Introduction
Pineapple (Ananas comosus) is a tropical fruit with attractive sensory properties and nutritional characteristics. It is considered a rich source of vitamins B and C, as well as minerals such as calcium, phosphorus and iron, among other compounds (Ancos et al., 2016). Ginger (Zingiber officinale) is known for its spicy taste and is an excellent source of nutrients, including minerals (Mn, Fe, Mg, Zn, K, P and Ca) and vitamins (C, B3, B6, B1, B2, B9 and E). It also contains bioactive phenols such as gingerols, paradols, shogaols and zingerones, among others (Mbaveng and Kuete, 2017).
In general, food powders obtained through spray drying and fluidised bed agglomeration are typically found in a non-thermodynamic amorphous state, where their behaviour depends on the glass transition temperature (Tg). This condition strongly influences the required storage conditions for the product. If the storage temperature is lower than Tg, the product may retain a glassy state. However, at higher temperatures, it can transition into a rubbery amorphous state, where the molecular mobility of water significantly increases, leading to important changes in its physical, physicochemical, chemical, sensory, microbiological and nutritional properties (Rahman, 2019). Additionally, water content (Xw) in powdered foods is a critical parameter during storage due to its plasticising effect on amorphous systems (Carter and Schmidt, 2012). An increase in Xw levels due to adsorption phenomena further enhances molecular mobility by reducing local viscosity (Staniszewska et al., 2022). Thus, the physical, chemical, and microbiological stability of powdered products is strongly influenced by the relationship between equilibrium Xw and aw at a given temperature.
Studies on food stability over time enable the determination of shelf-life behaviour under different conditions. In addition, modelling the kinetics of quality parameter changes allows for the prediction of product behaviour during storage (Chang et al., 2018a), making it an important tool for decision-making regarding the conditions required to ensure that the product meets established quality standards for consumers (Udomkun et al., 2016).
In general, powdered foods are microbiologically stable due to low aw and Xw values. However, these products can be affected during storage by intrinsic factors, such as the type and concentration of additives, chemical composition, the ratio of functional groups present (proteins, lipids, and carbohydrates), polarity and particle morphology, among others; as well as extrinsic factors, including environmental conditions (temperature, time, relative humidity, light, O2), packaging, and others (Muzaffar and Kumar, 2016; Rannou et al., 2015). The combined effect of these independent variables leads to deterioration in nutritional value (Zorić et al., 2017), as well as in quality characteristics such as fluidity, agglomeration, and colour (Lucas-Aguirre et al., 2019; Pereira et al., 2020).
With regard to the behaviour of active compounds in food, the development of kinetic models has enabled the simulation of quality attributes, or dependent variables of food, at a given t, thereby addressing the needs of both science and the food industry while also determining shelf life. In this context, kinetic models provide a structural framework that enables the quantitative description of the changes occurring within a food system (Chang et al., 2018a). The measurement or availability of appropriate kinetic constants for these changes allows for the estimation of the magnitude of change of a given compound during food processing or storage (Heldman, 2011).
The evolution or changes in the properties of fruit powders during storage have been reported in several studies: myrtle (Cheng et al., 2017), jambolan (de Carvalho et al., 2020), blueberry (Staniszewska et al., 2022), soursop (Chang et al., 2019), mango peel (Ferrari et al., 2021), blackberry (Ferrari et al., 2013), papaya (Udomkun et al., 2016; Wong and Lim, 2016), pink guava (Shishir et al., 2017) and coconut (Lucas-Aguirre et al., 2019). Within this context, the present research aimed at evaluating the stability of an agglomerated pineapple–ginger powder mixture (APGPM) obtained via fluidised bed processing and stored at different temperatures (15, 25 and 35°C) and times (0, 30, 60, 90, 120, 150 and 180 days).
Materials and Methods
An APGPM was obtained using a Lemar (China) FL5 fluidised bed dryer under the following operating conditions: air inlet temperature (TEA) of 70°C, atomisation pressure of 1 bar, fluidising air fan frequency of 30–34 Hz, peristaltic pump frequency for atomisation water feed of 3–4 Hz (10–15 mL/min), process time of 1 h and 45 min, material load of 3000 g, fluidising agent of 0.5% w/w silica dioxide, binding solution (SL) composed of ginger extract (50%) + water (50%) + ascorbic acid (AA) (3.33 g/L total solution), and an SL consumption of 2000 mL. The powder mix used in the formulation was obtained from the pineapple fruit MD2 variety, purchased at a supermarket in the city of Medellín.
Determination of physical and physicochemical variables
Xw was determined according to the official AOAC 930.15/90 method. Water activity (aw) was measured using a dew point hygrometer at 25°C (Aqualab 3TE series, Decagon). Bulk density (ρb) was determined following the methodology described by Pereira et al. (2020), with modifications, by weighing 2 g of sample and recording the volume in a 10 mL test tube. Compacted density (ρc) was determined by placing 2 g of sample in a Falcon tube and centrifuged at 5000 rpm for 10 min, after which the recorded volume was measured (Gagneten et al., 2019). Fluidity was determined using the Carr Index (CI) (Carr, 1965) (Equation 1), while cohesiveness was assessed using the Hausner Ratio (HR) (Hausner, 1967) (Equation 2).
