Electrical Parameters as a Tool for Evaluating the Quality and Functional Properties of Superfruit Purees

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The findings indicate that electrical parameters may be incorporated into process monitoring as an additional screening layer for fruit purées. By providing rapid feedback on compositional variability, this approach can help optimize raw material selection and support decision-making in industrial quality control workflows, while reducing reliance on laboratory-based chemical assays.

Abstract

This study aimed to evaluate the potential of electrical parameters for assessing the quality and health-promoting properties of fruit purees derived from twelve superfruit species native to north-eastern Poland. Their physicochemical characteristics were determined using reference methods, while electrical measurements were conducted with a custom-built system based on an equivalent circuit model (RCC). The recorded electrical parameters included impedance, admittance, and series and parallel capacitance across a frequency range of 100 Hz–1 MHz. Pronounced differences in dry matter, extract, ash content, and bioactive compounds were observed between species. Cluster analysis and PCA revealed that purées with higher bioactive compound content exhibited strong and statistically significant correlations between electrical parameters reflecting impedance and admittance and variables such as dry matter, total extract, and ash (p < 0.01). In contrast, capacitance-based parameters showed weaker and more composition-specific relationships. In purées with lower levels of bioactive compounds, the number and strength of correlations were reduced. These findings indicate that frequency-resolved electrical parameters may serve as a complementary, non-destructive tool for assessing composition-related variability in fruit purées and may support rapid quality evaluation alongside conventional assays.

1. Introduction

The modern approach to food production and consumption increasingly reflects growing awareness of the population regarding health and environmental sustainability. Consumers are seeking food products that are not only natural but also nutrient-dense and rich in bioactive compounds, which has fueled interest in functional foods, including especially superfruits. Raw materials particularly rich in polyphenols, flavonoids, vitamins, and other antioxidants include hardy kiwi (Actinidia arguta), cornelian cherry (Cornus mas), elderberry (Sambucus nigra), haskap berry (Lonicera caerulea), blueberries (Vaccinium spp.), cherry silverberry (Elaeagnus multiflora), and sea buckthorn (Hippophae rhamnoides). Their polyphenol-, flavonoid- and vitamin C-rich profiles have been associated with cardioprotective, anti-diabetic and anti-obesity effects in preclinical and clinical studies [1,2,3,4,5,6,7,8,9,10,11]. Furthermore, the literature emphasizes that natural sources of antioxidants often exhibit higher bioavailability than their synthetic counterparts, which further reinforces the importance of plant-based raw materials in the development of functional foods [5].

Despite the growing market potential of superfruit-derived products (e.g., purees), their limited stability and susceptibility to external factors remain a major technological challenge [12]. Preserving the sensory quality and nutritional value of foods during processing and storage requires methods that enable precise, rapid, and non-destructive monitoring of key quality parameters. Conventional chemical, physical, and sensory techniques, although accurate and widely accepted as reference methods, are often time-consuming, costly, and destructive to the samples. Therefore, a growing need emerges to develop and implement innovative quality assessment tools suitable for process control and final product evaluation [13,14].

One of the promising approaches in modern food analytics is the use of electrical methods. Fruit purees represent multiphase systems with a complex structure composed of macromolecules and micromolecules, colloids, and different forms of water. This compositional complexity determines their dielectric and conductive properties, which arise mainly from the presence of electrolytes, interactions between soluble and insoluble components, and the colloidal network. Consequently, electrical parameters reflect intrinsic chemical, physical, and microbiological interactions, making them a valuable tool for monitoring technological and quality-related changes in fruit purees [15,16]. Previous studies, including impedance-based assessments of fruit quality [17,18,19], have confirmed the applicability of impedimetric methods for evaluating fresh fruits and vegetables, for example, in assessing their ripeness and firmness, detecting internal defects, and monitoring changes during storage or under stress conditions.

In particular, electrical impedance spectroscopy (EIS) has been applied to whole fruits and vegetables, showing strong correlations between electrical parameters and physicochemical and sensory attributes [13,17,20,21]. However, data obtained for intact fruits cannot be directly extrapolated to the matrix of processed products with degraded cellular structures, such as fruit purees, due to differences in electrolyte distribution and the critical role of pectins and insoluble particles.

The present study differs from classical Electrical Impedance Spectroscopy (EIS) approaches in that it employs a custom-designed measurement setup and an RCC-based equivalent circuit model, tailored specifically to the multiphase structure of fruit purees. Unlike standard EIS, which typically relies on Cole–Cole or constant phase element (CPE) models, the RCC approach allows for a more targeted separation of bulk and interfacial effects. Therefore, the literature comparisons with EIS-based studies are used for contextual purposes only, and direct methodological equivalence should not be assumed.

Available studies on fruit purees are limited in number and scope, typically focusing on single fruit species, a narrow frequency range, individual electrical parameters (most often conductivity or impedance), or simplified equivalent electrical models [22,23,24,25]. In contrast, comprehensive multi-species analyses that simultaneously address a range of electrical parameters (conductive and capacitive) and their relationships with technological traits and bioactive properties remain scarce. A notable research gap concerns purees derived from local superfruits grown in north-eastern Poland—a region of growing importance for the development of functional foods and short supply chains. Addressing this gap may provide practical benefits not only for quality control and nutritional value preservation but also for supporting the sustainable growth of the regional food sector.

The aim of the study was to evaluate the applicability of electrical parameters (conductive and dielectric), measured with a custom-built system, as a novel tool for assessing the quality and functional properties of superfruit purees derived from north-eastern Poland.

In line with this overarching objective, the study pursued the following specific aims:

• To assess differences in technological traits and functional properties of purees from 12 superfruit species using conventional physicochemical and functional reference analyses.
• To determine the electrical profile of fruit purees using the RCC equivalent circuit model.
• To identify statistical correlations between electrical parameters and the technological traits and functional properties of the investigated purees.

These objectives enabled the testing of the following research hypotheses:

H1. 

Electrical parameters (Z, Y, Cp, Cs) are significantly correlated with the quality attributes and functional properties of superfruit purees.

H2. 

Electrical parameters measured using the RCC equivalent model provide a useful tool for evaluating the quality and functional properties of fruit purees.

2. Materials and Methods

The experimental material consisted of purees prepared from 12 superfruit species: blueberry (Vaccinium corymbosum); elderberry (Sambucus nigra); sea buckthorn (Hippophae rhamnoides); guelder rose (Viburnum opulus); blackberry (Rubus spp.); bird cherry (Padus serotina); black currant (Ribes nigrum); black mulberry (Morus nigra); haskap berry (Lonicera caerulea); hardy kiwi (Actinidia arguta); cornelian cherry (Cornus mas); cherry silverberry (Elaeagnus multiflora).

All fruits derived from north-eastern Poland (University of Warmia and Mazury, Olsztyn, Poland; 20°29′ E, 53°47′ N) and were harvested at the stage of consumption maturity during the 2022 growing season. Fruit samples of each species, weighing about 1.5 kg each, were collected in three terms, every five days. The fruits were washed and frozen at −18 °C for six months. After thawing, the fruits were steamed (100 °C/7 min), pureed, homogenized, heated, and pasteurized (85 °C/15 min). Independent fruit batches of each species were considered as biological replicates, whereas repeated measurements performed within the same batch were treated as technical replicates (n = 6).

