Physicochemical and techno-functional characterization of a composite flour for biodegradable edible spoons

Bengal gram (Cicer arietinum), an excellent plant source, is rich in proteins, amino acids, and polysaccharides that are used in increasing the hydration, emulsification, and texture of foods. Cereals and legumes are used in combination to obtain complementary nutritional and technological benefits [4, 5, 6] . Carrot powder is an important dietary source of β-carotene, dietary fiber, and antioxidants; turnip powder is known for its contribution of minerals, fiber, and phytochemicals; and bathua leaves (Chenopodium album) are rich in iron, calcium, vitamin C, folates, and antioxidants, which can provide substantial levels of micronutrients in food products. In addition to their nutritional benefits, vegetablebased flours significantly affect water absorption capacity, oil absorption capacity, water solubility index, water absorption index, foaming capacity, and emulsion activity, which determine dough properties, product texture, shelf stability, and product acceptance [2,7,8] .

Methodology 2.1 Study Design and Experimental Framework

A single factor completely randomized design (CRD) was used to analyze the effect of the ingredient type on various physicochemical and techno-functional parameters such as bulk and tapped densities, moisture and ash content, water absorption capacity (WAC), oil absorption capacity (OAC), water absorption index (WAI), water solubility index (WSI), foaming capacity (FC), foaming stability (FS), and emulsion activity (EA). Six samples of cereal-, legume-, leafy vegetable-, and root vegetable-based flours were prepared following standard methods and tested under the same experimental conditions to ensure that any differences between the ingredients were solely a result of the unique inherent physicochemical composition of each ingredient, rather than any external factor. To analyze these differences, the investigation was conducted in four major phases. The first phase involved the purchase of raw materials and preparation of test samples. The second phase was carried out to obtain values of the bulk and tapped densities, moisture, and ash contents. In the third phase, the techno-functional properties of the test flour samples were investigated to obtain their processing and product quality-related properties. The fourth phase used Design-Expert® statistical software for one-factor analysis of variance (ANOVA). Figure below summarizes the overall experimental procedure adopted in this study  Material selection  Sample preparation and storage  Analysis of selected functional properties  Determination of techno-functional properties  Analysis of the variance  Comparison of the flours All ingredients were prepared at their best quality. The samples were carefully checked for the presence of any debris and foreign material before the start of experimental analyses. Samples were then stored in airtight moistureproof polyethylene bags in ambient conditions (25±2 °C) for further testing and analysis in order to prevent any possible changes in their composition due to exposure to air and moisture.

Sample Preparation

To obtain reliable physicochemical and functional data, it is crucial that all samples undergo the exact same pretreatment to ensure consistent preparation. Hence, prior to all lab tests, the initial flour samples underwent the same pre-treatment procedure. All the raw ingredients (Sorghum, ragi, carrot, turnip and bathua) washed away and pretreated then dried in tray drier at the range of temperature 45-65℃ then grind all in pulveriser in the lab of svpu&at Meerut. The powders were then carefully combined by sterilized stainless steel spatulas into airtight high density polyethylene jars. Before all lab testing, all samples were stored at room temperature for around 24 h so that any difference due to storage temperature of the raw material on water absorption of flour could be minimized. Every experiment was conducted as a triplicate. The result was calculated as the mean (±S.D.) to minimize any experimental error and increase statistical reliability of the results.

Chemicals, Reagents and Laboratory Equipment

All chemicals were of analytical grade and all reagents were of laboratory grade in SVPUAT Meerut. Laboratory water generated from a laboratory water purification system was used for all hydration experiments. Commercially available, refined edible vegetable oil was used for oil absorption and emulsion activity experiments. No additional ingredients or preservatives were added to the flour sample for any experiment. The equipment used for experimentation included an analytical weighing balance (±0.001g), hot air oven, laboratory muffle furnace, centrifuge, vortex mixer, graduated measuring cylinders, desiccator, stainless-steel crucibles, moisture dishes, volumetric glassware, pipettes, magnetic stirrer, laboratory blender, and Design-Expert® software.

