Physiological Effects of Mercury on Handroanthus impetiginosus (Ipê Roxo) Plants

Abstract

Mercury (Hg) poses significant risks to human health, the environment, and plant physiology, with its effects influenced by chemical form, concentration, exposure route, and organism vulnerability. This study evaluates the physiological impacts of Hg on Handroanthus impetiginosus (Ipê Roxo) seedlings through SPAD index measurements, chlorophyll fluorescence analysis, and Hg quantification in plant tissues. Four-month-old seedlings were exposed for eight days to distilled water containing Hg at 0, 1, 3, 5, and 7 mg L⁻¹. The SPAD index decreased by 28.17% at 3, 5, and 7 mg L⁻¹, indicating reduced photosynthetic capacity. Chlorophyll a fluorescence analysis revealed a 50.58% decline in maximum efficiency (Fv/Fm) and a 58.33% reduction in quantum yield (ΦPSII) at 7 mg L⁻¹, along with an 83.04% increase in non-photochemical quenching (qn), suggesting oxidative stress and PSII damage. Transpiration decreased by 26.7% at 1 mg L⁻¹ and by 55% at 3, 5, and 7 mg L⁻¹, correlating with Hg levels and leaf senescence. Absorption, translocation, bioconcentration, and bioaccumulation factors varied among treatments. Hg accumulated mainly in stems (40.23 μg g⁻¹), followed by roots (0.77 μg g⁻¹) and leaves (2.69 μg g⁻¹), with limited translocation to leaves. These findings highlight Hg’s harmful effects on H. impetiginosus, an ecologically and commercially valuable species, addressing a gap in research on its Hg tolerance and phytoremediation potential.

1. Introduction

Mercury (Hg) is a toxic, persistent, and mobile contaminant whose volatility contributes to its wide dispersion in the environment, and it is considered one of the pollutants of greatest concern and toxicity due to its long-range atmospheric transport, its environmental persistence, and its capacity for bioaccumulation in the ecosystem [1,2]. Its main anthropogenic sources include coal burning, cement production, metal smelting, the chlor-alkali industry, waste disposal, and artisanal gold mining [3,4].

The increase in Hg emissions due to human activities and the increasing deposition of this metal in the soil have generated serious pollution problems [5]. This environmental compartment plays a vital role in the global Hg cycle, connecting the atmosphere and water. In addition to being a receptor, soil also functions as a source of mercury, receiving it from the environment and redistributing it to the atmosphere, water, and plants [6]. Hg contamination can inhibit crop growth and even cause plant death, posing a risk to human health due to bioaccumulation [7].

Hg interferes with chlorophyll (Chl) synthesis, photosynthesis, water, and nutrient transport, highlighting its harmful effect on plant physiology, especially in contaminated environments [8]. Its toxicity reduces photosynthetic pigments, such as Chl and carotenoids, compromises photosystem II (PSII) functioning, decreases quantum efficiency, increases oxidative stress, and directly impacts plant growth and development, especially in contaminated environments [9].

In the roots, Hg is predominantly absorbed and accumulated, causing metabolic changes, while its limited translocation to the aerial parts suggests that the roots function as a partial barrier against more severe leaf and stem damage [10]. However, the accumulation of Hg in the roots can interfere with the transport of water and nutrients, compromising water homeostasis, affecting fundamental metabolic processes, and reducing transpiration, which directly impacts the plant’s ability to sustain its metabolism under chemical stress [11,12].

Hg can induce important biochemical changes, such as increased antioxidant enzyme activity in response to the accumulation of reactive oxygen species generated by oxidative stress [13]. These oxidative processes, in addition to compromising metabolic integrity, also affect the mitotic behavior of plant cells and the functioning of organelles, such as chloroplasts, contributing to the reduction in biomass and growth inhibition, even in short-term exposures [14,15].

Changes in leaf color, often associated with the loss of photosynthetic pigments, together with the reduction in Chl indices and alterations in Chl a fluorescence, indicate Hg toxicity and reflect the impairment of the photosynthetic capacity essential for plant growth [16,17,18]. In addition to compromising the functioning of photosystem II and increasing oxidative stress, Hg causes growth retardation, alterations in cellular metabolism, and interferes in biochemical components and metabolic pathways in plants that accumulate the contaminant [19].

Mercury toxicity suppresses Chl synthesis in leaves, increases oxidizing enzyme activity, and negatively impacts mitotic behavior and metabolite leakage [20,21]. These symptoms, combined with the decrease in transpiration and the accumulation of Hg in the roots, highlight the vulnerability of plants to mercury, especially in environments where its concentration is high [22].

In this context, hydroponic experiments allow researchers to isolate and analyze the physiological effects of Hg, such as changes in nutrient absorption and internal transport, which are essential to unravel metabolic responses under controlled conditions before dealing with the complex variables of soil culture media [23,24]. Like other heavy metals, mercury cannot be degraded in ecosystems, which makes remediation based on removal or immobilization processes a key approach [25].

This work aims to understand the physiological effects of mercury on seedlings of Handroanthus impetiginosus, a species with phytoremediation potential. The analysis of these effects includes the evaluation of metabolic alterations, the impact on Hg uptake, translocation, and the physiological and physiological responses of the plant to chemical stress. These investigations are fundamental to understanding the mechanisms of tolerance and adaptation of plants to mercury, contributing to more effective strategies for environmental remediation.

2. Materials and Methods

2.1. Plant Material and Growing Conditions

Seedlings of H. impetiginosus, at four months old, were cultivated in a greenhouse at the Plant Production sector of the Federal University of Mato Grosso (UFMT), Sinop Campus, under controlled conditions (temperature: 25.5 °C, relative humidity: 63.3%, photoperiod: 12/12 h light/dark, and regular irrigation) to ensure uniform development before the experiment. The seedlings were selected in triplicates, ensuring uniformity in size and biomass, providing homogeneity to the experiment, and allowing for an accurate evaluation of the effects of Hg on plant development.

H. impetiginosus seedlings were produced from selected seeds of healthy mother trees with desirable morphological characteristics to obtain high-quality seedlings with minimal phenotypic and genotypic variation. The collected seeds were sown in plastic trays filled with commercial substrate and placed in a greenhouse (the same environment where the experiment was conducted).

They were irrigated twice daily to prevent excess or water deficit. After seedling establishment (complete expansion of the first pair of true leaves), the seedlings were transplanted into 5 L plastic bags. These containers were filled with a substrate composed of forest soil and commercial substrate in a 2:1 ratio, respectively. For this composite substrate, 40, 380, and 80 g of N, P₂O₅, and K₂O (in the forms of urea, single superphosphate, and potassium chloride) were mixed per cubic meter of substrate. The seedlings were irrigated by sprinkler irrigation. These steps were carried out following the nutritional recommendations of Silva et al. [26].

The choice of this species was due to its ecological relevance and potential in environmental restoration projects, while the use of plants at the seedling phase was strategic due to the favorable phenophase for transplanting and establishment in the field. The experiment lasted eight days to assess the early physiological effects of mercury exposure, as short-term responses can indicate initial toxicity before long-term acclimation or irreversible damage occurs.

The selection of homogeneous seedlings in triplicates is a consolidated practice in scientific experiments, as it reduces the variability between samples and increases the reliability of the results [27,28]. This strategy facilitates the identification of differences caused by the treatments applied. During the experiment, variations in the greenhouse microclimate, such as temperature and relative humidity, were monitored every 30 min with a CEM DT-171 Datalogger thermo-hygrometer (Instrutemp, São Paulo, SP, Brazil), ensuring the control of environmental conditions.

2.2. Contamination and Transplantation

The selected seedlings were removed from the cultivation containers, cleaned, and rinsed before being transferred to pots previously prepared with the contaminant solution. Each pot, with a capacity of 2000 cm³, was filled with 1500 mL of distilled water and subjected to different concentrations of Hg (0, 1, 3, 5, and 7 mg L⁻¹). The selected Hg concentrations represent a contamination gradient, from uncontaminated conditions to levels that surpass the thresholds set by international regulatory agencies for agricultural soils and potable water. This approach allows researchers to evaluate the physiological effects of Hg exposure under conditions that reflect both environmentally relevant and extreme contamination scenarios, contributing to a better understanding of plant tolerance and phytoremediation potential.

For the insertion of the seedlings, small openings were made in the lids of the pots, which were later sealed to minimize evaporation, allowing only the transpiration of the plants. In this study, the term ‘solution’ refers to the contaminant solution used in the experiment.

2.3. SPAD Index

The Chl content was measured daily, between 24 February and 3 March 2024, using the SPAD index on H. impetiginosus leaves. The measurements were performed on a pair of expanded leaves in the middle-third of the plant, which were selected and kept constant throughout the experiment, always between 7 am and 9 am [29,30,31]. The experiment followed a completely randomized design with three replications for each level of Hg contamination. Differences between treatments over time were evaluated by analysis of variance (ANOVA), and, when significant, the means were compared using the Scott–Knott test at a 5% probability. The results were presented based on the days after transplantation, highlighting the variation in the SPAD index as a function of time and mercury concentrations.