2.1. Physicochemical Analyses

The overall experimental workflow, including fruit processing, physicochemical and functional analyses, electrical measurements and statistical processing, is summarized in the technical roadmap presented in Figure 1. All chemicals used in the analyses were of analytical grade and were purchased from Centralchem (Bratislava, Slovak Republic).

2.1.1. Dry Matter, Ash, Protein and Fat Content

The contents of dry matter, ash, and crude protein were determined according to the AACC method 08-01 [26]. Nitrogen content was measured using the semi-micro Kjeldahl method, and crude protein content was calculated as N × 5.7. The conversion factor 5.7 was selected in accordance with the AACC 08-01 recommendations for plant-based, carbohydrate-rich matrices with relatively low protein content and is consistent with critical evaluations of nitrogen-to-protein conversion factors indicating that matrix-specific factors in the range 5.6–5.8 better reflect true protein levels than the generic factor 6.25 [26,27,28]. The results were expressed as percentages.

Fat content was determined with an Ankom XT15 Fat Extractor (Ankom Technology, Macedon, NY, USA) following the manufacturer’s instructions. The sample (1.5 g, W1) was weighed into a special filter bag (XT4, Ancom, Macedon, NY, USA) and dried at 105 °C for 3 h to remove moisture before the extraction. The dried bags were cooled in a desiccator for 15 min and reweighed (W2). Samples were then extracted with petroleum ether at 90 °C for 60 min. Afterwards, they were dried at 105 °C for 30 min in an oven, transferred to a desiccator, and reweighted (W3). Fat content (%) was calculated using the following equation: [(W2 − W3)/W1] × 100.

2.1.2. Total Extract Content

The total extract content was determined with the refractometric method [29]. The refractive index of the sample filtrate was measured and the extract content was read directly from the refractometer scale and expressed as percentage (m/m).

Preparation of samples: After removal of the non-edible portion, the thawed sample was mixed with the juice released during thawing. Then, a few drops of the mixture were filtered through a nylon cloth, and the filtrate was transferred to the refractometers. After the reading stabilized, the extract content was recorded.

2.1.3. Total Acidity

Total acidity was determined by titration with 0.1 M NaOH using phenolphthalein as an indicator [30]. Phenolphthalein (ρ20, alcoholic solution, r = 10 g/L) was used as the indicator.

Samples were prepared similarly across all product groups. Solid products were ground into a fine powder and thoroughly mixed. Frozen foods were thawed in a covered dish (at approx. 20 °C), with seeds and woody parts removed, then thoroughly mixed and ground in a mortar or homogenizer.

For total acidity determination, 25 g of the prepared sample was weighed to the nearest 0.01 g into a 250 mL beaker. Approximately 100 mL of distilled water were added, and the mixture was brought to a boil. The solution was then cooled and transferred quantitatively to a 250 mL volumetric flask, filled up with distilled water, stirred, and left to stand for about 15 min. The resulting solution was filtered and centrifuged at 12,000 rpm for about 10 min. The filtrate was used for determinations.

For the titration, 5 mL of the filtrate were mixed with 50 mL of distilled, and 3 or 4 drops of phenolphthalein were added as an indicator. The solution was titrated with NaOH. Two titrations were performed for each fruit sample.

Total acidity (X) was calculated in grams per 100 g of product according to the following equation:

$$\mathrm{X} = {\displaystyle \frac{\mathrm{V}\times \mathrm{N}\times \mathrm{K}\times {\mathrm{V}}_0\times 100}{{\mathrm{V}}_1\times \mathrm{m}}}$$

where

• V—volume of NaOH solution used for the titration of the solution, mL
• N—NaOH molarity, mol/dm³
• V₀—total volume of solution used to dilute and supplement the sample to a defined volume, mL
• V₁—volume of filtrate sample taken for titration, mL
• m—mass of sample, g
• K—factor used to convert the corresponding acid in individual products:
• K = 0.064—citric acid in products from berries and citrus; N = 0.1 mol/dm³; V₀ = 250 mL;
• V₁ = 5 mL; m = 25 g.

2.1.4. Preparation of Extract and Determination of Total Polyphenol Content and Radical Scavenging Activity

Samples (approx. 0.2 g) were extracted with 20 mL of 80% ethanol for 2 h. After centrifugation at 4000× g (Rotofix 32 A, Hettich, Tuttlingen, Germany) for 10 min, the supernatant was used for measurements (antioxidant activity, content of polyphenols).

The total polyphenol content was determined according to Singleton and Rossi [31] using the Folin–Ciocalteu reagent. To this end, 0.1 mL of the sample was mixed with 0.1 mL of the Folin–Ciocalteu reagent and 1 mL of 20% (w/v) sodium carbonate and left in the dark for 30 min. The absorbance at 765 nm was measured using the Jenway spectrophotometer (6405 UV/Vis, Stone, UK). Gallic acid (25–300 mg/L; R² = 0.998) was used as a standard, and results were expressed in mg/L of gallic acid equivalent.

Radical scavenging activity of the samples was measured using 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical [32]. The sample (1 mL) was mixed with 4 mL of a DPPH solution (0.025 g DPPH in 100 mL ethanol). Absorbance of the reaction mixture was determined at 515 nm using the Jenway spectrophotometer (6405 UV/Vis, Stone, UK). Trolox (6-hydroxy-2,5,7,8-tetramethylchromane-2-carboxylic acid) (10–100 mg/L; R² = 0.989) was used as the standard, and results were expressed in mg/g Trolox equivalents.

2.1.5. Total Flavonoid Content

The total flavonoid content was determined using the modified method of Willett [33]. The sample (0.5 mL) was mixed with 0.1 mL of a 10% (w/v) ethanolic solution of aluminum chloride, 0.1 mL of 1 M potassium acetate, and 4.3 mL of distilled water, and left in the dark for 30 min. Afterwards, absorbance at 415 nm was measured using the Jenway spectrophotometer (6405 UV/Vis, Stone, UK). Quercetin (0.5–20 mg/L; R² = 0.989) was used as the standard, and results were expressed in mg/g quercetin equivalent.

2.1.6. Total Ascorbic Acid (Vitamin C) Content

Ascorbic acid content was determined according to Klein and Perry [34]. A 0.5 g portion of fresh grape berries was extracted with 10 mL of 1% metaphosphoric acid, left for 45 min at room temperature, and filtrated (Whatman No. 4 filter). Next, the filtrate (1 mL) was mixed with 9 mL of 50 μmol/L 2,6-dichlorindophenol sodium salt hydrate, and left in dark for 30 min. The absorbance at 515 nm was measured using the Jenway spectrophotometer (6405 UV/Vis, Stone, UK). The calibration curve of L-ascorbic acid was used to calculate ascorbic acid content, and results were expressed as the ascorbic acid equivalent (mg AAE/100 g).

