Effect of Air Classification-Based Dry Fractionation on Structural, Thermal, and Functional Properties of Chickpea Protein Concentrate for Nanoemulsion Applications

Summary

Dry-extracted chickpea protein concentrate exhibited high protein content, strong foaming properties, and effective stabilization of nanoemulsion at a 3.0% w/v concentration. Structural and thermal analyses revealed an amorphous-dominant organization with low residual crystallinity and enhanced molecular flexibility, supporting its suitability as a sustainable, plant-based functional ingredient for food colloid systems.

Abstract

Chickpea protein concentrate (CPC) was obtained via a dry extraction approach and systematically characterized in terms of its compositional, functional, and structural properties to evaluate its suitability for nanoemulsion (NE) applications. The dry-extracted CPC possessed a protein content of 44.8% and demonstrated superior functional performance, including a foaming capacity of 61.1% and a high foam stability of 94.7%, reflecting efficient interfacial adsorption and cohesive film formation. NE formulation prepared using 3.0% w/v CPC as the emulsifying agent achieved a significant reduction in droplet size, yielding a Z-average droplet diameter of 152.7 nm and a low polydispersity index (0.30), indicating a fine, relatively uniform droplet size distribution and kinetically stable colloidal stability. Comparative differential scanning calorimetry (DSC) analysis of chickpea flour (CF) and CPC revealed two main endothermic transitions. While both samples exhibited a similar low-temperature transition at 68.4 °C associated with the release of bound water, CPC showed a substantially lower enthalpy change, indicating partial disruption of native molecular order following dry extraction. The X-ray diffraction (XRD) profile of the CPC utilized in the NE systems exhibited a broad amorphous halo within the 2θ range of 10°-30°, interspersed with limited low-intensity sharp reflections. These findings confirm an amorphous-dominant structure with partial crystalline regions, with the overall crystallinity of the concentrate estimated at approximately 15%. This study describes a reproducible and solvent-free protocol for the production of oil-in-water NEs using dry air-classified CPC, suitable for instructional use and potential industrial scale-up.

Introduction

Legume-derived proteins have gained significant attention as multifunctional ingredients for the design of structurally stable food emulsions. Among these sources, chickpea (Cicer arietinum) is particularly notable due to its high global production (the 3^rd most widely cultivated legume crop worldwide), substantial protein content (18%-24%), hypoallergenic nature, and balanced essential amino acid profile^1,2. Typically, protein isolates contain a higher protein concentration (80%-90%) as they undergo additional processing to remove carbohydrates and fats, whereas CPC (50%−75% protein) retains fiber and other essential nutrients³. These nutritional and agronomic advantages highlight chickpea protein as a viable alternative to conventional plant and animal protein emulsifiers. Despite their widespread use, emulsions stabilized with traditional low-molecular-weight surfactants often remain thermodynamically unstable and prone to coalescence, flocculation, and phase separation during storage¹. In contrast, NEs typically characterized by droplet diameters below 200 nm, exhibit enhanced kinetic stability, improved protection of encapsulated bioactive compounds, and increased dispersibility in aqueous systems. As a result, NE technology has emerged as an effective strategy for developing functional foods with controlled release and improved bioavailability of hydrophobic ingredients⁴.

A recent study has reported that CPC exhibits favorable interfacial and functional characteristics for NE formation, including strong water-binding capacity, notable foaming performance, and the ability to stabilize oil-water interfaces. CPC has also been evaluated as a potential substitute for egg yolk in mayonnaise-type emulsions due to its emulsification stability and clean-label appeal¹. Beyond such model systems, chickpea protein-based nanoemulsifiers have potential applications in various food matrices, including beverages (cloudy drinks, protein waters, antioxidant beverages, and the nanoencapsulation of curcumin, omega-3 fatty acids, carotenoids, and essential oils), plant-based dairy analogues, fat-reduced formulations, and bakery or confectionery fillings⁴.

Although the emulsifying functionality of chickpea protein (CP) has been widely reported⁵, nanoemulsifying systems derived from dry extraction routes have received comparatively limited attention, particularly regarding reproducibility, structural integrity, and scalability for food applications. Unlike conventional wet extraction protocols that require extensive pH adjustment, centrifugation, and solvent removal, air classification enables rapid protein enrichment under ambient conditions without the use of water, chemicals, or excessive thermal treatment³. Consequently, dry extraction offers distinct advantages over wet extraction methods by preserving protein functionality while reducing environmental burden and processing complexity^3,6.

