Electrophysiological Characterization of Aloe vera Under Abiotic Stress: A Quantitative Basis for Plant-Based Biodosimetry

Abstract

Environmental monitoring across extensive regions is often constrained by the high costs of conventional laboratory analysis. This study proposes a methodology for electrophysiological characterization of Aloe vera as a potential biological dosimeter for low-cost environmental sensing. Using an ATMega328P-based acquisition system with high-input-impedance signal conditioning, we recorded plant biopotentials under controlled abiotic stressors. Signal variations were evaluated as a function of leaf morphology, electrode placement, and environmental variables, including light intensity, soil moisture, water saturation, and pH. The statistical validation included Jaccard similarity coefficients for repeatability and Kruskal–Wallis tests for group comparisons. The measurements showed highly repeatable baseline behavior (Jaccard similarity in the range 0.95–0.99) and significant differences across stress conditions, particularly under changes in light intensity. These findings support the feasibility of using Aloe vera electrophysiological signals as a robust and low-cost basis for developing plant-based biosensing approaches in environmental monitoring applications.

1. Introduction

Electrical signaling (ES) represents one of the most fundamental mechanisms of physical communication in living organisms, surpassing chemical signaling in speed and enabling information transfer over long distances [1]. In plants, electrophysiological signals are commonly classified into action potentials (APs) and variation potentials (VPs). Although both are transient depolarizations that propagate through vascular tissues, they exhibit distinct characteristics that have been documented across multiple studies [2,3,4].

Action potentials (APs) are rapid electrical impulses that propagate along phloem membranes with relatively constant amplitude and velocity [5,6]. They arise from a short-duration sequence of depolarization and repolarization of the plasma membrane [7]. The generation of an AP is typically threshold-dependent: a stimulus must exceed a critical level to trigger the response, after which the amplitude remains largely independent of stimulus intensity [5]. These potential differences emerge from spatial and temporal changes in ion concentrations across cellular membranes [8]. In plants, the resulting voltages are usually of low magnitude, typically on the order of millivolts (mV) to tens of mV [9]. With appropriate sensors and instrumentation, these signals can be acquired and interpreted as indicators of the plant’s physiological state and surrounding environmental conditions [10]. Because electrophysiological responses are tightly coupled to biochemical and hydraulic processes triggered by external perturbations, plant electrical activity has been explored as a quantitative proxy for stress perception and response [11,12,13].

Recently, plant bioelectrical signaling has regained attention due to improved mechanistic understanding and advances in acquisition and analysis pipelines. Recent syntheses emphasize that electrical signals can encode stimulus-specific information and be leveraged as quantitative indicators of physiological status and abiotic-stress responses while also highlighting the current challenges in interpretation, reproducibility, feature robustness, and methodological standardization [14,15,16]. In parallel, the rapid growth of portable plant-sensing platforms is enabling continuous field-oriented monitoring and integration with data-driven approaches in precision agriculture and environmental surveillance [17,18]. Despite these advances, a major challenge in large-scale environmental monitoring remains the prohibitive cost of conventional laboratory analysis and extensive field sampling [19]. In this context, leveraging plant electrical signals as biodosimeters offers a promising low-cost alternative but requires careful characterization under well-controlled measurement conditions.

Aloe vera (L.) Burm.f. was selected as the target species because it is widely available, inexpensive to maintain, and resilient to abiotic stress due to its succulent physiology, which facilitates controlled experimentation without rapid tissue collapse under moderate perturbations. Aloe species have also been previously investigated in electrophysiological studies, where characteristic signal dynamics and rhythmic electrical patterns have been reported, supporting their feasibility as plant-sensing platforms [20,21]. Importantly, Aloe vera has already been demonstrated as a scalable plant-sensing platform in previous work, where bioelectrical signals enabled accurate discrimination between control plants and lead exposure using a low-cost Arduino-based acquisition system and interpretable machine-learning models [22]. Plants can act as effective biodosimeters because their electrophysiological activity is sensitive to a wide range of environmental stressors, including directional light, water stress, insect attacks, and pollutants (e.g., pesticides and heavy metals) [11,23]. Accordingly, a plant-based sensing platform should be able to detect, register, and convey information associated with physiological changes [24].

