Exposure to certain acute stressors results in an immediate behavioral and physiological response to these situations during a significant period of days. The goal of the current study is to evaluate the long-lasting effect of single exposure of restraint stress among mice after 0 h, 24 h, 48 h and 72 h. Five groups of mice are under experiment: a control group and four groups exposed to one session of restraint stress. All these groups have been studied for behavioral tests in order to evaluate their memories. This is done through a Y-labyrinth and an object recognition test, and anxiety by using open field device. In the second part of the study, enzymatic assays (concerning catalase, glutathione s transferase, glutathione peroxidase and superoxide dismutase) are used to evaluate oxidative stress. The enzymatic activity of the antioxidant system is assessed in five brain structures, including the cerebellum, olfactory bulb, spinal bulb, hypothalamus, and hippocampus.
The obtained results show that acute restraint stress leads to a decrease in memory function and to the development of an anxious state; concomitant to an increase of locomotor activity afterword. It causes disturbance of antioxidant balance in the brain by developing a state of oxidative stress. Indeed, restraint stress causes a change in anti-oxidant stress enzymatic activity in the brain, notably in post-stress period. In conclusion, acute restraint stress is responsible for altering cognitive functions, especially memory, and the development of anxious behavior, which could be a result of the generation of oxidative stress; effects that are persistent over an important period after the cessation of stress.
Citation: Nouhaila Chaoui, Hammou Anarghou, Meriem Laaroussi, Oumaima Essaidi, Mohamed Najimi, Fatiha Chigr. Long lasting effect of acute restraint stress on behavior and brain anti-oxidative status[J]. AIMS Neuroscience, 2022, 9(1): 57-75. doi: 10.3934/Neuroscience.2022005
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Exposure to certain acute stressors results in an immediate behavioral and physiological response to these situations during a significant period of days. The goal of the current study is to evaluate the long-lasting effect of single exposure of restraint stress among mice after 0 h, 24 h, 48 h and 72 h. Five groups of mice are under experiment: a control group and four groups exposed to one session of restraint stress. All these groups have been studied for behavioral tests in order to evaluate their memories. This is done through a Y-labyrinth and an object recognition test, and anxiety by using open field device. In the second part of the study, enzymatic assays (concerning catalase, glutathione s transferase, glutathione peroxidase and superoxide dismutase) are used to evaluate oxidative stress. The enzymatic activity of the antioxidant system is assessed in five brain structures, including the cerebellum, olfactory bulb, spinal bulb, hypothalamus, and hippocampus.
The obtained results show that acute restraint stress leads to a decrease in memory function and to the development of an anxious state; concomitant to an increase of locomotor activity afterword. It causes disturbance of antioxidant balance in the brain by developing a state of oxidative stress. Indeed, restraint stress causes a change in anti-oxidant stress enzymatic activity in the brain, notably in post-stress period. In conclusion, acute restraint stress is responsible for altering cognitive functions, especially memory, and the development of anxious behavior, which could be a result of the generation of oxidative stress; effects that are persistent over an important period after the cessation of stress.
Mercury (Hg) is a global environmental pollutant that is highly toxic and widely distributed throughout the environment, since it can be transported over long distances in the atmosphere [1]. In the soil, Hg chemistry is characterized by several processes such as adsorption and release from solid phases, oxidation and reduction, complexation with organic and inorganic ligands, and methylation. Of the various technologies used to remediate Hg-polluted soils [2], phytoextraction has been chosen in many cases, with contrasting results due to site-specific conditions [3,4,5,6].
The phytoextraction of metals and metalloids has received significant attention as a non-impact, environmentally safe remediation strategy for polluted soils. In the case of contamination derived from more than one metal, a thorough investigation of the soil properties is essential for determining the main components responsible for the mobility and bioavailability of metals and metalloids [7]. Arsenic (As) is often present along with Hg in many contaminated sites.
Hg and As are typically non-essential elements for plants, with different chemical characteristics and different behavior in relation to soil properties, such as pH and cation exchange capacity (CEC). Their removal often requires separate remediation strategies. For Hg-assisted phytoextraction, a thiosulfate salt is usually used [3,6], whereas a phosphate salt [8] is the most suitable additive for As. In presence of mixed heavy metal pollution, implementing of phytoextraction at field scale can require a long time to reduce metal concentrations to safe levels and to comply with environmental regulations. The use of the same mobilizing agent to increase the bioavailability and plant uptake of both contaminants would facilitate the phytoextraction process by greatly reducing both time and costs.
Phytoextraction has been confirmed as an efficient bioremediation technology for soil contaminated by heavy metals. Its approach is in agreement with the latest environmental sustainability criteria, making it an emerging eco-friendly technique for soil clean-up, enjoying good public acceptance [9]. Phytoextraction is related to the green technology of phytoremediation, which exploits the ability of plants to remove pollutants (especially metals) from soil or water via their roots and store them in the harvestable part of plants [10,11,12]. Phytoextraction efficiency is affected by several factors related to both the plants and the soil; particularly important is metal bioavailability, defined as the mobile and available contaminant fraction in soil for uptake by plants and soil organisms [7,13,14,15]. Indeed, the plants are able to uptake only the substances present in soil solution in bioavailable forms [16].
Phytoextraction is an effective and economical technology compared to conventional soil remediation techniques; moreover, it causes less soil disturbance, preserving the structure and fertility of soil [17]. In some cases this technology can also offer the possibility of bio-recovery of metals (bio-phytomining) [18,19]. The ability of phytoextraction to remove hazardous contaminants while simultaneously restoring the polluted site have led to this technique's wide acceptance among communities. Thus, assessing phytoextraction's success should consider not only the total metal amount removed from soil but also the positive environmental impacts obtained.
Recently, several studies have focused on researching strategies to improve the technique's efficiency. Among the latest developments related to improving the phytoextraction of metal, the use of PGPR bacteria (Plant Growth-Promoting Rhizobacteria) and genetic engineering have obtained positive results [20,21]. Assisted phytoextraction also appears very promising, since it exploits certain properties of fertilizers or chemical additives to promote the release of metals from the solid phase of soil, increasing the bioavailable metal concentration in soil solution and consequently metal uptake by plants [16,22].