2.4. Fluorescence

Chlorophyll a fluorescence in H. impetiginosus leaves was measured with an OS5p OptiSciences Fluorpen FP-100 light-modulated fluorometer (Opti-Sciences Ltda, Hudson City, NY, USA), following the Fv/Fm (dark-adapted state) and Y(II) (light-adapted state) protocols. Simultaneously, solar irradiance was recorded with an Apogee MP-200 handheld pyranometer (Apogee Instruments Inc., Logan City, UT, USA). During the eight days of the experiment, the evaluations were performed daily on the second or third adult leaf from the apical bud in plants subjected to 0, 1, 3, 5, and 7 mg L⁻¹ of Hg. The Fv/Fm readings evaluated the photochemical performance of PSII after nocturnal regeneration, with specific protocols for dark and light adaptive states [32].

The measured parameters included Fv/Fm (maximum quantum efficiency of PSII), ΦPSII (effective quantum yield), ETR (electron transport rate), NPQ (non-photochemical quenching), and qL (light quenching coefficient). The Fv/Fm ratio was calculated from the maximum and minimum fluorescence in the dark-adapted state, while ΦPSII evaluated the efficiency of light absorbed by the PSII. The ETR reflected the photosynthetic capacity, while NPQ and qL analyzed, respectively, the energy dissipation in non-photochemical forms and the proportion of open reaction centers in the PSII [33,34,35].

2.5. Colorimetry

Colorimetry is a quantitative method widely applied in color analysis, based on the parameters of luminosity, hue, and saturation, allowing for the objective and non-destructive measurement of chromatic properties. The variables involved are L*, a*, b*, C*, and h*;. Brightness (L*) defines the grayscale between white (100) and black (0). The hue is represented by the colors red (+a*), green (−a*), yellow (+b*), and blue (−b*), arranged in a circle. The hue angle (h*) expresses the hue, while the saturation (C*) measures the purity of the color, ranging from the center gray point to the pure color at the end of the circle. The farther away from the axis, the more saturated the color. Saturation (C*) ranges from 0 to 60, with no unit of measurement, and both parameters derive from the values of a* and b*.

Leaf colorimetry was performed using a portable digital Chl level analyzer, model TYS-B (U-Therm International (H.K.) Limited, Hong Kong, China), through a non-destructive method. For each plant, the leaves were analyzed directly in the field, without the need for collection, allowing the immediate acquisition of data and enabling the evaluation of the nitrogen requirement in the plants based on the measured Chl content [36]. Nitrogen availability is crucial for chlorophyll synthesis and photosynthetic efficiency. In this protocol, N-related parameters were considered to ensure an accurate assessment of photosynthetic pigments and plant responses to mercury stress.

2.6. Morphometric Analysis

Throughout the days of the experiment, any morphological changes were monitored. After the eighth day of the experiment, the pots were dismantled, and the seedlings were carefully removed. The seedlings were washed and dried before the collection of morphological data from each sample. The height of the plant was measured from the stem to the apical bud using a millimeter ruler. The diameter of the stem was determined with a digital caliper, while the number of leaves was counted visually. The plants were then separated into roots, stems, and leaves. Fresh mass (g) was measured and, after drying the plant material in an oven with forced air circulation at 65 °C until constant weight was reached, the dry mass (g) was recorded.

2.7. Quantification of Chlorophyll and Carotenoids

To quantify the contents of Chl a, Chl b, Chl a+b, and total carotenoids in leaves of H. impetiginosus, exposed to five treatments in triplicate (totaling 15 samples), the methodology described by Lichtenthaler [37] was followed, with adaptations. About 0.1 g of leaves (without midribs) were macerated in 80% acetone, and the volume was adjusted to 10 mL. The samples were centrifuged, and the absorbances were read at 470, 645, and 663 nm, using 80% acetone a blank control. The contents of total Chl, Chl a, Chl b, and total carotenoids were calculated using the following equations:

$$\mathrm{C}\mathrm{h}\mathrm{l} \mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}=7.15\ast A_{663}+18.71\ast A_{645}$$

(1)

$$\mathrm{C}\mathrm{h}\mathrm{l} a=12.25\ast A_{663}-2.79\ast A_{645}$$

(2)

$$\mathrm{C}\mathrm{h}\mathrm{l} b=21.50\ast A_{663}-5.10\ast A_{645}$$

(3)

$$\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{C}\mathrm{a}\mathrm{r}\mathrm{o}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{o}\mathrm{i}\mathrm{d}\mathrm{s}={\displaystyle \frac{1000\ast A_{470}-1.82\ast \mathrm{C}\mathrm{h}\mathrm{l} a-85.02\ast \mathrm{C}\mathrm{h}\mathrm{l} b}{198}}$$

(4)

2.8. Transpiration

The transpiration of the seedlings was measured at the end of the eighth day of the experiment, using a standardized approach to ensure the accuracy of the measurements. Each seedling was removed from the container containing the treated solution, and a 30 s interval was observed to allow possible water droplets to return to the container. After this period, the remaining volume of the solution in the container was measured with the aid of a high-precision graduated beaker [38]. To minimize experimental variations, all measurements were performed by the same person, ensuring consistency in the procedure. This method allowed researchers to determine precisely the amount of water lost by transpiration in each treatment, directly correlating the measured volumes with the impact of the different Hg concentrations on the physiological process of the seedlings.

2.9. Hg Concentration in Tissues

The analysis of mercury (Hg) concentrations in plant tissues (roots, stems, and leaves) followed the methodology described by Akagi and Nishimura [39]. About 0.3 g of dry material was digested in a mixture of HNO₃ (65%) and HClO₄ (70%) in a 1:1 ratio, with the addition of 5 mL of H₂SO₄ (98%). Digestion occurred in a block digester at 230 °C for 30 min. After cooling, the extracts were diluted in 25 mL volumetric flasks with distilled water. To avoid contamination, all glassware was previously decontaminated with 10% HNO₃. The total mercury content (THg) was analyzed using an Agilent 240FS AA atomic absorption spectrometer (Agilent Technologies, Santa Clara, CA, USA), equipped with VGA 77 vapor generation accessory (Agilent Technologies, Santa Clara, CA, USA). The standard solution used for the calibration curve was traceable to NIST (National Institute of Standards and Technology), provided by the Specsol brand.

2.10. Method Validation

The validation of the analytical method was conducted following the approach described by Neto et al. [40]. The relative accuracy, with a deviation of ±5.8%, was evaluated for the concentration of total mercury (THg) in leaves and soil using samples fortified at three different concentration levels, with seven replicates each. The accuracy, verified by the recovery of Hg in the fortified samples, ranged from 95% to 110%. The detection limit, calculated as the mean of 10 blanks plus three times the standard deviation, was established at 0.08 μg L⁻¹ in the sample solution, equivalent to 6.7 μg kg⁻¹ in the solid sample. The limit of quantification was defined as the mean of 10 blanks plus ten times the standard deviation, resulting in 0.16 μg L⁻¹ in the sample solution or 13.3 μg kg⁻¹ in the solid sample.

2.11. Indices, Factors, and Trends of Accumulation

The concentrations and accumulation trends were estimated using the translocation factor (TF), bioconcentration factor (BCF), bioaccumulation factor (BAF), and absorption index (AI), which were calculated from the mercury concentrations determined by the chemical analysis of the samples. TF was calculated as the ratio of Hg concentration in the aerial to root parts (Equation (5)) [41]. BCF was determined as the ratio of the concentration of metal in the roots to its concentration in the solution (Equation (6)) [42]. BAF was obtained by calculating the ratio of the concentration of metal in the shoot to the concentration in the solution (Equation (7)) [43]. AI was calculated as the ratio of the concentration of Hg in the plant to the dry biomass (mg kg⁻¹), where “[Hg] biomass” refers to the concentration of Hg in the dry biomass of the sample, and “[m] plant” is the dry biomass of the sample expressed in grams (Equation (8)) [44]. The total contents of TF, BCF, BAF, and AI were calculated using the following equations:

$$\mathrm{T}\mathrm{F}={\displaystyle \frac{\left[\mathrm{H}\mathrm{g}\right]\mathrm{a}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{a}\mathrm{l}}{\left[\mathrm{H}\mathrm{g}\right]\mathrm{r}\mathrm{o}\mathrm{o}\mathrm{t}}}$$

(5)

$$\mathrm{B}\mathrm{C}\mathrm{F}={\displaystyle \frac{\left[\mathrm{H}\mathrm{g}\right]\mathrm{r}\mathrm{o}\mathrm{o}\mathrm{t}}{\left[\mathrm{H}\mathrm{g}\right]\mathrm{s}\mathrm{u}\mathrm{b}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e}}}$$

