeneous structure, general appearance, crystallization, aroma, bitterness, sourness, melting in the mouth, and last taste in the mouth.

Statistical analysis

ANOVA and Tukey tests were performed using the SPSS 16.0 statistical package for Windows (SPSS Inc., USA). The relationships between desserts belonging to each fruit type were shown in lowercase letters as the relationships between frozen dessert samples prepared at the same rate but using different fruit types were shown in uppercase letters.

Result and discussion

Physicochemical properties of aquafaba

As a result of cooking legumes, water-soluble carbohydrates are dispersed into Aquafaba. The brix value of aquafaba was determined as 7.1 ± 0°Bx. Mustafa and Reaney (2020) reported that dry matter is 5.13%. In the study, the density of chickpea aquafaba was found to be 1.022 ± 0.011 g/ml. In similar study, the aquafaba density of chickpea was reported as 1.020 g/ml (Stantiall et al. 2018) and 1.01 g/ml (Mustafa et al. 2018). The protein content of aquafaba was determined to be 1.51 ± 0.41%. This result was similar to Stantiall et al. (2018), and Buhl et al. (2019) reporting protein concentration in aquafaba as 0.95% and 1.3%, respectively. Aslan and Ertas (2020) reported that the protein amount of aquafaba produced for cake making was 9.98%. The results obtained may vary according to the dry legume/water ratio. Proteins are the main component of foaming ability as they are amphiphilic consisting of hydrophilic and hydrophobic parts. These amphiphilic properties create a correlation between foaming ability and protein content. In addition, these proteins are heat stable and can be frozen, thawed, heated, or refrigerated for repeated use (Mustafa et al. 2018).

The foaming capacity was determined as 85 ± 0% at 0 min after whipping and the foam has a stable and homogeneous appearance. The foaming stability after 30 min was calculated as 81 ± 0.23% and a partial decrease in volume was observed. Mustafa et al. (2018), in a study examining the foaming capacity of aquafaba recovered from canned chickpeas of different brands, reported that the foaming capacity ranged from 182.22 to 480.01%, and the foaming stability ranged from 77.21 to 91.61%. In another study, the addition of additives such as citric acid and salt to Aquafaba and experiments were made at different dry matter/water ratios. The foaming capacity was between 504.71 and 510.01%, and the foaming stability was between 81.17 and 82.10% (Nguyet et al. 2021). In another study, the foaming capacity of Aquafaba obtained from Garbanzo chickpeas was 58 (Stantiall et al. 2018). Differences in results may be due to differences in chickpea variety, processing conditions, canning process conditions, and additives.

Rheological properties of ice cream-type frozen desserts

The shear stress versus shear rates of the ice cream-type frozen dessert mixes were shown in Fig. 1. Rheological properties indicate the flow character of a fluid and are essential because of their influence on the sensory quality of ice cream. Most of the ice cream mixes showed non-Newtonian pseudoplastic flow behavior (Bahramparvar and Tehrani 2011). The flow behaviors (n value) of all mixes of dessert samples were less than 1 (Table 2), thus they showed a pseudoplastic flow behavior. The flow behavior index varied from 0.28 to 0.64, meanwhile the consistency coefficient varied from 8.68 to 41.30 Pa·sn. In accordance with the consistency coefficient (K), the samples (B_0.44C_0.11A_0.44, S_0.44C_0.11A_0.44 and N_0.44C_0.11A_0.44) with the lowest sugar content and the highest fruit ratio showed the lowest values, in accord with the lower value of the viscosity. The consistency index was significantly affected by the variety and ratio of the fruit, so even small differences in the fruit ratio affected this value. The reason for the increase in consistency index may be due to compounds that can interact with water, such as fiber, pectin, and starch in the fruit content.

Fig. 1.