Solubility was determined according to the methodology of Chauhan and Patil (2013), modified by Marulanda et al. (2018). Wettability was assessed as the time required for 1 g of sample to disappear from the surface of a 100 mL volume of water at 20°C (Marulanda et al., 2018). Hygroscopicity was determined using the sorption isotherm methodology described by Daza et al. (2016), employing the gravimetric method at a constant and controlled relative humidity of 68%, maintained with a supersaturated potassium iodide solution at 25°C. Particle size was measured using a Mastersizer 3000 analyser (Malvern Instruments) and reported as the volume-equivalent diameter (D[4,3]). Colour was determined using CIE-Lab coordinates, measured with an X-RITE sphere spectrophotometer (model SP64) under illuminant D65, with a 10° observer and the specular component included.
The total phenolic (TP) content was determined from a methanolic extract obtained following the methodology described by Gallón et al. (2020) and quantified using the Folin–Ciocalteu reagent. Gallic acid calibration curves, ranging from 0 to 300 µg/mL (R2 = 0.989), were used, and TP results were expressed as mg gallic acid equivalent (GAE)/100 g db.
Antioxidant capacity was assessed through DPPH and ABTS free radical scavenging activity in the methanolic extract (Gallón et al., 2020). Trolox equivalent (TE) calibration curves were used for ABTS (50–250 µM, R2 = 0.998) and DPPH (0.02–0.12 mg/mL, R2 = 0.997), with results expressed as mg TE/100 g db.
The total flavonoid (TF) content was determined using the colorimetric method described by Sharma et al. (2016), with modifications. A 500 µL aliquot of extract was mixed with 150 µL of NaNO2 (5% w/v), 150 µL of AlCl3 (10% w/v), and 700 µL of NaOH (1 M). A standard calibration curve was prepared using quercetin in the range of 10–30 µg/mL, and absorbance was measured at 510 nm. Results were expressed as mg quercetin equivalent (QE)/100 g db.
Vitamin C (Vit. C) content was determined by placing 1.5 g of sample in a graduated test tube and adding a 0.02 M KH2PO4 buffer solution, adjusted to pH 3.0 with 85% orthophosphoric acid, to a final volume of 20 mL. The mixture was vortexed for 2 min and centrifuged at 5000 rpm for 15 min at 4°C. The supernatant was then filtered through a 0.45 µm cellulose acetate membrane filter and collected in an amber vial. Quantification was performed using HPLC (Shimadzu Prominence 20A) with a Luna® 5 µm C18(2) 100 Å column (250 × 4.6 mm). The mobile phase consisted of 0.02 M KH2PO4 (pH 3.06), with a flow rate of 1 mL/min and a pressure of 1172 psi. Retention times ranged from 4.317 to 4.456 min, with an injection volume of 5 µL and detection at 244 nm. An analytical standard solution of L-ascorbic acid (Sigma-Aldrich 47863, Lot LRAC1812) was used, and results were expressed as mg AAE/100 g db (Lucas et al., 2018).
β-carotene (β-Car) content was determined following the methodology of Etzbach et al. (2020), with minor modifications. A 1 g sample was dissolved in 10 mL of distilled water before carotenoid extraction, mixed with 10 mL of a hexane-acetone solution (60:40) and centrifuged at 8965 g for 5 min at 4°C. The supernatant was filtered through a 0.45 µm PVDF syringe filter. Identification and quantification were performed using HPLC on a Prominence UFLC 20A system (Shimadzu, Kyoto, Japan), coupled to a Prominence SPD-M20A diode array detector, with a Luna® C18(2) 100 Å column (250 × 4.6 mm ID, 5.0 µm Dp). The mobile phase consisted of acetonitrile:methanol:acetone (60:30:10), with a flow rate of 1.2 mL/min, a column temperature of 45°C, an injection volume of 20 µL and detection at 450 nm. The separation was carried out in isocratic mode with an analysis time of 45 min. The β-Car concentration was determined using the external standard method, with a β-carotene standard curve (Sigma-Aldrich C4582) in the range of 1–30 µg/mL (R2 = 0.999), and a retention time of 19.52 min. Results were expressed as µg/100 g db.