Determination of Physicochemical Properties

Physicochemical characterization is essential for generating the initial data needed to assess flour performance in terms of processing, storage, handling, and product quality. In this study, four physicochemical parameters were measured including bulk density, tapped density, moisture content, and ash content. These are important because they can affect flour packaging, transportation, mixing, water absorption properties and its shelf-life stability.

Determination of bulk density (BD)

The bulk density was determined as described in Eleazu et al., (2014) [14] by adding 50 g of flour sample to a graduated cylinder, and the volume recorded. The bulk density was calculated as weight per unit volume of sample Bulk Density (g/mL) =

Weight of Sample (g) Bulk Volume (mL) -Eq (3.1)

Determination of Tapped Density (TD)

The flour samples were gently filled into 10 mL graduated plastic cylinders. The bottom of the cylinder was gently tapped on a laboratory bench covered with foam several times until there was no further diminution of the sample level. The weight of the sample was calculated and the bulk density was calculated as weight of sample per unit volume of sample (Kaur et al., 2005) [15] .

Determination of Moisture Content

Moisture contents of flours samples were determined in a standard manner (AOAC, 2012) [16] by drying the product in a hot air oven. About 5 g of flour samples were accurately weighed into the pre-heated and pre-weighed moisture dishes then placed into hot air oven which is thermostatically controlled. Samples were dried at 105±2 °C in the oven for a period of approximately 4-6 hr, with constant weight attained. The hot-dried sample in the moisture dishes was then cooled in the desiccators containing dry silica gel to cool down to room temperature, followed by reweighing on an analytical balance. The moisture content of each sample was determined using equation 3.

Where:  W₁ = Initial weight of flour sample (g)  W₂ = Final oven-dried weight (g)

Determination of Ash Content

Ash content was analyzed in dry ashing as per standard (AOAC, 2012) [16] procedure. About 2 g of flour samples were accurately weighed into previously ignited and weighed porcelain crucibles. The sample material was first charred over a low flame to avoid loss of the materials during charring then, it was placed inside the laboratory muffle furnace at 550 °C until 5-6 h of light grey or white colored ash was obtained. The crucibles were removed from the furnace and placed inside a desiccator for cooling to ambient temperature and the weighed ash residue was weighed using an analytical balance. Ash was obtained from the following formula.

Weight of Ash

Sample Weight

Determination of Techno-Functional Properties

Flour's techno-functional properties are crucial in determining whether they are useful for food processing operations. These functional properties of the flour are mainly influenced by the starch, protein, dietary fiber, lipids and naturally occurring polysaccharides. The technofunctional characteristics of flour are particularly important for composite flour technology in which cereal starch, legume protein and vegetable fiber interact to form a matrix, which may change in water holding, oil binding, viscosity, foaming, emulsifying and texture attributes. Thus, technofunctional properties of composite flours are important for their application in bakery products, noodles, snacks, gluten free foods, beverages, soups, infant foods and nutritional supplements. [9] [10] .

Determination of water absorption capacity (WAC)

Water absorption capacity was examined using the technique stated by Okaka and Potter (1979) [17] . One gram of each flour sample was weighed & mixed with 10 mL of distilled water in a centrifuge tube. The mixture was centrifuged for 30 min at 2000 rpm while remaining at room temperature for the first 30 min (28 °C ± 2 °C). The supernatant was decanted at the end. The difference between the volume of the supernatant & the initial volume of water given to the sample was used to compute the water absorption capacity (WAC).