Effects of aquafaba on shear stress-shear rate rheograms of fruit-based dessert mixes. While the abbreviations S, N, B, C, A represent Strawberry, Nectarine, Banana, Sugar and Aquafaba, respectively, the numbers represent the percentages in the mixture. (S) Strawberry (×S_0.11C_0.44A_0.44; — S_0.20C_0.40A_0.40; ☐ S_0.27C_0.36A_0.36; + S_0.33C_0.33A_0.33; ◼ S_0.36C_0.27A_0.36;● S_0.40C_0.20A_0.40;▲ S_0.44C_0.11A_0.44), (N) Nectarine (N_0.11C_0.44A_0.44; —N_0.20C_0.40A_0.40; ☐ N_0.27C_0.36A_0.36; + N_0.33C_0.33A_0.33; ◼N_0.36C_0.27A_0.36;● N_0.40C_0.20A_0.40; ☐ N_0.44C_0.11A_0.44), (B) Banana (×B_0.11C_0.44A_0.44; — B_0.20C_0.40A_0.40; ◆ B_0.27C_0.36A_0.36; + B_0.33C_0.33A_0.33; ◼ B_0.36C_0.27A_0.36;● B_0.40C_0.20A_0.40; ▲ B_0.44C_0.11A_0.44), D equal proportions of ingredients (● B_0.33C_0.33A_0.33; + S_0.33C_0.33A_0.33; ◼ N_0.33C_0.33A_0.33)

Table 2.

Herschel-Bulkley model parameters of fruit-based ice cream-type frozen dessert with Aquafaba

Samples	τ0 (Pa)	K (Pa·sn)	n	R2
S0.33C0.33A0.33	1.05 ± 1.82cA	22.52 ± 4.66bA	0.33 ± 0.02cdA	0.983
S0.36C0.27A0.36	7.62 ± 1.31bcB	18.80 ± 1.27bcA	0.37 ± 0.01cC	0.967
S0.40C0.20A0.40	16.11 ± 0.01abB	12.48 ± 2.39cdA	0.44 ± 0.02bB	0.942
S0.44C0.11A0.44	15.21 ± 2.32abB	8.68 ± 0.30dA	0.50 ± 0.01aB	0.967
S0.27C0.36A0.36	7.43 ± 7.46bcAB	32.54 ± 4.31a1B	0.31 ± 0.03dA	0.954
S0.20C0.40A0.40	14.57 ± 4.44abA	34.03 ± 4.17a1B	0.33 ± 0.00cdC	0.908
S0.11C0.44A0.44	19.10 ± 6.04aA	31.57 ± 2.86aB	0.35 ± 0.02cdA	0.917
N0.33C0.33A0.33	17.93 ± 6.29abB	21.24 ± 8.24bA	0.39 ± 0.05abA	0.926
N0.36C0.27A0.36	5.40 ± 2.33bB	41.30 ± 4.86aC	0.33 ± 0.01cB	0.935
N0.40C0.20A0.40	20.65 ± 2.33aB	23.59 ± 4.86bB	0.46 ± 0.01bB	0.929
N0.44C0.11A0.44	30.21 ± 4.22aC	10.55 ± 0.51cA	0.64 ± 0.02aC	0.923
N0.27C0.36A0.36	16.41 ± 7.68abB	26.37 ± 3.18bA	0.35 ± 0.05cA	0.901
N0.20C0.40A0.40	20.77 ± 6.75aA	24.90 ± 0.71bA	0.38 ± 0.02abB	0.918
N0.11C0.44A0.44	19.60 ± 2.14aA	28.11 ± 2.30bB	0.38 ± 0.00abB	0.944
B0.33C0.33A0.33	4.15 ± 3.93cA	30.06 ± 0.50bA	0.35 ± 0.02cA	0.999
B0.36C0.27A0.36	0.03 ± 0.05cA	27.21 ± 2.95bcB	0.30 ± 0.01dA	0.999
B0.40C0.20A0.40	0.00 ± 0.00cA	25.48 ± 1.51cA	0.28 ± 0.01dA	0.994
B0.44C0.11A0.44	1.35 ± 1.31cA	19.93 ± 1.76dB	0.29 ± 0.02dA	0.996
B0.27C0.36A0.36	0.36 ± 0.62cA	36.79 ± 2.52aB	0.33 ± 0.01cA	0.999
B0.20C0.40A0.40	12.89 ± 3.14bA	29.21 ± 0.58bcAB	0.43 ± 0.00bC	0.997
B0.11C0.44A0.44	22.33 ± 5.09aA	20.20 ± 0.41dA	0.53 ± 0.01aC	0.995

*τ₀: yield stress; K: consistency index; n: flow behavior index

Different lowercase letters indicate that the difference between samples of the same fruit variety statistically significant. Those shown with uppercase letters show that the samples prepared with different fruit types but containing the same amount of fruit, sugar and aquafaba are different from each other (p < 0.05). While the abbreviations S, N, B, C, A represent Strawberry, Nectarine, Banana, Sugar and Aquafaba, respectively, the numbers represent the percentages in the mixture

Intermolecular associations and reduction in particle size increased yield stress (Kurt and Atalar 2018). According to the yield stress, the samples (S_0.11C_0.44A_0.44 and B_0.11C_0.44A_0.44) with the highest sugar content and the lowest fruit ratio showed the highest values, in harmony with the lower particle size. However, for dessert mix samples containing nectarine, the product with the highest fruit content (N_0.44C_0.11A_0.44) had the highest yield stress. This situation may be caused by the stabilizing and thickening properties due to the fiber structure and pectin substances in the peel of the nectarine puree.