(6)

$$\mathrm{B}\mathrm{A}\mathrm{F}={\displaystyle \frac{\left[\mathrm{H}\mathrm{g}\right]\mathrm{a}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{a}\mathrm{l}}{\left[\mathrm{H}\mathrm{g}\right]\mathrm{s}\mathrm{u}\mathrm{b}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e}}}$$

(7)

$$\mathrm{A}\mathrm{I}={\displaystyle \frac{\left[\mathrm{H}\mathrm{g}\right]\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{a}\mathrm{s}\mathrm{s}}{\left[\mathrm{m}\right]\mathrm{p}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{t}}}$$

(8)

2.12. Statistical Analysis

Statistical analysis was performed using R (version 4.4.0, R Foundation for Statistical Computing, Vienna, Austria) and RStudio (version 2024.4.2.764). The following packages were used: agricolae (1.3-7), coin (1.4.3), dplyr (1.1.4), flextable (0.9.6), gapminder (1.0.0), ggplot2 (3.5.1), gridExtra (2.3), gt (0.10.1), multcompView (0.1-10), officer (0.6.6), Scott–Knott (1.3.2), tidyverse (2.0.0), tidyr (1.3.1), VennDiagram (1.7.3), and writexl (1.5.0). The assumptions of normality, evaluated by the Shapiro–Wilk test, and homoscedasticity were analyzed. For indices that did not initially meet the assumption of normality, the inverse (hyperbolic) transformation of the data was applied. For data that met both assumptions, analysis of variance (ANOVA) was applied to identify significant differences between the means (p < 0.05). When significant differences were found, the means were compared using the Scott–Knott test. Pearson’s correlation was used to determine the relationship between the variables analyzed. All statistical tests were performed in triplicate.

3. Results

3.1. Morphological Analysis

Based on the morphometric analysis of the plants used in this study, homogeneity was verified in the dimensions of height, stem diameter, number of leaves, length and width (longitudinal) of the leaves, as well as in the leaves evaluated according to the SPAD index. All measured dimensions are shown in Figure 1. Pairs of cotyledon leaves were identified in repeats 3 of the 0 mg L⁻¹ treatment, 2 of the 1 mg L⁻¹, 3 of the 3 mg L⁻¹, and 1 of the 5 mg L⁻¹ treatment. No cotyledons were identified in the 7 mg L⁻¹ treatment. The visual changes in the leaves throughout the experiment can be seen in Figure 2.

The ANOVA results confirm that the selected plants are statistically similar. For height, no difference was observed between the treatments (ANOVA, F = 0.076, p = 0.788). The diameter also did not show differences (ANOVA, F = 0.195, p = 0.666). The number of leaves was equally uniform among the plants (ANOVA, F = 1.627, p = 0.224). Regarding leaf length, the data indicated uniformity (ANOVA, F = 0.162, p = 0.694). The longitudinal analysis of the leaf reinforced this similarity (ANOVA, F = 0.056, p = 0.816). Finally, the SPAD index also did not show significant differences (ANOVA, F = 1.218, p = 0.290). These values confirm that the selected plants had similar stages of development.

3.2. SPAD Index

Measurements of Chl content in a pair of leaves of each of the plants were recorded daily between 24 February and 3 March 2024 (from the 1st to the 8th day after transplanting) using the Konica Minolta Chlorophyll Meter, model SPAD 502 Plus (Konica Minolta Sensing Americas, Inc., São Paulo, Brazil). All repetitions of the SPAD index measurements occurred on the same sheets throughout the study period, always in the morning. The values obtained are shown in

Table 1. Chl a content based on the SPAD index in purple Ipê seedlings, over the 8 days under increasing Hg levels.

SPAD Index
[Hg] (mg L−1)	Day 01	Day 02	Day 03	Day 04	Day 05	Day 06	Day 07	Day 08	Reduction
0	33.98 Aa	35.27 Aa	31.58 Ba	29.73 Ca	29.75 Ca	27.65 Da	27.93 Da	26.48 Da	21.02%
1	30.15 Aa	29.35 Ab	27.20 Ab	25.95 Bb	25.52 Bb	23.23 Bb	22.92 Bb	22.97 Ba	16.55%
3	30.13 Aa	29.42 Ab	26.35 Bb	24.48 Bb	22.62 Cb	20.65 Cb	18.70 Db	18.13 Db	38.15%
5	31.78 Aa	32.67 Aa	28.95 Aa	27.43 Aa	27.33 Aa	24.80 Ba	22.70 Bb	19.87 Bb	24.21%
7	29.17 Aa	28.77 Ab	26.45 Ab	24.90 Bb	24.85 Bb	22.07 Bb	20.35 Bb	17.30 Bb	22.17%

Different capital letters in the lines indicate a statistical difference according to the Scott–Knott test (p < 0.05); Different lowercase letters in the columns indicate statistical difference by the Scott–Knott test (p < 0.05). Equal letters do not differ from each other significantly.

.

The analysis of variance showed significant differences in the SPAD index both among all the values measured (ANOVA, F = 32.01, p < 0.01) and in the daily readings throughout the experiment, with the exception, as expected, of the measurement performed on the first day of index reading.

Thus, we obtained day 02 (ANOVA, F = 4.381, p = 0.008), day 03 (ANOVA, F = 3.712, p = 0.017), day 04 (ANOVA, F = 3.181, p = 0.031), day 05 (ANOVA, F = 5.978, p = 0.002), day 06 (ANOVA, F = 4.609, p = 0.006), day 07 (ANOVA, F = 4.614, p = 0.006), and day 08 (ANOVA, F = 5.884, p = 0.002). However, SPAD 01 did not present significant differences between the treatments (ANOVA, F = 2.007, p = 0.124). A strong negative correlation was observed between Hg concentration and the SPAD index on day 08 (r = −0.842), while, on day 02, the correlation was moderate (r = −0.475). These results indicate that the increase in concentration is associated with a significant reduction in Chl levels through the SPAD index, especially at 08 days of evaluation.

3.3. Fluorescence

To evaluate the fluorescence in H. impetiginosus leaves and their efficiency in the absorption and use of sunlight for photosynthesis, the following parameters were recorded: Fv/Fm (maximum quantum efficiency of PSII), ΦPSII (effective quantum yield of PSII), ETR (electron transport rate), Fvs/Fms (maximum efficiency of PSII in light state), NPQ (non-photosynthetic quenching), qp (photochemical quenching coefficient) qn (non-photochemical quenching), and qL (light quenching coefficient).

According to the results presented in

Table 2. Fluorescence parameters of Chl a (Fv/Fm, Y (ΦPSII), Fvs/Fms, qp (Fqs/Fvs), qn (nF/Fv), ETR, NPQ, qL) in H. impetiginosus seedlings under increasing levels of mercury.