However, a key unmet need in current food colloid research is a clear mechanistic understanding of how dry extraction modifies protein structure and thermal behavior, and how these changes translate into nanoemulsifying performance and colloidal stability. In particular, a systematic evaluation of structure-function relationships involving molecular organization, interfacial activity, and foaming behavior is required to advance the application of CPC-based food colloid systems⁷.

The novelty of this study lies in demonstrating the use of dry air-classified CPC as a reproducible, solvent-free nanoemulsifying agent, while directly correlating its compositional enrichment with structural, thermal, and interfacial functionality. Therefore, the present study aims to demonstrate that CPC obtained via dry air classification can function as an effective nanoemulsifier by systematically linking compositional enrichment with its structural, thermal, and interfacial properties. Particular emphasis is placed on physicochemical characterization, foaming capacity and stability, and XRD analysis to elucidate the structure-function relationships governing NE formation and stability.

Protocol

Sample preparation
Protein separation from chickpea flour (CF)
Kabuli chickpeas (Cicer arietinum L.), harvested during the 2025 growing season and sourced from southeastern Türkiye, were processed using an impact-based air classifier milling system, in which particles were subjected to centrifugal forces and repeated impacts against the grinding disc and ring gear. Following an initial pre-milling step, coarse grits were further milled to produce CF using an air classifier mill. During impact milling, an airflow rate of 40-45 m³/h, a classifier speed of 7,000-8,000 rpm, and a feed rate of 200 kg/h were applied, in accordance with previously reported operating conditions and an in-house optimization protocol, as described in the literature⁸.

Protein-rich fine fractions were subsequently obtained from CF by air classification at ambient temperature, using the same air classifier system. The classifier wheel speed was set to 10,000 rpm, while the feed rate was maintained at approximately 200 kg/h and the airflow at 52 m³/h, as previously described⁸. This separation step selectively enriched the protein fraction based on differences in particle size, density, and aerodynamic properties.

Following air classification, the resulting powder exhibited a fine particle size distribution (d(0.9) = 20-22 µm); therefore, no sieving step was applied to avoid material loss and unnecessary mechanical stress. The protein-enriched fraction was directly packaged in 25 kg gas-flushed polyethylene bags and stored at 4 °C to minimize moisture uptake and preserve functional properties until further processing.

Nanoemulsion preparation
CPC was used as the sole emulsifying agent to prepare oil-in-water (O/W) NEs targeting an active protein concentration of 3.0% w/v in the final formulation. This concentration was selected based on preliminary screenings of 1.0% w/v, 2.0% w/v, and 3.0% w/v CPC, which indicated that 3.0% provided the most effective droplet size reduction and the highest short-term physical stability. Based on the measured protein content of the CPC powder (44.8% w/w), the required powder concentration was calculated to be 6.67% w/v. CPC functioned as the emulsifier in the continuous aqueous phase, while medium-chain triglyceride (MCT) oil was used exclusively as the dispersed oil phase at a fixed concentration of 5.0% v/v, corresponding to 5.0 mL oil per 100 mL formulation. No low-molecular-weight surfactants were used in any formulations⁹.

The aqueous CPC dispersion was prepared by dissolving the calculated amount of CPC powder in ultrapure water under continuous magnetic stirring at 800 rpm for 1,800 s to ensure complete hydration and homogeneous protein dispersion. Complete hydration was confirmed by the absence of visible particles or sediment.

The oil phase was then slowly added to the hydrated CPC solution under continuous stirring, followed by high-shear homogenization at 12,000 rpm for 240 s, producing a coarse (conventional) emulsion, visually identified by a uniform, opaque appearance without visible oil separation. These conditions were selected to avoid protein aggregation while ensuring sufficient droplet disruption.

NEs were subsequently obtained by probe sonication of the coarse emulsion at 30% amplitude for 180 s, performed in an ice-water bath to maintain the sample temperature below 30 °C and prevent protein aggregation. Temperature was monitored intermittently during sonication. Preliminary optimization experiments (data not shown) evaluated sonication times of 60 s, 120 s, and 180 s, and 180 s was selected as the optimal condition based on reproducible formation of NEs with droplet diameters below 200 nm and low PDI. Therefore, all NEs reported in this study were prepared using the optimized sonication time of 180 s.

Successful NE formation was supported by the appearance of a stable, slightly opalescent dispersion with no phase separation after 1,800 s of standing. Samples exhibiting visible creaming or phase separation were excluded from further analysis. All samples were equilibrated to room temperature (25 ± 2 °C) prior to physicochemical characterization⁹.