Microstructure properties of frozen-dessert mix

The foam structure of the ice cream-type frozen dessert mixes were seen in the form of intertwined rings (Attachment 2). The fact that the image clarity of the banana-based samples was lower than the strawberry and nectarine-based samples could be due to the starch and fibrous structure found in bananas. It appeared that the foam distribution and size was not completely homogeneous in mixes. However, others were more homogeneous than other samples of the same fruit type. The most homogeneous appearance in strawberry-based mix was formed in the S_0.27C_0.36A_0.36, and this was the most admired sample among other strawberry-based dessert in terms of firmness, homogeneous structure and general appearance. Similarly, the most homogeneous appearance in nectarine based mix was formed in the N_0.27C_0.36A_0.36, and this was the most admired sample among other nectarine-based dessert in terms of firmness and general appearance. The most homogeneous appearance in banana-based mix was formed in the B_0.20C_0.40A_0.40, and this was the most admired sample among other banana -based dessert in terms of homogeneous structure and general appearance. It was stated that larger air bubbles were related to greater foam stability (da Silva et al. 2020). Therefore, S_0.44C_0.11A_0.44, N_0.44C_0.11A_0.44, and B_0.44C_0.11A_0.44 which had larger bubbles, lower dry matter, and partially higher overrun could show more stable foam properties.

Quality characteristics of fruit based ice cream-type frozen dessert

Overrun

Overrun results of the samples were shown in Table 3. The overrun value is an important matter that affects the quality parameters of frozen desserts, such as color, texture, melting parameters and sensory properties. The overrun values varied from 116.75 to 395.93%. The highest overrun value was found in B_0.11C_0.44A_0.44, S_0.40C_0.20A_0.40, N_0.44C_0.11A_0.44. The effect of the fruit type on the overrun value was found to be statistically significant (p < 0.05). Similarly, it was reported in a study that the addition of durian puree increased the overflow of ice cream (the ability to bind water and form fruit gels), while the addition of jackfruit, melon, and pumpkin puree reduced the overflow of ice cream (Rawendra and Dwi 2020). The characteristics of the fruit variety also affect the overrun value of the ice cream.

Table 3.

Overrun (%), dry matter (%), L*, a*, and b* results of fruit-based ice cream-type frozen dessert with aquafaba

