The drying of fruit peels is a fundamental step in the valorization of agricultural by-products, enabling the conversion of unstable waste into high-value functional ingredients. The literature extensively documents the drying of various fruit residues, highlighting diverse findings for citrus peels (orange, lemon, grapefruit) [ 8, 9], apple [ 10], banana [ 11], pineapple [ 12], peach [ 13] and others. Several drying methods are employed: Microwave drying—effective for preserving color and phenolic content in citrus peels [ 9]; convective drying (hot air)—can lead to browning and is usually efficient in terms of drying rate [ 8]; freeze drying retains the highest levels of bioactive compounds and is particularly effective for citrus peels [ 9]; however, it is extremely expensive. Vacuum drying allows the quality of dried products to be maintained by reducing the drying temperature and preventing thermal degradation [ 8]; infrared drying has shown promise in preserving phenolic compounds while being energy efficient [ 14]. Despite these advancements across multiple fruit matrices, most of the current research remains focused on citrus peels, often utilizing relatively expensive technologies such as freeze-drying or vacuum-microwave systems. While these methods offer superior quality, their high capital and operating costs can be prohibitive for large-scale industrial by-product upcycling. In contrast, apple peels [ 10] represent a massive industrial waste stream that differs structurally from the oil-rich citrus matrices. Therefore, there is a significant research need to improve simpler, more accessible methods, such as convective hot-air drying, which remains the industrial standard due to its ease of implementation and lower cost. However, the long duration and high energy intensity of convective drying remain major drawbacks. The objective of this study was to evaluate the efficacy of convective drying across a practical temperature range (40–80 °C) for apple peel valorization. Furthermore, a single hybrid process (convective drying at 40 °C supplemented with a low-intensity microwave load of 100 W) was investigated to evaluate the efficacy of minimal microwave assistance in enhancing drying rates. This approach aims to assess whether a moderate energy supplement can effectively overcome internal mass transfer resistance at low temperatures, thereby reducing thermal stress on sensitive bioactives and preventing product degradation often associated with high-power microwave treatments. The research focuses on finding a balance between process simplicity, energy consumption, and the retention of critical quality parameters such as ascorbic acid and color. By analyzing the kinetics and energy intensity through a mechanistic lens, this study aims to provide a robust and economically viable drying solution. 2.1. Material The research material was apple ( Malus domestica) peels from the Jonagold cultivar. Apples were purchased from a local orchardist (geographical location of the orchard: 52.3838147003593 N, 17.099227595312577 E) and stored under refrigeration conditions (4 °C). Before the drying process, the apples were washed and then peeled with an automatic peeler. The resultant peelings, which exhibited comparable thickness (approx. 5 mm), were cut into strips measuring approximately 40–50 mm in length and arranged in a single layer (skin side down) on a perforated round weighing pan (diameter approximately 210 mm). The length and thickness of the slices were measured with the use of a digital caliper. The weight of a single batch was approximately 16 g. The initial moisture content of the peels was determined using a XM120 moisture analyzer (Precisa Gravimetrics AG, Dietikon, Switzerland) with an accuracy of 0.01%. On average, the moisture content equaled 0.8126 ± 0.0098 kg/kg (wet basis) or 4.3361 ± 0.0523 kg/kg (dry basis). 2.2. Drying Procedure The prepared peels were subjected to a drying process in a laboratory-scale hybrid dryer designed and constructed by PROMIS-TECH (Wrocław, Poland), the scheme of which is presented in Figure 1. The experimental apparatus consists of a multisource hybrid dryer capable of integrating convective, microwave, and ultrasonic techniques, either simultaneously or as independent drying modes. The system is equipped with an air heating system ( Figure 1—(1, 3)) and an Air-borne Ultrasound System—AUS (Pusonics, Madrid, Spain) (9). This ultrasonic unit operates at a frequency of 26 kHz with a maximum power output of 200 W, facilitating the generation of sound pressure levels exceeding 170 dB. Furthermore, microwave radiation is supplied at 2.45 GHz with a peak power of 500 W, generated by a magnetron (10) (Muegge, Reichelsheim, Germany). The ambient air is drawn through a fan (1) into a heating conduit. Subsequently, the heated air enters the drying chamber from the bottom of the sample pan. (6). Ultrasonic energy is delivered from the upper section of the