2.2. Electrical Measurements

Electrical parameters of the fruit purees (200 mL, 20 ± 0.01 °C) were measured using a measurement system consisting of:

• A sensor—a glass cell with two stainless steel plate electrodes mounted on the smaller inner walls of the container (own construction),
• An LCR meter, type E4980a (Agilent Technologies, Santa Clara, CA, USA).
• A metal container with a water jacket connected to a thermostat (PolyScience, Niles, IL, USA),

The electrical properties of the purees were evaluated based on impedance (|Z|), admittance (|Y|), parallel capacitance (Cp), and series capacitance (Cs) over a broad frequency range (100 Hz–1 MHz) at a voltage of 250 mV. The frequency range adopted in this study (100 Hz–1 MHz) was selected based on our previous work [14,35,36,37] and the operating capabilities of the LCR meter. The lower limit (100 Hz) helped to reduce the influence of electrode polarization and electrochemical phenomena at very low frequencies, whereas the upper limit (1 MHz) ensured stable operation of the measurement system and is consistent with the frequency ranges commonly used in dielectric studies of fruit products. Because the LCR meter recorded impedance components separately rather than the full complex impedance in a single measurement, the characterization was carried out as frequency-resolved analysis of impedance components, rather than impedance spectroscopy (EIS). This simplified, model-free approach facilitates direct use of the measured parameters in multivariate data analysis and is more convenient for potential routine quality-control applications than full EIS model fitting.

The glass container (L × W × H: 94 × 55 × 80 mm) was equipped with two stainless-steel plate electrodes mounted on opposite inner walls. The active area of each electrode was 44 cm², and the distance between them was 92 mm. The container was filled with 200 mL of fruit puree and placed inside a metal jacket with a water circulation system connected to a thermostat (PolyScience, Niles, IL, USA) to maintain the sample at 20 ± 0.1 °C. Prior to measurement, the samples were conditioned for 24 h in a climate chamber (Memmert ICP 500, Memmert, Schwabach, Germany). The electrode connections (1 m cables) were calibrated using the open/short/load compensation function of the Agilent E4980A LCR meter (Agilent Technologies, Santa Clara, CA, USA). To avoid polarization and electrolysis effects at the electrode—sample interface, only alternating current with a sinusoidal waveform was applied within the frequency range 100 Hz–1 MHz [38,39].

The analysis of the electrical properties of fruit purees was conducted according to an equivalent RCC electrical model (series-parallel resistance + capacitance)—Figure 2, previously developed by our research group for apple juice [14,36,37] and apple purée [38] characterization. A schematic diagram of the measuring system is presented in Figure 3.

Although the measurement system used in this study is based on a simplified RCC model rather than classical EIS, it was specifically adapted to the structural characteristics of homogenized fruit purees. This approach enables rapid, low-cost analysis better suited for dispersed matrices. Therefore, the literature comparisons with EIS should be interpreted as indicative rather than strictly equivalent.

2.3. Statistical Analysis

Statistical analyses were performed using Statistica 13.0 software (StatSoft Inc., Tulsa, OK, USA). The significance of differences between fruit purees was evaluated by analysis of variance (ANOVA) at significance levels of p < 0.05 and p < 0.01. Based on the selected quality attributes, hierarchical cluster analysis was conducted using Ward’s method, which allowed the classification of the 12 types of fruit purees into two distinct clusters.

The cluster analysis included all variables describing the tested fruit purees, covering a wide range of physicochemical parameters. These comprised: dry matter, protein, fat, total extract, total acidity, total ash content, polyphenols, flavonoids, antioxidant activity, and ascorbic acid. These attributes characterize the composition, bioactive compound content, and antioxidant properties of the samples. Due to the diversity of measurement units and scales across these parameters, data standardization was performed prior to cluster analysis to ensure comparability and equal weighting in classification outcomes.

The correlations between technological and functional traits and the electrical parameters of the fruit purees were determined using Principal Component Analysis—PCA [40,41]. PCA was applied to explore relationships in the multidimensional dataset while preserving the overall structure of interdependencies between variables. Prior to the analysis, the assumptions of factor analysis were verified using the correlation matrix, the Kaiser–Meyer–Olkin test (KMO > 0.6) and Bartlett’s test of sphericity (p < 0.05). Data were standardized to ensure the comparability of variables. All required criteria were met, confirming the appropriateness and validity of applying PCA in this study [42].

3. Results and Discussion

3.1. Physicochemical Analysis

The analysis of chemical composition and bioactive properties of purees from 12 superfruit species revealed significant differences in both their technological parameters and the content of bioactive compounds. Dry matter (DM) content ranged from ~10.51% in elderberry puree to ~25.54% in bird cherry puree (

Table 1. Results of measurements of technological and health-promoting parameters of fruit purees.

Fruit Purees	Dry Matter (%)	Protein (%)	Fat (%)	Total Extract (%)	Total Acidity (%)	Total Ash (%)	Polyphenols (mg GAE/g d.m.)	Flavonoids (mg QE/g d.m.)	Antioxidant Activity (mg TEAC/g d.m.)	Ascorbic Acid (mg/g d.m.)
Blueberry	13.766 a	2.510 b	0.336 ab	12.25 de	1.304 c	0.136 d	35.206 bc	6.525 c	46.201 a	11.677 a
Elderberry	10.513 c	2.175 g	0.285 ab	9.00 b	0.798 a	0.865 f	94.081 e	51.169 f	73.158 i	12.234 ad
Sea buckthorn	10.916 c	1.195 a	2.486 d	9.50 bc	3.001 b	0.314 b	26.700 abc	11.375 e	41.326 g	16.826 b
Guelder rose	14.224 ab	2.880 i	0.163 a	12.00 d	1.624 e	0.170 d	59.541 d	17.146 d	57.998 c	14.047 e
Blackberry	11.952 e	2.065 f	0.410 ab	10.00 c	0.821 a	0.322 b	41.559 cd	8.665 ce	69.664 h	16.669 b
Black currant	14.282 b	1.930 e	0.220 ab	12.75 ef	2.989 b	0.413 ab	34.627 abc	0.284 a	52.676 b	9.890 c
Black mulberry	14.008 ab	0.875 c	0.507 b	13.00 a	0.866 a	0.558 ce	19.674 ab	2.909 ab	34.481 f	11.571 a
Haskap berry	15.802 d	2.462 b	0.357 ab	13.50 a	2.658 h	0.467 ac	44.279 cd	15.244 d	46.466 a	10.939 ac
Hardy kiwi	18.905 g	1.125 a	0.851 c	15.25 g	1.527 d	0.478 ac	15.598 a	14.968 d	24.852 d	11.397 a
Cornelian cherry	15.620 d	2.995 j	0.257 ab	14.75 g	1.938 f	0.472 ac	31.235 abc	2.199 ab	57.278 c	13.697 de
Cherry silverberry	12.713 f	2.700 h	0.254 ab	13.00 af	2.016 g	0.408 ab	15.993 ab	0.561 a	50.250 b	16.376 b
Bird cherry	25.542 h	1.675 d	0.291 ab	24.50 h	0.855 a	0.586 e	20.567 ab	5.396 bc	30.165 e	7.527 f

^a–j—values marked with different letters differ significantly at the level of p < 0.01. ^a–a—values marked with the same letters do not differ statistically significantly.