Weight of hydrated sediment-Original sample weight

Original sample weight × 100 -Eq (3.5)

Determination of Oil Absorption Capacity (OAC)

The oil absorption capacity was determined using the procedure stated by Okaka and Potter (1979) [17] . One gram (1 g) of each sample was measured using a weighing balance in an already-weighed centrifuge tube. 10 mL of refined vegetable oil (Soyabean oil, Sp. Gravity 0.9092) were mixed with the sample & allowed to stand for 30 min at 2000 rpm. Oil absorption capacity is expressed as% oil bound per gram flour.The unabsorbed oil was poured out, and the sediment weighed. The oil absorption capacity was calculated using Eq. (3.6).

Original sample weight × 100 -Eq (3.6)

Determination of Water Absorption Index (WAI)

Water absorption index (WAI) determine by the method of Suraiya Jamal et al. (2016) [18] . 1 g of sample was weighed and placed in a centrifuge tube. Then 6 ml of distilled water was added for suspension. The tubes along with the samples were heated in shaking water bath at the temperature of 80 °C for 30 minutes. The solution was centrifuged at 2500rpm for 10 minutes. After the centrifugation, the supernatants were carefully poured into Petri dish for drying at 105 °C for 10 hours in an oven, while the sediments were weighed as such. Water absorption index was calculated on the basis of wet sediments. The water solubility index of starches was carried out as described by Anderson and Sefa-dedeh (2001) [19] with little modification. 1 g each of the starches and 10 ml of water were mixed in a 15 ml plastic centrifuge tube and were immersed in water bath for 30 min at 37 °C This was then centrifuged at 4000 rpm for 10 min after which the supernatant was collected in a pre-weighed beaker and the residue was weighed after the water was evaporated at 105 °C; the percentage of residue with respect to the amount of starch used was taken as the water solubility index.

WAI(

Weight of dried soluble solids Original flour weight × 100 -Eq (3.8)

Determination of Foaming Capacity (FC) and Foaming Stability (FS)

The foam capacity (FC) and Foam stability (FS) by Narayana and Narsinga Rao (1982) [20] were determined as described with slight modification. The 1.0 g flour sample was added to 50 mL distilled water at 30±2 °C in a graduated cylinder. The suspension was mixed and shaken for 5 min to foam. The volume of foam at 30 s after whipping was expressed as foam capacity. Foaming capacity was calculated as described in equation below.

Where  V₁ = Initial volume before whipping (mL)  V₂ = Final foam volume immediately after whipping (mL)

The volume of foam was recorded 1 hour after whipping to determine foam stability as per percent of initial foam volume

Determination of Emulsion Activity (EA)

Emulsifying activity was determined as described by Okaka and Potter (1979) [17] . The sample (0.5 g) was added to 10 ml distilled water and shaking the mixture for 3 min in a centrifuge tube. The mixture was made up to 12.5 ml by adding oil and homogenized for 3 min. The resulting emulsion was centrifuged at 2000 RPM for 5 min and then the emulsion volume was measured. After the mixture has been spun, 3 layers were formed, i.e. top (oil), middle (emulsion), and the bottom (water) layers. The total height of each phase was then measured in the graduated tube.

Below Equation was used to calculate the emulsion activity.

Regression Model Development

Design-Expert® produced coded-factor and actual-factor equations for every response looked into. Because the factor coefficients are standardized, the coded equations were useful in determining the contribution of each ingredient to each response variable. On the other hand, the actual-factor equations, which gave the responses in terms of the initial ingredient levels, were used for prediction.

The coded regression model used in this study is described as follows:

Based on the analysis, it was observed that highly significant regression model fits were produced by the Design-Expert® software for all of the functional characteristics being explored. The coded and actual mathematical equations for the functional properties of water absorption capacity, oil absorption capacity, water absorption index, water solubility index, foaming capacity, foaming stability, and emulsion activity are given below.