Building on this rationale, the objective of this study is to provide a quantitative electrophysiological characterization of Aloe vera under controlled abiotic stressors, specifically light intensity, soil moisture, prolonged water excess, and soil pH shifts. In addition to evaluating stress-dependent signal patterns, this work places emphasis on methodological standardization by assessing baseline signal reproducibility, leaf-size effects, and electrode-spacing considerations, aiming to establish robust and reproducible measurement conditions that support future plant-based monitoring applications and align with recent efforts toward reproducible electrome-based plant monitoring frameworks [16].

2. Materials and Methods

This section describes the experimental protocol used to acquire Aloe vera bioelectrical signals and evaluate their modulation under controlled abiotic factors. The methodology specifies plant material and biological replication, the low-cost electronic acquisition system and sensors, and standardized measurement steps and treatment-specific protocols. The evaluated factors include light intensity, soil moisture level, prolonged water excess, and substrate pH shifts, together with methodological controls for baseline reproducibility, leaf-size effects, and electrode-spacing considerations.

2.1. Plant Material and Experimental Replication

A total of 70 mature Aloe vera plants were used in this study. All specimens were cultivated under controlled laboratory conditions in Zacatecas, Mexico, and selected based on homogeneous morphological characteristics (average height ∼40 cm, uniform green coloration, and absence of visible tissue damage).

To ensure biological independence and avoid carry-over effects between treatments, the experimental design was organized into independent groups. Each plant was assigned exclusively to a single experimental condition, and only one leaf per plant was instrumented to prevent interference caused by multiple electrode insertions.

Signal reproducibility was assessed using 10 plants under identical baseline conditions, from which six representative cycles were selected for detailed comparative analysis. Leaf-size comparison involved 16 independent plants distributed equally across four length categories (8, 12, 15, and 20 cm; $n=4$ per group). Electrode-distance evaluation was performed on 10 plants, with two independent plants per insertion distance (1, 3, 5, 6, and 8 cm).

Light-intensity experiments were conducted using 12 plants, with two plants per illumination level (12%, 22%, 32%, 48%, 68%, and 92%). Soil-moisture variation was evaluated in 10 plants, with two independent plants per humidity percentage (5%, 34%, 38%, 80%, and 94%). Prolonged water-excess stress over seven consecutive days was monitored in six independent plants. Finally, pH variation experiments were conducted on six plants, three assigned to acidic treatment (aluminum sulfate) and three to alkaline treatment (calcium carbonate).

In all cases, a 60–120 min acclimation period was allowed after electrode insertion to enable recovery from insertion wounding and re-establishment of baseline electrophysiological activity prior to signal acquisition.

2.2. Electronic System Proposed for Signal Acquisition of the Aloe vera

Figure 1 shows a general diagram of the parts that make up the electrical signal acquisition system of the Aloe vera plant. The first block (Figure 1(B1))) is composed of the data acquisition unit, the ATMega328P microcontroller (Microchip Technology Inc., Chandler, AZ, USA). Its main advantages are its low cost and practicality in implementation. It is a microcontroller widely used in the development of different projects [19].

The second block (Figure 1(B2)) represents the signal coupling stage that is performed by the LM324N operational amplifier (Texas Instruments, Dallas, TX, USA). It is useful for its low consumption, low cost, and high input impedance and low output impedance and ideal in applications where the nature of the signal is on the order of millivolts (mV) [25].

The third block (Figure 1(B3)) corresponds to the stage of measuring the electrical signal. It consists of two electrodes inserted into the Aloe vera leaf at a distance of 5 cm from each other. Since the electrodes serve as an interface, it is important to note that a current will flow through them, which is usually of small magnitude, although it is still significant [26]. In this study, hypodermic needles were used as electrodes. They were made of chrome–nickel stainless steel. This material is inert and is covered with a layer of silicone that makes the insertion into the body smoother. The external diameter is 0.91 mm, 20 G caliber, identified with the color yellow. Selected because the electrical resistance in a conductor is inversely related to its cross-sectional area: the greater the cross-sectional area, the lower the resistance.

Finally, the fourth block (Figure 1(B4)) consists of a data storage unit. The data is collected by a Micro SD module. It allows the information to be collected by the ATMega328P from the electrodes and the different sensors to be stored. The information can then be viewed on a PC screen.