dryer. In the configuration illustrated in Figure 1, a transducer (4) induces vibrations on a specially profiled cylindrical plate with a diameter of 400 mm. These ultrasonic waves are directed through a cone-shaped sleeve toward the material, which is placed on a rotating pan (6) within the drying chamber. Precise monitoring of the drying kinetics is achieved through high-accuracy instrumentation. The sample mass reduction is recorded using a PS6000.R2 laboratory balance (8) (Radwag, Radom, Poland) with a resolution of 0.01 g. The surface temperature of the material is monitored using an infrared pyrometer, model CT LT15 model (5) (Optris, Berlin, Germany), which has a precision of 0.1 °C. The system is managed by an industrial PLC controller (11) and dedicated computer software (12), which allows for the regulation of process variables, including air temperature (30–90 °C), air velocity (1–5 m/s), microwave power (stepless from 100 to 500 W), ultrasound power (stepless from 50 to 200 W) and drying duration. Furthermore, a comprehensive data acquisition system registers real-time parameters such as air conditions at the inlet and outlet (velocity, temperature, and humidity) measured with HD29371TC1.5 and HD4817ETC1.5 (DLETAOHM, Selvazzano Dentro, Italy) sensors (2) with a precision of 0.01 m/s, 0.1 °C, 0.01%, respectively, material mass, surface temperature, and total energy consumption (kWh). The studies presented employed drying under forced convection (CV) conditions at varying temperatures, as well as hybrid convection-microwave drying (CVMW) methods. The values of individual process parameters are presented in Table 1. The experimental matrix was intentionally designed using a targeted screening approach to identify the critical stability limits of the apple peel matrix. The convective temperature gradient (40, 50, 60, and 80 °C) was selected to focus on the non-linear degradation zone of ascorbic acid. Based on preliminary studies and literature reports [ 22], the most significant kinetic changes for this marker occur between 50 °C and 60 °C; therefore, the inclusion of 70 °C was deemed redundant as the trend between 60 °C and 80 °C already followed a predictable, stabilized trajectory. Furthermore, the hybrid microwave-assisted treatment was limited to a single combination (100 W at 40 °C) to serve as a boundary condition for the process. Since this minimum available power setting (100 W) already induced a significant decrease in ascorbic acid content and adversely affected product quality markers at the lowest convective temperature, higher microwave power levels or temperatures were scientifically excluded. This strategic selection of parameters allowed for the precise identification of the ‘technological window’ while preventing unnecessary thermal stress on the samples, which would inevitably lead to total degradation of the thermolabile compounds investigated. The adopted experimental design was based on previous experience and the technological capabilities of the dryer. It was assumed that drying would take place within a temperature range from a minimum (40 °C) to a maximum (80 °C). The exclusion of 70 °C from the study was undertaken as the greatest loss of ascorbic acid (one of the quality parameters evaluated during the study) occurs between 50 °C and 60 °C [ 22]. Furthermore, given the similar values of the evaluated parameters (for kinetics, energy consumption and product quality) observed for processes carried out at 50 °C and 60 °C, it was decided that the latter process would be carried out at the highest possible temperature. The microwave radiation at a frequency of 2.45 GHz, continuously emitted at a power of 100 W—the minimum power setting available on the device—was utilized. To prevent the material from overheating, microwaves were applied at the lowest possible temperature of the drying medium, that is, 40 °C. The adverse effect of microwaves on the quality parameters under evaluation led to the discontinuation of research into higher power levels. Temperature monitoring during the drying trials was conducted using a pyrometer ( Figure 1—(7)). However, due to the experimental setup where the samples were dispersed on a rotating pan to ensure drying uniformity, the pyrometer primarily captured the surface temperature of the pan rather than the discrete samples. Because of this methodological limitation and the resulting interference from the background temperature, the measured values did not accurately represent the sample temperature and were thus excluded from the report. During each drying process, the process parameters (air flow velocity, temperature, radiation power) and the mass and temperature of the samples were automatically recorded at predetermined time intervals (∆ t). The drying process continued until the sample mass change was less than 0.1 g in 3 consecutive measurements, that is, during 900 or 360 s of the process (depending on the data recording interval ∆ t— Table 1). Each drying process was carried out in triplicate. 