Samples	Overrun (%)	Dry matter (%)	L*	a*	b*
S0.33C0.33A0.33	168.40 ± 6.55eB	37.68 ± 0.07dA	73.09 ± 2.17bc	6.55 ± 2.20bc	9.80 ± 1.44a
S0.36C0.27A0.36	286.66 ± 10.34bcC	32.15 ± 0.21eA	72.80 ± 2.76bc	8.58 ± 2.54ab	10.22 ± 1.22a
S0.40C0.20A0.40	395.93 ± 7.04aC	25.01 ± 0.05fA	73.36 ± 4.52bc	10.04 ± 4.24ab	10.81 ± 1.42a
S0.44C0.11A0.44	273.20 ± 8.80cdB	16.74 ± 0.03gA	67.47 ± 6.27c	13.25 ± 3.05a	11.62 ± 1.46a
S0.27C0.36A0.36	294.01 ± 10.40bB	40.47 ± 0.39cA	79.76 ± 2.59ab	4.21 ± 1.69bcd	9.63 ± 0.65a
S0.20C0.40A0.40	276.01 ± 8.14bcdC	44.11 ± 0.05bA	80.59 ± 1.35ab	1.89 ± 0.96cd	9.42 ± 0.60a
S0.11C0.44A0.44	263.55 ± 4.22dB	48.35 ± 1.12aA	86.01 ± 1.85a	− 1.84 ± 0.27d	8.91 ± 0.31a
N0.33C0.33A0.33	238.89 ± 9.62bC	39.74 ± 0.73cB	83.45 ± 4.49a	− 2.83 ± 1.00ab	19.11 ± 1.50ab
N0.36C0.27A0.36	169.46 ± 10.91cdA	34.28 ± 0.35dB	81.60 ± 0.23a	− 3.37 ± 0.18b	19.30 ± 3.40ab
N0.40C0.20A0.40	272.81 ± 3.80aB	27.73 ± 0.24eA	80.69 ± 2.07a	− 2.97 ± 0.06ab	19.93 ± 1.61ab
N0.44C0.11A0.44	278.97 ± 3.44aB	19.62 ± 0.78fB	76.42 ± 1.28a	− 1.86 ± 0.32a	20.74 ± 1.76a
N0.27C0.36A0.36	139.62 ± 9.71eA	41.99 ± 0.32cA	81.65 ± 4.20a	− 3.81 ± 0.19bc	18.66 ± 1.10ab
N0.20C0.40A0.40	185.58 ± 6.75cB	45.02 ± 1.35bA	81.94 ± 0.66a	− 3.40 ± 0.27b	17.83 ± 1.94ab
N0.11C0.44A0.44	159.80 ± 8.49dA	48.86 ± 1.15aA	83.83 ± 2.85a	− 4.55 ± 0.43c	14.82 ± 1.04b
B0.33C0.33A0.33	116.75 ± 9.53dA	44.07 ± 0.16cC	81.80 ± 2.80ab	− 4.38 ± 0.31bc	14.07 ± 0.81bc
B0.36C0.27A0.36	212.41 ± 5.00cB	39.22 ± 0.03dC	80.66 ± 1.89bc	− 3.74 ± 0.33ab	14.28 ± 0.41bc
B0.40C0.20A0.40	248.96 ± 8.12bA	32.45 ± 1.41eB	78.90 ± 1.17bc	− 3.86 ± 0.18ab	14.78 ± 0.82b
B0.44C0.11A0.44	220.82 ± 4.56cA	24.98 ± 0.20fC	74.90 ± 1.12c	− 3.18 ± 0.09a	16.19 ± 0.28a
B0.27C0.36A0.36	128.95 ± 6.84dA	46.07 ± 0.98bcB	78.82 ± 3.35bc	− 4.05 ± 0.49b	13.34 ± 0.59cd
B0.20C0.40A0.40	132.89 ± 6.84dA	47.50 ± 0.39bA	87.32 ± 4.17a	− 4.40 ± 0.15bc	12.36 ± 0.11de
B0.11C0.44A0.44	268.43 ± 5.88aB	50.24 ± 0.30aA	84.36 ± 0.79ab	− 4.81 ± 0.24c	11.95 ± 0.31e

*Different lowercase letters indicate that the difference between samples of the same fruit variety statistically significant. Those shown with uppercase letters show that the samples prepared with different fruit types but containing the same amount of fruit, sugar and aquafaba are different from each other (p < 0.05). While the abbreviations S, N, B, C, A represent Strawberry, Nectarine, Banana, Sugar and Aquafaba, respectively, the numbers represent the percentages in the mixture

Dry matter amounts of fruit-based ice cream-type frozen dessert

Dry matter analysis result of the samples was given in Table 3. The dry matter content of the strawberry, nectarine, and banana-based dessert samples ranged between 17 and 48%, 20–49%, and 25–50%, respectively. Similarly, Çakmakçi et al. (2016) found the amount of dry matter in ice cream between 37.29 and 41.38%. The changing the amount of fruit content in banana and nectarine-based ice cream samples affected the dry matter amount less than strawberry-based dessert. It is seen that the use of different fruits in the samples with high fruit ratio creates a significant difference on the dry matter percentage (p < 0.05). Sugar makes the function of a dense sweetener and a source of dry matter in ice cream (Polischuk et al. 2013). As a result that phenomenon, the highest dry matter content was found in ice cream samples with the highest sugar and the lowest fruit ratio S_0.11C_0.44A_0.44, N_0.11C_0.44A_0.44, and B_0.11C_0.44A_0.44. The least dry matter content was found to be the lowest in sugar and the highest fruit ratio S_0.44C_0.11A_0.44, N_0.44C_0.11A_0.44, and B_0.44C_0.11A_0.44 samples were found.