To determine the electrophysiological response of Aloe vera, the electronic assembly shown in Figure 2 has been utilized. Different sensors were considered to delimit the conditions in which the acquisition of the electrical signal of the Aloe vera plant was carried out. The sensor for temperature and relative humidity is DHT11 (Aosong Electronics Co., Guangzhou, China), for soil moisture percentage FC-28 (Keyestudio, Shenzhen, China), for light intensity a 4-pin LDR light sensor module (Keyestudio, Shenzhen, China), and a Micro SD storage module (Catalex Electronics, Shenzhen, China) to store the information collected by the microcontroller. The proposed design allows the acquisition of the electrical signal in Aloe vera plants.

This arrangement allows a gross potential difference to be obtained; i.e., the acquired signal reflects the ionic imbalance generated by the plant due to different types of stress.

Table 1. Costs of the electronic circuit for the acquisition of the electrical signal of the Aloe vera plant.

Component	Cost [US$]
ATMega328p	3
DHT11	3
LDR	1
Resistor 820, 20 KΩ	1
FC-28	2
Micro SD Module	2
LM324	1
Battery 9V	2
Electrodes	1
Micro SD Memory	1
Total	17

shows the costs of each component, as well as the total price of the equipment.

2.3. Proposed Experimental Design for Acquiring the Electrical Signal of the Aloe vera Plant

To verify the reliability of the electrical signals captured by the acquisition system, specific tests were implemented using the Aloe vera plant. All experimental conditions were evaluated using independent plants assigned exclusively to a single treatment group (one instrumented leaf per plant). The methodology adopted to measure biopotentials is described according to the following 4 steps:

(i)

Conditions of the Aloe vera plant. Mature Aloe vera plants grown under laboratory conditions in Zacatecas, Mexico, were used. Plants had an approximate height of ∼40 cm and uniform green coloration without visible tissue damage. For baseline/control recordings, leaves of approximately 7–8 cm length (and 3–4 cm width) were preferentially selected; for the leaf-size experiment, leaves were selected according to the predefined length categories (8, 12, 15, and 20 cm).

(ii)

Position of the electrodes. The first electrode is inserted into the Aloe vera leaf, near the stem, about 1 cm from the stem. The second one is inserted into the same Aloe vera leaf, near the tip of the leaf and in the direction of the first electrode. The distance between the tips of the two electrodes was 5 cm. The penetration of the electrodes was approximately 0.2 cm. See Figure 3.

(iii)

Electronic equipment. Once the electrodes are in place, the micro SD storage drive is inserted and the equipment is turned on. It is essential to allow a 60–120 min acclimation period for the plant to recover from electrode insertion wounding and re-establish baseline electrophysiological activity. Once this is done, data is acquired for 20 min, obtaining a sample every 1 s.

(iv)

Experiments and voltage condition variations. Once the electrodes were inserted, some additional characteristics of the measurement environment were recorded, such as a soil moisture of 60% at temperature of 25 °C with humidity of 37.9% and an LDR module resistor of 7 kΩ. Subsequently, the variations in the different conditions of stress and the recording of the biopotentials were carried out. The experiments are described in the subsections below.

Figure 3. Configuration of the electrode insertion in the Aloe vera plant. (A) Electronic system for the acquisition of the electrical signal. (B) Pair of electrodes inserted into the Aloe vera leaf.

Figure 3. Configuration of the electrode insertion in the Aloe vera plant. (A) Electronic system for the acquisition of the electrical signal. (B) Pair of electrodes inserted into the Aloe vera leaf.

The first three are experiments focused on methodological considerations made to establish standard measurement conditions, such as signal reproducibility, leaf-size considerations, and ideal electrode spacing. Moreover, some other experiments are carried out varying conditions such as light intensity, different percentages of soil moisture, water stress and changes in soil pH exerted on the plant and the effect it has on the electrical signal.

2.3.1. Signal Reproducibility

The importance of measuring reproducibility lies in demonstrating that the electronic acquisition system provides accurate and stable electrical signal measurements under identical baseline conditions, making the results comparable to those reported in the literature. The Jaccard similarity coefficient was calculated to quantify the similarity between independent recordings obtained under control conditions. The objective was to establish a baseline electrical response pattern to serve as a reference for subsequent stress experiments.