Experimental design and data analysis
A completely randomised factorial design was employed, considering the independent variables: storage time (0, 30, 60, 90, 120, and 180 days) and temperature (15, 25, and 35°C), and the dependent variables: Xw, aw, solubility, hygroscopicity, wettability, CI, RH, colour parameters (L, a*, b*), antioxidant activity (ABTS and DPPH), TP, TF, β-Car and Vit. C. The samples were packed in multilayer bags (Alico S.A) with a laminated film thickness of 12 μm (PET), 8 μm aluminium foil, and a polyethylene sealing layer of 100 μm, resulting in a total weight of 136.5 g/m2. The bags had a water vapour permeability of <1 cm3/(m2•24 h•atm) and an oxygen permeability of <1 cm3/(m2•24 h•atm). They were stored in climatic chambers with controlled relative humidity (65%) and packed under ambient conditions. Each package contained 100 g of APGPM. The results, obtained from three replicates, are presented as mean ± standard deviation.
A two-way analysis of variance (ANOVA) was employed to evaluate the effect of temperature and storage time on the response variable. In the model, time and temperature were treated as continuous variables, with different experimental levels. Each specific combination of time and temperature corresponded to an independent sample, as no repeated measurements were taken on the same sample, even though all samples originated from the same initial batch.
When significant differences were found, Tukey’s test was applied as a post hoc analysis. Statistical analysis was performed using Statgraphics Centurion XVII.II software.
Degradation kinetics of the active compounds
Variations in active compound content and antioxidant activity were analysed using zero-, first-, and second-order kinetic models, as described in Equations 3, 4, and 5, respectively. The reaction order was determined by regression analysis in Microsoft Excel® to identify the best-fitting model (R2). Additionally, the effect of temperature was evaluated using the Arrhenius equation (Equation 6) to determine the activation energy (Ea) (Heldman, 2011).
Ct = C0 – kt (3)
Ct = C0 exp(–kt) (4)
Results and Discussion
The properties of pineapple + ginger agglomerate powder (APGPM) were Xw = 4.8 ± 0.2%, aw = 0.143 ± 0.003, bulk density (ρb) = 0.38 ± 0.01 g/mL, solubility = 95.5 ± 0.3%, wettability = 8.1 ± 0.1 s, hygroscopicity = 17.3 ± 0.2%, CI = 4.1 ± 0.1%, HR = 1.05 ± 0.01, antioxidant activity: DPPH (324.1 ± 6.8 mg Trolox equivalent (TE)/100 g dry basis (db)), ABTS (287.4 ± 5.1 mg TE/100 g db), TP = 373.8 ± 4.1 mg gallic acid equivalent (GAE)/100 g db, TF = 232.7 ± 2.5 mg quercetin equivalent (QE)/100 g db, Vit.C = 253.4 ± 4.0 mg ascorbic acid equivalent (AAE)/100 g db, β-Car = 753.2 ± 4.7 µg/100 g db, and particle size (D[4,3]) = 111.6 ± 2.6 µm.
Table 1 presents the significant differences (P < 0.05) of the dependent variables according to ANOVA.
Table 1. ANOVA (P value) of the APGPM storage study.
| Variable | Time | Temperature | Interaction Time–Temperature |
|---|---|---|---|
| Xw | 0.000 | 0.003 | 0.124 |
| aw | 0.000 | 0.565 | 0.274 |
| Solubility | 0.000 | 0.295 | 0.346 |
| Wettability | 0.000 | 0.239 | 0.014 |
| Hygroscopicity | 0.000 | 0.185 | 0.048 |
| CI | 0.000 | 0.002 | 0.026 |
| HR | 0.039 | 0.879 | 0.790 |
| L | 0.000 | 0.005 | 0.016 |
| a* | 0.000 | 0.000 | 0.000 |
| b* | 0.000 | 0.244 | 0.270 |
| TP | 0.000 | 0.042 | 0.182 |
| TF | 0.000 | 0.027 | 0.001 |
| ABTS | 0.000 | 0.003 | 0.712 |
| DPPH | 0.000 | 0.000 | 0.006 |
| β-Car | 0.000 | 0.000 | 0.003 |
| Vit-C | 0.000 | 0.000 | 0.000 |
Moisture and water activity
Figure 1 presents the mean values and standard deviations for Xw and aw of APGPM during storage. Xw and aw are crucial parameters influencing the stability of powdered food products. In dehydration processes, the rate of mass transfer is pivotal in determining the final state of the material. When these rates are high, the product tends to acquire an amorphous state, which can range from vitreous to gummy.
Figure 1. Xw (A) and aw (B) of the APGPM during storage (blue: 15°C, orange: 25°C, and green: 35°C).
The latter state is prone to accelerating deterioration reactions due to increased water mobility within the food matrix, thereby reducing its quality over storage time (Karaca et al., 2015). Nevertheless, the inherent characteristics of the product and the interaction between temperature, Xw, and aw play a crucial role in determining its shelf life.
These results position the product within the established range for dehydrated powdered products, thereby ensuring reduced rates of physicochemical and biochemical deterioration reactions, as well as microbial growth (Shishir et al., 2017).