CAUTION: Handling of high-energy equipment (homogenizer and sonicator) was conducted in accordance with institutional laboratory safety procedures. Hearing protection and splash shielding were used during sonication. No acids or bases were used during emulsion preparation; therefore, no chemical neutralization or hazardous waste disposal steps were required.

Nutritional and physicochemical characterization of chickpea flour (CF) and chickpea protein concentrate (CPC)
Compositional Analysis
The nutritional composition of CF and CPC samples was determined using Official Methods of Analysis of the Association of Official Analytical Chemists (AOAC). Crude fiber was analyzed according to AOAC 991.43, total ash according to AOAC 923.03, crude fat according to AOAC 920.39, and crude protein according to AOAC 984.13, using a nitrogen-to-protein conversion factor of N × 6.25. The total carbohydrate content of all samples was determined by difference by subtracting the sum of moisture, protein, fat, and ash percentages from 100%³.

Color analysis
The color parameters of the samples were measured using a bench-top colorimeter operating in reflectance mode. Prior to measurement, the instrument was standardized using the black and white calibration standards supplied by the manufacturer. To ensure uniform and reproducible measurements, 5.0 g of powdered sample was gently loaded into a round glass cuvette (64.0 mm internal diameter) to create a smooth, homogeneous surface. A sufficient layer thickness (≥ 50.0 mm) was applied to minimize the influence of substrate and background effects and to render the translucent powder effectively opaque under reflectance conditions. All measurements were conducted in reflectance mode at room temperature.

Color coordinates were expressed in the CIELAB color space, where L* represents lightness (0 = black, 100 = white), a* represents the red-green axis, and b* represents the yellow-blue axis. Additional color parameters, including total color difference (ΔE*), chroma (C*), hue angle (H°), and color index (CI), were calculated according to the equations described in¹¹ (Eqs. 1–4) as follows:

     (Eq. 1)

    (Eq. 2)

    (Eq. 3)

    (Eq. 4)

pH analysis
The pH of the CF and CPC samples was determined using a digital pH meter equipped with a glass electrode by inserting the electrode directly into the sample dispersion at 25.0 ± 2.0 °C. Prior to measurement, the pH meter was calibrated using standard buffer solutions (pH 4.0 and 7.0). All measurements were conducted in triplicate (n = 3) to ensure analytical reproducibility.

Moisture content
The residual moisture content of the CF and CPC samples was determined using a rapid moisture analyzer operated under controlled heating conditions. All measurements were performed in triplicate (n = 3) to ensure analytical reproducibility.

Structural and functional characterization of CPC
XRD analysis
XRD analysis of CPC was performed using a laboratory X-ray diffractometer equipped with Cu-Kα radiation (λ = 1.5406 Å). Diffractograms were recorded over a 2θ range of 10°-90° at a scanning rate of 2.5° min^-1, operating at 40 mA and 45 kV, following a previously reported procedure¹².

Peak identification, background subtraction, and curve fitting were carried out using standard XRD analysis software. The degree of crystallinity was calculated as the ratio of the integrated area of the crystalline reflections to the total area under the diffractogram, according to the method described by¹³, as shown in Eq. (5):

    (Eq. 5)

The apparent crystallite size (D) was estimated from the XRD data using the Scherrer equation (Eq. 6), applied to the most intense diffraction peaks:

      (Eq. 6)

where D is the apparent crystallite size (nm), K is the shape factor (assumed to be 0.9), λ is the X-ray wavelength, β is the full width at half maximum (FWHM, in radians) of the selected diffraction peak, and θ is the Bragg angle.

Differential scanning calorimetry (DSC) analysis
Differential scanning calorimetry (DSC) analysis of CF and CPC was performed using a laboratory differential scanning calorimeter. Approximately 10.0 ± 0.1 mg of sample was accurately weighed and sealed in a concave aluminum crucible with a pierced lid, while an empty aluminum crucible was used as the reference. Measurements were conducted under a nitrogen atmosphere (20 mL/min) to minimize oxidative effects. Samples were heated from 0 °C to 400 °C at a constant heating rate of 5 °C min^-1 under dynamic scanning conditions. Temperature and sensitivity calibrations were performed prior to analysis to ensure measurement accuracy and reproducibility.