For this purpose, ten independent Aloe vera plants were evaluated under identical environmental conditions. From this group, six representative baseline recordings (one leaf per plant) were selected for detailed pairwise similarity analysis. Each recording lasted 1200 s, with the electrode signal sampled every 1 s. The Jaccard coefficient is described according to Equation (1):

$$J(A,B)={\displaystyle \frac{|A\cap B|}{|A\cup B|}}$$

(1)

where $|A\cap B|$ represents the size of the intersection of the sets A and B, that is, the number of elements they have in common. $|A\cup B|$ represents the size of the union of the sets A and B, that is, the total number of elements in both sets without duplications. The value of the Jaccard coefficient varies between 0 and 1 [27].

2.3.2. Leaf-Size Difference

The purpose of this experiment was to determine whether the electrical potential difference in Aloe vera varies according to leaf length. Sixteen independent plants were evaluated and distributed equally across four leaf-size categories: 8 cm, 12 cm, 15 cm, and 20 cm (n = 4 plants per size group). Only one leaf per plant was instrumented to ensure biological independence between measurements.

One of the baseline recordings obtained from the reproducibility experiment (independent control plant) was used as a reference signal (control). Subsequently, descriptive statistical analysis was performed using box and density plots to analyze the distribution of each size group compared to the reference signal and to determine differences between the signals [28]. Figure 4 shows the representative leaf sizes used in this experiment.

By applying these techniques, the variations and distributions of the electrical signal of Aloe vera (differences or similarities) can be properly interpreted, which is essential to support and validate the use of this tool in the present research. This descriptive analysis serves as a necessary preliminary step to understand in depth the electrical properties of Aloe vera, allowing an effective exploration of its possible applications and behaviors as a biosensor or biodosimeter [28,29]. Subsequently, the Kruskal–Wallis statistical test was performed to determine if there were statistically significant differences between the control signal and each leaf-size group. Equation (2) describes the Kruskal–Wallis test.

$$H=\left({\displaystyle \frac{12}{N(N+1)}}\right)\sum _{i=1}^N{\displaystyle \frac{R_i^2}{n_i}}-3(N+1),$$

(2)

where N is the total number of observations, $R_i$ is the sum of the ranks for group i, and $n_i$ is the number of observations in group i. In this context, the null hypothesis assumes that all samples originate from the same distribution, meaning there is no difference in electrical signal responses between the different leaf sizes and the reference signal. The alternative hypothesis proposes that at least one group originates from a different distribution, indicating that at least one leaf-size category exhibits a significantly different electrical response. If the p-value is less than 0.05, the null hypothesis is rejected and it can be concluded that significant differences exist between at least two leaf-size groups [30].

2.3.3. Distance Between Electrodes

There is no standard guideline in the literature to determine the optimal spacing between electrodes for measuring plant electrical signals. Therefore, the electrical response of Aloe vera was acquired using five electrode insertion distances: 1, 3, 5, 6, and 8 cm. This experiment was conducted using ten independent plants, with two plants evaluated per insertion distance (n = 2 per group). Only one leaf per plant was instrumented.

All measurements were performed under the same baseline experimental conditions, varying only the distance between electrodes. This experiment aimed to identify a practical electrode spacing that provides a stable baseline response while still capturing clear signal variations for subsequent stress experiments.

2.3.4. Stress from Different Light Levels

The purpose of this experiment was to determine changes in electrical potential difference associated with variations in light intensity. This experiment was performed using twelve independent Aloe vera plants distributed across six light levels (n = 2 plants per level), with each plant assigned exclusively to one intensity condition and one instrumented leaf per plant. Plants were exposed to the selected light condition for 24 h. Light intensity was expressed as a percentage derived from the LDR module reading (relative scale), corresponding to 12, 22, 32, 48, 68, and 92%.

2.3.5. Stress from Different Percentages of Soil Moisture

The purpose of this experiment was to evaluate changes in the bioelectrical potential response under different soil moisture levels. This experiment was performed using ten independent Aloe vera plants distributed across five moisture percentages (n = 2 plants per level), with each plant assigned exclusively to one moisture condition and one instrumented leaf per plant.