In the last decade, synthetic chelators such as the aminopolycarboxylic acids (APCAs), including EDTA (ethylenediaminetetraacetic acid), HEDTA (hydroxyethyl ethylenediamine triacetic acid), and DTPA (diethylenetriamine pentaacetic acid), have been the most commonly employed chemical agents in assisted phytoextraction [23,24,25]. However, their high mobilizing capacity and long persistence in soil may cause increased metal concentrations in soil solution. Indeed, the amount of metal released often exceeds the bioavailable quantity absorbable by plants [26,27,28], with the possibility of their leaching towards ground water [29,30,31]. For this reason, new biodegradable mobilizing agents, such as natural low-molecular-weight organic acids (NLMWOAs), EDDS (ethylene diamine disuccinate), NTA (nitrilotriacetate), and humic substances, which could limit the metals' leaching from soil with reduced additional negative effects on the surrounding environment, have been tested recently. However, they do not eliminate the risk of contaminant mobilization and the associated hazards [22,32,33,34].
Repeated phytoextraction cycles are often needed to reduce soil metal concentration to acceptable levels [35,36]. After the first harvesting, a certain amount of metal can remain in soil and further cycles of plant growth can reduce residual metals to bioavailable forms. When the bioavailable metal pool is exhausted, phytoextractionefficiency is progressively reduced [37] and the process can be regarded as completed. The residual metal fractions in soil can be considered harmless and permanently unavailable [16]. In order to verify the technology's success and the absence of extractable metals, both metal concentration in plants and the amount of metal extracted by mobilizing agents from soil must be examined.
This study aimed to evaluate the efficiency of repeated phytoextraction cycles to remove Hg and As by means of Brassica juncea (Indian mustard) from a multi-contaminated soil. Two mobilizing agents, ammonium thiosulfate, (NH4)2S2O3, and potassium dihydrogen phosphate, KH2PO4, were used to increase metal bioavailability in soil with the further goal of investigating the possibility of using only one additive to remove both Hg and As from soil simultaneously. Four growing cycles on the same soil sample were carried out, with or without consecutive addition of mobilizing agents. Results showed that ammonium thiosulfate notably increased the plant uptake not only of Hg but also of As, with an efficiency comparable to that obtained by phosphate used to mobilize As. Treatment with a single additive can offer advantageous new developments for phytoextraction technology, since both time and costs are reduced.
Contaminated soil usedin this study was collected from an industrial site located in northern Italy. Soil samples were collected at a depth of 0-1 m, air-dried, and passed through a 2-mm sieve for laboratory analysis. The following soil physical properties were determined according to standard methods [38]: soil pH, using a 1:2.5 soil/water ratio, cation exchange capacity using barium acetate, and texture (sand, silt and clay) via the pipette method. Organic matter content was measured with RC-412 Multiphase Carbon Determinator and N content with FP-528 Nitrogen/Protein Analyzer For Organic Samples. Total concentrations of Hg and As were determined via acid digestion using the EPA Method 3051A [39].
The bioavailable fractions of metals in soil samples were evaluated by specific chemical extraction techniques. The Hg bioavailable fractions were determined by two steps of a sequential extraction procedure [40] with 1M NH4Cl (ammonium chloride) (soil/extractant ratio of 1:50 for 1 h) and 0.27M (NH4)2S2O3 (soil/extractant ratio of 1:20 for 2 h). The maximum amount of extractable As was quantified, adopting the first two steps of modified Wenzel's sequential extraction [41] in which 0.05M NaNO3 (sodium nitrate) and 0.05M KH2PO4 (soil/extractant ratio of 1:25 for 2 h) were added sequentially. NaNO3 was used instead of (NH4)2SO4 (ammonium sulfate), since a weaker extractant better simulates readily available As in this soil. The supernatant was separated after centrifugation at 15.000 rpm for 15 min.
To evaluate thelong-term release of potentially bioavailable Hg and As from soil solid phases, five consecutive extractions with 0.27M (NH4)2S2O3 [3,5] were conducted on the same soil sample. As extractability was also determined using 0.05M KH2PO4 [42]. Each extraction was performed by shaking soil and extractant (ratio of 1:25) for 2 h, using 50 mL polypropylene centrifuge tubes. The supernatant was separated after centrifugation at 15.000 rpm for 15 min, and a new extraction was carried out on the remaining amount of soil.
Extractions were run in triplicate and the extracts were analyzed for Hg and As content after filtration.
To maintain the real situation of the polluted soil, the sampled soil was prepared by eliminating the coarser material without sieving to 2 mm and accurately homogenized. The trials were carried out in 250 mL microcosms. The pots were filled with 200 g of contaminated soil and sown with 0.30 g of B. juncea seeds. This species was selected because of its versatility, rapid growth and ease of cultivation, as exhibited in previous microcosm studies [42,43,44]. The first harvest was considered preliminary to the long-term phytoextraction test, based on a total of four growing cycles.
During the growing period, the plants were watered daily with deionized water without additional nutrients. Two weeks after sowing, soil treatments with mobilizing agents, 0.27M ammonium thiosulfate (T) and 0.05M potassium dihydrogen phosphate (P), were started following the procedure in previous works [42,45,46]. The solutions were added to soil by splitting the total dose, 10 mL for each additive, over 5 days of applications to avoid or at least minimize possible toxic effects on plants [8]. Control microcosms (C) with untreated soil were run simultaneously. The pots were arranged in a completely randomized design and three replicates for control and twelve replicates for each treatment were prepared, with a total of 27 microcosms.
At the end of treatment, plants were harvested, separating roots from shoots, and prepared for analysis.
After the first harvest three further growing cycles were performed. The experimental design including the first growing cycle is reported in Figure 1. At each re-growth, the same sowing and treatment procedure was adopted. In some microcosms the treatments were repeated, while in other pots the treatments were stopped (nt, not treated). At the end of the fourth growing cycle, microcosms received the additive, T or P, only one time (T/nt/nt/nt or P/nt/nt/nt), two times (T/T/nt/nt or P/P/nt/nt), three times (T/T/T/nt or P/P/P/nt) and four times (T/T/T/T or P/P/P/P).
About 2 months passed between one harvest and another. The plants were watered daily or as necessary.
At each growing cycle, 10 days after the end of treatments, all plants were harvested and aerial parts were separated from roots. Vegetal samples were washed with deionized water and roots were further washed in an ultrasound bath (Branson Sonifier 250 ultrasonic processor; Branson, Danbury, CT, USA) for 10 min to eliminate the possible soil particles remaining on radical surfaces.
The dry mass of shoots and roots was gravimetrically determined after drying in a ventilated oven at 50 °C to a constant weight. Dry plant samples were ground into a fine powder and digested with acid for metal analysis. The plants were evaluated in terms of growth (biomass values), accumulation, translocation and uptake of Hg and As.
Metal content in soil and plant samples was determined in accordance with EPA Method 3051A [39] and EPA Method 3052 [47], respectively.