Fluorescence Parameters                                                                  Treatments
	Day	0 mg L−1	1 mg L−1	3 mg L−1	5 mg L−1	7 mg L−1
ETR	1	26.58 ± 3.90 Aa	28.19 ± 3.93 Aa	28.47 ± 7.53 Aa	33.9 ± 3.35 Aa	35.24 ± 4.67 Aa
	2	38.16 ± 3.92 Aa	33.9 ± 5.23 Aa	32.68 ± 8.44 Aa	42.13 ± 6.03 Aa	35.56 ± 7.86 Aa
	3	28.98 ± 12.97 Aa	25 ± 10.99 Aa	24.88 ± 12.87 Aa	30.52 ± 5.49 Aa	30.95 ± 9.58 Aa
	4	16.49 ± 1.12 Ab	9.53 ± 3.04 Ab	20.32 ± 14.59 Ab	19.14 ± 1.44 Ab	15.95 ± 5.14 Ab
	5	35.36 ± 6.60 Aa	26.42 ± 2.93 Aa	26.46 ± 14.62 Aa	30.16 ± 3.62 Aa	32.72 ± 8.10 Aa
	6	24.69 ± 9.58 Ab	20.48 ± 2.90 Ab	19.84 ± 10.90 Ab	19.57 ± 2.73 Ab	18.98 ± 0.30 Ab
	7	18.51 ± 11.53 Ab	18.7 ± 8.08 Ab	13.58 ± 8.86 Ab	12.21 ± 0.55 Ab	14.02 ± 0.89 Ab
	8	20.44 ± 6.17 Ab	20.12 ± 8.45 Ab	17.92 ± 5.98 Ab	9.57 ± 6.10 Bb	7.09 ± 2.30 Bb
Fv/Fm	1	0.79 ± 0.01 Aa	0.79 ± 0.03 Aa	0.80 ± 0.01 Aa	0.81 ± 0.00 Aa	0.80 ± 0.02 Aa
	2	0.76 ± 0.01 Aa	0.72 ± 0.02 Ba	0.74 ± 0.02 Aa	0.76 ± 0.02 Aa	0.76 ± 0.03 Aa
	3	0.65 ± 0.08 Aa	0.49 ± 0.19 Ab	0.55 ± 0.18 Aa	0.65 ± 0.02 Aa	0.59 ± 0.14 Aa
	4	0.71 ± 0.04 Ab	0.58 ± 0.14 Ab	0.67 ± 0.10 Aa	0.74 ± 0.01 Aa	0.71 ± 0.07 Aa
	5	0.67 ± 0.04 Ab	0.56 ± 0.11 Ab	0.63 ± 0.06 Aa	0.68 ± 0.04 Aa	0.65 ± 0.08 Aa
	6	0.61 ± 0.09 Ab	0.59 ± 0.11 Ac	0.62 ± 0.07 Aa	0.68 ± 0.05 Aa	0.66 ± 0.06 Aa
	7	0.53 ± 0.11 Ac	0.51 ± 0.15 Ac	0.57 ± 0.10 Aa	0.54 ± 0.11 Aa	0.54 ± 0.10 Aa
	8	0.57 ± 0.08 Ac	0.52 ± 0.15 Ac	0.58 ± 0.09 Aa	0.43 ± 0.07 Aa	0.44 ± 0.10 Aa
FVs/Fms	1	0.60 ± 0.06 Aa	0.59 ± 0.02 Aa	0.67 ± 0.02 Aa	0.63 ± 0.05 Aa	0.57 ± 0.10 Aa
	2	0.48 ± 0.09 Aa	0.44 ± 0.06 Ab	0.40 ± 0.06 Ab	0.49 ± 0.07 Aa	0.49 ± 0.03 Aa
	3	0.39 ± 0.10 Ab	0.26 ± 0.07 Ab	0.32 ± 0.11 Ac	0.41 ± 0.09 Ab	0.38 ± 0.07 Ab
	4	0.55 ± 0.08 Aa	0.46 ± 0.12 Aa	0.56 ± 0.10 Aa	0.61 ± 0.05 Aa	0.59 ± 0.07 Aa
	5	0.40 ± 0.07 Ab	0.31 ± 0.07 Ab	0.28 ± 0.05 Ac	0.34 ± 0.04 Ab	0.33 ± 0.08 Ab
	6	0.33 ± 0.09 Ab	0.29 ± 0.06 Ab	0.28 ± 0.08 Ac	0.33 ± 0.04 Ab	0.31 ± 0.06 Ab
	7	0.30 ± 0.10 Ab	0.27 ± 0.08 Ab	0.25 ± 0.08 Ac	0.22 ± 0.03 Ab	0.21 ± 0.02 Ab
	8	0.30 ± 0.11 Ab	0.27 ± 0.09 Ab	0.23 ± 0.09 Ac	0.18 ± 0.04 Ab	0.19 ± 0.01 Ab
NPQ	1	1.54 ± 0.61 Aa	1.68 ± 0.15 Ab	0.93 ± 0.10 Ab	1.77 ± 0.83 Aa	2.09 ± 0.95 Ab
	2	2.78 ± 1.23 Aa	2.47 ± 1.20 Aa	3.42 ± 0.75 Aa	2.52 ± 0.75 Aa	2.31 ± 0.47 Aa
	3	2.09 ± 0.55 Aa	1.92 ± 1.17 Ab	2.04 ± 0.73 Aa	1.88 ± 0.94 Aa	1.7 ± 0.88 Ab
	4	1.07 ± 0.36 Aa	0.75 ± 0.46 Ab	0.64 ± 0.33 Ab	0.82 ± 0.35 Aa	0.78 ± 0.30 Ab
	5	2.26 ± 0.51 Aa	2.12 ± 0.85 Aa	3.30 ± 0.03 Aa	3.36 ± 0.93 Aa	3.23 ± 1.57 Aa
	6	2.33 ± 0.38 Aa	2.71 ± 0.79 Aa	3.42 ± 0.65 Aa	3.68 ± 0.65 Aa	3.45 ± 0.73 Aa
	7	1.95 ± 0.48 Aa	2.02 ± 0.84 Aa	3.22 ± 0.14 Aa	3.36 ± 1.10 Aa	3.57 ± 1.38 Aa
	8	2.28 ± 1.02 Aa	2.33 ± 1.19 Aa	4.01 ± 1.22 Aa	2.88 ± 0.27 Aa	2.76 ± 1.42 Aa
qL	1	0.09 ± 0.05 Ab	0.09 ± 0.02 Ab	0.06 ± 0.03 Ac	0.10 ± 0.03 Aa	0.13 ± 0.05 Aa
	2	0.23 ± 0.09 Aa	0.22 ± 0.03 Aa	0.23 ± 0.03 Ab	0.22 ± 0.03 Aa	0.18 ± 0.02 Aa
	3	0.20 ± 0.05 Aa	0.32 ± 0.04 Aa	0.24 ± 0.04 Ab	0.20 ± 0.04 Aa	0.24 ± 0.02 Aa
	4	0.06 ± 0.02 Ab	0.04 ± 0.01 Ab	0.13 ± 0.18 Ac	0.05 ± 0.02 Aa	0.05 ± 0.02 Aa
	5	0.27 ± 0.10 Ba	0.27 ± 0.13 Ba	0.30 ± 0.13 Aa	0.27 ± 0.01 Ba	0.32 ± 0.08 Aa
	6	0.21 ± 0.05 Aa	0.22 ± 0.03 Aa	0.21 ± 0.06 Ab	0.19 ± 0.03 Aa	0.20 ± 0.05 Aa
	7	0.18 ± 0.05 Aa	0.21 ± 0.07 Ab	0.16 ± 0.08 Ab	0.17 ± 0.01 Aa	0.22 ± 0.01 Aa
	8	0.21 ± 0.03 Aa	0.25 ± 0.16 Ab	0.28 ± 0.08 Ab	0.20 ± 0.22 Aa	0.11 ± 0.03 Aa
qn	1	0.73 ± 0.10 Aa	0.77 ± 0.01 Ab	0.59 ± 0.04 Ab	0.71 ± 0.08 Ab	0.80 ± 0.15 Ac
	2	0.92 ± 0.13 Aa	0.95 ± 0.10 Aa	1.03 ± 0.08 Ab	0.91 ± 0.09 Ab	0.90 ± 0.05 Ac
	3	1.01 ± 0.17 Aa	1.24 ± 0.11 Aa	1.19 ± 0.33 Aa	0.94 ± 0.21 Aa	0.89 ± 0.06 Ac
	4	0.70 ± 0.16 Aa	0.68 ± 0.31 Ab	0.55 ± 0.20 Ab	0.58 ± 0.12 Ab	0.57 ± 0.09 Ac
	5	1.00 ± 0.11 Aa	1.16 ± 0.19 Aa	1.22 ± 0.13 Aa	1.12 ± 0.05 Aa	1.13 ± 0.14 Ab
	6	1.18 ± 0.27 Aa	1.21 ± 0.12 Aa	1.23 ± 0.15 Aa	1.15 ± 0.09 Aa	1.17 ± 0.10 Ab
	7	1.13 ± 0.18 Aa	1.34 ± 0.24 Aa	1.34 ± 0.22 Aa	1.44 ± 0.23 Aa	1.43 ± 0.15 Ab
	8	1.22 ± 0.31 Aa	1.32 ± 0.28 Aa	1.37 ± 0.23 Aa	2.34 ± 0.71 Aa	1.60 ± 0.05 Aa
qp	1	0.19 ± 0.05 Aa	0.2 ± 0.03 Ab	0.17 ± 0.05 Ab	0.23 ± 0.03 Aa	0.26 ± 0.05 Aa
	2	0.35 ± 0.08 Aa	0.33 ± 0.02 Aa	0.34 ± 0.05 Aa	0.36 ± 0.01 Aa	0.30 ± 0.05 Aa
	3	0.29 ± 0.09 Aa	0.38 ± 0.06 Aa	0.32 ± 0.05 Aa	0.30 ± 0.02 Aa	0.34 ± 0.04 Aa
	4	0.12 ± 0.02 Aa	0.08 ± 0.01 Ab	0.19 ± 0.19 Ab	0.13 ± 0.02 Aa	0.11 ± 0.04 Aa
	5	0.37 ± 0.10 Aa	0.35 ± 0.12 Aa	0.37 ± 0.15 Aa	0.37 ± 0.01 Aa	0.41 ± 0.08 Aa
	6	0.29 ± 0.08 Aa	0.29 ± 0.02 Aa	0.28 ± 0.09 Ab	0.26 ± 0.02 Aa	0.26 ± 0.05 Aa
	7	0.24 ± 0.09 Aa	0.27 ± 0.08 Ab	0.20 ± 0.10 Ab	0.22 ± 0.01 Aa	0.26 ± 0.01 Aa
	8	0.27 ± 0.00 Aa	0.21 ± 0.17 Ab	0.26 ± 0.07 Ab	0.23 ± 0.23 Aa	0.13 ± 0.04 Aa
Y (ΦPSII)	1	0.11 ± 0.02 Aa	0.11 ± 0.02 Aa	0.12 ± 0.03 Aa	0.14 ± 0.01 Aa	0.14 ± 0.02 Aa
	2	0.16 ± 0.02 Aa	0.14 ± 0.02 Aa	0.13 ± 0.04 Aa	0.17 ± 0.03 Aa	0.15 ± 0.03 Aa
	3	0.12 ± 0.05 Aa	0.10 ± 0.05 Aa	0.10 ± 0.05 Aa	0.12 ± 0.02 Aa	0.13 ± 0.04 Aa
	4	0.06 ± 0.00 Ab	0.04 ± 0.01 Ab	0.08 ± 0.06 Ab	0.08 ± 0.01 Aa	0.06 ± 0.02 Ab
	5	0.14 ± 0.03 Aa	0.11 ± 0.01 Aa	0.11 ± 0.06 Aa	0.12 ± 0.02 Aa	0.13 ± 0.03 Aa
	6	0.10 ± 0.04 Ab	0.08 ± 0.01 Ab	0.08 ± 0.05 Ab	0.08 ± 0.01 Aa	0.08 ± 0.01 Ab
	7	0.07 ± 0.05 Ab	0.07 ± 0.03 Ab	0.05 ± 0.04 Ab	0.05 ± 0.00 Aa	0.05 ± 0.01 Ab
	8	0.08 ± 0.03 Ab	0.08 ± 0.04 Ab	0.07 ± 0.03 Ab	0.04 ± 0.03 Aa	0.03 ± 0.01 Ab