2.3. Assessment of the Drying Kinetics Based on the data obtained, the spatial average moisture content X ପ୍ତ t i (dry basis) over drying time was calculated as follows [ 23]: X ପ୍ତ ( t i ) = m t i − m s m s (1) where m( ti) (kg) is the sample mass measured at time ti, and ms (kg) is the mass of dry matter. The drying kinetics of apple peels could be assessed in terms of the dimensionless moisture content ( Yi) and the drying rate ( DRi), in accordance with the following equations [ 23]: Y i = X ପ୍ତ t i X ପ୍ତ 0 (2) D R i = − d m w d t = − m t i − m t i − 1 t i − t i − 1 (3) where X ପ୍ତ 0 is the initial moisture content, dmw (kg) is the weight loss of the sample, and dt (s) is the time interval at which the weight loss dmw occurred. The average drying rate, DRav, for a given drying process was calculated using the following equation: D R a v = Δ m w D T (4) where ∆ mw (kg) is the mass of moisture (water) removed from the sample by drying, and DT (s) is the total drying time. 2.4. Determination of the Effective Diffusion and Mass Transfer Coefficients and Activation Energy Effective diffusion Deff and mass transfer α coefficients were calculated according to the methodology presented by Szadzińska et al. [ 23] with the following equations: d X ପ୍ତ d t = − π 2 D e f f 4 l 2 X ପ୍ତ − X e = − k X ପ୍ତ − X e (5) α = k ⋅ l (6) where l (m) is the sample half-thickness, Xe is the equilibrium moisture content, and k (1/s) is the drying constant: k = π 2 D e f f 4 l 2 (7) The drying constant k was determined by linear approximation of the − d X ପ୍ତ / d t i = f X ପ୍ତ i curves, where − d X ପ୍ତ / d t i is the rate of moisture content change: − d X ପ୍ତ d t i = X ପ୍ତ t i − 1 − X ପ୍ତ t i t i − t i − 1 (8) X ପ୍ତ i is the average moisture content (averaged over a time period): X ପ୍ତ i = X ପ୍ତ t i + X ପ୍ତ t i − 1 2 (9) The drying constant k is the slope of the obtained lines. It should be noted that while the theoretical model (5) accounts for the equilibrium moisture content ( Xe), this parameter was omitted in the graphical representation of drying rates. From a mathematical standpoint, Xe acts as a constant offset that shifts the experimental curve without altering its slope. Since the determination of the drying constant k (7) is derived directly from the slope of the linear approximation, the exclusion of Xe from the visual plots does not affect the calculated kinetic parameter. The activation energy Ea was estimated under the assumption that the relationship between effective diffusivity and temperature is of the Arrhenius type [ 24]: D = D 0 exp − E a R ⋅ T (10) where D0 (m 2/s) is the preexponential factor of the Arrhenius equation, R (J·mole −1·K −1) is the universal gas constant, and T (K) is absolute temperature. A plot of ln D as a function of 1 / T produced a straight line with a slope equal to − E a / R ; thus, activation energy may be calculated. 2.5. Assessment of the Energy Intensity of the Processes The total energy consumption ( EC) for each drying experiment was measured using a NERIS DVH5161-M (SBE France (ACEAN), Boulogne Sur Mer, France), with an accuracy of ±1%. The measurement covered the entire drying system, including the heating elements, fans, and control units. Data were recorded from the start of the process until the sample reached the constant mass (as defined in Section 2.2). The results were expressed in kilowatt-hours (kWh) and then normalized per unit of initial mass or water removed to allow for comparative analysis [ 25]: S E C = 3.6 ⋅ E C Δ m w (11) where 3.6 is the value of 1 kWh in MJ. 2.6. Assessment of the Product’s Quality Quality parameters are critical from the perspective of food products. Material that does not meet stringent requirements cannot be approved for consumption. Therefore, it has no market value. Given the very large number of quality parameters that can be evaluated, in each case, those with the broadest informational spectrum are selected. In the presented studies, the following were selected: water activity, color, and ascorbic acid retention. 2.6.1. Water Activity Measurements ( aw) The water activity of the raw and dried samples was determined using the LabMaster-aw apparatus (Novasina AG, Lachen, Switzerland). Measurement was carried out at a constant temperature of 25 °C until a stable aw value was obtained. The value was considered stable if there was no change greater than 0.001 of the unit value within 3 min [ 28]. 