Samples were digested with HNO3 (65%, v/v) and H2O2 (30%, v/v) mixture in a PTEF-TMF (polytetrafluoroethylene-tetra-fluoromethoxil) pressure digestion vessel using a microwave oven (FKV-ETHOS 900). Total Hg and As concentrations in digested samples and soil extracts were determined using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) with Liberty AX Varian spectrometer.
Metal concentrations were expressed in milligrams per kilogram dry weight (mg kg−1). All data reported are the average of three replicates.
Quality assurance and quality control were performed by testing the standard solution every 10 samples. Certified reference material (BCR n°141) was used to control the quality of the analytical system. Detection limits were 2 μg L−1 for Hg and 5 μg L−1 for As, respectively. The recovery of spiked samples ranged from 93 to 101% with a RSD of 1.91 of the mean.
All statistical analysis was performed using STATISTICA version 6.0 (Statsoft, Inc., Tulsa, OK, USA). Treatments effects were analyzed using one-way analysis of variance (ANOVA). Differences among means were compared and a post-hoc analysis of variance was performed using the Tukey Honestly Significant Difference test (p < 0.05).
Soil was characterized by the following parameters: pH 8, clay 7.1%, silt 13.1%, sand 79.8%, CEC 15.6 cmol(+)kg−1, organic matter 1.48%, total N 0.08%. Metal concentrations wereAs 37.6 and Hg 67.0 mg kg−1 soil.
Bioavailable metals are the fraction of the total amount of metals in soil available for plant uptake in a given time period [13,15,48]. Bioavailability evaluation is essential for phytoextraction tests, since only the amount present in soil solution can be taken up by plants [16,49].
The sequential extractionsadopted provided useful information on mobility and long-term bioavailability of metals in soil (Table 1).
Since Hg was not extracted by NH4Cl, most of it should be considered strongly bound to soil surfaces. Thiosulfate extracted about 16% of Hg total concentration. The action of thiosulfate may be ascribed to Hg affinity for thiol groups, with consequent formation of complexes with sulfur containing ligands [50]. Previous studies have shown the effectiveness of thiosulfate for increasing Hg bioavailability in soil [29,51,52,53,54]. Also, the As extractability test revealed a low solubility of this element in the soil used. Readily bioavailable As, extracted by NaNO3, was negligible, whereas KH2PO4 extracted about 20% of the total concentration. This last extractant interacts with As fractions specifically adsorbed on soil surfaces. This solubilization can be explained by competition between phosphate and arsenate ions for soil sorption sites [55,56,57]. These ions have a high chemical similarity in that phosphate moves the As adsorbed on soil constituents through competitive exchange [58].
These data indicate that it is only possible to solubilize sufficient amounts of the two metals by adding thiosulfate and phosphate. Since the aim of this study was to evaluate the results of consecutive phytoextraction cycles, repeated soil extractions were also performed. Thiosulfate was used as an extractant for Hg and As. For As, phosphate was also used.
As expected, when the extractions were repeated, the bioavailable amount of Hg and As in soil tended to decrease (Figure 2). After the second consecutive extraction, Hg concentration was significantly reduced by 67% and then tended to decrease to zero at the fifth extraction. Likewise, As extractability showed a progressive reduction, similar for both extractants used.
With a view to plant growth, results suggest that more treatments with these additives can effectively mobilize additional amounts of phytoavailable metals. The use of mobilizing agents can promote the phytoextraction process of Hg and As and enhance metal uptake in plants. However, after about five repeated extractions, further metal amounts cannot be released from soil. A residual fraction of metal remains irreversibly bound to soil surfaces. This fraction is nearly inert and not considered dangerous for human health and the environment [3].
In phytoextraction tests, it is necessary to evaluate the re-growth capacity of plants in contaminated soil, since repeated harvests may be required to reduce metal amounts to acceptable levels in the soil [59,60]. B. juncea showed high tolerance for elevated concentrations of Hg and As, and throughout the course of the experiment (four growing cycles) no visual symptoms of phytotoxicity were detected, either in control or treated soils. B. juncea biomass production of each re-growth is reported in Table 2.
Growing Cycle 1 | Growing Cycle 2 | Growing Cycle 3 | Growing Cycle 4 | |||||
Treatment | Biomass | Treatment | Biomass | Treatment | Biomass | Treatment | Biomass | |
Shoot | C | 0.43 ± 0.11 | C/C | 0.52 ± 0.12 | C/C/C | 0.41 ± 0.14 | C/C/C/C | 0.34 ± 0.18 |
T | 0.52 ± 0.15 | T/nt | 0.10 ± 0.04 | T/nt/nt | 0.38 ± 0.10 | T/nt/nt/nt | 0.33 ± 0.12 | |
T/T | 0.30 ± 0.05 | T/T/nt | 0.29 ± 0.08 | T/T/nt/nt | 0.25 ± 0.08 | |||
T/T/T | 0.22 ± 0.12 | T/T/T/nt | 0.29 ± 0.10 | |||||
T/T/T/T | 0.12 ± 0.04 | |||||||
P | 0.49 ± 0.08 | P/nt | 0.37 ± 0.08 | P/nt/nt | 0.43 ± 0.11 | P/nt/nt/nt | 0.25 ± 0.13 | |
P/P | 0.68 ± 0.11 | P/P/nt | 0.50 ± 0.13 | P/P/nt/nt | 0.35 ± 0.09 | |||
P/P/P | 0.40 ± 0.09 | P/P/P/nt | 0.42 ± 0.11 | |||||
P/P/P/P | 0.39 ± 0.08 | |||||||
Root | C | 0.11 ± 0.08 | C/C | 0.04 ± 0.005 | C/C/C | 0.03 ± 0.02 | C/C/C/C | 0.03 ± 0.01 |
T | 0.10 ± 0.02 | T/nt | 0.03 ± 0.004 | T/nt/nt | 0.03 ± 0.01 | T/nt/nt/nt | 0.08 ± 0.02 | |
T/T | 0.02 ± 0.005 | T/T/nt | 0.04 ± 0.01 | T/T/nt/nt | 0.06 ± 0.02 | |||
T/T/T | 0.02 ± 0.005 | T/T/T/nt | 0.07 ± 0.02 | |||||
T/T/T/T | 0.02 ± 0.005 | |||||||
P | 0.11 ± 0.04 | P/nt | 0.05 ± 0.01 | P/nt/nt | 0.06 ± 0.02 | P/nt/nt/nt | 0.08 ± 0.01 | |
P/P | 0.02 ± 0.005 | P/P/nt | 0.05 ± 0.03 | P/P/nt/nt | 0.07 ± 0.02 | |||
P/P/P | 0.06 ± 0.02 | P/P/P/nt | 0.08 ± 0.02 | |||||
P/P/P/P | 0.09 ± 0.03 |
The decreased yield following thiosulfate addition can be ascribed to the increased Hg uptake by plants. As also observed by Pedron et al. [46], repeated thiosulfate treatments appear to increase the phytotoxic effect due to Hg, which can also adversely affect root development and consequently the growth of the entire plant [20,61].Phosphate addition did not promote Hg uptake and the biomass production remained nearly the same. Radical yield was fairly similar among various re-growths, with a trend of reduction compared to biomass of the first growth.