Xw exhibited a progressive increase during storage, with the highest values observed at 35°C. Consequently, ANOVA revealed significant statistical differences concerning the storage time and temperature of the independent variables. In general, the Xw and aw values obtained for APGPM were consistently higher than those reported for pineapple powder or mixtures obtained via spray drying (4.815 ± 0.176% and 0.143 ± 0.003, respectively). This difference arises because agglomerated powders absorb moisture from SL, which is not entirely removed during processing, resulting in a final Xw higher than the initial value. The Xw behaviour observed aligned with previous studies on other spray-dried products, such as sweet guava (Shishir et al., 2017), black cumin powder (Varastegani et al., 2019), soursop (Chang et al., 2018a) and coconut (Lucas-Aguirre et al., 2019), as well as products obtained through alternative technologies, including orange fibre (Fernández-López et al., 2009) and pineapple (Shiby et al., 2017).
Conversely, aw exhibited a trend similar to Xw; however, a sharp increase was noted mainly at 30 days for all temperatures. Subsequently, an asymptotic trend was observed at 15 and 25°C, whereas at 35°C, aw continued to rise progressively, reaching its highest values. This behaviour is primarily attributed to the driving force for mass transfer generated by the water chemical potential differential between APGPM (aw = 0.142 at day 0) and the storage chamber (aw = 0.650), which induces water adsorption at the active sites on the surface of APGPM until equilibrium is achieved (from Day 30 onwards) (Wilson et al., 2014).
This water transfer from the storage chamber to APGPM is regulated by the water vapour permeability of the packaging used (<1 cm3/[m2 * 24 h atm]).
Reconstitution properties
Figure 2 presents the mean values and standard deviations for solubility, hygroscopicity and wettability of the APGPM during storage.
Figure 2. Solubility, hygroscopicity, and wettability of the APGPM during storage.
In general, during storage, APGPM exhibited acceptable solubility (83.8 ± 0.6% to 92.3 ± 1.3%), with a gradual decrease over 180 days, becoming more pronounced between days 150 and 180. The ANOVA showed significant differences (P < 0.05) only for storage time but not temperature. Similar behaviours have been reported during the storage of Nigella sativa powder at 4°C for 12 months (92.6% to 91.9%) (Varastegani et al., 2019). Other studies have observed reductions in solubility during storage, including: a 35% decrease in soursop powder at 35°C for 90 days (Chang et al., 2018b); a decline from 97.1 to 85.1% in papaya powder stored at 38 ± 2°C, 90% relative humidity, for 7 weeks (Wong and Lim, 2016); and a decrease in mango peel powder over 6 months under ambient conditions (Wilson et al., 2014).
Wettability values ranged between 5.7 ± 0.5 and 19.6 ± 0.9 s, with ANOVA showing significant statistical differences (P < 0.05) concerning storage time and the storage time–temperature interaction. Wettability increased over time, revealing two homogeneous groups: one comprising the 25 and 35°C samples, which exhibited higher values, and another consisting of the 15°C samples, which showed lower values. In general, the results obtained could be considered characteristic of powders with good instantaneity (Cuq et al., 2013), similar to those observed in other agglomerated food powders: N. sativa (6.56 ± 0.73 s) (Mohammed et al., 2019), hydrolysed collagen (12 s) (Andreola et al., 2015), spinach with maltodextrin (6 s) and gum arabic (5 s), among others.
The behaviour of solubility and wettability is influenced by the increase in Xw over time. This phenomenon enhances the wetting of the solid bridges within the agglomerated particles, leading to a restructuring of the microstructure. As a result, pores collapse, causing caking that restricts water diffusion into the interior, thereby reducing solubility and increasing wetting time (Haider and Palzer, 2016).
Hygroscopicity is a key property of low-moisture foods, which represents the ability of a product to absorb water molecules from the surrounding environment. Greater adsorption capacity occurs when the food structure is drier and when there is a higher affinity between the surface’s active sites and the surrounding water molecules (Janiszewska-Turak et al., 2017). This response corresponds to the Xw equilibrium reached by APGPM under the conditions to which it is subjected (temperature: 25°C, relative humidity: 68%). ANOVA revealed significant statistical differences in hygroscopicity (P < 0.05) concerning storage time and the storage time–temperature interaction. Hygroscopicity exhibited a progressive decline over time, with lower values observed at 35°C after 180 days (17.3 ± 0.5% to 11.4 ± 0.5%). This behaviour was consistent with the Xw of APGPM over time, where lower hygroscopicity values reflect higher Xw levels. In this context, hygroscopicity is a variable influenced by the water vapour permeability of the packaging used. Therefore, ensuring minimal permeability to H2O and O2 vapour contributes to improved APGPM stability during storage.
Flowability and cohesiveness
Figure 3 presents the mean values and standard deviations for flowability and cohesiveness, measured as CI and HR, of the APGPM during storage.
Figure 3. Flowability and cohesiveness, measured as CI and HR, of the APGPM during storage.