Results and Discussion

Physicochemical Characterization of Individual Flour Samples

Assessing the potential of cereals, legumes, and vegetablesbased flours as a base for nutritionally enhanced flour formulations begins with physicochemical characterization. These physicochemical properties are critical, as they determine flour flow, packaging, shipment, storage characteristics, and process performance and also affect hydration characteristics and the food quality of the product derived from them. These differences are associated with the variations in their botanical origin, chemical composition, shape and size of starch granules, and particle size, along with differences in their content of dietary fiber and minerals. Six types of flour such as sorghum flour, finger millet flour, Bengal gram flour, carrot powder, turnip powder, and bathua powder were used in this study, and the physicochemical properties of these flours were evaluated.

The result reveals significant differences among all studied ingredients, which confirms that the differences in the composition of raw material may cause variations in their physicochemical properties, and these values provide a reference for later studies of functional properties of water adsorption, oil absorption, emulsion, and foaming capacity.

Bulk Density and Tapped Density

It seems that relatively higher bulk density of bathua powder was due to its relatively fine particle size and compact fibrous matrix of tissue which allows efficient particle packing. Relatively higher bulk density observed in sorghum and finger millet may be due to the presence of starch in the endosperm and less porous particle. Table 5 shows the results of bulk density of investigated flours, it can be observed that they were not same, values ranged from 0.455 g/ml to 0.568 g/ml. Among them carrot powder possesses lowest bulk density due to its cellular matrix, which dehydrated to become porous and has large volume per mass unit. These low-density vegetable powders may have good hydration and swelling capacity during food making. From the industrial point of view, ingredients with higher bulk density can minimize packaging volume, transportation cost, and storage volume. While ingredients with low bulk density can improve texture, hydration and swelling property of flour-based bakery products and instant food items. So, if high density cereal flour is combined with low density vegetable powder, then composite flour should possess a good blend between processing efficiency and functionally active properties. Tapped density is a measure of the highest packing achieved following mechanical compaction and is often correlated with the compressibility, storage and handling of powders in the industry. A large difference in the bulk and tapped density indicates greater compressibility and inter-particle empty space.

Moisture Content

Moisture content is among the primary quality factors affecting the storage stability, microbial safety, enzyme activity, and shelf life. A lower moisture content improves the quality of the product and prevents microbial activity and chemical breakdown of food products. The moisture contents of the different flours were found to be in the range of 5.216 to 9.002% (Table 5). The flour sample from Bengal gram contained the maximum (9.002±0.235%) moisture, and the flour sample from turnip contained the minimum moisture content (5.216±0.359%). Carrot flour also showed the minimum moisture content (5.976±0.472), and sorghum, finger millet, and bathua flour contained a moderate moisture content in comparison to the above. The lower moisture content of flour powder may be due to efficient drying during powder processing. Such flours are preferred, and their low moisture content results in high shelf life, a low rate of microbial growth, and good storage quality. However, Bengal gram flour had the highest moisture content, indicating its storage quality could be improved. All the studied samples showed acceptable values of moisture content required for commercial flour storage, indicating the suitability of raw materials used for composite flour.

Ash Content

Ash content is the major criterion of food ingredients that indicates the total amount of inorganic matter left when food ingredients are completely incinerated. It is the most common indicator of mineral content such as calcium, potassium, magnesium, phosphorus, and iron in the ingredients. Ingredients having high ash content are of higher nutritional value. High ash content of bathua flour shows that the ingredient is very rich in mineral content and has a high potential to increase mineral content while making composite flour products. It is also seen that vegetables like turnip and carrot have much higher mineral contents than cereals because of naturally occurring micronutrient contents. However, sorghum and finger millet showed low ash values because minerals are generally low in cereal grains as compared to vegetables. Thus, bathua flour and other vegetable flour samples showed high mineral contents and high potential to increase mineral contents and increase nutritional values of composite flour.

Techno-Functional Properties of Flour Samples

The techno-functional characteristics of flours play a crucial role in food processing; they significantly affect final product quality by influencing properties such as texture, moisture content, emulsification, and foaming, as well as consumer acceptability. These characteristics are significantly influenced by the chemical composition of starch, protein, dietary fiber, lipids, and native polysaccharides. As the present investigation involved cereal, legume, and vegetable powders with differing compositions, diverse functional properties were anticipated.