In this experiment, the potential toxic effect of Hg and As was probably opposed by phosphorus and sulfur fertilization, which facilitated the plants' growth. Splitting the total dose of mobilizing agents also helped minimize phytotoxic effects [62,63]. Thiosulfate and phosphate are frequently used in phytoremediation at lab scale, since they can act both as mobilizing and detoxifying agents or nutrients, increasing sulfur, phosphorus and nitrogen availability in soil. In particular, sulfur seems to stimulate the plant's defensive systems through synthesis of sulfur-containing metabolites (glutathione and phytochelatins), allowing intracellular As detoxification processes [64,65,66]. Wu et al. [67] reported that in presence of high metal concentrations in soil, an elevated content of sulfur in B. juncea shoots was found, suggesting a possible physiological need of plants for metal tolerance mechanisms. In several studies [68,69,70,71], a biomass increase after phosphorus fertilization in different plant species grown in presence of As was observed. The influence of phosphorus nutrition on plant arsenate metabolism is probably due to interaction between both ions for biochemical processes in cell roots [72], causing a decrease in As phytotoxicity [73]. Tu and Ma [74] noted that As stimulated phosphorus uptake in Pteris vittata, producing a growth benefit and mitigating As phytotoxicity. However, considerable contradictory data remain regarding the influence of Hg and As on plant growth, so complete knowledge of tolerance mechanisms in plants is lacking. In phytoextraction field implementation, various agronomic strategies might be further considered to increase the vegetal biomass and reduce the phytotoxic effects of metals.
Addition of mobilizing agents significantly increased the Hg and As concentration in B. juncea tissues. Phosphate and thiosulfate similarly influenced As absorption by plants. The As concentration increased greatly compared to control plants, in which the metal concentration was below the detection limit. Only the addition of thiosulfate significantly increased the Hg concentration; obviously phosphate had no influence on Hg uptake, so no data are reported.
In the repeated phytoextraction cycles, the effects of additives on metal concentrations in plants are reported in Tables 3 and 4.
Growing Cycle 1 | Growing Cycle 2 | Growing Cycle 3 | Growing Cycle 4 | |||||
Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | |
Shoot | C | 0.52 ± 0.1 | C/C | 1.47 ± 0.6 | C/C/C | 1.42 ± 0.5 | C/C/C/C | 0.80 ± 0.4 |
T | 121 ± 20 | T/nt | 52.8 ± 12 | T/nt/nt | 21.4 ± 4.8 | T/nt/nt/nt | 16.9 ± 2.3 | |
T/T | 173 ± 26 | T/T/nt | 63.8 ± 9.8 | T/T/nt/nt | 15.2 ± 1.7 | |||
T/T/T | 104 ± 16 | T/T/T/nt | 61.4 ± 14 | |||||
T/T/T/T | 96.4 ± 15 | |||||||
Roots | C | 33.1 ± 12 | C/C | 18.6 ± 2.3 | C/C/C | 12.8 ± 1.8 | C/C/C/C | 4.23 ± 0.3 |
T | 834 ± 42 | T/nt | 161 ± 15 | T/nt/nt | 99.5 ± 10 | T/nt/nt/nt | 56.0 ± 2.8 | |
T/T | 399 ± 28 | T/T/nt | 151 ± 16 | T/T/nt/nt | 104 ± 11 | |||
T/T/T | 558 ± 29 | T/T/T/nt | 452 ± 34 | |||||
T/T/T/T | 561 ± 22 |
Growing Cycle 1 | Growing Cycle 2 | Growing Cycle 3 | Growing Cycle 4 | |||||
Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | |
Shoot | C | bdl | C/C | bdl | C/C/C | bdl | C/C/C/C | bdl |
T | 7.32 ± 1.0 | T/nt | 5.53 ± 1.2 | T/nt/nt | 3.21 ± 0.8 | T/nt/nt/nt | 2.17 ± 0.8 | |
T/T | 6.62 ± 0.9 | T/T/nt | 4.70 ± 1.2 | T/T/nt/nt | 3.12 ± 1.2 | |||
T/T/T | 9.68 ± 1.3 | T/T/T/nt | 7.5 ± 0.3 | |||||
T/T/T/T | 13.1 ± 0.9 | |||||||
P | 7.35 ± 1.2 | P/nt | 4.75 ± 0.8 | P/nt/nt | 2.81 ± 0.4 | P/nt/nt/nt | 1.59 ± 0.6 | |
P/P | 7.81 ± 1.4 | P/P/nt | 6.6 ± 0.9 | P/P/nt/nt | 4.8 ± 0.1 | |||
P/P/P | 15.4 ± 1.5 | P/P/P/nt | 12.1 ± 0.7 | |||||
P/P/P/P | 18.6 ± 1.1 | |||||||
Roots | C | bdl | C/C | bdl | C/C/C | bdl | C/C/C/C | bdl |
T | 45.9 ± 7.2 | T/nt | 32.7 ± 8.2 | T/nt/nt | 25.9 ± 6.5 | T/nt/nt/nt | 12.3 ± 1.6 | |
T/T | 108 ± 15 | T/T/nt | 37.2 ± 5.4 | T/T/nt/nt | 14.2 ± 0.8 | |||
T/T/T | 85.1 ± 15 | T/T/T/nt | 25.9 ± 5.2 | |||||
T/T/T/T | 60.5 ± 4.8 | |||||||
P | 97.5 ± 6.3 | P/nt | 86.1 ± 11 | P/nt/nt | 80.2 ± 12 | P/nt/nt/nt | 71.3 ± 14 | |
P/P | 154 ± 19 | P/P/nt | 96.2 ± 9.8 | P/P/nt/nt | 66.4 ± 14 | |||
P/P/P | 105 ± 12 | P/P/P/nt | 59.2 ± 12 | |||||
P/P/P/P | 68.8 ± 10 | |||||||
bdl: below detection limits. |
Regarding Hg, thiosulfate addition increased the metal's mobility, thereby significantly increasing the concentration in shoots and roots of B. juncea with respect to controls. Data showed that without one further addition of thiosulfate (T/nt) the concentration of the Hg dropped from 121 to 52.8 mg kg−1 from the first to the second cycle. On the contrary, if the thiosulfate was added a second time, Hg concentration increased compared to that found in the first cycle, from 121 to 173 mg kg−1. In the third growing cycle, Hg concentration decreased from 52.8 to 21.4 mg kg−1 if no more thiosulfate treatment was added to soil. The same trend also occurred in the microcosms treated with thiosulfate in the previous two cycles but not in the third (T/T/nt), with concentration values that decreased from 173 to 63.8 mg kg−1. The third addition of thiosulfate (T/T/T) increased the concentration up to 104 mg kg−1. However, this value was lower than that found as the maximum uptake in the second cycle. Finally, in the fourth growth cycle, in microcosms with one addition of thiosulfate (T/nt/nt/nt), the value fell to 16.9 mg kg−1. A similar value, 15.2 mg kg−1 was also found after two thiosulfate additions (T/T/nt/nt). Where thiosulfate was added three times (T/T/T/nt), Hg concentration decreased from 104 to 61.4 mg kg−1 if compared to the previous cycle. After four treatments with thiosulfate (T/T/T/T), the plants tended to accumulate a certain amount of Hg with a mean value of 96.4 mg kg−1. A similar trend is also found for the roots. For example, where only one treatment with thiosulfate (T) was performed, Hg concentration decreased from a value of 834 mg kg−1 in the first cycle to 56.0 mg kg−1 in the fourth cycle (T/nt/nt/nt). Where thiosulfate was added four times (T/T/T/T), data show that the roots continued to absorb a certain amount of Hg.