Different capital letters in the lines indicate a statistical difference according to the Scott–Knott test (p < 0.05); Different lowercase letters in the columns indicate statistical difference by the Scott–Knott test (p < 0.05). Equal letters do not differ significantly from each other.

, significant differences were observed for Fv/Fm (ANOVA, F = 32,003, p < 0.01), ΦPSII (ANOVA, F = 13,695, p = 0.003), Fvs/Fms (ANOVA, F = 43.65, p < 0.01), and ETR (ANOVA, F = 13,694, p = 0.003). For qn (nF/Fv), there was also a significant difference (ANOVA, F = 22.405, p < 0.01). On the other hand, NPQ (ANOVA, F = 2.675, p = 0.128), qp (ANOVA, F = 1.616, p = 0.217), and qL (ANOVA, F = 0.912, p = 0.357) did not show statistically significant differences.

3.4. Chlorophyll and Carotenoid Content

The analysis of variance did not identify a significant difference between the groups Chl a (F = 1.441, p > 0.05), Chl b (F = 0.9, p > 0.05), total Chl (a+b) (F = 1.069, p > 0.05), and carotenoids (F = 0.882, p > 0.05). The correlations between Chl a, Chl b, Chl a+b, and carotenoids were strong at all concentrations: 0 (r = 0.986 to 0.999), 1 (r = 0.927 to 0.999), 3, 5, and 7 (r = 0.993 to 1.000), indicating joint variation as the treatments change, as shown in

Table 3. Chl a, b, total, and carotenoid content in H. impetiginosus seedlings under increasing Hg levels.

Photosynthetic Pigment Concentrations
Hg (mg L−1)	Chl a	Chl b	Chl a+b	Carotenoids
0	12.07 ± 1.69 a	4.74 ± 0.84 a	16.81 ± 2.52 a	1421.99 ± 215.46 a
1	7.26 ± 0.76 a	2.99 ± 0.32 a	10.25 ± 1.08 a	904.18 ± 79.58 a
3	9.47 ± 4.18 a	5.12 ± 2.59 a	14.59 ± 2.76 a	1408.56 ± 294.38 a
5	9.93 ± 1.49 a	4.76 ± 1.10 a	14.69 ± 2.58 a	1413.76 ± 220.70 a
7	7.78 ± 3.69 a	4.17 ± 1.71 a	11.95 ± 2.40 a	1205.06 ± 264.31 a

Values followed by the same letter do not differ significantly according to the Scott–Knott test (p < 0.05).

.

3.5. Colorimetry

The analysis of the colorimetric data of the H. impetiginosus seedlings showed variation in the chromatic characteristic related to the luminosity of the leaves of the evaluated treatments (Figure 3), considering that each triplicate analyzed was cultivated at Hg concentrations of 0, 1, 3, 5 and 7 mg L⁻¹.

In the analysis of the chromatic coordinates a* and b*, as well as the color saturation (C*) and the hue angle (h), no significant differences were observed between the treatments (ANOVA, p > 0.05). The values of a* ranged from −30.41 to −25.79 (F = 2.81, p = 0.192), b* from 4.24 to 6.63 (F = 0.044, p = 0.848), C* from 1.69 to 5.31 (F = 0.372, p = 0.585), and h from −16.11 to −5.47 (F = 1.961, p = 0.256).

For the luminosity analysis (L*), significant differences were observed between the treatments (ANOVA, F = 135, p = 0.00137), with values ranging from 6.03 to 13.96. Treatments 5 and 7 exhibited the highest luminosities, suggesting lighter colors compared to the others.

3.6. Transpiration

There was variation in the transpiration of the seedlings as a function of Hg concentration, with a strong negative correlation (r = −0.916), suggesting that the variations in the Hg contents applied directly influenced the transpiration process of the plant. A strongly negative Pearson’s correlation was also found between the number of leaves that presented senescence and the total number of leaves (r = −0.899), confirming a clear trend of greater senescence in treatments with shorter permanence of the total number of leaves, and a moderate negative correlation was found between leaf senescence and transpiration (r = −0.792).

Figure 4 shows that the perspiration data ranged from 293.33 mL in treatment 0 to 130.56 mL (mean of treatments 3.5 and 7 mg L⁻¹). Comparing the index obtained, the plants in 1 mg L⁻¹ of Hg transpired 26.7% less than the 0 mg L⁻¹ treatment, while, in concentrations 3, 5 and 7 mg L⁻¹, they varied negatively in 55% (ANOVA, F = 9.7, p < 0.05). Based on the Scott–Knott test, it was found that the 0 mg L⁻¹ and 1 mg L⁻¹ Hg treatments form distinct groups, with significantly different averages from the 3, 5 and 7 mg L⁻¹ treatments. Specifically, the treatments form three groups: the 0 mg L⁻¹ treatment with the highest perspiration (293.33 mL), the 1 mg L⁻¹ treatment with intermediate sweat (215.00 mL), and the 3 mg L⁻¹, 5 mg L⁻¹, and 7 mgL⁻¹ treatments with an average sweat of 130.56 mL.

3.7. Hg Contents

For the analysis of Hg contents in plant tissues, significant differences were observed between the treatments for Hg content in leaves (ANOVA, F = 3.5, p < 0.05) and roots (ANOVA, F = 12.37, p < 0.01) but not in stems (ANOVA, F = 2.49, p < 0.05). The mean Hg content ranged from 0.85 μg g⁻¹ (mean of the treatments 0, 1, 3, and 5 mg L⁻¹) and 2.69 μg g⁻¹ (treatment 7 mg L⁻¹) in the leaves, 0.44 μg g⁻¹ (treatment 0 mg ^L−1) and 40.23 μg g⁻¹ (mean of the treatments 1, 3, 5 and 7 mg L⁻¹) in the stems, and 0.13 μg g⁻¹ (mean of treatments 0 and 1 mg L⁻¹) and 0.77 μg g⁻¹ (mean of treatments 3.5 and 7 mg L⁻¹) in the roots. The highest mean value was observed in the stem under treatments 1, 3, 5, and 7 (40.23 μg g⁻¹), while the lowest was in the root system under treatments 0 and 1 (0.13 μg g⁻¹), as shown in

Table 4. Average values of Hg contents (μg g⁻¹) in leaves, stems, and roots of H. impetiginosus seedlings subjected to different levels of Hg concentrations.

Hg Content (μg g−1)
[Hg] (mg L−1)	Leaves	Stem	Roots
0	0.61 ± 0.2 Aa	0.44 ± 0.5 Aa	0.08 ± 0.1 Ba
1	0.81 ± 0.6 Aa	16.81 ± 0.7 Bb	0.19 ± 0.1 Ba
3	0.7 ± 0.4 Aa	28.1 ± 5.6 Bb	0.53 ± 0.2 Bb
5	1.3 ± 0.8 Aa	36.32 ± 7.5 Bb	0.75 ± 0.2 Bb
7	2.69 ± 1.4 Ab	79.71 ± 62.4 Bb	1.02 ± 0.3 Ab
Average	1.22 ± 0.68	32.28 ± 15.34	0.51 ± 0.18

Different capital letters in the lines indicate statistical difference by the Scott–Knott test (p < 0.05); Different lowercase letters in the columns indicate statistical difference by the Scott–Knott test (p < 0.05). Equal letters do not differ significantly from each other.

.

Pearson’s correlation shows a strong positive correlation between Hg contents in different parts of the plant, with coefficients of 0.9548 between leaves and stems, 0.8599 between leaves and roots, and 0.9452 between stems and roots. These results indicate that concentration consistently influenced the distribution of Hg in the different parts of the plant. The results of Pearson’s correlation also indicated that there was a moderate positive correlation between treatment and Hg content in leaves (r = 0.6725) and stems (r = 0.6725) and a strong positive correlation with roots (r = 0.9103). Hg contents increase with the presence of Hg, being higher in stems (treatments 1, 3, 5, and 7 mg L⁻¹) and roots (treatments 5 and 7 mg L⁻¹). The leaves show less accumulation compared to the stems but similar or slightly higher values than the roots in some treatments, highlighting differences in mercury distribution among the plant parts.