Water Solubility Index (WSI

The Water Solubility Index (WSI) of the extrudates was significantly influenced by the type of ingredient incorporated (F(5,12) = 9.95, p = 0.0006), as revealed by one-way ANOVA. The model explained 80.57% of the total variation in WSI (R² = 0.8057), with an adjusted R² of 0.7248 and a predicted R² of 0.5629, the close agreement between which confirmed the adequacy and predictive reliability of the model. An adequate precision ratio of 8.271 (>4) further validated an acceptable signal-to-noise ratio for navigating the design space. Among the ingredients evaluated, Carrot-incorporated samples exhibited the highest WSI (30.86%), followed by Bengal Gram (23.28%), Turnip (16.86%), and Bathua (16.61%), while Ragi (7.90%) and Sorghum (6.99%) recorded the lowest WSI values. The higher WSI observed in Carrot and Bengal Gram-based formulations may be attributed to greater starch degradation, dextrinization, and gelatinization during extrusion, leading to the formation of smaller, more soluble molecules, whereas the lower WSI in Sorghum and Ragi could be associated with their comparatively lower starch and higher fiber content, which limit water-soluble fragment formation during processing.

Water Absorption Index (WAI)

The effect of ingredient type on water absorption index (WAI) was evaluated using a one-factor ANOVA. The model was highly significant (F = 1175.35, p < 0.0001), indicating that ingredient type had a statistically significant effect on WAI, with only a 0.01% probability that this variation arose from noise. The model accounted for 99.80% of the total variability (R² = 0.9980), and the close agreement between the Adjusted R² (0.9971) and Predicted R² (0.9954)a difference well under 0.2confirmed the model's strong predictive reliability. A low coefficient of variation (C.V. = 1.35%) indicated high reproducibility across replicates, and an Adequate Precision ratio of 84.76 (far exceeding the minimum desirable threshold of 4) confirmed an adequate signal-to-noise ratio for the model to be used to navigate the design space. Among the ingredients, Turnip exhibited the highest WAI (4.473%), followed closely by Carrot (4.241%), while Bengal Gram recorded the lowest WAI (2.026%). Bathua, Ragi and Sorghum showed intermediate values of 4.174%, 2.979% and 3.391%, respectively. These results suggest that Turnip, Sorghum, and Carrot possess a greater capacity to bind water within their matrix, likely attributable to differences in their polysaccharide, fiber, and protein composition relative to Bengal Gram flour.

Water Absorption Capacity (WAC)

There was a considerable difference in the WAC of different flour types examined in the present study. Bathua flour displayed the highest value (316.33%), followed by carrot flour (296.942%), turnip flour (284.56%), Bengal gram flour, finger millet flour (128.36%), and sorghum flour (108.46%). Bathua flour exhibited high WAC, which can be attributed to its high dietary fibre content; the presence of pores inside the cells could also provide a large surface area that enables numerous interactions with water molecules through hydrophilic binding. Carrot and Turnip powder demonstrated high absorption due to the presence of pectin and soluble polysaccharides. Compared with vegetable powder samples, cereal flours showed lower values, as starches possess lesser hydrophilic groups than dietary fibers found in vegetable flours. The analysis of variance (ANOVA) showed a highly significant difference among the where the F-value was found to be high (2194.88) and the p-level 0.0001 (p < 0.0001), R² was found to be 0.9989. The high value of R² confirmed that the proposed model fitted the data well.