Treatment with phosphate increased the amount of As in B. juncea aerial parts. Without further addition of phosphate, this amount tended to decrease in the subsequent growth cycles, going from 7.35 mg kg−1 to the final value of 1.59 mg kg−1. When the phosphate treatment was repeated (P/P in the second cycle), the plants absorbed an amount of As similar to that of the first cycle. This quantity remained constant even in the third cycle in the absence of any further addition of mobilizing agent (P/P/nt) and slightly decreased in the fourth cycle (P/P/nt/nt). In the third growth cycle, when the phosphate was added three times (P/P/P) the As concentration in the aerial part rose to 15.4 mg kg−1. In the fourth cycle of growth, where phosphate solution was not added, As concentration decreased slightly, whilefurther addition of phosphate (P/P/P/P) increased the value up to 18.6 mg kg−1. It is well-known that phosphate ion is the specific mobilizing agent for As. The addition of thiosulfate caused an absorption trend of As similar to that resulting from the addition of phosphate, with an increase in the amount of As absorbed by B. juncea compared to controls. When the treatment was not repeated, the concentration of As in the aerial part tended to decrease from 7.32 mg kg−1 in the first cycle to 2.17 mg kg−1 in the fourth cycle. When treatment with thiosulfate was repeated, the amount of As absorbed by the plant increased up to 13.1 mg kg−1 in the fourth cycle (T/T/T/T). When the thiosulfatetreatments were not repeated, there was a decreased As concentration in B. juncea plants in each cycle of growth, with a pattern similar to that described for microcosms treated with phosphate. Data regarding plant uptake showed the existence of a residual bioavailability of As in soil after the first treatments, and its increase with subsequent additions of both phosphate and thiosulfate in the following growing cycles.
In agreement with several findings [3,69,75,76], Hg and As concentration in shoot tissues was significantly lower than in root tissues, indicating low mobility of metals within the plants. Hg and As remained stored in radical cells due to the roots' defensive mechanism [42]. Both the plant's specific features and the soil component can influence the uptake and the translocation of metals [5]. To obtain an efficient phytoextraction process, themetal fraction mobilized with additives should not only be taken up into roots but also subsequently transported to the easily harvestable plant portion. The ratio of metal concentration in shoot to root, translocation factor (TF), describes a plant's ability to move the metal from the root system to aboveground tissues. Species with TF ≥ 1 are generally considered hyperaccumulators [11,77,78,79], while the species with TF values slightly less than 1 are considered potentially suitable for phytoextraction. In this experiment TF values were considerably lower than 1, although the effect of treatments was relevant. Although the TF values were found to be low, B. juncea has a well-known high phytoextraction potential [6,80,81]. In fact, it is considered a metal-tolerant plant. The lower metal concentrations in plant tissues, compared to hyperaccumulator species, are balanced by higher biomass and faster growth rates that allow a greater total extraction [82].
In each growing cycle, Hg and As were concentrated mainly in roots rather than in shoots; however, in the time span of each growth cycle (about 30 days), the plants partially moved the absorbed metals from roots to aerial parts. Thiosulfate improved the translocation of Hg in B. juncea aerial parts although TFs remained considerably lower than 1. Similar results [51] have been reported for Lepidium sativum, in which Hg translocation increased tenfold after thiosulfate addition, compared to control plants. No significant effect of phosphate on TF of As for Pityrogramma calomelanos species has been reported [83]. However, metaltranslocation in plants is influenced by several factors such as plant species, soil properties and soil metal concentration [84,85].
The "total accumulation" was evaluated to obtain the total metal amount extracted by plants, calculating the product of metal concentration and the aerial biomass. This parameter provides an estimation of phytoextraction efficiency, since it includes both metal uptake and vegetal biomass production [86]. Data of total accumulation showed the mobilizing agents' effectiveness on phytoextraction of both metals more clearly (Figures 3 and 4).
The continued extractive action of plants during more than one cycle of growth increased the removal of the bioavailable fraction. Although the laboratory data do not provide definite conclusions regarding performance in the field, the results suggested a potential applicability of repeated assisted phytoextraction for this soil.
In the aerial part, the addition of thiosulfate drastically increased the total accumulation of Hg. By further additions of thiosulfate, interesting values of total accumulation of Hg are obtained. In the roots the trend was generally similar to that of the aerial part.
Concerning As, the addition of phosphate increased the total accumulation in the aerial part. At each re-growth, further increases in total accumulation occurred only when phosphate was added. The addition of thiosulfate increased the total accumulation of As compared to controls; however, this parameter tended to decrease at each subsequent re-growth. For both metals, the trend of total accumulation is ascribable to the toxic effect of Hg, which is absorbed by the plant due to the addition of thiosulphate, causing decreased biomass production.