Thermal transitions were characterized by determining the onset temperature (T_o), peak temperature (T_p), endset temperature (T_e), and the enthalpy change (ΔH) associated with each transition. In addition, the endothermic peak width (EPW) and peak height index (PHI) were calculated according to Eqs. (7) and (8), respectively:

EPW= (Te−Tp)    (Eq. 7)

PHI =ΔH/(Tp− To)     (Eq. 8)

Foaming capacity (FC) and stability (FS)
The foaming capacity (FC) and foam stability (FS) of a CPC aqueous dispersion (3.0 g/L) were evaluated at pH 7.0, adjusted as needed using 0.1 N hydrochloric acid (HCl). A 30 mL aliquot of protein dispersion were transferred into 50 mL polypropylene centrifuge tubes and homogenized using a high-speed homogenizer operated at 11,000 rpm for 120 s to generate foam. Foam formation was visually confirmed by the rapid increase in sample volume and the formation of a stable foam layer immediately after homogenization.

FC was calculated as the percentage increase in volume immediately after homogenization, while FS was determined based on the retained foam volume after 600 s, 1,800 s, 3,600 s, and 7,200 s. All measurements were performed in triplicate (n = 3), and the FC and FS values were calculated according to Eqs. (9) and Eqs. (10), respectively¹⁴:

    (Eq. 9)

   (Eq. 10)

CAUTION: Dilute hydrochloric acid was handled using appropriate laboratory safety precautions, including gloves and eye protection. Waste solutions were disposed of according to institutional chemical safety guidelines.

Physicochemical stability of CPC and CPC-based NEs
Average particle size and particle size distribution
Particle size distribution and Z-average hydrodynamic diameter of the samples were determined using dynamic light scattering (DLS). The Z-average hydrodynamic diameter and the polydispersity index (PDI) were recorded to characterize the mean droplet size and the uniformity of the size distribution, respectively^15,16.

Prior to measurement, samples were diluted with distilled water at a ratio of 1:100 (v/v) to minimize multiple scattering effects and ensure reliable light scattering measurements. Analyses were conducted at a controlled temperature of 25 ± 2 °C. The PDI was used as an indicator of droplet size distribution homogeneity, with lower PDI values corresponding to narrower size distributions. Measurements were performed on day 0 (freshly prepared NEs) and after 7 days of storage to evaluate the short-term physical stability of the NE system¹⁶. Samples exhibiting visible creaming, sedimentation, or phase separation prior to measurement were excluded from DLS analysis.

ζ-potential of particles
The ζ-potential of the samples was determined to assess the net surface charge and electrostatic stability of the droplets using electrophoretic light scattering (ELS), following previously described methodologies^15,16. Measurements were conducted at a controlled temperature of 25.0 ± 2 °C, and undiluted samples were used to preserve the original ionic environment of the NEs.

The mean ζ-potential values and corresponding standard deviations were calculated for each sample to evaluate electrostatic interactions and colloidal stability of the emulsions. All measurements were performed using water as the dispersant, in accordance with an established

internal standard operating procedure¹⁵. Samples showing visible phase separation or creaming prior to analysis were excluded from ζ-potential measurements.

Method validation and expected outcomes
Method validation was achieved by evaluating key physicochemical parameters, including Z-average hydrodynamic diameter, PDI, ζ-potential, and physical stability under stress. Successful protocol execution was supported by the reproducible formation of NEs with droplet sizes below 200 nm and PDI ≤0.30. To further validate stability beyond simple storage, a centrifugation stress test at 4,000 rpm for 900 s was performed. The absence of visible phase separation or creaming after centrifugation, coupled with consistent ζ-potential and pH profiles over 7 days of storage, collectively supports the robust emulsifying capacity of CPC and the reproducibility of the proposed protocol.

Statistical analysis
Compositional and functional measurements were conducted in triplicate (n=3), while structural analyses (XRD and DSC) were performed as single measurements, representative runs. The results are presented as the mean value ± standard deviation (SD). Statistical evaluations were performed using one-way analysis of variance (ANOVA) via in SPSS software. For all analyses, a p-value of < 0.05 was considered to indicate statistical significance. In cases where significant differences were identified, Tukey's Honestly Significant Difference (HSD) post-hoc test was employed for multiple comparisons. Statistical connecting letters (e.g., a, b, c) presented in the tables and figures were derived from the results of the Tukey HSD test; means sharing the same letter are not significantly different at the 5% significance level.