The CI represents the percentage of powder compressibility, with flowability classified as very good (<15%), good (15–20%), medium (20–35%), poor (35–45%), and very poor (>45%) (Carr, 1965; Thakur and Nanda, 2022). CI was highly sensitive to storage conditions, with the ANOVA revealing significant statistical differences (P < 0.05) to time, temperature and their interaction. In this context, and according to the fluctuations observed in CI, APGPM exhibited good flowability (4.1 ± 0.9% to 19.7 ± 0.9%) during storage.
On the other hand, HR represents a measure of APGPM cohesiveness, classified according to Hausner (1967), as low (<1.2), intermediate (1.2–1.4) and high (>1.4). The mean HR values ranged from 1.05 ± 0.01 to 1.24 ± 0.03, indicating classification of cohesiveness as low to intermediate. The ANOVA identified significant statistical differences (P < 0.05) for HR only with time, showing an increasing trend with temperature. However, the most pronounced changes occurred after 90 days, with higher values observed at higher temperatures.
APGPM demonstrated good flow properties during storage, primarily due to the presence of SiO2, which possesses fluidising and anticompacting properties. SiO2 reduces the likelihood of particles sticking together by minimising cohesive forces, thereby preventing caking. In general, the flow characteristics of powdered foods are affected by storage conditions (time, temperature and packaging materials), density, particle size, capillary activity and the migration of cohesive chemical components to the particle surface (Cruz-Tirado et al., 2021).
For both CI and HR, the most significant increase was observed at 35°C between days 120 and 180. This behaviour aligns with the increase in Xw over time and temperature, which enhances material plasticity, increases molecular mobility and promotes the formation of liquid bridges between particles (Ferrari et al., 2013; Zungur et al., 2017). The flow characteristics of APGPM were consistent with those reported for olive powder stored at 4, 25 and 60°C for 180 days (Zungur et al., 2017), soy milk powder stored at 10, 25, 35 and 55°C for 150 days (Cruz-Tirado et al., 2021), and bee pollen-enriched milk powder stored at 5, 25 and 40°C for 365 days (Thakur and Nanda, 2022).
Colour
Figure 4 presents the mean values and standard deviations for Colour (L, a*, b*), of the APGPM during storage.
Figure 4. Colour (L, a*, b*) of the APGPM during storage.
Colour is a fundamental sensory attribute of food, playing a crucial role in consumer perception. It influences purchasing and consumption decisions while also serving as an indicator of product quality and condition, which is perceived visually (Mathias-Rettig and Ah-Hen, 2014). Food colour results from biochemical reactions occurring during processing and storage (de Carvalho et al., 2020). Its stability during storage depends on multiple factors, including storage time, temperature, relative humidity, light exposure, moisture content and product composition (Chang et al., 2018a).
ANOVA revealed significant statistical differences (P < 0.05) in luminance (L) and chromaticity (a) in relation to storage time, temperature and their interaction. Additionally, chromaticity (b) exhibited significant differences (P < 0.05) only with storage time. Luminance (L) is closely associated with browning in food matrices, ranging from black (L = 0) to white (L = 100). For APGPM, L was the most relevant colour parameter, with values ranging from 51.3 ± 0.7 to 71.2 ± 0.6 at 15°C, 51.3 ± 0.7 to 64.9 ± 0.6 at 25°C and 51.3 ± 0.7 to 64.8 ± 0.1 at 35°C.
The evolution of L over storage time showed a significant increase during the first 30 days at all temperatures: by 38% at 15°C and by 26% at 35°C. Subsequently, values remained stable for approximately 90–120 days before declining to levels similar to those found at Day 0 (L = 51.3 ± 0.7) (Figure 4).
The behaviour observed in the initial phase remains unclear and is also evident in chromaticity parameters a and b. The increase in surface water absorption in APGPM during this period (as indicated by rising Xw and aw) would theoretically result in changes in surface refractive indices and increased light absorption, potentially leading to a less clear appearance of the samples. However, the opposite trend was observed. This suggests that, during the early storage phase, water diffuses into the deeper layers, where it preferentially adsorbs, leaving the porous and dry surface of APGPM exposed to the spectrophotometer’s light beam, thereby increasing L values. After 30 days, APGPM may undergo simultaneous degradation processes within the matrix, including phenolic oxidation and polymerisation, as well as non-enzymatic browning reactions (Maillard reaction), among others (de Carvalho et al., 2020). Additionally, Δa and Δb values remained low (≤5.0), indicating minimal variations (a: 0.3 ± 0.0–2.6 ± 0.0, b: 15.2 ± 0.4–11.9 ± 0.7), which are considered non-critical and imperceptible to the human eye (Lucas-Aguirre et al., 2019). These or similar behaviours have been reported by several authors during the storage of other fruit powders, such as pineapple (Lima et al., 2019), banana (Barooah et al., 2018), jambolan (de Carvalho et al., 2020) and soursop (Chang et al., 2018a), among others.