Both extractability tests and microcosm experiments show that more than one treatment with the additives used can effectively mobilize increasing amounts of metals, exploiting the bioavailable pools. The ability of thiosulfate to induce Hg solubilization in soil and stimulate metal accumulation in plants is well-known [6,42,80]. Some researchers suggest that sulfur releases the Hg from soil sites to form stable complexes that are more easily absorbed by roots and preferentially transported to shoots [5,53,54,87].
The results of this experiment suggest that the thiosulfate also increased As phytoextraction. The increased phytoavailability in soil is probably due to competition between sulfate and arsenate ions for sorption sites on the same surface of oxides [88]. Thus, thiosulfate application in soils co-contaminated with Hg and As can prove an effective solution for simultaneous removal of both elements during assisted phytoextraction remediation, reducing both the time and cost of the phytoextraction process.
After only one harvest, bioavailable fractions of Hg and As still remained in soil. Further growing cycles decrease the bioavailable metal pools. Repeated additions of thiosulfate and phosphate further increased the metal's availability in soil, promoting plant uptake and increasing the metal's removal from contaminated soil.
Using assisted phytoextraction, mobilizing agents that have a short life-span in the soil should be used. The induced mobilization of contaminants must be effective only during the time needed to increase the uptake of the plants and then must disappear quickly enough to prevent leaching. This condition is generally not feasible and the residue contaminants remain in soluble form [89]. Thus, it is likely that contaminants may be leached along the soil profile and this risk must be accurately checked at field scale.
The promising laboratory results of this study need to be confirmed with further studies at field scale, where several agronomic strategies can be adopted to reduce the phytotoxic effects of metals and increase the vegetal biomass, enhancing the feasibility of phytoextraction technology. To obtain greater efficiency in the field, the best combination of numbers of repeated harvests and treatments with mobilizing agents should be evaluated according to the specific characteristics of soil and environmental factors that could influence plant growth at the contaminated site.
This study was supported by Eni S.p.A, Research & Technological Innovation Department, San Donato Milanese (Italy) and fully funded by Syndial S.p.A.
The authors declare that there is no conflict of interest.
[1] |
Lloyd C, Smith J, Weinger K (2005) Stress and Diabetes: A Review of the Links. Diabetes Spectrum 18: 121-127. https://doi.org/10.2337/diaspect.18.2.121 ![]() |
[2] |
Manni L, Fausto VD, Fiore M, et al. (2008) Repeated Restraint and Nerve Growth Factor Administration in Male and Female Mice: Effect on Sympathetic and Cardiovascular Mediators of the Stress Response. Curr Neurovasc Res 5: 1-12. https://doi.org/10.2174/156720208783565654 ![]() |
[3] |
Wirtz PH, Redwine LS, Baertschi C, et al. (2008) Coagulation activity before and after acute psychosocial stress increases with age. Psychosom Med 70: 476-481. https://doi.org/10.1097/PSY.0b013e31816e03a5 ![]() |
[4] |
Quick SK, Shields PG, Nie J, et al. (2008) Effect modification by catalase genotype suggests a role for oxidative stress in the association of hormone replacement therapy with postmenopausal breast cancer risk. Cancer Epidemiol Biomarkers Prev 17: 1082-1087. https://doi.org/10.1158/1055-9965.EPI-07-2755 ![]() |
[5] |
Chaplin TM, Hong K, Bergquist K, et al. (2008) Gender differences in response to emotional stress: an assessment across subjective, behavioral, and physiological domains and relations to alcohol craving. Alcohol Clin Exp Res 32: 1242-1250. https://doi.org/10.1111/j.1530-0277.2008.00679.x ![]() |
[6] |
Harris RBS, Mitchell TD, Simpson J, et al. (2002) Weight loss in rats exposed to repeated acute restraint stress is independent of energy or leptin status. Am J Physiol Regulatory Integrative Comp Physiol 282: R77-R88. https://doi.org/10.1152/ajpregu.2002.282.1.R77 ![]() |
[7] |
Hamer M, Stamatakis E (2008) Inflammation as an intermediate pathway in the association between psychosocial stress and obesity. Physiol Behav 94: 536-539. https://doi.org/10.1016/j.physbeh.2008.03.010 ![]() |
[8] |
Vallès A, Martí O, García A, et al. (2000) Single exposure to stressors causes long-lasting, stress-dependent reduction of food intake in rats. Am J Physiol Regulatory Integrative Comp Physiol 279: R1138-R1144. https://doi.org/10.1152/ajpregu.2000.279.3.R1138 ![]() |
[9] |
Charrier C, Chigr F, Tardivel C, et al. (2006) BDNF regulation in the rat dorsal vagal complex during stress-induced anorexia. Brain Res 1107: 52-57. https://doi.org/10.1016/j.brainres.2006.05.099 ![]() |
[10] |
Adam TC, Epel ES (2007) Stress, eating and the reward system. Physiol Behav 91: 449-458. https://doi.org/10.1016/j.physbeh.2007.04.011 ![]() |
[11] |