Results

Nutritional and physicochemical characterization of CF and CPC
Compositional parameters
The compositional parameters of the CF and CPC are summarized in Table 1. The CPC contained 44.8% protein, 5.8% crude fat, and 45.9% total carbohydrates, demonstrating a substantial enrichment of protein relative to CF as a result of the dry fractionation process. The increased protein content observed in CPC confirms the effectiveness of air classification in concentrating protein-rich fracti...

Discussion

In this study, CPC was obtained by air classification and characterized in terms of its compositional, functional, structural, and colloidal properties, with a particular focus on its application as a plant-based nanoemulsifier. Non-thermal methods, such as air classification, can yield a marked enrichment of protein content relative to CF, yielding a CPC with a protein content of 44.8%³. Compared with the predominantly wet-extraction-based CPC reported in the literature, the present work extends ...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
50 mL conical tubes	Corning	352070	Polypropylene centrifuge tubes
Air classifier mill		CSM1250	Air classifier mill used for protein fractionation
Analytical balance	Sartorius	BCE224I-IS	Analytical balance (max. capacity 120 g)
Automatic pipettes	Brand	3123000055	Adjustable pipettes (200 μL, 1 mL, 5 mL)
Centrifuge	Eppendorf	5810R	Refrigerated centrifuge
Chickpea sample		—	Food-grade chickpeas
Colorimeter	HunterLab	A60-1014-593	Instrument for colour analysis
Differential scanning calorimeter	NETZSCH	—	DSC analysis
Digital thermometer	Hanna Instruments	HI-98501	Temperature monitoring
Dipotassium hydrogen phosphate (Na2HPO4)	Sigma-Aldrich	S7907	Analytical grade
Fat analyzer	C. Gerhardt GmbH & Co. KG	13-0005	Soxhlet-based fat analysis
High-speed homogenizer	VELP	SA20900010	Homogenization of coarse emulsions
Hydrochloric acid (HCl)	Sigma-Aldrich	320331	Analytical grade
Hydrochloric acid solution (0.1 N)	Sigma-Aldrich	H1758	pH adjustment
Kjeldahl catalyst tablets	C. Gerhardt GmbH & Co. KG	12-0328	Kjeldahl analysis
Magnetic stirrer	IKA	3339000	Sample mixing and hydration
Medium-chain triglyceride oil	Ataman Kimya A.	https://www.atamanchemicals.com /medium-chain-triglycerides-mct _u30009/?lang=TR#:~:text =Orta%20zincirli%20trigliseritler %20(MCT)%2C%20hindistance vizi%20ve%20hurma%20%C3 %A7ekirde%C4%9Fi%20ya%C 4%9Flar%C4%B1nda,g%C3%B Cne%C5%9F%20kremleri%20i% C3%A7in%20%C4%B1slat%C4% B1c%C4%B1%20ajand%C4%B1r.	Food and pharmaceutical grade oil
Moisture analyzer	Mettler Toledo	HC103	Moisture determination
Particle size and zeta potential analyzer	Malvern Instruments	ZEN3600	DLS and electrophoretic mobility
pH meter	Mettler Toledo	MET-30671567	pH measurement
Plastic centrifuge tubes	ISOLAB	078.02.003	Disposable plastic tubes
Porcine pepsin	Sigma-Aldrich	P7012	Enzyme (1:10,000)
Potassium dihydrogen phosphate (KH2PO4)	Sigma-Aldrich	P5379	Analytical grade
Probe sonicator	Bandelin	—	Emulsion sonication
Protective goggles	Baymax	BX-2500	Laboratory safety equipment
Protein analyzer	C. Gerhardt GmbH & Co. KG	12-0520	Protein determination
Protein digestion system	C. Gerhardt GmbH & Co. KG	12-0700	Kjeldahl digestion unit
Sodium chloride (NaCl)	Sigma-Aldrich	S9625	Analytical grade
Sodium hydroxide (NaOH)	Sigma-Aldrich	S5881	Analytical grade
Spatula	—	https://www.blabmarket.com/ meta-etiket/plastik-spatul?srsltid =AfmBOoqsvXR_3rQgU1n8QBn DyR_P9D52v2Hahy27RLOH7Zg VbFzzcbsb	Plastic spatula
Ultrapure water system	ELGA Labwater	PC110COBPM1	Water resistivity 18.2 MΩ·cm
Volumetric flask	Schott Duran	2120117	100 mL volumetric flask
Water bath	Memmert	WTB24	Temperature control (20–25 °C)
X-ray diffractometer (Cu–Kα)	PANalytical	STEM-LE-0294-LC	XRD analysis (45 kV, 40 mA)