), indicating large differences in the concentration of soluble and insoluble constituents (DM includes both fractions), and thus reflecting potential processing suitability. The relationship between DM and soluble solids content (SSC/TSS) as indicators of fruit quality has been repeatedly confirmed, for instance in kiwifruit, where higher DM was found to correlate with elevated SSC and better sensory acceptability [43,44]. The purees with a higher DM content, particularly those from bird cherry, haskap berry, and kiwifruit, exhibited a more favorable technological profile, e.g., higher TSS. For bird cherry, advantageous physicochemical properties (including total extract content, %) were reported, haskap typically exhibited SSC values from 10.8 to 14.7 °Brix, while kiwifruit had well-established DM/SSC quality thresholds [45,46]. These characteristics indicate a strong potential for using these purees in functional food applications. This is consistent with comprehensive reviews indicating that fruit matrices rich in dry matter and soluble solids, particularly in the case of superfruits and berry-type crops, constitute an important raw material base for the development of functional foods due to their high load of bioactive constituents and documented health-promoting effects [7,11,47].

The protein content in the analyzed fruit purees ranged from ~0.88% (black mulberry) to ~3.00% (cornelian cherry) (Table 1). Such low values result from the naturally limited protein fraction in fruits, in which carbohydrates and secondary metabolites predominate, while proteins constitute only a small proportion of the dry matter. Comparable levels have also been reported in the literature for cherry silverberry, mini kiwi, and cornelian cherry, where proteins likewise accounted for only a minor share of the nutritional composition of these fruits [1,2,3,4,7,11].

The fat content of most purees was generally low (<1%), except for sea buckthorn puree, which exhibited significantly higher levels of approx. 2.5% (Table 1). This observation is consistent with previous reports highlighting the presence of unique unsaturated fatty acids, including palmitoleic acid (omega-7), known for its antiviral potential and anti-inflammatory properties [7,47,48,49].

In terms of mineral composition, evaluated indirectly through total ash content, the highest values were found in elderberry (0.84%) and bird cherry (0.60%) purees (Table 1). Literature data confirm that elderberries are rich in minerals, particularly potassium, calcium, magnesium, and iron, reported in both fresh and processed forms [6,11,50,51]. Similarly, bird cherry fruits are recognized as valuable sources of macro- and microelements, including calcium, iron, and potassium [6,52]. Although direct mineral composition was not analyzed in this study, the variations in ash content may have important implications not only for dietary value but also for technological properties, such as ionic conductivity of the purees and, consequently, their electrical characteristics, which will be further elaborated in the following sections [23,24,53,54].

In terms of phenolic compounds, the highest total polyphenol content was determined in elderberry puree (~94 mg GAE/g d.m.), followed by guelder rose (~60 mg GAE/g d.m.) and haskap berry (~45 mg GAE/g d.m.). These high concentrations were reflected in strong antioxidant activity assessed by the DPPH method, with elderberry puree showing the highest radical scavenging capacity (~73 mg TEAC/g d.m.), which ultimately confirmed its high functional value (Table 1). Similar relationships have been reported in the literature, where a strong correlation was demonstrated between phenolic content (including anthocyanins) and antioxidant activity in processed products from elderberry, guelder rose, and haskap berry [7,55,56,57,58]. This compositional profile is in line with broader evidence indicating that high intakes of bioavailable plant antioxidants, particularly berry-derived polyphenols, are associated with beneficial modulation of cardiometabolic risk markers and inflammatory status [5,8,9].

An interesting group was represented by blackberry and cherry silverberry purees, which—despite their moderate polyphenol contents (~42 and 16 mg GAE/g d.m., respectively)—exhibited high vitamin C concentrations of 16.67 and 16.83 mg/g d.m. (Table 1). The retention of such considerable amounts of ascorbic acid after pasteurization may be attributed both to the mild processing conditions and the potential protective effect of phenolic compounds, which can mitigate its oxidative degradation. Similar observations concerning a high vitamin C content and its stabilization in the presence of polyphenols have been reported for processed products derived from blackberries and silverberry fruits [6,7,11,59,60]. Moreover, interventional and analytical studies on berry juices indicate that matrices combining ascorbic acid with polyphenols can effectively enhance systemic antioxidant status and contribute to the improvement of selected cardiovascular and metabolic biomarkers [8,61,62].

Based on the collected data, three distinct groups of purees with similar compositional profiles can be distinguished: Group I—purees with a high polyphenol content and strong antioxidant activity (elderberry, guelder rose, blackberry, haskap berry), Group II—purees with a comparatively higher protein content (cornelian cherry, cherry silverberry, guelder rose, blueberry, haskap berry), and Group III—products with a high vitamin C concentration (blackberry, cherry silverberry, sea buckthorn).

These pronounced differences indicate that local superfruits can be considered valuable sources of specialized functional components—ranging from antioxidants, through nitrogenous compounds, to vitamin C—making them potentially attractive raw materials for various sectors of the food industry [7,17,63]. At the same time, this compositional diversity provides a strong rationale for exploring the potential of using electrical parameters to identify specific quality profiles, which could serve as rapid and non-destructive indicators of both technological and functional properties. The ranges of polyphenols, vitamin C and other bioactive constituents observed in the present set of twelve superfruit purees are comparable to those reported for berry- and superfruit-based products in studies documenting improvements in glycemic control, lipid profile and low-grade inflammation [7,8,9,10,11,62,63]. This supports the interpretation that the investigated purees represent compositionally dense matrices with a realistically achievable health-promoting potential in the context of functional food formulations.

3.2. Electrical Characterization

The electrical properties of fruit purees were evaluated based on changes in impedance (|Z|), admittance (|Y|), parallel capacitance (Cp), and series capacitance (Cs) across a broad frequency range from 100 Hz to 1 MHz. These parameters reflect both the conductive properties (arising from the presence and mobility of electrolytes) and the dielectric properties (representing the ability to polarize and store charge), which are inherently linked to the specific physicochemical structure of the purees. The analysis of parameter variations as a function of frequency (f) enabled the discrimination of different between purees and the characterization of their distinctive physicochemical features.

The experimental data were interpreted using an RCC equivalent model, comprising a resistor and two capacitances arranged in series (Cs) and parallel (Cp) modes. This approach enabled the separation of bulk capacitance (Cs), associated with the dielectric properties of the aqueous matrix, from interfacial capacitance (Cp), related to polarization at the boundaries of dispersed microstructures [62]. The use of the RCC scheme captures the multiphase nature of fruit purees, in which resistive components predominate while interfacial effects contribute significantly to the overall electrical response.

Although constant phase elements (CPEs) are often applied to describe biological and food matrices with distributed time constants [64,65,66], the simplified RCC model provided a practical framework for comparing fruit species and for identifying electrical parameters that correlate with technological and bioactive properties. On this basis, the RCC framework was applied to analyze the frequency-resolved parameters of the studied fruit purees.