Laurent L, Jean A, Manrique C (2013) Anorexia and drugs of abuse abnormally suppress appetite, the result of a shared molecular signal foul-up. Animal Models of Eating Disorders . Totowa: Humana Press 319-331. https://doi.org/10.1007/978-1-62703-104-2_19 ![]() |
[12] |
Gu H, Tang C, Yang Y (2012) Psychological stress, immune response, and atherosclerosis. Atheroscler 223: 69-77. https://doi.org/10.1016/j.atherosclerosis.2012.01.021 ![]() |
[13] |
Paskitti ME, McCreary BJ, Herman JP (2000) Stress regulation of adrenocorticosteroid receptor gene transcription and mRNA expression in rat hippocampus: time-course analysis. Mol Brain Res 80: 142-152. https://doi.org/10.1016/S0169-328X(00)00121-2 ![]() |
[14] |
Johnson JD, Barnard DF, Kulp AC, et al. (2019) Neuroendocrine regulation of brain cytokines after psychological stress. J Endocr Soc 3: 1302-1320. https://doi.org/10.1210/js.2019-00053 ![]() |
[15] |
Chigr F, Rachidi F, Tardivel C, et al. (2014) Modulation of orexigenic and anorexigenic peptides gene expression in the rat DVC and hypothalamus by acute immobilization stress. Front Cell Neurosci 8: 198. https://doi.org/10.3389/fncel.2014.00198 ![]() |
[16] |
Hayashi T (2014) Conversion of psychological stress into cellular stress response: Roles of the sigma-1 receptor in the process. Psychiatry Clin Neurosci 69: 179-191. https://doi.org/10.1111/pcn.12262 ![]() |
[17] |
Chaudhari N, Talwar P, Parimisetty A, et al. (2014) A molecular web: endoplasmic reticulum stress, inflammation, and oxidative stress. Front Cell Neurosci 8: 213. https://doi.org/10.3389/fncel.2014.00213 ![]() |
[18] |
Santos CXC, Tanaka LY, Wosniak JJ, et al. (2009) Mechanisms and implications of reactive oxygen species generation during the unfolded protein response: roles of endoplasmic reticulum oxidoreductases, mitochondrial electron transport, and NADPH oxidase. Antioxid Redox Signal 11: 2409-2427. https://doi.org/10.1089/ars.2009.2625 ![]() |
[19] |
Bernasconi R, Molinari M (2011) ERAD and ERAD tuning: disposal of cargo and of ERAD regulators from the mammalian ER. Curr Opin Cell Biol 23: 176-183. https://doi.org/10.1016/j.ceb.2010.10.002 ![]() |
[20] |
Chaudhuri O, Koshy ST, Da Cunha CB, et al. (2014) Extracellular matrix stiffness and composition jointly regulate the induction of malignant phenotypes in mammary epithelium. Nat Mater 13: 970-8. https://doi.org/10.1038/NMAT4009 ![]() |
[21] |
Ellman GL, Courtney KD, Andres JV, et al. (1961) A new and rapid colorimetric determination of acetylcholinesterase activity. Biochem Pharmacol 7: 88-95. https://doi.org/10.1016/0006-2952(61)90145-9 ![]() |
[22] |
Buege JA, Aust SD (1978) Microsomal lipid peroxidation. Methods Enzymol 105: 302-310. https://doi.org/10.1016/S0076-6879(78)52032-6 ![]() |
[23] |
Aebi H (1974) Catalase. Methods Enzym Anal 2: 673-684. https://doi.org/10.1016/B978-0-12-091302-2.50032-3 ![]() |
[24] |
Flohe L, Gunzler WA (1984) Assays of glutathione peroxidase. Methods Enzymol 105: 114-121. https://doi.org/10.1016/S0076-6879(84)05015-1 ![]() |
[25] |
Habig WH, Pabst MJ, Jakoby WB (1974) Glutathione-S-transferase the first step in mercapturic acid formation. J Biol Chem 249: 7130-9. ![]() |
[26] |
Asada K, Takahashi M, Nagate M (1974) Assay and inhibitors of spinach superoxide dismutase. Agric Biol Chem 38: 471-473. https://doiorg/10.1080/00021369.1974.10861178 ![]() |
[27] |
Lowry OH, Rosebrough NJ, Farr AL, et al. (1951) Protein measurement with the Folin phenol reagent. J Biol Chem 193: 265-275. ![]() |
[28] |
Kovács LÁ, Schiessl JA, Nafz AE, et al. (2018) Both basal and acute restraint stress-induced c-Fos expression is influenced by age in the extended amygdala and brainstem stress centers in male rats. Front Aging Neurosci 10: 248. https://doi.org/10.3389/fnagi.2018.00248 ![]() |
[29] |
Bland ST, Schmid MJ, Der-Avakian A, et al. (2005) Expression of c-fos and BDNF mRNA in subregions of the prefrontal cortex of male and female rats after acute uncontrollable stress. Brain Res 1051: 90-99. https://doi.org/10.1016/j.brainres.2005.05.065 ![]() |
[30] | Migdal C, Serres M (2011) Espèces réactives de l'oxygène et stress oxydant. Med Sci 27: 405-412. https://doi.org/10.1051/medsci/2011274017 |
[31] |
Cherian DA, Peter T, Narayanan A, et al. (2019) Malondialdehyde as a marker of oxidative stress in periodontitis patients. J Pharm Bioallied Sci 11: S297-S300. https://doi.org/10.4103/JPBS.JPBS_17_19 ![]() |
[32] | Tirani MM, Haghjou MM (2019) Reactive oxygen species (ROS), total antioxidant capacity (AOC) and malondialdehyde (MDA) make a triangle in evaluation of zinc stress extension. J Anim Plant Sci 29: 1100-1111. |
[33] |
Čolović M, Krstić D, Petrović S, et al. (2010) Toxic effects of diazinon and its photodegradation products. Toxicol Lett 193: 9-18. https://doi.org/10.1016/j.toxlet.2009.11.022 ![]() |
[34] |
Akhgari M, Abdollahi M, Kebryaeezadeh A, et al. (2003) Biochemical evidence for free radicalinduced lipid peroxidation as a mechanism for subchronic toxicity of malathion in blood and liver of rats. Hum Exp Toxicol 22: 205-11. https://doi.org/10.1191/0960327103ht346oa ![]() |
[35] | Abdollahi M, Ranjbar A, Shadnia S, et al. (2004) Pesticides and oxidative stress: a review. Med Sci Monit 10: 141-7. |