3.8. Indices, Factors, and Trends of Accumulation

As observed in

Table 5. Mean values of Hg absorption index (AI) (μg g⁻¹) in leaves, stems, and roots of H. impetiginosus.

Hg Absorption Index (μg)
Treatment	Root System	Aerial Part	Whole Plant
1	0.41 ± 0.19 Aa	78.29 ± 0.31 Ba	78.70 ± 0.45 Ba
3	0.87 ± 0.08 Ab	120.10 ± 26.12 Bb	120.97 ± 25.86 Bb
5	1.57 ± 0.17 Ac	177.94 ± 25.21 Bb	179.51 ± 25.21 Bb
7	1.40 ± 0.45 Ac	207.46 ± 144.12 Bb	208.19 ± 144.25 Bb
Mean	1.06 ± 0.22	145.95 ± 47.8	146.84 ± 48.94

Different capital letters in the lines indicate a statistical difference according to the Scott–Knott test (p < 0.05); Different lowercase letters in the columns indicate statistical difference by the Scott–Knott test (p < 0.05). Equal letters do not differ significantly from each other.

, significant differences were identified in the Hg levels absorbed by the root system between the different treatments (ANOVA, F = 19.84, p < 0.01). For the shoot and the total Hg content in the plant, the analyses showed marginally significant differences between the treatments (ANOVA, F = 3.33, p = 0.05) and (ANOVA, F = 3.383, p = 0.05), respectively. The results indicate that, with the presence of Hg, there was an increase in root absorption in treatments 1 and 3 mg L⁻¹, stabilizing between treatments 5 and 7 mg L⁻¹. For the shoot and the total content in the plant, a similar trend was observed, with an initial increment followed by stabilization at the highest Hg levels.

The results of the translocation factors (TFs), bioconcentration (BCF), and bioaccumulation (BAF) are presented in

Table 6. Comparison of translocation factors (TF), bioconcentration (BCF), and bioaccumulation (BAF) between different concentrations.

Bioremediation Factors
[Hg] (mg L−1)	(TF)	(BCF)	(BAF)
1	102.16 ± 12.44 a	0.19 ± 0.072 a	17.62 ± 1.03 a
3	56.85 ± 11.05 a	0.18 ± 0.057 a	9.60 ± 1.76 b
5	52.27 ± 13.06 a	0.15 ± 0.045 a	7.52 ± 1.36 b
7	90.94 ± 28.54 a	0.15 ± 0.044 a	11.77 ± 10.28 b

Different letters in the columns indicate that the means are significantly different from each other by the Scott–Knott test (p < 0.05).

. The BAF showed a significant difference between treatments (ANOVA, F = 33.99, p < 0.01); however, the factors TF (ANOVA, F = 0.7650, p > 0.05) and BCF (ANOVA, F = 0.2720, p > 0.05) were similar between treatments. The TF presented mean values of 75.56. On the other hand, the BCF had an average of 0.17. Conversely, the BAF varied between 9.63 (mean value of the 3.5 and 7 mg L⁻¹ treatments) and 17.62 (1 mg L⁻¹).

4. Discussion

4.1. Morphological Analysis

The successful establishment of Handroanthus impetiginosus seedlings under controlled conditions ensured uniform growth and minimized external environmental influences. The conditions for seedling production, including nutrition, irrigation, and overall management, were carefully controlled to prevent any interference from water, nutritional, or phytosanitary stress on the plants during the application of the treatments. The plants exhibited consistent morphological traits, with an average height of 27.05 cm, a stem diameter of 7.01 mm, an average of 14 leaves per plant, a leaf length of 12.39 cm, and a longitudinal leaf length of 5.47 cm. Standardized cultivation practices were essential to ensure that the observed effects were primarily driven by Hg stress rather than variations in plant development. These controlled conditions provided a solid basis for interpreting the physiological and biochemical responses observed in the experiment.

Figure 1 confirms that the evaluated morphological parameters did not show significant differences among seedlings, ensuring uniformity and appropriate conditions for the application of experimental treatments. These statistical data reinforce that the selected seedlings were morphologically homogeneous, providing a solid basis for the evaluation of subsequent treatments.

4.2. SPAD Index

The values obtained by the SPAD index over the eight days of the experiment showed a trend of reduction in Chl levels in H. impetiginosus, accompanied by an increase in mercury content in the treatments. Significant differences were observed on most measurement days, Table 1, with the exception of the first day (initial measurement), performed post-transplant and before contact with the contaminant.

The SPAD index, which determines Chl concentration by measuring leaf absorbance, is also an indicator of nitrogen (N) status in plants [45]. The values of this index, according to Xiong et al. [46], are indirectly related to nitrogen concentration. Table 1 shows a progressive reduction in the index throughout the experiment, suggesting that mercury toxicity may be associated with nitrogen depletion [47].

When analyzing the daily readings (Table 1), it was observed that, from the second day onwards, the treatments with 1, 3, and 7 mg L⁻¹ of Hg already showed reductions in the mean SPAD values, which were statistically significant. This downward trend persisted in the subsequent days, especially in treatments with higher Hg concentrations, such as 3, 5 and 7 mg L⁻¹, which recorded a mean SPAD of 18.43 on the eighth day, representing a reduction of 28.17%. Treatment 1 mg L⁻¹, in turn, registered SPAD 22.97, with a reduction of 16.55% compared to the initial day. Data confirm that Hg exposure reduces Chl levels, with a more severe impact at high concentrations [48]. The results showed that the mean values of the 3, 5, and 7 mg L⁻¹ treatments were significantly lower than those of the control, showing that increasing concentrations of mercury compromise Chl levels.

Similar results were reported by Deng et al. [49] in studies with Microsorium Pteropus, demonstrating that high levels of Hg²⁺ are highly phytotoxic, reducing Chl content due to cellular toxicity. In this study, with H. impetiginosus, the SPAD index gradually decreased in all treatments, with more marked reductions at higher concentrations. Lower concentrations, such as 1 mg L⁻¹, also showed decreases in SPAD values, although less expressive. These data reinforce that mercury impairs the photosynthetic capacity of plants, with more severe effects at high concentrations [48].

The effects of mercury on the SPAD index can be attributed to its toxicity, which interferes with Chl synthesis and photosynthetic function [50]. Mercury is known to cause oxidative stress in plants, leading to Chl degradation and, consequently, decreased SPAD values [14]. Studies conducted by Wang et al. [9] suggest that Hg may also interfere with the absorption of essential nutrients, aggravating the reduction in Chl. As noted by Gai et al. [51], exposure to heavy metals, such as mercury, also reduced nitrogen levels in Tabebuia roseoalba (Ipê-branco), reinforcing the connection between environmental contamination and nutritional depletion.

4.3. Fluorescence

The analysis of the parameters related to PSII revealed punctual changes in variables such as the electron transport rate (ETR), the maximum efficiency of PSII in light state (Fvs/Fms), effective quantum yield (ΦPSII), and non-photochemical extinction (qn), evidencing the impact of Hg concentrations on the functionality of PSII. Fvs/Fms showed a substantial reduction from the fifth day in all treatments (Table 2), suggesting that mercury reduces the maximum energy conversion capacity in the PSII, indicating that Hg affects both the basal state and the state under light, which is in line with previous studies that highlight the affinity of Hg for the sulfhydryl groups of the PSII proteins, impairing electron transport [52,53].

However, ΦPSII showed a moderate relationship with Hg concentrations, suggesting that other factors may modulate this parameter, possibly by compensatory mechanisms in electron transport or by the activation of photoprotective pathways [9]. These observations indicate that the impact of Hg on PSII occurs progressively, affecting more intensely the parameters directly related to maximum photosynthetic efficiency, while variables such as ΦPSII may reflect the physiological plasticity of the plant in the face of toxicity [54].

The decrease in Fvs/Fms values reflects damage to the PSII, reducing the photochemical efficiency. In the treatments with a higher presence of Hg (5 and 7 mg L⁻¹), the mean final values (days 5 to 8) were 0.2682, significantly lower than those observed in healthy plants, which vary between 0.75 and 0.83 [55]. This decline, of 50.58% compared to the average recorded in the initial days (1 to 4) of measurement, demonstrates the extent of the impact of mercury. Similar results were reported by Wang [9] in studies with Chlorella pyrenoidosa (H. Chick), where exposure to Hg²⁺ caused an increase in initial fluorescence (F0) and a reduction in photosynthetic efficiency, suggesting damage to PSII without changes in maximum fluorescence.