The first dripping time and complete melting time of fruit-based ice cream-type frozen dessert

The melting feature of ice cream is important in terms of melting in the mouth during consumption and having an idea about how it should be stored at certain temperatures. The change of first drip and melting time of dessert during storage was shown in Fig. 2. During 2 months of storage, the first dropping times of strawberry, nectarine, and banana-based dessert samples varied between 348 and 1538 s, 369–1689 s, and435–1985 s, respectively. In addition, during 2 months of storage, the complete melting time of strawberry, nectarine and banana-based dessert samples was between 1234 and 3403 s, 1260–3705 s, and 1007–3362 s, respectively. While strawberry-based and banana-based desserts melted late in the 15th day, nectarine-based desserts melted late in the 60th day. The first drop and complete melting time of samples with high sugar content (S_0.11C_0.44A_0.44, N_0.11C_0.44A_0.44, and B_0.11C_0.44A_0.44), were found to have the lowest values. Alamprese et al. (2002) indicated that there was an inverse correlation between sugar concentration and melting time. This can be explained by the fact that the increase in sugar content negatively affects the freezing point of the ice cream mix. As a result of the decreasing of the freezing point, the solid fraction decreased, thus melting occurred faster, and the melting time was shortened (Kirmaci et al. 2014). The first drop and complete melting time of samples with high fruit pure content (B_0.44C_0.11A_0.44, S_0.44C_0.11A_0.44, N_0.44C_0.11A_0.44), were found to have the highest melting time values. Similarly, the addition of ginger paste to ice cream significantly increased the first dripping time (Gabbi et al. 2018).

Fig. 2.

Change in first dripping and completely melting time of ice cream-type frozen dessert during storage. While the abbreviations S, N, B, C, A represent Strawberry, Nectarine, Banana, Sugar and Aquafaba, respectively, the numbers represent the percentages in the mixture. (S) Strawberry (×S_0.11C_0.44A_0.44; — S_0.20C_0.40A_0.40; ☐ S_0.27C_0.36A_0.36; + S_0.33C_0.33A_0.33; ◼S_0.36C_0.27A_0.36;● S_0.40C_0.20A_0.40;▲ S_0.44C_0.11A_0.44), (N) Nectarine (× N_0.11C_0.44A_0.44; — N_0.20C_0.40A_0.40; ☐ N_0.27C_0.36A_0.36; + N_0.33C_0.33A_0.33; ◼ N_0.36C_0.27A_0.36;● N_0.40C_0.20A_0.40;▲ N_0.44C_0.11A_0.44), (B) Banana (×B_0.11C_0.44A_0.44; — B_0.20C_0.40A_0.40; ☐ B_0.27C_0.36A_0.36; + B_0.33C_0.33A_0.33; ◼B_0.36C_0.27A_0.36;● B_0.40C_0.20A_0.40;▲ B_0.44C_0.11A_0.44)

Color properties of fruit-based ice cream-type frozen dessert

Color properties of the desserts were shown in Table 3. It was seen that the sugar, Aquafaba, and fruit puree differences of the banana-based dessert samples were important for the L* (lightness), a* (redness), and b* (yellowness) values (p < 0.05). The highest b* value was obtained in the (B_0.44C_0.11A_0.44) banana sample with the highest fruit ratio. The highest b* and a* values were observed in the (S_0.44C_0.11A_0.44) strawberry samples with the highest fruit ratio. In the nectarine samples (N_0.44C_0.11A_0.44) with the highest fruit ratio, the b* value is the highest. This was shown that as the fruit ratio increased, the natural fruit color was linked to the final product. Color changes were linked to the color of the added ingredients. The highest L* values were observed in ice cream samples with the highest sugar content and the lowest fruit ratio. The increase in sugar ratio positively affected the L* value of all dessert samples. In a study, the L* value of fruit dessert samples decreased as the fruit ratio increased, and the b* value increased in parallel with the fruit ratio (Çakmakçi et al. 2016). In another study, it was determined that the highest b* value was seen in the dessert containing the most fruit puree (Aloglu et al. 2018).