In order to improve the clarity of presentation, the impedance comparison between fruit purees was made at a single representative frequency (1 kHz). The differences in |Z| at this frequency are shown in Figure 4a, while Figure 4b illustrates the frequency-dependent behavior of |Z| across the entire range 100 Hz–1 MHz for blueberry puree (representative example).

Frequency-dependent changes in impedance (|Z|), Figure 4a revealed significant differences among the fruit purees, reflecting variations in their chemical composition and structure. The highest Z values were recorded for blueberry (Z_1kHz = 199.92 Ω) and guelder rose (Z_1kHz = 142.46 Ω) purees, which can be attributed to their higher dry matter content, which restricts ion mobility and increases electrical resistance [23,53]. In contrast, the lowest Z values at high frequencies (1 MHz) were recorded for elderberry (49.27 Ω), sea buckthorn (78.73 Ω), and cherry silverberry (75.10 Ω) purees. These observations may be linked to a higher mineral content and a more diluted liquid phase, indicative of lower viscosity or finer particle dispersion, both of which facilitates conduction. The decrease in Z values observed with increasing frequency indicates the growing contribution of capacitive reactance, which is typical of colloidal systems containing water and electrolytes [24]. The differences noted between fruit species suggest that impedance can serve as a sensitive indicator for differentiating products based on their composition and structure. Nevertheless, multivariate approaches, such as PCA, are required for unambiguous classification, as previous studies on the dielectric characterization of juices and purees, demonstrated that multivariate analysis provides more effective sample discrimination than simple comparisons of absolute values [25].

Similarly, for admittance (|Y|)—which is the reciprocal of impedance—comparative analysis between fruit purees was carried out at 1 kHz (corresponding values derived directly from |Z|), whereas frequency-dependent variation was discussed qualitatively based on the characteristic pattern observed across the full range 100 Hz–1 MHz. Admittance (|Y|), defined as the reciprocal of impedance, increased with measurement frequency (f), which is consistent with the typical behavior of capacitive dispersive systems. At 1 kHz, Y values ranged from 5.04 × 10⁻³ S (blueberry) to 1.998 × 10⁻² S (elderberry). Across the entire frequency range (100 Hz–1 MHz), the highest admittance values were consistently observed for elderberry, cherry silverberry, sea buckthorn, and blueberry purees (approximately 1.25 × 10⁻² S to >2.0 × 10⁻² S), which is consistent with their low impedance and suggests higher concentrations of low-molecular-weight substances (organic acids, vitamin C, minerals) that enhance conductivity [22].

Conversely, blueberry and guelder rose purees exhibited the lowest Y values, most likely due to their higher dry matter content and greater viscosity, which restricts ion mobility and charge transport [25,65]. For the remaining purees (blackberry, black mulberry, cornelian cherry, black currant, bird cherry, mini kiwi, haskap berry), Y values ranged from 9.60 × 10⁻³ to 1.30 × 10⁻² S, with relatively limited variation across the studied frequency band. This indicates a relative stability of electro-diffusion properties in these systems, which is advantageous for measurement reproducibility and for potential applications in sample modeling and classification [25,38].

The above findings suggest that admittance, like impedance, is a sensitive indicator of differences in the composition and properties of fruit purees. Its relatively stable values across a broad frequency range make it a viable parameter for developing predictive models of food quality.

Changes in parallel capacitance (Cp) exhibited a pronounced decreasing trend with increasing frequency, which is consistent with the typical behavior of dispersive systems with complex structures. At a low frequency (f = 100 Hz), Cp values ranged from 2.49 × 10⁻⁷ F for blueberry to 4.80 × 10⁻⁶ F for elderberry (Figure 5a). At a higher frequency (f = 1 kHz), the values decreased to 4.20 × 10⁻⁹ F and 6.91 × 10⁻⁸ F, respectively (Figure 5b). At the highest frequencies tested (1 MHz), Cp reached its lowest values, ranging from 1.89 × 10⁻¹¹ F (blueberry) to 1.64 × 10⁻¹⁰ F (elderberry) (Figure 5c). A similar dielectric response—a successive decline in capacitance with increasing frequency—has been previously observed in studies on fruits and juices, and was attributed to the dominant role of interfacial (Maxwell-Wagner) relaxation as well as the gradual reduction in dipolar polarization at higher frequencies [14,24,35].

Likewise parallel capacitance (Cp), equivalent series capacitance (Cs) exhibited a distinct decreasing trend with increasing frequency, which is typical for dielectric systems with a dispersed structure. Across the measurement range, Cs systematically declined from the order of 10⁻⁴ F at 100 Hz to 10⁻⁸ F at f = 1 MHz. This pattern indicates that the efficiency of polarization mechanisms (both interfacial and dipolar) diminishes progressively as frequency increases, since the relaxation times of dipoles and ions exceed the period of exposure to the applied electric field. Consequently, the effective capacitance decreases with frequency, a phenomenon commonly attributed to Maxwell–Wagner relaxation in colloidal systems containing water and electrolytes. This behavior has been extensively documented in dielectric studies of fruit juices and plant tissues within the 100 Hz-1 MHz range (Figure 6).

Higher Cs values at low frequencies (determined in guelder rose, black currant, and mini kiwi purees) indicate an enhanced capacity of the system for interfacial polarization. This behavior can be attributed to increased matrix heterogeneity (presence of solid particles, pectins, cell wall fragments) and higher concentrations of soluble components in the aqueous phase. These fractions include amino acids, organic acids, and soluble proteins, which, due to their mobility and ability to interact with the electric field, promote charge accumulation at phase boundaries, and enhance ionic conductivity. However, considering the low protein content of the analyzed fruit purees (typically < 3%), the contribution of soluble proteins to polarization phenomena is presumed to be marginal compared to that of organic acids, minerals, and vitamin C, as discussed in Section 3.1.

In contrast, lower Cs values (determined in elderberry and black mulberry purees) suggest a more homogeneous microstructure or a lower content of components promoting polarization (Table 1), such as mineral salts (e.g., potassium, calcium) [50,51,52], organic acids (e.g., citric, malic) [21,49,53], vitamin C [6,34,59,60], and in a lesser extent, soluble proteins and amino acids [1,27,28]—all of which possess charge or dipolar character enabling interaction with the electric field. These interpretations align with previous EIS studies on plant materials and their derivatives, where these phenomena are typically described using RC or Cole–Cole equivalent circuit models. The reduction in Cs with increasing frequency reflects the differentiated response of the analyzed fruit purees to an alternating electric field, which can be leveraged for diagnostic and comparative assessments of their quality and potential functional properties [25]. Although the measurement approach used in this study differs from classical EIS, the observed trends in Cs(f) are comparable and can be interpreted within similar theoretical frameworks.