2.6.2. Color of the Products Measurements The color of the raw and dried samples was determined using a CR400 colorimeter (Konica Minolta, Tokyo, Japan) equipped with a D65 light source. Before measurement, the device was calibrated on a standard white plate. The absolute color of the samples was then measured on the inner part of the peels, covered with flesh. Based on the measurements, color coordinates in the CIELAB space were determined, such as: L*—lightness; a*—chromatic component for colors from red (+ a*) to green (− a*); b*—chromatic component for colors from yellow (+ b*) to blue (− b*); C*—chroma; and h—hue. Measured values were used to determine the indices: color change index dE, yellowness YI, and browning BI according to the following equations [ 32]: d E = L 0 ∗ − L d ∗ 2 + a 0 ∗ − a d ∗ 2 + b 0 ∗ − b d ∗ 2 (12) Y I = 142.86 ⋅ b ∗ L ∗ (13) B I = 100 ⋅ Z − 0.31 0.17 (14) where Z = a ∗ + 1.75 ⋅ L ∗ 5.645 ⋅ L ∗ + a ∗ − 3.012 ⋅ b ∗ (15) Symbols with index 0 refer to values measured for raw material, with index d for dried samples, without index for raw material or dried samples. 2.6.3. Ascorbic Acid Retention Ascorbic acid is one of the most sensitive compounds found in food products, as it is susceptible to the effects of light, atmospheric oxygen, and elevated (high) temperatures. For this reason, it is often used as a quality marker in food processing. A high loss of ascorbic acid usually indicates a severe processing method and a potentially negative impact on other quality parameters [ 33]. The ascorbic acid content AAC was determined using the modified voltammetric method presented by Yu and Chen [ 34]. The measurements were carried out in a classic, three-electrode quartz vessel with a nominal volume of 10 mL. The working electrode was a glassy carbon electrode modified with sulfuric acid (VI), and its potential was measured against a silver chloride reference electrode. Platinum wire was utilized as an auxiliary electrode. The electrolyte utilized was 0.05 M KNO 3. Ascorbic acid was extracted from ground apple skins into 25 mL of 0.05 M KNO 3. The total ascorbic acid content was determined using the multiple standard addition technique. The voltammetric method developed for the determination of ascorbic acid was validated through the assessment of its linearity range as well as the limits of detection (LOD) and quantification (LOQ). The LOD was calculated from the parameters of the calibration curve, and the LOQ was defined as three times the LOD. The method demonstrated excellent linearity over the concentration range of 1.6–1000 mg/L. The limit of detection was 0.5 mg/L, whereas the limit of quantification was 1.6 mg/L. Optimization of the extraction procedure for ascorbic acid from apple peels involved evaluating the influence of KNO 3 concentration and extraction time. The concentrations of KNO 3 examined were 0.005 M, 0.01 M, 0.05 M, and 0.1 M, while the extraction times tested were 5, 10, 15, and 30 min. The best extraction conditions were established as 0.05 M KNO 3 and an extraction time of 15 min, which yielded the highest extraction efficiency. The precision of the method, expressed as the standard deviation of ascorbic acid content (mg/g) in the analyzed samples, ranged from 0.05 to 0.46, indicating satisfactory repeatability for quantitative analysis. 2.7. Statistical Analysis The experimental data were processed with OriginPro 2025b (OriginLab, Northampton, MA, USA). The data presented are mean ± standard error of the mean (SEM) [ 35]. A one-way analysis of variance (ANOVA) and a Tukey post hoc test mean comparison were performed. Statistically significant differences at the level of p 4) [ 32]. In the CV40 and CV80 convection processes, the color change was smaller ( dE ≈ 6) compared to other processes ( Figure 7) and resulted mainly from the change in the lightness L* ( Figure A3). In the CV50 and CV60 convection processes and the convective-microwave (CVMW) process, a significant color change was observed ( dE ≈ 9–10). In this case, the dE value was predominantly influenced by alterations in both the lightness ( L*) and the a* (red-green) component. It is worth noting that, regardless of the drying conditions, dried products were characterized by greater lightness than the raw material (increase in the L* value, Figure A3), which may have a positive effect on the perception of color [ 32]. The drying conditions also affected the chroma C* and hue values. Products subjected to drying temperatures of 40 and 80 °C exhibited a C* value that was comparable to that of the raw material ( Figure 8a). In contrast, products exposed to drying temperatures of 50 and 60 °C demonstrated a slightly diminished value of C*, suggesting a less pronounced color intensity and a shift towards gray shades. Products obtained after drying in a convective-microwave process (CVMW) exhibited the highest C* value, indicating an increase in color intensity compared to the raw material. When analyzing hue h ( Figure 8b), a slight increase in value can be observed for all dried products except those dried by convection at the lowest temperature of 40 °C. From an analysis of the browning index BI and the yellowness index YI, it can be observed that products dried by convection at 40 and 80 °C, as well as by the convective-microwave process (CVMW), had values of both parameters similar to those of the raw material ( Figure 9). In the