The values observed for the ΦPSII indicated a reduction of 36.30% in the 3 mg L⁻¹ treatment, and 58.33% in the 7 mg L⁻¹ Hg treatment, in relation to the initial measurements. This result reflects the impact of the experimental environment on the photosynthetic capacity of plants [56,57].

On the other hand, the photochemical extinction coefficient (qp) remained stable between the treatments, with no statistically significant differences, indicating that the experimental conditions did not directly influence this parameter. This result suggests that the electron transport efficiency in PSII remained functional, even under different Hg concentrations, demonstrating the physiological resilience of qp in situations of moderate stress [9].

In contrast, the non-photochemical extinction (qn) showed an increase of 83.04% in comparison of the pooled means of the 1, 3, 5, and 7 mg L⁻¹ treatments of the initial days (1 to 4) compared to the final days (5 to 8), showing an increase in these parameters with the presence of the contaminant. This increase reflects a greater dissipation of non-photochemical energy, a fundamental mechanism to minimize damage to photosystem II during stress. Changes in this parameter may be related to the activation of the xanthophyll cycle, promoting the dissipation of excess light energy as heat and protecting the photosynthetic apparatus against oxidative damage [58].

The NPQ and qL parameters did not show significant relationships with time, indicating stability of these factors in the conditions analyzed. An increase in NPQ in mercury treatments may suggest greater energy dissipation in the form of heat, a typical response to stress caused by excess light or contaminants [59].

The electron transport rate (ETR) was significantly altered, indicating changes in the electronic flux of the PSII. The ETR showed a progressive reduction throughout the experiment. Treatments 0.1 and 3 had a mean ETR of 29.59 on the initial days (1 to 4) and a mean of 18.39 on the final days (5 to 8). On the other hand, the 5 and 7 mg L⁻¹ treatments showed the greatest decline (75.43%), from 33.90 (mean of days 1 to 4) to 8.53 (mean of days 5 to 8). Studies conducted by Wang et al. [9] and Deng et al. [49] reported similar results in Microsorium pteropus and Chlorella pyrenoidosa, respectively.

Exposure to mercury caused a significant decrease in photochemical efficiency and electron transport in H. impetiginosus. The reduction in the values of Fvs/Fms, ΦPSII, and the ETR, as well as the increase in qn, reflects the negative effects of mercury on the photosynthetic capacity of plants.

4.4. Chlorophyll and Carotenoid Content

The levels of Chl and carotenoids in H. impetiginosus did not show significant discrepancies throughout the treatments with different concentrations of mercury, as shown in Table 3. The analysis revealed that these pigments were not significantly affected by the presence of Hg, suggesting that mercury, under the conditions tested, did not directly interfere with their biosynthesis.

Although a trend of reduction in Chl and carotenoid levels was observed in treatments with higher mercury concentrations, such as 1 and 7 mg L⁻¹, these changes were not statistically significant. This trend may be associated with mercury-induced oxidative stress, a factor known to compromise the biosynthesis of photosynthetic pigments [60]. The decrease in the levels of carotenoids, pigments responsible for photoprotection, may indicate a lower ability of plants to dissipate excess light energy, increasing their vulnerability to photooxidative stress [61,62].

Despite this reduction, intermediate Hg concentrations, such as 3 and 5 mg L⁻¹, did not result in significant variations in pigment levels, maintaining values close to those of the control. This pattern may suggest the existence of compensatory or stress tolerance mechanisms under these specific conditions, allowing plants to preserve their levels of photosynthetic pigments [63]. This adaptive responsiveness highlights the complexity of the interaction between mercury and plant physiological processes [64,65].

4.5. Colorimetry

The analysis of the colorimetric data of the H. impetiginosus seedlings showed significant variations in the chromatic characteristics in response to the different levels of Hg contamination. The luminosity values (L*) ranged from 6.02 (mean of 0 and 1 mg L⁻¹) to 13.28 (mean of 5 and 7 mg L⁻¹), indicating a relatively low shade range. The treatments with higher Hg concentrations (5 and 7 mg L⁻¹) showed the highest luminosities, suggesting that the leaves of these seedlings exhibit lighter colors compared to the treatments with lower contamination. This clarity may be associated with mercury-induced stress, which can result in the degradation of Chl and other photosynthetic pigments, leading to a duller appearance of leaves [66].

The chromatic coordinates a and b reflect the predominance of shades of green (negative values for a*) and blue (positive values for b*), as shown in Figure 3. In the treatments with 1 and 7 mg L⁻¹ of mercury, no significant differences were observed in the absolute values of a* and b* in relation to the other treatments, indicating that the color saturation remained stable under the conditions evaluated. This stability suggests that the treatments tested did not measurably impact color saturation [67].

When there is an increase in saturation, this phenomenon may be related to mercury-induced oxidative stress, which stimulates the production of accessory pigments as a protective mechanism against photosynthetic damage [68]. These pigments can contribute to the adaptation of plants in environments with higher mercury concentration, although this effect was not significant in this experiment.

The color saturation (C*) ranged from 1.69 to 6.63, which is relatively low in all treatments. This low saturation may reflect the decrease in photosynthetic efficiency and vigor of plants exposed to mercury [65]. Additionally, the hue angle values (h) suggest a distribution of colors along the chromatic spectrum, with subtle differences between treatments. These subtle differences in the hue angle may indicate slight variations in pigment composition, which are more pronounced in plants under stress [60].

These results suggest that mercury directly influences the coloration of H. impetiginosus leaves, resulting in noticeable changes in colorimetric parameters. In particular, the higher luminosity observed in treatments with higher Hg content may be indicative of chlorosis, a condition often associated with mercury toxicity [1]. Chlorosis is characterized by the loss of Chl, which causes a bleaching of the leaves [69]. The results of Xiong et al. [70], analyzing plants of the species Citrus reticulata, characterized chlorosis from the reduction in photosynthetic pigments by up to 18.50%. In our study, the treatments (5 and 7 mg L⁻¹) showed an increase in luminosity (L*) by 109.10% and 131.66%, respectively, indicating Hg-induced chlorosis, as can be visually observed in Figure 2. However, this effect was not statistically significant for the other colorimetric parameters, as demonstrated in Figure 3.

The higher color saturation, observed specifically in the 5 and 7 m L⁻¹ treatments, can be interpreted as an adaptive response of the plants to mitigate the effects of mercury. Plants subjected to environmental stress, such as heavy metal contamination, often accumulate pigments such as anthocyanins and carotenoids [71]. These compounds, in addition to intensifying the colors of the leaves, perform antioxidant functions, protecting plant cells against oxidative damage [72,73].

4.6. Transpiration

The data presented in Figure 4 show a substantial variation in sweating rates between the different treatments. The plants in the control treatment (0 mg L⁻¹ of Hg) had the highest transpiration rate (293.33 mL); on the other hand, the plants submitted to the treatment with 1 mg L⁻¹ of Hg had a transpiration 26.7% lower than that of the control. The treatments with 3, 5, and 7 mg L⁻¹ of Hg, statistically grouped by the Scott–Knott test, obtained an average of 130.56 mL, which, when compared to the control treatment, represents an average reduction of 55.5% in sweating. Comparing these results with Moreno et al. [38], where Brassica juncea transpiration reduced from 1.4 to 5.1 times with concentrations of 0.05 to 10 mg L⁻¹ of Hg, mercury has a significant impact on reducing plant transpiration.

There were significant variations in the transpiration process of H. impetiginosus under different Hg concentrations, according to the results measured by the transpiration analysis. A strong negative correlation was observed between Hg treatments and transpiration (−0.916), suggesting that the increase in Hg levels applied directly influenced the ability of plants to transpire. This effect can be attributed to mercury toxicity, which can compromise water and nutrient absorption, negatively affecting plant physiology [9].

The analysis also pointed to a strongly negative correlation between the number of leaves that presented senescence and the total number of leaves (−0.900), indicating that treatments with higher Hg concentration resulted in higher leaf senescence. Early leaf senescence is indicative of plant stress, which can be accentuated by the presence of mercury, a metal known to cause cell damage and interfere with crucial metabolic processes [74]. Gworek et al. [8] points out that Hg contamination causes early senescence, leaf fall, and death due to oxidative stress and cell damage, as Hg binds to sulfhydryl/thiol groups of proteins, causing disruption in Chl synthesis and photosynthesis, leading to leaf senescence.

The reduced transpiration capacity observed in treatments with higher Hg levels can be explained by the interference of mercury in the absorption of water by the roots [38]. Mercury can damage the structure and function of the roots, preventing the efficient uptake of water and essential nutrients. This results in a lower availability of water for physiological processes, including transpiration [75]. In turn, the presence of mercury can induce the formation of reactive oxygen species (ROS), causing oxidative stress and damage to cell membranes, which further compromises the ability of plants to maintain water homeostasis [76].

The higher rate of leaf senescence in mercury treatments suggests that toxin-induced stress, where plants, when facing difficulties in the absorption and translocation of water and nutrients, cause the prioritization of resource allocation for the maintenance of vital functions, resulting in the loss of non-essential leaves [77]. This resource allocation strategy, although necessary for short-term survival, can reduce photosynthetic capacity and, consequently, productivity in the long term [78].