From a practical standpoint, the analysis of Cs(f) in combination with other electrical parameters (Z, Y, Cp) enhances the sensitivity of sample differentiation and strengthens the reliability of inferences regarding the structural characteristics of fruit puree matrices—an approach previously demonstrated in the literature for fruit juices, fresh produce, and extensively discussed in reviews addressing EIS modeling in plant systems [16,67].

In summary, the fruit purees analyzed in this study exhibited distinct electrical profiles that reflected their physicochemical and structural properties. Blueberry and guelder rose purees exhibited the highest impedance (|Z|) and the lowest admittance (|Y|), along with low capacitance values (Cp, Cs). This pattern indicates a more compact and homogeneous internal structure with a limited presence of ionic components, which may reduce the ability of the system to accumulate electrical charge [53]. In contrast, elderberry, cherry silverberry, and sea buckthorn purees showed the lowest impedance and the highest admittance, as well as relatively high capacitance values. These findings can be attributed to higher contents of readily conducting compounds, such as organic acids, vitamin C, and mineral salts, together with phenolic and other bioactive fractions that enhance the susceptibility of the system to interfacial polarization [6,24].

The observed differences in impedance, admittance, and capacitance confirm that electrical parameters can serve as sensitive indicators of compositional and structural variability in fruit purees, making them viable for differentiation and classification. However, one-dimensional interpretation (based on single parameters) offers limited explanatory power. Therefore, integrating electrical measurements with multivariate statistical methods, such as PCA, enables a more comprehensive assessment of the relationships between electrical properties and technological or functional attributes. Such combined approaches are widely documented in the literature on impedance spectroscopy in foods and plant-based materials [25,35], as they enhance the robustness of conclusions and support a more holistic evaluation of puree quality.

3.3. Correlations

A multistage statistical analysis was performed to investigate the relationships between the chemical composition, bioactive properties, and electrical parameters of the analyzed fruit purees. In the first step, Ward’s method was applied to enable hierarchical classification of the samples, resulting in the identification of two distinct clusters (Figure 7), which represent dataset-specific groupings within the investigated set of twelve superfruit purees rather than generalizable clusters for fruit species.

Cluster 1 included blueberry, guelder rose, blackberry, and sea buckthorn purees, which were characterized by moderate polyphenol levels combined with relatively high antioxidant activity and ascorbic acid content, as well as lower impedance and higher admittance values. Cluster 2 comprised black currant, cherry silverberry, haskap berry, black mulberry, hardy kiwi, cornelian cherry, bird cherry, and elderberry purees; this group showed a broader internal variability, including the highest polyphenol content (elderberry) and the highest dry matter level (bird cherry), together with generally higher impedance values and lower admittance. This classification should be regarded as exploratory and valid exclusively for the present dataset of twelve superfruit purees, given the limited number of products analyzed and the specific set of variables considered. It provides a dataset-specific basis for further analysis of the correlations between electrical properties and chemical composition within the tested samples, in line with previous reports on the application of clustering in the evaluation of fruit juices and fresh produce [16,68]. In addition, this separation is consistent with the expected behavior of multiphase systems described by the RCC model—samples with higher levels of soluble constituents (e.g., organic acids, vitamin C) showed markedly lower resistance values and therefore lower impedance and higher admittance. In contrast, samples with a higher dry matter content were characterized by higher impedance values, which is consistent with restricted ion mobility and reduced ability of the system to polarize [35,54].

Principal Component Analysis (PCA) for Cluster 1 (blueberry, sea buckthorn, guelder rose, blackberry) demonstrated clear associations between electrical parameters and key physicochemical variables (Figure 8 and Figure 9). The loading vectors for impedance (Z) were directed towards dry matter and total extract, whereas admittance (Y) was positioned in the opposite direction, closer to total ash and vitamin C. These tendencies correspond directly to the correlation coefficients presented in

Table 2. Correlations between electrical parameters (Z, Y, Cp, Cs) and the chemical composition, bioactive compounds, and antioxidant properties of fruit purees classified into Cluster 1.

Parameters	|Z|					|Y|
	100 Hz	1 kHz	10 kHz	100 kHz	1 MHz	100 Hz	1 kHz	10 kHz	100 kHz	1 MHz
Dry matter	0.834 *	0.834 *	0.835 *	0.836 *	0.840 *	−0.929 **	−0.929 **	−0.930 **	−0.930 **	−0.933 **
Protein	0.738	0.737	0.738	0.740	0.743	−0.881 *	−0.881 *	−0.882 *	−0.883 *	−0.884 *
Fat	−0.659	−0.658	−0.659	−0.661	−0.661	0.815 *	0.813 *	0.815 *	0.817 *	0.815 *
Total extract	0.927 **	0.927 **	0.927 **	0.928 **	0.931 **	−0.964 **	−0.965 **	−0.965 **	−0.965 **	−0.967 **
Total acidity	−0.467	−0.465	−0.466	−0.467	−0.465	0.602	0.600	0.602	0.603	0.598
Total ash	−0.931 **	−0.931 **	−0.931 **	−0.932 **	−0.935 **	0.926 **	0.927 **	0.926 **	0.926 **	0.928 **
Polyphenol	0.243	0.243	0.244	0.247	0.253	−0.466	−0.466	−0.469	−0.471	−0.473
Flavonoids	−0.256	−0.256	−0.255	−0.252	−0.245	0.108	0.106	0.105	0.103	0.097
Antioxidant activity	−0.148	−0.150	−0.149	−0.147	−0.148	−0.068	−0.065	−0.069	−0.070	−0.067
Vitamin C	−0.988 **	−0.988 **	−0.988 **	−0.988 **	−0.989 **	0.942 **	0.943 **	0.942 **	0.941 **	0.942 **
	Cp					Cs
Dry matter	−0.977 **	−0.972 **	−0.949 **	−0.997 **	−0.989 **	0.726	0.477	0.451	−0.006	−0.513
Protein	−0.932 **	−0.931 **	−0.977 **	−0.946 **	−0.936 **	0.642	0.419	0.570	0.017	−0.482
Fat	0.826 *	0.834 *	0.951 **	0.777	0.800 *	−0.320	−0.099	−0.469	0.196	0.597
Total extract	−0.987 **	−0.983 **	−0.906 **	−0.982 **	−0.994 **	0.665	0.382	0.243	−0.155	−0.623
Total acidity	0.562	0.580	0.750	0.446	0.506	0.117	0.301	−0.244	0.429	0.642
Total ash	0.942 **	0.937 **	0.811 *	0.941 *	0.954 **	−0.668	−0.386	−0.122	0.172	0.605
Polyphenol	−0.587	−0.578	−0.700	−0.699	−0.622	0.734	0.691	0.933 **	0.527	0.072
Flavonoids	−0.058	−0.035	−0.063	−0.275	−0.138	0.802 *	0.948 **	0.846 *	0.962 **	0.691
Antioxidant activity	−0.094	−0.105	−0.369	−0.075	−0.066	−0.121	−0.089	0.590	0.096	−0.015
Vitamin C	0.915 **	0.915 **	0.782	0.856 *	0.906 **	−0.450	−0.132	0.106	0.424	0.780

Z—impedance, Y—admittance, Cp—parallel equivalent capacitance; Cs—series equivalent capacitance, **—p < 0.01; *—p < 0.05.