case of products dried using the CV50 and CV60 processes, a significant decrease in the BIYI values was observed. Statistical analysis revealed a significant (at p ≤ 0.05) strong positive correlation between browning index BI and yellowness Index YI (Pearson’s coefficient r = 0.98, Figure A4). The color of dried fruits and vegetables is another important quality indicator. It is one of the first attributes a consumer assesses and is closely related to their perception of its quality, freshness, and flavor [ 30]. Drying conditions, particularly temperature, air velocity, and the technology used, have a significant impact on the final color of the product, because of their influence on enzymatic and nonenzymatic reactions. Studies on apple drying show that both air temperature and velocity have a notable effect on color [ 57, 58]. Increasing the drying temperature can accelerate browning reactions that affect overall color change [ 58]. However, in most cases, higher temperatures also reduce drying time, which can limit the duration of browning reactions and thus the overall color change [ 30, 57, 59]. Therefore, finding an optimal temperature is crucial to minimizing browning and overall color change. Microwave-assisted drying methods, including vacuum-microwave drying and combined convective-microwave drying, often result in better color retention compared to traditional hot-air drying. This is primarily due to the fact that microwaves generate heat volumetrically within the product, leading to a much faster and more uniform temperature increase. This rapid heating can quickly deactivate the enzymes responsible for browning [ 58, 60]. 3.3.3. Ascorbic Acid Content ( AAC) Last but not least, the quality parameter evaluated in the studies was the ascorbic acid content AAC. In this study, the samples dried at 40 °C (CV40) were strategically selected as the reference baseline for calculating relative ascorbic acid ( AA) retention. This approach was necessitated by the requirement for a stabilized analytical matrix, as direct voltammetric measurements on raw apple peels are scientifically compromised by the high activity of endogenous ascorbate oxidase and complex matrix interferences. In the raw state, these biochemical factors induce rapid, uncontrolled analyte degradation during the extraction phase, leading to poor measurement reproducibility and an unreliable baseline. By utilizing the mildest drying condition (CV40) as the reference, the enzymatic activity is effectively neutralized and the matrix is stabilized. This ensures that the comparative analysis reflects the actual impact of process intensity (higher temperatures and microwave energy) on nutrient retention, rather than being confounded by the inherent instability of the raw material. It was found that products subjected to drying at higher temperatures (50, 60, and 80 °C) and with microwave application (CVMW), exhibited a smaller AAC. The relative change for convection processes was approximately 7–8%, while for the convective-microwave process (CVMW) it increased significantly to 20% ( Table 3). The temperature gradients of 40, 50, 60, and 80 °C were strategically selected to investigate the boundaries of the ‘energy–quality nexus’ in apple peel drying. The exclusion of 70 °C was justified by the observed asymptotic behavior of ascorbic acid ( AA) degradation. Preliminary tests and the final results confirmed that AA content stabilized at a similar level for treatments at 50, 60, and 80 °C, indicating that a degradation plateau is reached within this range. Consequently, the existing matrix effectively captures the transition from the high-retention zone (40 °C) to the stabilized low-retention zone (50–80 °C), making additional sampling at 70 °C redundant for the mechanistic understanding of the process. The amount of ascorbic acid in dried fruits and vegetable peels is very important due to several aspects, in particular its nutritional value, as a quality indicator, and waste valorization. Ascorbic acid is an essential nutrient and potent antioxidant for the human body, helping to prevent diseases and support overall health. Dried fruit peels, especially apple peels, can be a significant source of these nutrients. Therefore, maintaining a high AAC in dried products is vital to maintain their health benefits. It is also known that ascorbic acid is highly susceptible to degradation from heat, oxygen and light; therefore, its retention level is often used as an indicator of overall quality of the processed foods. Significant loss of ascorbic acid often indicates a more general degradation of other sensitive compounds and sensory qualities, such as color and flavor. Finally, fruit peels, such as those from apples and oranges, are often discarded but are rich sources of bioactive compounds, including ascorbic acid. Drying is a key step in valorizing these by-products for use in functional foods or nutraceuticals, making AAC preservation a primary goal. Since ascorbic acid is a highly thermolabile compound, an increase in the temperature of the drying agent generally results in a decrease in the content of this compound in products [ 61]. However, some researchers have observed a non-linear relationship between AAC and the temperature of the drying agent. In this case, intermediate temperatures of 50–60 °C resulted in greater losses of ascorbic acid compared to high temperatures of 70–80 °C [ 62, 63]. This phenomenon can be attributed to the reduction in drying time, which signifies that the material is exposed to unfavorable factors such as high temperature (above 45 °C), light, and oxygen for a more limited duration. 