Soil moisture percentage was obtained using the soil-moisture sensor module and set at 5, 34, 38, 80, and 94%. These levels were selected to cover a wide range from very dry to near-saturation conditions, enabling observation of the electrical response under contrasting water-availability states. The selected moisture setpoints were chosen to span operational extremes of the sensor scale (very dry to near saturation) and to bracket intermediate levels where succulent plants may transition between mild water deficit and high-moisture stress responses.

2.3.6. Stress from Continuous Plant Watering

This experiment aimed to evaluate the bioelectrical response of Aloe vera under prolonged water excess (waterlogging-like) conditions. Six independent plants were used (n = 6), each assigned exclusively to this treatment (one instrumented leaf per plant). Soil moisture was maintained at values equal to or greater than 95% throughout the experiment.

Electrical signals were recorded 12 h after initiating continuous watering and subsequently every 24 h, following the same acquisition protocol. Monitoring continued for 7 days or until visible symptoms consistent with water excess stress (e.g., reduced turgor and leaf softening) were observed. The 7-day window was selected as a practical time frame to capture progressive physiological deterioration under sustained near-saturation conditions while maintaining daily measurement continuity without requiring long-term growth-chamber experiments.

2.3.7. Stress Due to pH Level Change

This experiment evaluated the bioelectrical response of Aloe vera under acidic and alkaline pH shifts. Six independent plants were used in total, with three plants assigned to the acidic treatment (aluminum sulfate) and three plants assigned to the alkaline treatment (calcium carbonate); only one leaf per plant was instrumented.

Soil pH was quantified using a direct soil pH meter (BLUE LAB PENSOILPH) with a measurement range of 0.0–14.0 pH, resolution of 0.1 pH, and accuracy of ±0.1 pH at 25 °C, featuring automatic temperature compensation. The device was calibrated prior to measurements using two-point calibration (pH 7.0 and pH 4.0 or pH 10.0 buffer solutions) according to the manufacturer’s specifications. Measurements were performed directly in the pot substrate within the rhizosphere zone at approximately 2 cm depth. For each reported pH value, three readings were taken at different points of the pot and averaged.

Under baseline conditions, the soil/substrate pH was measured and recorded as 6.6 (control). Subsequently, aluminum sulfate was applied as an acidic substrate at concentrations of 0, 5, 10, 15, and 20 g/L. The pH was measured 10 min after each concentration increment and then every 30 min until reaching the target acidic level (pH ≈ 3.6). After the pH stabilized within ±0.1 units for at least 15 min, the electrical signal was recorded using the same acquisition protocol described previously [31,32].

Conversely, calcium carbonate was applied as an alkaline substrate using the same concentration steps (0, 5, 10, 15, and 20 g/L). The pH was measured 10 min after each increment and then every 30 min until reaching the target alkaline level (pH ≈ 12.5). After stabilization within ±0.1 pH units for at least 15 min, the electrical signal response was recorded [33,34].

3. Results and Discussion

In this section, the results and discussion concerning the proposed experiments are presented according to: (1) signal reproducibility, (2) leaf-size considerations, (3) distance between electrodes, (4) stress from different light levels, (5) stress from different percentages of soil moisture, (6) stress from continuous plant watering, and (7) stress due to pH level change.

3.1. Signal Reproducibility

Figure 5 graphically shows six representative baseline recordings of the electrical signal obtained from independent Aloe vera plants under identical control conditions. The measurement window spans 1200 seconds (s). Figure 5A shows the six recordings, which exhibit amplitudes between approximately 200 millivolts (mV) and 220 mV, indicating a consistent baseline voltage level across the plants. Additionally, the waveform morphology is comparable to that reported in the literature (Figure 5B) [35,36], supporting the ability of the proposed system to capture the characteristic electrophysiological pattern of Aloe vera.

Subsequently, a descriptive statistical analysis was performed to examine the distribution of the six baseline recordings. Figure 6 displays the summarized histograms. Each recording shows a central tendency around 200 mV, with variations in the presence and length of right-side tails. These tails suggest the existence of occasional higher-amplitude values across plants, which is an important factor to consider when interpreting the electrophysiological behavior.

Finally, Figure 7 shows the pairwise Jaccard similarity coefficients among the six representative baseline recordings. The coefficients ranged from 0.95 to 0.99, indicating a very high degree of similarity between independent plants measured under identical conditions. This confirms the visual agreement observed in Figure 5 and supports the repeatability of the recorded baseline electrophysiological response under controlled conditions [37].