4.7. Hg Contents

The analysis of mercury (Hg) levels in the plant tissues of H. impetiginosus revealed considerable differences between the treatments, especially in the leaves and roots, as shown in Table 4. The average Hg contents ranged from 0.85 μg g⁻¹ (mean of the 0, 1, 3, and 5 mg L⁻¹ treatments) to 2.69 μg g⁻¹ (7 mg L⁻¹ treatment) in the leaves, 0.44 μg g⁻¹ (0 mg L⁻¹ treatment) to 40.23 μg g⁻¹ (mean of the 1, 3, 5 and 7 mg L⁻¹ treatments) in the stems, and 0.13 μg g⁻¹ (mean of the 0 and 1 mg L⁻¹ treatments) and 0.77 μg g⁻¹ (mean of the 3.5 and 7 mg L⁻¹ treatments) in the roots. The highest mean value was observed in the stem under treatments 1, 3, 5, and 7 (40.23 μg g⁻¹), while the lowest was in the root system under treatments 0 and 1 (0.13 μg g⁻¹). These results indicate a substantial accumulation of Hg in stems, particularly in treatments with high concentrations of mercury, a behavior similar to that observed in aquatic plants [79]. These results indicate that the increase in treatments influenced in a different way the Hg levels in the different parts of the plant, with specific distribution patterns according to the part analyzed.

The detection of traces of Hg in the control treatment, despite the absence of mercury addition, can be attributed to the presence of background levels in the substrate used in the development of seedlings, resulting from atmospheric deposition and environmental factors that make Hg a ubiquitous contaminant [80,81].

The results indicate distinct patterns of Hg accumulation between treatments, depending on the tissue analyzed. The roots showed an increasing and more uniform Hg accumulation between the treatments, with significant differences in the highest levels of exposure. This suggests that the distribution of Hg varies according to physiological functions and translocation dynamics between tissues, with roots acting as the main entry route and leaves and stems responding differently to mercury-induced stress [82].

The greater accumulation of Hg in the stems can be explained by the translocation of the metal from the roots to other parts of the plant [83]. However, the lower accumulation in leaves compared to stems suggests a restriction or regulation mechanism that limits the amount of Hg reaching leaves, where it could cause more direct damage to photosynthesis and other essential physiological processes [84,85].

The reduction in the ability of plants to absorb water and nutrients, mentioned above, can be attributed to the toxic effect of mercury on the roots [86]. The presence of Hg can damage the structure and function of the roots, compromising the efficient absorption of water and nutrients. Not only does this reduce evapotranspiration, but it can also affect the growth and overall health of the plant [12].

Usually, in plants exposed to contamination by toxic metals, there are greater accumulations of the contaminant in roots and leaves to the detriment of accumulation in stems [87]; however, Marrugo-Negrete et al. [88] also found greater Hg accumulation in stems of a genotype of Vigna unguiculata L. exposed to treatments up to 8 mg kg⁻¹. In experiments carried out with Thallium (Tl) by Holubík et al. [89], higher concentrations of this metal were also found in the stems. Hydroponic experiments are essential to identify contaminant effects on plant development, tolerance, accumulation, bioconcentration, and metal translocations from roots to leaves [90].

The ability of H. impetiginosus to uptake and translocate Hg, particularly its accumulation in stems, suggests a potential role for this species in phytoremediation strategies. Its capacity to tolerate and compartmentalize mercury in specific tissues highlights its relevance for further studies aimed at the remediation of contaminated environments.

4.8. Indices, Factors, and Trends of Accumulation

Bioconcentration factors (BCFs) and bioaccumulation factors (BAFs) assess the content of toxic metals in the plant, while the translocation factor (TF) measures the transfer of metals between plant parts [91]. The absorption index (AI), on the other hand, expresses the concentration obtained in the reading of the sample by the atomic absorption equipment, representing the amount of contaminant in the sample [92]. Both are essential for us to obtain a strong perspective on the plant’s ability to respond to contact with Hg.

The analysis indicated significant differences in Hg absorption, especially in the roots, according to the treatments applied (Table 5). These results suggest that the different levels of Hg contamination mainly influence the uptake of Hg by the roots, with accumulation tendencies in the shoot and in the plant.

Hg absorption indices (AIs) varied between treatments, with substantial differences identified in the roots. The AI increased from 0.41 μg g⁻¹ in treatment 1 to 0.87 μg g⁻¹ in treatment 3 and stabilized at 1.49 μg g⁻¹ in treatments 5 and 7. In the aerial part, the values ranged from 78.29 μg g⁻¹ in treatment 1 to 168.50 μg g⁻¹ in treatments 3.5 and 7. In the whole plant, the Hg absorption index (AI) increased from 78.70 μg g⁻¹ in treatment 1 to 169.56 μg g⁻¹ in treatments 3, 5, and 7, following the pattern observed in shoots. These results indicate that the increase in Hg levels promoted greater initial absorption, with stabilization in the higher treatments, suggesting a possible saturation in the physiological accumulation capacities of the plant [60].

The factors of translocation (TF), bioconcentration (BCF), and bioaccumulation (BAF) were analyzed between the different treatments. The TF, which measures the efficiency of Hg translocation from the roots to the shoot, presented an overall average of 75.56, with no significant variations between the treatments as shown in Table 6, indicating that the increase in the concentration of Hg in the solution did not consistently alter the efficiency of translocation of the element from the roots to the shoot [93].

The bioconcentration factor (BCF), which evaluates the ability of the roots to accumulate Hg from the solution, also showed no significant differences between the treatments (ANOVA, F = 0.2720, p > 0.05), with an overall average of 0.17. These results indicate that the Hg uptake by the roots was similar regardless of the Hg concentration applied. This relatively stable index indicates that, although the amount of Hg accumulated in the plants varies, the proportion of Hg in relation to the solution remains comparatively constant between treatments [94].

On the other hand, the bioaccumulation factor (BAF) showed significant differences between the treatments (Table 6). Treatment 1 had a mean BAF of 17.62, significantly higher than the combined mean of treatments 3, 5, and 7, which was 9.63. This variation suggests that the plants in the treatment with lower Hg concentration had a higher relative capacity for total Hg accumulation.

The results obtained for the experiment with H. impetiginosus are compatible with those reported in hydroponic experiments with Lupinus albus L. [95], where variations in the BCF between 0.08 and 0.23 and the TF between 48.90 and 79.60 were obtained; however, with a lower BAF, variations between 0.13 and 0.50 were obtained. The trend of greater Hg accumulation in the roots indicates that these parts of the plants are more susceptible to contamination, reflecting the first line of contact with the contaminant [96]. The lower translocation efficiency in higher treatments suggests a possible plant defense strategy, limiting the transport of Hg to the aerial part where it could cause greater physiological damage [12,69].

These findings reinforce the potential of H. impetiginosus as a phytoremediation species, given its capacity to absorb and compartmentalize Hg while limiting excessive translocation to sensitive aerial tissues. This characteristic suggests its applicability in strategies for mitigating mercury contamination in affected environments.

5. Conclusions

The toxic element mercury negatively impacts several physiological functions in H. impetiginosus seedlings. Increasing mercury levels compromises photosynthetic efficiency, as indicated by the reduction in the SPAD index and changes in the photochemical step of photosynthesis, including the decreased quantum efficiency of PSII, reduced electron transport (ETR), and effective quantum yield (ΦPSII), as well as increased non-photochemical extinction (qn). Despite this, the contents of Chl (a+b) and carotenoids remained stable over the eight days, suggesting compensatory mechanisms of photosynthetic protection.

Seedling transpiration decreased significantly with increasing mercury concentration, indicating limitations in water regulation. This reduction reached 55.5% in the highest treatments compared to the control, with a strong negative correlation (−0.916) between Hg concentration and transpiration, suggesting that mercury directly interferes with water absorption by the roots and stomatal regulation. Mercury accumulation was more pronounced in stems, followed by roots, with lower translocation to leaves in most treatments. This pattern suggests an absorption strategy that potentially minimizes damage to photosynthetic tissues. The translocation factors range from 52.27 to 102.16, while the bioaccumulation factors showed significant differences, with values from 7.52 to 17.62, highlighting the species’ ability to concentrate mercury in different parts of the plant.

The results suggest that H. impetiginosus, found in the Cerrado–Amazon transition, has potential for phytoremediation due to its ability to accumulate mercury over a short period. The stabilization of absorption indices (AIs) and the greater accumulation in the roots indicate tolerance strategies, limiting the translocation of the contaminant to the aerial part. The oxidative stress caused by mercury, evidenced by the increase in non-photochemical extinction (qn) and the reduction in Fv/Fm, ΦPSII, and ETR values, reflects the activation of compensatory mechanisms that confer greater tolerance to contamination. Future studies could deepen the understanding of tolerance mechanisms and explore the use of this species in environmental remediation systems, particularly in areas impacted by mercury contamination.