3.4. Practical Implications for By-Product Valorization and End-Use Suitability The selection of the optimal drying protocol for apple peels must be dictated by the intended application, as process parameters affect quality markers in a non-linear manner. Our results demonstrate the following: For Long-term Storage and Microbiological Stability, convective drying at 80 °C (CV80) is the most effective, yielding the lowest water activity ( aw) compared to all other treatments (CV80 CV50 ~ CV60 ~ CV80 ≫ CVMW) indicate that even the lowest microwave power (100 W) induces severe degradation of thermolabile compounds compared to purely convective methods. Consequently, while CVMW accelerates the process, it is suboptimal for applications where the recovery of antioxidant markers is the primary objective. In summary, the end-use of the by-product defines the ‘best’ treatment: CV80 for stability and energy efficiency, and CV50/CV60 for superior aesthetic properties, whereas CVMW remains a boundary condition illustrating the maximum tolerable thermal stress for the apple peel matrix. The convective and convective-microwave drying of apple peels were examined regarding process kinetics and their impact on the final quality of the dried product. Convective-microwave drying proved to be the most effective from a kinetics perspective but was associated with the greatest deterioration in material quality. During convective drying, temperature significantly influenced process kinetics: the higher the temperature, the more efficient the drying process. Furthermore, increasing the temperature caused only minor changes in the analyzed quality parameters. Given the positive effects on drying kinetics and the lack of adverse effects on energy intensity or quality, high-temperature convective drying appears to be a promising method for preserving apple peels. However, to fully understand the impact of drying on product quality, future analyses should be expanded to include indicators such as polyphenol content and antioxidant potential—parameters that are important for apple peels. Integrating the parameters evaluated in each area (kinetics, energy consumption, and quality) is not easy due to their large number and the mutual influence of process conditions. The parameters evaluated for the above-mentioned aspects are closely related, and it is not possible to modify any one of them without affecting others. For example, it is possible to obtain a high-quality product by applying mild drying conditions; however, this will affect both process kinetics (drying rate) and energy intensity. On the other hand, drying under severe conditions can lead to a significant reduction in drying time and (even) a reduction in the consumption of energy, but the products obtained are of poor quality, making them worthless. Considering the interdependence between the particular parameters, the best program should be characterized by a reasonable drying rate and energy intensity of the process, combined with the highest possible product quality. The good kinetics of convection-microwave drying suggest future research directions. These involve finding convection-microwave drying conditions that do not significantly degrade the kinetics of the process while significantly improving the quality of the resulting dried product. Convective drying assisted by intermittent microwaves may be an appropriate solution. Author Contributions Conceptualization D.M., J.Z. and G.M.; Data curation D.M., J.Z., K.K. and P.M.; Formal analysis D.M., J.Z., K.K., P.M. and G.M.; Investigation D.M., J.Z., K.K. and P.M.; Methodology D.M., G.M. and J.Z.; Visualization D.M.; Writing—original draft D.M., G.M. and J.Z.; Writing—review and editing D.M., G.M. and J.Z. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by the Ministry of Science and Higher Education in Poland. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The dataset is available on request from the authors. Conflicts of Interest The authors declare no knowledge of existing or possible conflicts of interest. Appendix A Figure A1. Sample plots of the rate of moisture content change over average moisture content for: CV40 ( a), CV50 ( b), CV60 ( c), CV80 ( d), and CVMW ( e). Figure A1. Sample plots of the rate of moisture content change over average moisture content for: CV40 ( a), CV50 ( b), CV60 ( c), CV80 ( d), and CVMW ( e). Figure A2. Sample energy consumption ( EC) versus time ( t) curves for individual processes: points—experimental data; lines—linear regression ( y = a + b × x). Figure A2. Sample energy consumption ( EC) versus time ( t) curves for individual processes: points—experimental data; lines—linear regression ( y = a + b × x). Figure A3. Color components in the CIELAB space: L*—lightness; a*—chromatic coordinate from green to red; b*—chromatic coordinate from blue to yellow (error bars represent the SEM; black squares represent the parameter value for the dried product; red line represents the parameter value for the raw material). Figure A3. Color components in the CIELAB space: L*—lightness; a*—chromatic coordinate from green to red; b*—chromatic coordinate from blue to yellow (error bars represent the SEM; black squares represent the parameter value for the dried product; red line represents the parameter value for the raw material). Figure A4. Correlation matrix of the analyzed variables: DR av—average drying rate; DT—drying time; SEC—specific energy consumption; D eff—effective diffiusion diffusion coefficient; a w—water activity; dE—color change index; BI—browning index; YI—yellowness index (numerical values indicate Pearson’s correlation coefficient r; circle diameter and color intensity are proportional to coefficient magnitude, with larger and more saturated circles denoting stronger correlations; color hue indicates relationship direction, with red for positive r > 0 and blue for negative r 0 and blue for negative r < 0; asterisks (*) indicating statistically significant correlations at p ≤ 0.05). References Scheme of hybrid dryer [ 21]: 1—fan; 2—hot-wire thermo-anemometer, temperature and humidity sensor; 3—heater; 4—ultrasound transducer; 5—pyrometer; 6—samples; 7—rotatable balance pan; 8—balance; 9—air-borne ultrasound generation system; 10—microwave generation system; 11—control cabinet; 12—control and data acquisition workstation. Scheme of hybrid dryer [ 21]: 1—fan; 2—hot-wire thermo-anemometer, temperature and humidity sensor; 3—heater; 4—ultrasound transducer; 5—pyrometer; 6—samples; 7—rotatable balance pan; 8—balance; 9—air-borne ultrasound generation system; 10—microwave generation system; 11—control cabinet; 12—control and data acquisition workstation. Dependency of the dimensionless moisture content Y on time ( a) and drying rate DR on dimensionless moisture content ( b) for particular processes. Dependency of the dimensionless moisture content Y on time ( a) and drying rate DR on dimensionless moisture content ( b) for particular processes. Average drying rate DRav ( a) and drying time DT ( b) for particular processes (error bars represent the SEM; bars labeled with different lowercase letters are significantly different according to Tukey’s HSD test at p < 0.05). Average drying rate DRav ( a) and drying time DT ( b) for particular processes (error bars represent the SEM; bars labeled with different lowercase letters are significantly different according to Tukey’s HSD test at p < 0.05). The relationship between the effective diffusion coefficient and air temperature for convectively dried apples. The relationship between the effective diffusion coefficient and air temperature for convectively dried apples. Specific energy consumption SEC for particular processes (error bars represent the SEM; bars labeled with different lowercase letters are significantly different according to Tukey’s HSD test at p < 0.05). Specific energy consumption SEC for particular processes (error bars represent the SEM; bars labeled with different lowercase letters are significantly different according to Tukey’s HSD test at p < 0.05). Water activity aw of raw and dried samples (error bars represent the SEM; bars labeled with different lowercase letters are significantly different according to Tukey’s HSD test at p < 0.05). Water activity aw of raw and dried samples (error bars represent the SEM; bars labeled with different lowercase letters are significantly different according to Tukey’s HSD test at p < 0.05). Color change index dE of dried samples (error bars represent the SEM; bars labeled with different lowercase letters are significantly different according to Tukey’s HSD test at p < 0.05). Color change index dE of dried samples (error bars represent the SEM; bars labeled with different lowercase letters are significantly different according to Tukey’s HSD test at p < 0.05). Chroma C* ( a) and hue h ( b) of raw and dried samples (error bars represent the SEM; bars labeled with different lowercase letters are significantly different according to Tukey’s HSD test at p < 0.05). Chroma C* ( a) and hue h ( b) of raw and dried samples (error bars represent the SEM; bars la
Convective Drying of Apple Peel as a Preservation Procedure in Fruit Waste Valorization
Vorheriger Beitrag