3.2. Leaf-Size Difference

Figure 8 shows the electrical signal responses of independent Aloe vera plants grouped according to leaf length (8, 12, 15, and 20 cm; n = 4 plants per size category). A baseline control signal (7 cm leaf length, independent plant) is included for comparison.

Differences are observed between the leaf-size groups compared to the reference signal. The mean values of the measured signals are $209.702\pm 31.83$, $208.45\pm 39.05$, $209.07\pm 34.30$, and $209.47\pm 26.21$ mV for 8, 12, 15, and 20 cm leaves, respectively. The control signal exhibited a mean value of 208.76 mV. Although the mean differences are subtle, variations in dispersion and distribution patterns suggest that leaf size may influence the electrophysiological response of Aloe vera.

The standard deviation values indicate noticeable variability within groups. A trend toward reduced dispersion is observed in larger leaves, which may suggest a more stable electrical response as leaf size increases. Smaller leaves (8 and 12 cm) show slightly higher variability, which could be associated with developmental stage differences or structural characteristics. These observations are consistent with reports suggesting that plant developmental stage and physiological state can influence electrical behavior [38,39].

Descriptive statistics were used to generate the box and density plots shown in Figure 9, illustrating the distribution of electrical responses across independent plants in each size group.

The box and density plots reveal distinct distribution patterns among the size categories. The 8 cm and 12 cm groups exhibit longer right-side tails, indicating greater variability in signal amplitude. Although the central tendencies are similar across the groups, differences in dispersion suggest that morphological characteristics such as leaf size may influence the regularity of the electrophysiological response.

To statistically evaluate these differences, the Kruskal–Wallis test was applied. The test yielded a statistic of $H=25.3392$ with a p-value of $4.299\times {10}^{-5}$. These results allow rejection of the null hypothesis of equal medians across groups, indicating that at least one leaf-size category exhibits a statistically significant difference in electrical response compared to the others [30]. This finding supports the hypothesis that morphological variation, such as leaf size, can influence the bioelectrical behavior of Aloe vera.

3.3. Distance Between Electrodes

Figure 10 shows the electrical responses of independent Aloe vera plants measured at different inter-electrode distances (1, 3, 5, 6, and 8 cm; n = 2 plants per distance, one instrumented leaf per plant). Although all the configurations exhibit a baseline voltage level centered close to ∼200 mV, the recordings differ in terms of transient excursions and dispersion. In particular, intermediate distances (3–6 cm) show more pronounced voltage peaks in the time-domain signal, whereas the 1 cm configuration remains more concentrated around the baseline response.

To further assess variability, Figure 11 summarizes the voltage distributions using box plots and density curves. The distributions overlap around ∼200 mV, but clear differences appear in their tails and outlier magnitudes. The annotated extreme values in Figure 11 indicate that 3 cm and 5 cm exhibit the largest high-voltage outliers (max ≈ 350.22 mV and max ≈ 333.33 mV, respectively), while 1 cm shows a narrower high-end range (max ≈ 251.59 mV). The minimum values remain within a similar range across configurations (min ≈ 164.59–188.59 mV), indicating that the main differences arise from the occurrence and magnitude of high-amplitude events rather than systematic shifts in the baseline level.

The density curves (Figure 11B) further support this behavior: the 1 cm configuration shows the most concentrated distribution (sharper peak), consistent with a more stable recording and fewer extreme excursions. Conversely, 3 cm and 5 cm display heavier right tails, consistent with sporadic high-amplitude responses and/or higher susceptibility to electrode–interface effects and measurement noise. While shorter distances favor repeatability, they may reduce sensitivity to stronger transient responses. In contrast, excessively large separations can introduce greater variability due to increased influence of electrode placement and tissue heterogeneity.

Considering the above, the 5 cm configuration was selected as the standard distance for the remainder of this work because it offers a practical compromise: it maintains a baseline comparable to the other distances while capturing representative electrical excursions with clear separability in the distribution (Figure 10 and Figure 11) [40]. This standardization also improves reproducibility across the different stress-condition experiments reported in the following sections.

3.4. Stress from Different Light Levels

Figure 12 shows the electrical responses of independent Aloe vera plants exposed to different light intensity levels (12%, 22%, 32%, 48%, 68%, and 92%; n = 2 plants per level) compared to the control signal. Light percentage values were obtained using the LDR module, where 0% represents total darkness and 100% corresponds to direct sunlight exposure.