Sensory analysis

The sensory results obtained by evaluating the sensory properties of frozen dessert samples according to 11 different criteria were given in Fig. 3. Only the cold intensity was found to be statistically different in the banana-based dessert samples (p < 0.05). The cold intensity value of the banana-based dessert sample (B_0.11C_0.44A_0.44) with high sugar content was scored low by the panelists. Since the high sugar content negatively affected the melting time of the ice cream samples, this situation negatively affected the intensity of coldness. Aroma and melting in mouth criteria were found to be statistically significant in strawberry-based samples (p < 0.05). While the dessert with low sugar content (S_0.44C_0.11A_0.44) got the lowest score in all ice creams, the sample (S_0.36C_0.27A_0.36) scored the highest. Increasing the volatility of the aroma components of sugar may be effective in achieving these results (Selli and Kilic Buyukkurt 2020). In nectarine-based dessert samples, the increase in the sugar content (36–44% w/w) and the decrease in fruit content (27–11% w/w) had a negative effect on the sensory properties. In the nectarine-based ice cream samples, those with a low fruit ratio scored low on the last taste in the mouth. In the nectarine-based dessert samples, those with a low fruit ratio scored low on the last taste by the panelists. The same result was observed with the banana-based sample. It was rated by the panelists that Aquafaba did not cause bitterness and sourness in the ice cream samples. The overall acceptability of Strawberry and Nectarine samples received higher scores than the samples containing Banana. Sugar content also affected overall acceptability. Low sugar content is rated low. In general, samples with a balanced sugar-fruit ratio were given higher scores.

Fig. 3.

Sensory analysis results of ice cream-type frozen dessert with aquafaba. While the abbreviations S, N, B, C, A represent Strawberry, Nectarine, Banana, Sugar and Aquafaba, respectively, the numbers represent the percentages in the mixture. (S) Strawberry (×S_0.11C_0.44A_0.44; — S_0.20C_0.40A_0.40; ☐ S_0.27C_0.36A_0.36; + S_0.33C_0.33A_0.33; ◼S_0.36C_0.27A_0.36; ●S_0.40C_0.20A_0.40; ▲S_0.44C_0.11A_0.44), (N) Nectarine (×N_0.11C_0.44A_0.44; — N_0.20C_0.40A_0.40; ☐ N_0.27C_0.36A_0.36; + N_0.33C_0.33A_0.33; ◼N_0.36C_0.27A_0.36; ●N_0.40C_0.20A_0.40; ▲N_0.44C_0.11A_0.44), (B) Banana (×B_0.11C_0.44A_0.44; — B_0.20C_0.40A_0.40; ☐ B_0.27C_0.36A_0.36; + B_0.33C_0.33A_0.33; ◼B_0.36C_0.27A_0.36; ●B_0.40C_0.20A_0.40; ▲B_0.44C_0.11A_0.44)

Conclusion

Aquafaba's improvement in parameters such as foaming capacity, foam stability, and gelling provide important gains for ice cream-type products. With all benefits of Aquafaba, it has the potential to lift the limitations of ice cream consumption and those who prefer a vegan diet, those who are lactose intolerant and allergic to certain proteins in milk. Moreover, the high foaming capacity (1250%) and stability (100%) of aquafaba make it possible for the aeration process, which is the most important feature for ice cream production. The consistency coefficient (K) showed a low value for the samples with the lowest sugar content and the highest fruit ratio (B_0.44C_0.11A_0.44, S_0.44C_0.11A_0.44and N_0.44C_0.11A_0.44) and the fruit variety statistically affected this value. Those samples also had larger bubble microstructure, lower dry matter, and partially higher overrun could show more stable foam properties. The high amount of fruit increased the overrun value, and the effect of the fruit type on the overrun value was found to be statistically significant (p < 0.05). The samples with the longest melting time belong to the B_0.44C_0.11A_0.44, S_0.44C_0.11A_0.44 and N_0.44C_0.11A_0.44 with the lowest sugar content and the highest fruit ratio, and it was found that the amount of fruit puree had a positive effect on the melting rate and increased the resistance of frozen dessert to melting. Aquafaba did not cause bitterness or sourness in dessert samples and did not affect the taste of the products. As a result, chickpea cooking water, which is economically worthless, is a suitable raw material for obtaining alternative products which could be an option for individuals who have allergies of dairy proteins, lactose intolerance or prefer a vegan diet. Further research can be conducted for people on a special food diet based on the assumptions that emerge from the findings.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

EE: Investigation, Validation; EA: Investigation, Validation; MC: Investigation, Validation; NCI: Writing- Reviewing and Editing, Visualization, Formal analysis; OST: Writing- Reviewing and Editing, Project administration, Supervision.

Funding

This work was funded by the Scientific and Technological Research Council of Turkey (TUBITAK), Project No: 1919B012000716.

Availability of data and material

It is open to sharing with appropriate request.

Declarations

Conflict of interest

The author declare that they have conflict of interest.