Oil Absorption Capacity (OAC)

Oil absorption capacity is a quality characteristic that reflects the ability of flour to absorb or retain lipids when incorporated into food formulations during food processing. High oil absorption capacity increases flavor retention, sensory attributes and the tenderness of the processed foods. The higher oil absorption in carrot and bathua powders could be due to the porous fibrous structure and the ability of hydrophobic protein domains to trap the oil molecules. However, lower oil binding capacity was recorded in turnip powder indicating lesser interactions between oil and the powder. A highly significant model F-value of 43.81, p < 0.0001, and R2 of 0.9481 suggested that ingredient was highly significant for oil absorption capacity.

Emulsion Activity (EA)

The emulsion activity of the flour samples was significantly influenced by ingredient type (F (5,12) = 477.75, p < 0.0001), as revealed by one-way ANOVA. The model explained 99.50% of the total variation in EA (R² = 0.9950), with an adjusted R² of 0.9929 and a predicted R² of 0.9888, the close agreement between which confirmed excellent model adequacy and predictive reliability. An adequate precision ratio of 55.426 (>4) further validated a very strong signal-to-noise ratio. Among the ingredients evaluated, Bengal Gram incorporated samples exhibited a markedly higher EA (39.50%) than all other formulations, followed by Sorghum (16.50%), Ragi (10.50%), Bathua (7.50%), Carrot, (6.00%) and Turnip which recorded the lowest EA (5.5%). The pronounced emulsifying activity of is likely attributable to a higher proportion of soluble, surface-active proteins capable of adsorbing at the oil-water interface, whereas the carbohydrate/pectin-dominant composition of turnip and carrot limited its capacity to stabilize an emulsion.

Foaming Capacity (FC)

Ingredient type had a statistically significant effect on foaming capacity (F(5,12) = 29.23, p < 0.0001). The model accounted for 92.41% of the variability in FC (R² = 0.9241), with an adjusted R² of 0.8925 and a predicted R² of 0.8293, indicating reasonable agreement and adequate predictive capability of the model. The adequate precision ratio of 13.757 confirmed a sufficient signal-to-noise ratio for reliable use of the model. Turnip exhibited the highest foaming capacity (8.70%), followed by Bathua (7.38%) and Bengal Gram (6.90%), while Carrot showed the lowest value (4.72%), closely followed by Ragi (4.92%) and Sorghum (5.56%). The superior foaming capacity of Turnip suggests a favorable proportion of flexible, soluble proteins able to rapidly unfold and lower interfacial tension at the air-water boundary, promoting greater incorporation of air during whipping.

Foaming Stability (FS)

One-way ANOVA revealed a highly significant effect of ingredient type on foaming stability (F (5,12) = 105.10, p < 0.0001). The model explained 97.77% of the total variation in FS (R² = 0.9777), with an adjusted R² of 0.9684 and a predicted R² of 0.9498, demonstrating strong model adequacy and predictive reliability. The adequate precision ratio of 25.678 confirmed an excellent signal-to-noise ratio. Turnip again showed the highest foaming stability (6.09%), followed by Bengal Gram (5.17%) and Bathua (4.10%), while Ragi recorded the lowest value (1.64%), followed closely by Carrot (2.36%) and Sorghum (2.38%). The greater foam stability of Turnip is consistent with its high foaming capacity, indicating that its protein fraction forms a more cohesive, viscoelastic interfacial film capable of resisting bubble drainage and coalescence over time.

Conclusion

This study successfully developed and characterized a novel cereal-legume-vegetable composite flour from sorghum, finger millet, Bengal gram, carrot, turnip, and bathua, formulated for the development of edible spoons as a sustainable alternative to single-use plastic cutlery. Significant variation was observed across ingredients in physicochemical and techno-functional properties, with bathua showing the highest water absorption capacity and carrot the highest oil absorption capacityproperties directly relevant to dough cohesion, mould-ability, and structural rigidity required for edible cutlery. These findings demonstrate that strategic ingredient selection can tailor composite flour functionality to produce a firm, food-safe, and biodegradable spoon, offering a nutrient-dense and environmentally responsible alternative to conventional plastic and single-ingredient edible cutlery.

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