According to Figure 12, lower light percentages (12%, 22%, 32%, and 48%) are associated with attenuation of the voltage level compared to the control signal. This reduction may be related to decreased photosynthetic activity under limited light availability. In contrast, higher light levels (68% and 92%) show voltage responses closer to or exceeding the control baseline, suggesting enhanced physiological activity under sufficient illumination [41].

To statistically assess these observations, Figure 13 presents the corresponding box and density plots for the independent plant groups.

The distributions exhibit similar central tendencies across light levels; however, differences appear in dispersion and extreme values. The 68% group shows maximum and minimum values comparable to the control signal, while the 92% group presents slightly higher extreme values. The 32% and 48% levels display lower maximum voltages relative to the control conditions. These patterns suggest that light intensity modulates the variability and amplitude of the electrical response, consistent with the photosensitive behavior reported in plants [20].

Since the distributions were not normal, non-parametric statistical analysis was applied. The Kruskal–Wallis test yielded a statistic of $H=3833.81$ with $p<0.001$, indicating statistically significant differences among at least some light-intensity groups. The low p-value suggests that the observed variations in median electrical response are unlikely to occur by chance.

In summary, the statistical analysis confirms that light intensity significantly influences the electrical response of Aloe vera. These findings support the interpretation that changes in illumination conditions modulate the plant’s electrophysiological behavior.

3.5. Stress from Different Percentages of Soil Moisture

Figure 14 displays the electrical responses of independent Aloe vera plants exposed to different soil moisture percentages (5%, 34%, 38%, 80%, and 94%; n = 2 plants per level) compared to the control signal.

A broadly similar baseline behavior is observed among the groups; however, variations in amplitude and waveform morphology are evident across moisture levels. Compared to the control signal, the 94% humidity condition shows reduced amplitude and a widening of the signal distribution, suggesting altered physiological activity under near-saturation conditions. Intermediate moisture levels, such as 38% and 80%, exhibit more pronounced deviations, potentially reflecting thresholds of water-related stress. At lower moisture levels (5% and 34%), the signals resemble the control condition, although the 5% group shows slightly higher-amplitude excursions, indicating increased variability in electrical response.

To further evaluate these differences, box and density plots were generated (Figure 15).

The median of the control signal is slightly higher than those observed at 38%, 80%, and 94% moisture levels but lower than the medians at 5% and 34%. Considerable overlap exists between the control, 38%, 80%, and 94% distributions, indicating partially similar response patterns. In contrast, the 5% and 34% groups show higher averages and greater dispersion, suggesting that lower soil moisture levels are associated with increased variability in the electrical response [42].

The non-parametric Kruskal–Wallis test yielded a statistic of $H=137.7$ with a p-value of $5.50183\times {10}^{-28}$. Since $p<0.05$, the null hypothesis of equal medians across groups is rejected, confirming statistically significant differences in electrical responses among at least some moisture conditions. These results indicate that soil moisture level influences the electrophysiological behavior of Aloe vera, with both deficit and excess conditions associated with measurable changes in signal characteristics.

3.6. Stress from Continuous Plant Watering

Figure 16 shows the electrical responses of independent Aloe vera plants (n = 6) subjected to continuous excess watering over a seven-day period. Each plant was monitored longitudinally, and the electrical signal was recorded at defined time intervals during the experiment.

Progressive attenuation and distortion of the signal is observed as the days advance. The behavior resembles that observed under high soil moisture percentages, with a gradual reduction in signal amplitude over time. This pattern may be associated with physiological adjustments under prolonged water excess conditions, potentially involving reduced transpiration and altered cellular activity [43].

To further characterize the temporal evolution, box and density plots were generated (Figure 17).

The plots reveal a progressive decrease in variability and amplitude across the seven-day period. Initial recordings show wider distributions and greater dispersion, which gradually stabilize toward lower-amplitude responses. These visual trends suggest a systematic modification of the electrophysiological behavior under sustained water excess.

The Kruskal–Wallis test yielded a statistic of $H=1382.67$ with a highly significant result ($p<{10}^{-300}$), indicating that the electrical response changes significantly over the seven-day excess-watering period. These findings support the interpretation that prolonged water excess produces measurable and statistically significant alterations in the electrical behavior of Aloe vera.