Active compounds
Based on the initial content of active compounds and antioxidant activity of APGPM, favourable nutritional conditions are emphasised, particularly as a source of Vit. C. However, during storage, a decreasing trend was observed in antioxidant activity and bioactive compounds (Vit. C, β-Car, TF and TP) with storage time, making these variables the most critical during storage. The ANOVA analysis revealed that bioactive compounds and antioxidant activity were significantly influenced by storage time, temperature and their interaction.
During storage, the decrease in antioxidant activity (DPPH and ABTS) and TP and TF concentrations is associated with the increase in Xw and aw over time and rising temperature (Figures 5A and 5B). This phenomenon affects molecular mobility, leading to the activation of hydrolytic or oxidative enzymes such as polyphenol oxidase, thereby inducing chemical oxidation reactions (Udomkun et al., 2016). The effect of temperature on phenolic compounds such as TP and TF is related to the changes they can undergo in their structure, by breaking the carbon–oxygen bond that causes the loss of hydroxyl (OH) groups responsible for their biological activities and antioxidant properties.
Figure 5. Evolution of antioxidant activity and active compounds of APGPM during storage (blue: 15°C, orange: 25°C and green: 35°C). (A) ABTS, (B) DPPH, (C) TP, (D) TF, (E) Vit. C, (F) β-Car.
On the other hand, both temperature and storage time can impact β-Car contents through two primary degradation mechanisms: oxidation and isomerisation. Oxidation may occur through self-activation (autooxidation), light exposure (photooxidation) or enzymatic catalysis (enzymatic oxidation). Conversely, isomerisation, primarily influenced by temperature, involves the transformation of trans-β-Car into the cis-β-Car form, which exhibits lower biological activity.
During storage, the degradation of Vit. C is primarily driven by temperature, alongside other factors such as oxygen availability, pH, transition metals (iron and copper) and light exposure. Additionally, salts, aw and the presence of other vitamins, among other factors, also play significant roles.
It is important to note that the Vit. C content in APGPM results from both its natural presence in pineapple and ginger and its addition in the binding solution during agglomeration. This distinction is relevant when interpreting degradation kinetics, as the stability of an added compound can differ from that of a naturally occurring one due to potential matrix effects. The food matrix may provide structural or chemical protection that influences degradation rates, either by limiting oxygen exposure or interacting with other bioactive compounds. Therefore, the observed degradation reflects both the loss of added Vit. C and the naturally occurring fraction, which may degrade at different rates depending on the storage conditions.
This degradation process involves oxidation, wherein ascorbic acid undergoes a reversible reaction to form dehydroascorbic acid, establishing an oxidation–reduction system. Subsequently, dehydroascorbic acid undergoes further oxidation, transforming into 2,3-diketogulonic acid, which lacks biological activity. Through Strecker degradation, 2,3-diketogulonic acid is further broken down, producing carbon dioxide and furfural (Badui, 2006).
Table 2 presents the kinetic fits of the active compounds and the antioxidant activity of APGPM during storage. It describes the most suitable reaction order (n), degradation rate constant (k), regression coefficients (R2) and Ea. The optimal degradation kinetics for the quality attributes are as follows: zero-order (for TF and DPPH), first-order (for TP and Vit. C) and second-order (for ABTS and β-car).
Table 2. Kinetic adjustments of active compounds and antioxidant activity of APGPM during storage.
| T | n | ABTS | DPPH | TP | TF | Vit. C | β-car |
|---|---|---|---|---|---|---|---|
| 2 | 0 | 0 | 1 | 1 | 2 | ||
| 15°C | k(mg day−1) | 2 × 10−5 | 25.9 | 0.7 | 4 × 10−3 | 4.6 × 10−3 | 9 × 10−6 |
| R2 | 0.91 | 0.93 | 0.93 | 0.77 | 0.96 | 0.98 | |
| 25°C | k(mg day−1) | 5 × 10−4 | 33.9 | 0.8 | 5.4 × 10−3 | 6.7 × 10−3 | 1x10−5 |
| R2 | 0.96 | 0.88 | 0.96 | 0.96 | 0.98 | 0.95 | |
| 35°C | k(mg day−1) | 5 × 10−3 | 27.2 | 0.8 | 6 × 10−3 | × 10−2 | 3 × 10−5 |
| R2 | 0.96 | 0.94 | 0.91 | 0.92 | 0.96 | 0.95 | |
| Ea (kJ/mol) | 34.0 | 2.3 | 5.6 | 20.6 | 0.17 | 44.0 |
APGPM, agglomerated pineapple–ginger powder mixture; β-Car, β-carotenoids; Ea, activation energy; k, degradation rate constant; n, reaction order; R2, coefficient of determination; TF, total flavonoids; TP, total phenols; Vit. C, vitamin C.
In general, the degradation rate constant (k) was higher at elevated temperatures, attributed to the thermosensitive nature of the active compounds analysed. This relationship serves as an indicator of their thermal degradation, where lower values indicate greater stability of the compound (de Carvalho et al., 2020). The degradation mechanisms of the active compounds may be affected by their physical state, as well as the presence of O2 and high water activity, influencing the degradation rate due to increased molecular mobility (Cruz-Tirado et al., 2021).