.

Specifically, |Z| showed positive correlations with dry matter (r = 0.834–0.840, p < 0.05) and total extract (r = 0.927–0.931, p < 0.01), and negative correlations with total ash (r = −0.931 to −0.935, p < 0.01) and vitamin C (r = −0.988 to −0.989, p < 0.01). Conversely, |Y| demonstrated strong negative correlations with dry matter (r = −0.929 to −0.933, p < 0.01) and total extract (r = −0.964 to −0.967, p < 0.01), and strong positive correlations with total ash (r = 0.926–0.928, p < 0.01) and vitamin C (r = 0.942–0.943, p < 0.01). In addition, |Y| was significantly and consistently negatively correlated with protein content across all frequencies (r ≈ −0.881 to −0.884, p < 0.05), highlighting the secondary role of proteins in charge transport, especially in matrices characterized by moderate levels of low-molecular-weight components such as vitamin C and mineral substances (ash). Similarly, a significant positive correlation was observed between admittance and fat content (r ≈ 0.813 to 0.817, p < 0.05), suggesting a possible contribution of lipid-associated matrix effects on ionic mobility. In summary, |Z| and |Y| respond in opposite ways to the balance between solid-phase constituents (DM, extract) and soluble, ionizable compounds (ash, vitamin C), effectively capturing the compositional variability within this cluster.

In the case of dielectric parameters, distinct patterns were observed. Cp (parallel capacitance) exhibited very strong correlations (p < 0.05; p < 0.01) with total ash (r = 0.811–0.954; depending on frequency) and vitamin C (r = 0.856–0.915), whereas correlations with dry matter, protein, and total extract were strongly negative (r = −0.949 to −0.997; p < 0.01). Thus, Cp appears to be particularly associated with variables that determine ionic conductivity and the concentration of water-soluble constituents (Figure 9a, Table 2).

Cs (series capacitance), in contrast, revealed statistically significant relationships predominantly with the polyphenol fraction, especially flavonoids (e.g., r = 0.802 at 100 Hz, p < 0.05; r = 0.948 at 1 kHz, p < 0.01; r = 0.846 at 10 kHz, p < 0.05; r = 0.962 at 100 kHz, p < 0.01) and with polyphenols at 10 kHz (r = 0.933, p < 0.01). The frequency-selective nature of these associations indicates that Cs is sensitive to relaxation mechanisms related to the presence of phenolic compounds (Figure 9b, Table 2), which may undergo orientation and interfacial polarization due to their dipolar hydroxyl groups and potential for hydrogen bonding with aqueous and matrix components. These molecular interactions are consistent with known dielectric relaxation behavior in complex food systems.

Taken together, the PCA structure and the correlation coefficients (Table 2) demonstrate that Z/Y are most strongly linked to variation in dry matter, extract, ash and vitamin C, whereas Cp/Cs differentiate samples according to ionic components and phenolic composition within Cluster 1.

For Cluster 2, the PCA loadings (Figure 10 and Figure 11) and correlation coefficients (

Table 3. Correlations between electrical parameters (Z, Y, Cp, Cs) and the chemical composition, bioactive compounds, and antioxidant properties of fruit purees classified into Cluster 2.

Parameters	|Z|					|Y|
	100 Hz	1 kHz	10 kHz	100 kHz	1 MHz	100 Hz	1 kHz	10 kHz	100 kHz	1 MHz
Dry matter	0.695	0.694	0.695	0.706	0.759	−0.713	−0.712	−0.713	−0.717	−0.741
Protein	−0.354	−0.356	−0.356	−0.345	−0.263	0.259	0.258	0.257	0.251	0.201
Fat	0.331	0.331	0.333	0.341	0.340	−0.295	−0.294	−0.295	−0.299	−0.295
Total extract	0.861 *	0.860 *	0.861 *	0.874 *	0.916 **	−0.895 *	−0.895 *	−0.895 *	−0.902 **	−0.922 **
Total acidity	0.338	0.342	0.340	0.337	0.402	−0.430	−0.434	−0.433	−0.430	−0.465
Total ash	−0.769	−0.771	−0.771	−0.778	−0.828 *	0.851 *	0.854 *	0.855 *	0.859	0.886 *
Polyphenol	−0.846 *	−0.847 *	−0.849 *	−0.859 *	−0.875 *	0.886 *	0.888	0.889 *	0.895 *	0.904 **
Flavonoids	−0.860 *	−0.861 *	−0.861 *	−0.865 *	−0.873 *	0.902 **	0.903 **	0.903 **	0.906 **	0.910 **
Antioxidant activity	−0.738	−0.740	−0.741	−0.743	−0.729	0.737	0.738	0.739	0.739	0.728
Vitamin C	−0.251	−0.253	−0.251	−0.230	−0.182	0.175	0.174	0.172	0.157	0.121
	Cp					Cs
Dry matter	−0.715	−0.717	−0.546	−0.255	−0.668	0.843 *	0.817 *	−0.014	−0.142	0.028
Protein	0.221	0.227	−0.124	−0.535	−0.355	−0.440	−0.448	0.355	0.488	0.649
Fat	−0.280	−0.290	−0.302	−0.020	−0.096	0.351	0.483	0.117	−0.058	−0.121
Total extract	−0.893 *	−0.897 *	−0.725	−0.262	−0.746	0.761	0.762	0.008	−0.054	−0.019
Total acidity	−0.496	−0.486	−0.138	−0.228	−0.696	0.553	0.491	−0.257	−0.172	0.202
Total ash	0.896 *	0.897 *	0.619	0.276	0.843 *	−0.766	−0.708	0.088	0.040	−0.072
Polyphenol	0.898 *	0.908 *	0.732	0.168	0.638	−0.716	−0.686	−0.017	−0.011	0.102
Flavonoids	0.910 **	0.912 **	0.580	0.065	0.629	−0.702	−0.539	0.194	0.139	0.186
Antioxidant activity	0.744	0.751	0.428	−0.095	0.347	−0.760	−0.776	0.148	0.244	0.308
Vitamin C	0.152	0.139	−0.508	−0.559	−0.203	−0.464	−0.302	0.729	0.834	0.575

Z—impedance. Y—admittance. Cp—parallel equivalent capacitance; Cs—series equivalent capacitance. **—p < 0.01; *—p < 0.05.

) revealed a substantially lower number of statistically significant associations compared to Cluster 1. Impedance (|Z|) and admittance (|Y|) values across all analyzed frequencies were primarily related to total extract content and selected groups of bioactive compounds. Total extract demonstrated significant positive correlations (p < 0.05; p < 0.01) with impedance (r = 0.861–0.916), and correspondingly negative correlations with admittance (r = −0.895 to −0.922). Likewise, both Z and Y were significantly (p < 0.05; p < 0.01) correlated with total ash (Z: r = −0.828 at 1 MHz; Y: r = 0.851–0.886), which indicates that mineral constituents remain a relevant factor modulating electrical response also within this subset.