3.7. Stress Due to pH Level Change

Figure 18 displays the electrical responses of independent Aloe vera plants subjected to controlled pH variation using aluminum sulfate (acidic treatment, n = 3 plants) and calcium carbonate (alkaline treatment, n = 3 plants). The baseline pH under control conditions was 6.6. Sequential concentration increments (0, 5, 10, 15, and 20 g/L) were applied to progressively modify soil pH.

In the acidic treatment (Figure 18A), the first concentration step reduced pH to approximately 6.3, with no marked deviation from the baseline behavior. As the concentration increased and the pH approached approximately 3.6, the signal exhibited distortion and elongation patterns, particularly at 20 g/L. These changes may reflect physiological stress associated with acidic soil conditions and altered root functionality [44].

In the alkaline treatment (Figure 18B), progressive increases in pH up to approximately 12.5 were associated with observable waveform deformation and variability changes. Highly alkaline conditions are known to reduce nutrient availability (e.g., iron, manganese, zinc, and phosphorus), potentially affecting plant physiological processes [44].

To further examine the data distribution, box and density plots were generated (Figure 19 and Figure 20).

Figure 19 shows that, as aluminum sulfate concentration increases (and pH decreases), greater variability in electrical response is observed. The Kruskal–Wallis test yielded approximately $H=203.47$ with a p-value of $6.74\times {10}^{-43}$, indicating statistically significant differences among the concentration levels. These results support the interpretation of a dose-dependent electrophysiological response under acidic stress.

Figure 20 indicates variability in response under alkaline treatment; however, the trend appears to be less systematic compared to the acidic case. The presence of outliers and dispersion patterns suggests complex electrophysiological adaptation under highly alkaline conditions. Overall, both acidic and alkaline deviations from near-neutral pH (6.6) produced measurable changes in the electrical signal of Aloe vera.

These findings confirm that controlled pH shifts significantly influence plant electrophysiological behavior. The statistical and descriptive analyses collectively support the conclusion that variations in soil chemistry represent a relevant modulating factor of electrical activity in Aloe vera [45,46,47,48,49].

Although statistically significant differences were observed across the treatments, the relatively limited number of biological replicates per condition represents an inherent constraint of the present study. Accordingly, the findings should be interpreted as controlled proof-of-concept evidence rather than broad ecological generalization. Future work should incorporate larger sample sizes, temporal replication, and multi-season validation to further strengthen statistical robustness and external validity.

Overall, the results demonstrate that the electrical activity of Aloe vera is sensitive to controlled variations in abiotic factors, including light intensity, soil moisture, prolonged water excess, and pH shifts. The consistent baseline reproducibility, together with statistically significant stress-induced deviations, supports the feasibility of using low-cost acquisition systems for plant-based environmental monitoring. Collectively, these findings contribute to the methodological standardization of plant electrophysiology and establish a reproducible experimental framework that may facilitate future integration with advanced signal-processing and data-driven analytical approaches.

4. Conclusions

This study presented a controlled experimental framework to characterize the bioelectrical activity of Aloe vera using a low-cost Arduino-based acquisition system. The baseline measurements showed high repeatability under standardized conditions, supporting the reliability of the proposed setup for subsequent stress experiments. The results further indicate that measurement factors such as leaf size and electrode spacing can modulate the recorded signal, highlighting the importance of methodological standardization in plant electrophysiology.

Across the abiotic treatments, statistically significant differences were observed under changes in light intensity, soil moisture, prolonged water excess, and substrate pH, suggesting that Aloe vera electrical activity is sensitive to multiple stress-related perturbations. These findings support the feasibility of using succulent plants as practical bioelectrical sensing platforms for controlled monitoring scenarios, while also emphasizing that broader generalization requires larger biological replication and multi-season validation.

Overall, the proposed protocol and results provide a reproducible baseline for future work aiming to integrate plant electrical signals with advanced signal-processing and data-driven models for environmental monitoring applications. Future work will specifically evaluate the performance of Aloe vera biodosimetry for in situ detection of heavy-metal contamination and other relevant soil pollutants under field-like conditions, extending the controlled stress-characterization framework reported here.