On the other hand, Ea represents the minimum energy required for the degradation process to occur, meaning the energy needed for molecules to transition from the initial state to the formation of degradation products. In this context, a higher Ea is preferable, as it indicates greater stability of the active compounds during storage.
The Ea values obtained for the different bioactive compounds and antioxidant activity indicators varied, reflecting differences in their susceptibility to temperature-induced degradation. Higher Ea values were associated with compounds exhibiting greater resistance to thermal degradation, whereas lower values indicated increased vulnerability to storage conditions.
The reaction order observed for each parameter aligns with previous studies on the degradation kinetics of bioactive compounds in fruit powders (de Carvalho et al., 2020; Cruz-Tirado et al., 2021). The zero-order kinetics observed for TF and DPPH suggest a constant degradation rate, independent of the remaining concentration. In contrast, the first-order kinetics identified for total phenolics (TP) and Vit. C indicate that the degradation rate is proportional to the concentration of the compound, meaning that higher initial concentrations lead to faster degradation. The second-order kinetics for ABTS and β-Car suggest a more complex degradation mechanism, potentially influenced by interactions with other matrix components or secondary oxidative reactions.
Furthermore, the degradation rate constants increased with storage temperature, highlighting the thermosensitive nature of these compounds. This behaviour aligns with Arrhenius kinetics, reinforcing the importance of controlling temperature during storage to preserve the functional properties of APGPM. Additionally, the combined effects of high water activity and oxygen availability may accelerate oxidative reactions, further compromising the stability of bioactive compounds over time.
In summary, the degradation of active compounds in APGPM follows distinct kinetic models depending on the compound type, with temperature playing a key role in determining the rate of deterioration. Strategies such as minimising oxygen exposure, optimising moisture content, and implementing appropriate packaging solutions could help mitigate degradation and extend the shelf life of APGPM while maintaining its nutritional and antioxidant properties.
Figure 5 illustrates a gradual decrease in the ABTS and DPPH variables during 180 days of storage. Both exhibit similar retention levels at storage temperatures of 15, 25 and 35°C: 50.7, 51.9 and 33.2% for ABTS, and 53.6, 61.2 and 34.0% for DPPH, respectively. ABTS fluctuates from 287.4 to 145.8, 149.2, and 96.5 mg TE/100 g dry basis, while DPPH ranges from 324.1 to 173.6, 198.6, and 110.2 mg TE/100 g dry basis, respectively. Both antioxidant properties undergo greater degradation under the highest thermal stress (35°C), as previously discussed.
The kinetic models that provided the best regression fit for the ABTS and DPPH variables were of second and zero order, respectively. The k values were (2 × 10–5, 50 × 10–5 and 500 × 10–5 mg/day¹) for ABTS and (25.9, 33.9 and 27.2 mg/day¹) for DPPH at 15, 25, and 35°C, respectively. A low activation energy requirement (Ea = 2.3 kJ/mol) for DPPH degradation was observed. Additionally, the regression coefficients obtained, ranging from a minimum of 0.88 to a maximum of 0.96, are considered acceptable. Similar results were reported for dehydrated papaya stored at 30°C, with ABTS and DPPH retention levels of 66 and 42%, respectively (Udomkun et al., 2016). Conversely, Mishra et al. (2014) reported 83.7% retention levels in plums stored at 4°C.
The APGPM TP exhibited the lowest retention levels after 150 days of storage at 15, 25 and 35°C: 69.7, 65.6 and 62.9%, respectively. These values were very similar to those recorded at 180 days and, as expected, were lower at higher temperatures (35°C). Regarding reaction kinetics, TP followed a zero-order model with R2 values of 0.93, 0.96 and 0.91 and k values of 0.7, 0.8 and 0.8 mg/day¹ at 15, 25 and 35°C, respectively, with an Ea of 5.6 kJ/mol.
Regarding the TF in APGPM, at 15, 25 and 35°C, their retention levels after 180 days of storage were 52.7, 33.6, and 30.1%, respectively. Figure 5D illustrates a greater TF loss at 15 and 25°C during the first 30 days (29.8 and 33.7%, respectively), whereas at 35°C, the highest loss occurred during the first 60 days (50.1%). The kinetic fit of TF followed a first-order model with R2 values of 0.77, 0.96 and 0.92, and k values of 4 × 10–3, 5.4 × 10–3 and 6 × 10–3 mg/day at 15, 25 and 35°C, respectively, with an Ea of 20.6 kJ/mol.