Furthermore, pronounced correlations were found for phenolic compounds: polyphenols and flavonoids displayed strong negative correlations with impedance (r = −0.846 to −0.875 for polyphenols; r = −0.860 to −0.873 for flavonoids; p < 0.05) and corresponding strong positive correlations with admittance (r = 0.886–0.904 for polyphenols; r = 0.902–0.910 for flavonoids; p < 0.05 and p < 0.01). These relationships confirm that within Cluster 2, bioactive compounds (phenolic fraction) exert a measurable impact on electrical response, even though their absolute contents are generally lower than in Cluster 1.

Capacitive parameters showed a narrower range of significant relationships. Cp was significantly correlated (p < 0.05; p < 0.01) with total extract (r = −0.893 to −0.897) and total ash content (r = 0.843–0.896). while Cs demonstrated only few significant associations—notably with dry matter (r = 0.817 at 1 kHz. p < 0.05) and vitamin C (r = 0.729 at 10 kHz. p < 0.05). This limited correlation profile suggests that structural/polarization-related components in Cluster 2, particularly those influencing Cs, have a lesser impact on dielectric response. However, Cp still shows meaningful associations, particularly with ash and extract content.

Taken together, the statistical analysis for Cluster 2 confirms that electrical parameters still track compositional variation, but the number and strength of correlations are lower and less uniform compared to Cluster 1. From an application-oriented perspective, the electrical response of Cluster 1 purees (blueberry, guelder rose, blackberry and sea buckthorn) can be regarded as a preliminary reference profile for superfruit products with favorable technological characteristics. Within this cluster, a consistent pattern of comparatively lower impedance and higher admittance across the analyzed frequency range co-occurred with higher total extract and ash contents and elevated vitamin C levels, i.e., with a denser matrix of technologically relevant and nutritionally important constituents. Although the present data do not allow the formulation of strict threshold values, this pattern delineates an indicative operational window in which electrical parameters reliably mirror the technological quality of superfruit purees. Considering that vitamin C and phenolic compounds are recognized as key mediators of the cardioprotective and anti-inflammatory effects reported in the literature for these fruits [5,6,7,9,10,59,60]. The corresponding electrical fingerprints may thus serve as rapid, indirect indices of their functional potential within the studied product set. Within this dataset, this pattern can therefore be regarded as a preliminary ‘ideal’ electrical profile for superfruit purees combining favorable technological attributes with a high load of health-relevant bioactive constituents. Cluster 2 purees, in turn, exhibited a more heterogeneous chemical profile and generally lower levels of bioactive compounds, which is consistent with the weaker and less uniform correlations between electrical parameters and composition observed for this group. The contrast between the two clusters further substantiates that the diagnostic value of electrical parameters increases together with compositional density and bioactive load—in line with previous multivariate studies on electrically monitored fruit matrices [16,35].

Overall, the integration of electrical measurements with multivariate statistical tools, such as PCA, provided a useful and statistically sound framework for differentiating fruit purees according to their physicochemical and functional profiles. This comprehensive approach underscores the potential of electrical parameters as non-destructive indicators of technological and nutritional quality within the studied set of samples. Importantly, the consistency of the observed correlations within both clusters—although varying in strength and number—suggests that impedance-based metrics may serve as practical markers enabling not only classification, but also inference about compositional attributes of fruit purees. However, the stronger and more numerous relationships observed in Cluster 1 indicate that the hypothesis H1 is primarily supported for superfruit purees with relatively uniform and compositionally dense matrices, whereas for the remaining samples the diagnostic power of electrical properties is more limited. When interpreted in the context of current evidence on the cardiometabolic and anti-inflammatory benefits of superfruit- and berry-based products [7,8,9,10,11,62], these findings suggest that electrically derived quality indices may also serve as rapid proxies for health-relevant compositional traits in superfruit purees.

Among the analyzed electrical parameters, admittance (|Y|) and impedance (|Z|) demonstrated the most consistent and composition-dependent correlations, especially with dry matter, ash, extract, and vitamin C. In contrast, dielectric parameters exhibited higher selectivity: Cp effectively reflected ionic and water-soluble matrix components, whereas Cs was more responsive to phenolic fractions at specific frequencies. This differentiation highlights the complementary diagnostic roles of resistive and capacitive properties in evaluating fruit puree quality in this experimental context [16,17,23,24,25,53].

4. Conclusions

The study enabled a comprehensive evaluation of fruit purees in terms of their chemical composition, bioactive properties, and electrical parameters across a broad frequency range, using the RCC equivalent circuit model. The combination of chemical assays and electrical measurements allowed a more complete characterization of quality attributes compared with the use of chemical parameters alone.

Fruit purees from selected native superfruits—particularly elderberry, guelder rose, Blackberry, and haskap berry—contained high levels of bioactive compounds, which translated into high antioxidant activity. These results highlight the potential of these raw materials for functional food applications and confirm the relevance of further research on local fruit species.

In Cluster 1 (blueberry, guelder rose, Blackberry, sea buckthorn), clear and statistically significant correlations were observed between impedance (|Z|) and admittance (|Y|) and the contents of dry matter, total extract, and ash, which confirms that these electrical parameters are sensitive to compositional variation within this subset of fruit purees. Within the limits of the present dataset, this provides partial support for hypothesis H1, indicating that electrical properties can reflect the technological characteristics of superfruit purees with relatively uniform and dense compositional profiles, whereas in more heterogeneous matrices these relationships are weaker and less consistent.

Dielectric parameters (Cp and Cs) also showed statistically significant correlations with selected compositional variables. Cp demonstrated stronger and more consistent relationships, particularly with ash and extract, whereas Cs exhibited selective responsiveness to phenolic fractions at specific frequencies. Overall, these relationships were weaker and more frequency-dependent than those observed for |Z| and |Y|. Taken together, these findings provide preliminary support for hypothesis H2, indicating that capacitance-type parameters obtained from the RCC model can also provide useful information regarding the physicochemical characteristics of fruit purees, although their diagnostic contribution is more selective and depends on fruit matrix and measurement frequency.

PCA and cluster analysis enabled the differentiation of the investigated purees into two groups with distinct chemical and electrical characteristics. In Cluster 1, the relationships between electrical parameters and compositional variables were more consistent and statistically robust, especially for Y and Cp. In Cluster 2, these associations were sparser and limited mainly to |Z|, |Y|, and Cp, indicating the reduced diagnostic sensitivity of Cs and greater chemical heterogeneity within this group. This confirms that the diagnostic potential of electrical measurements is greater in samples with more uniform compositional profiles.

The applied RCC-based electrical measurement approach shows promise as a rapid and non-destructive tool for quality evaluation of fruit purees. Its advantages include reduced reagent consumption, lower analytical costs, and the possibility of application in online process monitoring. At the same time, electrical measurements should be considered complementary rather than substitutive to chemical analyses, because they cannot fully replace detailed compositional and functional characterization. Future studies should focus on extending this approach towards industrial real-time quality control and on validating the use of electrical indicators in a wider range of fruit-based products.