Udomkun et al. (2016) reported zero-order kinetics for dehydrated papaya stored in aluminium-laminated polyethylene, with a k value of 1.1/day (R2 = 0.99). However, when polyamide/polyethylene packaging was used, the k value increased to 1.3/day¹ (R2 = 0.97). Similarly, Daza et al. (2016) observed TP content losses exceeding 25% in all samples after 120 days of storage. Varastegani et al. (2019) reported retention values for spray-dried N. sativa TF after 12 months of storage, ranging between 58 and 68%. Conversely, de Carvalho et al. (2020) found that TF in jambolan powder stored at 4, 25 and 35°C remained highly stable, showing no significant statistical differences with respect to temperature or storage time. The decrease in TP and TF concentrations during storage could be attributed to the activation of oxidative enzymes, such as polyphenol oxidase, or chemical oxidation triggered by molecular mobility, temperature, oxygen exposure or light (Zorić et al., 2017).
The Vit. C content in APGPM after 180 days of storage showed retention levels of 40.0, 27.2 and 12.8% at 15, 25 and 35°C, respectively. Figure 5E illustrates a progressive degradation over time, with higher degradation occurring at higher temperatures. The kinetic fit of Vit. C in APGPM followed a first-order mathematical model, with R2 values of 0.96, 0.98 and 0.96, k values of 4.6 × 10–3, 6.7 × 10–3 and 1 × 10–2 mg/day, and an Ea of 0.17 kJ/mol. This suggests that vitamin C is the least stable of the active components studied, as it requires less energy for its oxidative processes to occur, leading to the formation of dehydroascorbic acid—which is still bioavailable but less stable—and ultimately to its further oxidation.
Based on the results obtained, a reference portion of 30 g of APGPM is sufficient to prepare 250 g of a pineapple and ginger drink with approximately 11.0 °Brix. After 180 days of storage, this portion would provide 27.8, 19.0 and 8.8% of the daily Vit. C requirement, according to the World Health Organisation (WHO) recommendation of 100 mg of Vit. C per day, at 15, 25 and 35°C, respectively.
In Colombia, Resolution 821 of 2021 from the Ministry of Health and Social Protection establishes the daily reference nutrient requirement value (NRV-N) for Vit. C at 83 mg. Accordingly, a 30 g portion of APGPM provides 33.5, 22.9 and 10.7% of the NRV-N at storage temperatures of 15, 25 and 35°C, respectively.
Finally, the β-carotene (β-Car) content in APGPM after 180 days of storage showed retention levels of 42.3, 39.1 and 0% at 15, 25 and 35°C, respectively. It is important to note that, at 35°C, β-Car was not quantifiable using the HPLC calibration curve applied; therefore, its value was considered as 0. The evolution of TF over time revealed a progressive decrease throughout storage (Figure 2F), and ANOVA identified two homogeneous groups: one at 15 and 25°C, and another at 35°C, with significantly lower retention at 35°C across all time points. The kinetic fit of β-Car in APGPM followed a second-order mathematical model, with R2 values of 0.95 and 0.95 and k values of 9 × 10–6, 10 × 10–6 and 30 × 10–6 mg/day¹ for 15, 25 and 35°C, respectively, with an Ea of 44.0 kJ/mol.
Several studies have reported different reaction orders for the degradation of active compounds during storage in powdered food products: Zorić et al. (2017) reported zero and first-order kinetics for the degradation of phenolic compounds in sour cherry powder stored at 4, 20 and 37°C for 365 days. Ferrari et al. (2021) reported zero-order kinetics for Vit. C degradation in mango peel powder stored at 10, 15, and 25°C for 180 days; Shiby et al. (2017) reported first-order kinetics for Vit. C degradation in pineapple powder; Syamila et al. (2019) reported first-order kinetics for β-car, lutein and α-tocopherol in spinach powder stored at 4, 20 and 40°C. On the other hand, Daza et al. (2016) reported phenol losses under first-order kinetics in cagaita powder stored at 25°C for 150 days.
Conclusions
At the end of storage, Xw and aw values confirmed the physicochemical stability of APGPM, with flowability classified as good to very good and cohesiveness ranging from low to intermediate. Among the colour parameters, luminance (L) was the most critical, while chromaticity values a and b remained stable (Δa* and Δb* < 5), making them imperceptible to the human eye. The degradation kinetics exhibited strong model fits (R2 between 91 and 99%), except for TP at 15°C (R2 = 0.77). Retention levels of active compounds and antioxidant capacity after 180 days of storage at 15, 25, and 35°C were: ABTS (50.7–33.2%), DPPH (53.6–34.0%), TP (69.7–62.9%), TF (52.7–30.1%), Vit. C (40.0–12.8%) and β-car (42.3–0%), confirming higher degradation rates at elevated temperatures.
The findings highlight the relevance of storage conditions in preserving the nutritional and functional quality of APGPM, with 15 and 25°C providing optimal stability. This study offers valuable insights into the shelf life prediction of APGPM, supporting its potential for commercial applications in functional food formulations. Furthermore, future research on sorption isotherms and phase transitions is recommended to refine shelf life estimations, ensuring better stability and product performance under different storage environments.