[36] |
Dal-Zotto S, Martí O, Delgado R, et al. (2004) Potentiation of glucocorticoid release does not modify the long-term effects of a single exposure to immobilization stress. Psychopharmacology 177: 230-237. https://doi.org/10.1007/s00213-004-1939-y ![]() |
[37] |
Akkerman S, Blokland A, Reneerkens O, et al. (2012) Object recognition testing: Methodological considerations on exploration and discrimination measures. Behav Brain Res 232: 335-347. https://doi.org/10.1016/j.bbr.2012.03.022 ![]() |
[38] |
Parent MB, Baxter MG (2004) Septohippocampal Acetylcholine: Involved in but not Necessary for Learning and Memory?. Learn Mem 11: 9-20. https://doi.org/10.1101/lm.69104 ![]() |
[39] |
Micheau J, Marighetto A (2011) Acetylcholine and memory: A long, complex and chaotic but still living relationship. Behav Brain Res 221: 424-429. https://doi.org/10.1016/j.bbr.2010.11.052 ![]() |
[40] |
Deschamps R, Moulignier A (2005) La mémoire et ses troubles Memory and related disorders. EMC- Neurol 2: 505-525. https://doi.org/10.1016/j.emcn.2005.07.003 ![]() |
[41] |
Hasselmo ME (2006) The role of acetylcholine in learning and memory. Curr Opin Neurobiol 6: 710-715. https://doi.org/10.1016/j.conb.2006.09.002 ![]() |
[42] |
Picciotto MR, Higley MJ, Mineur YS (2012) Acetylcholine as a neuromodulator: cholinergic signaling shapes nervous system function and behavior. Neuron 76: 116-129. https://doi.org/10.1016/j.neuron.2012.08.036 ![]() |
[43] |
Haam J, Yakel JL (2017) Cholinergic modulation of the hippocampal region and memory function. J Neurochem 142: 111-121. https://doi.org/10.1111/jnc.14052 ![]() |
[44] |
Newman EL, Gupta K, Climer JR, et al. (2012) Cholinergic modulation of cognitive processing: insights drawn from computational models. Front Behav Neurosci 6: 24. https://doi.org/10.3389/fnbeh.2012.00024 ![]() |
[45] |
Torres LF, Duchen LW (1987) The mutant mdx: inherited myopathy in the mouse: morphological studies of nerves, muscles and end-plates. Brain 110: 269-99. https://doi.org/10.1093/brain/110.2.269 ![]() |
[46] |
Hedner M, Larsson M, Arnold N, et al. (2010) Cognitive factors in odor detection, odor discrimination, and odor identification tasks. J Clin Exp Neuropsychol 32: 1062-7. https://doi.org/10.1080/13803391003683070 ![]() |
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Growing Cycle 1 | Growing Cycle 2 | Growing Cycle 3 | Growing Cycle 4 | |||||
Treatment | Biomass | Treatment | Biomass | Treatment | Biomass | Treatment | Biomass | |
Shoot | C | 0.43 ± 0.11 | C/C | 0.52 ± 0.12 | C/C/C | 0.41 ± 0.14 | C/C/C/C | 0.34 ± 0.18 |
T | 0.52 ± 0.15 | T/nt | 0.10 ± 0.04 | T/nt/nt | 0.38 ± 0.10 | T/nt/nt/nt | 0.33 ± 0.12 | |
T/T | 0.30 ± 0.05 | T/T/nt | 0.29 ± 0.08 | T/T/nt/nt | 0.25 ± 0.08 | |||
T/T/T | 0.22 ± 0.12 | T/T/T/nt | 0.29 ± 0.10 | |||||
T/T/T/T | 0.12 ± 0.04 | |||||||
P | 0.49 ± 0.08 | P/nt | 0.37 ± 0.08 | P/nt/nt | 0.43 ± 0.11 | P/nt/nt/nt | 0.25 ± 0.13 | |
P/P | 0.68 ± 0.11 | P/P/nt | 0.50 ± 0.13 | P/P/nt/nt | 0.35 ± 0.09 | |||
P/P/P | 0.40 ± 0.09 | P/P/P/nt | 0.42 ± 0.11 | |||||
P/P/P/P | 0.39 ± 0.08 | |||||||
Root | C | 0.11 ± 0.08 | C/C | 0.04 ± 0.005 | C/C/C | 0.03 ± 0.02 | C/C/C/C | 0.03 ± 0.01 |
T | 0.10 ± 0.02 | T/nt | 0.03 ± 0.004 | T/nt/nt | 0.03 ± 0.01 | T/nt/nt/nt | 0.08 ± 0.02 | |
T/T | 0.02 ± 0.005 | T/T/nt | 0.04 ± 0.01 | T/T/nt/nt | 0.06 ± 0.02 | |||
T/T/T | 0.02 ± 0.005 | T/T/T/nt | 0.07 ± 0.02 | |||||
T/T/T/T | 0.02 ± 0.005 | |||||||
P | 0.11 ± 0.04 | P/nt | 0.05 ± 0.01 | P/nt/nt | 0.06 ± 0.02 | P/nt/nt/nt | 0.08 ± 0.01 | |
P/P | 0.02 ± 0.005 | P/P/nt | 0.05 ± 0.03 | P/P/nt/nt | 0.07 ± 0.02 | |||
P/P/P | 0.06 ± 0.02 | P/P/P/nt | 0.08 ± 0.02 | |||||
P/P/P/P | 0.09 ± 0.03 |
Growing Cycle 1 | Growing Cycle 2 | Growing Cycle 3 | Growing Cycle 4 | |||||
Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | |
Shoot | C | 0.52 ± 0.1 | C/C | 1.47 ± 0.6 | C/C/C | 1.42 ± 0.5 | C/C/C/C | 0.80 ± 0.4 |
T | 121 ± 20 | T/nt | 52.8 ± 12 | T/nt/nt | 21.4 ± 4.8 | T/nt/nt/nt | 16.9 ± 2.3 | |
T/T | 173 ± 26 | T/T/nt | 63.8 ± 9.8 | T/T/nt/nt | 15.2 ± 1.7 | |||
T/T/T | 104 ± 16 | T/T/T/nt | 61.4 ± 14 | |||||
T/T/T/T | 96.4 ± 15 | |||||||
Roots | C | 33.1 ± 12 | C/C | 18.6 ± 2.3 | C/C/C | 12.8 ± 1.8 | C/C/C/C | 4.23 ± 0.3 |
T | 834 ± 42 | T/nt | 161 ± 15 | T/nt/nt | 99.5 ± 10 | T/nt/nt/nt | 56.0 ± 2.8 | |
T/T | 399 ± 28 | T/T/nt | 151 ± 16 | T/T/nt/nt | 104 ± 11 | |||
T/T/T | 558 ± 29 | T/T/T/nt | 452 ± 34 | |||||
T/T/T/T | 561 ± 22 |
Growing Cycle 1 | Growing Cycle 2 | Growing Cycle 3 | Growing Cycle 4 | |||||
Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | |
Shoot | C | bdl | C/C | bdl | C/C/C | bdl | C/C/C/C | bdl |
T | 7.32 ± 1.0 | T/nt | 5.53 ± 1.2 | T/nt/nt | 3.21 ± 0.8 | T/nt/nt/nt | 2.17 ± 0.8 | |
T/T | 6.62 ± 0.9 | T/T/nt | 4.70 ± 1.2 | T/T/nt/nt | 3.12 ± 1.2 | |||
T/T/T | 9.68 ± 1.3 | T/T/T/nt | 7.5 ± 0.3 | |||||
T/T/T/T | 13.1 ± 0.9 | |||||||
P | 7.35 ± 1.2 | P/nt | 4.75 ± 0.8 | P/nt/nt | 2.81 ± 0.4 | P/nt/nt/nt | 1.59 ± 0.6 | |
P/P | 7.81 ± 1.4 | P/P/nt | 6.6 ± 0.9 | P/P/nt/nt | 4.8 ± 0.1 | |||
P/P/P | 15.4 ± 1.5 | P/P/P/nt | 12.1 ± 0.7 | |||||
P/P/P/P | 18.6 ± 1.1 | |||||||
Roots | C | bdl | C/C | bdl | C/C/C | bdl | C/C/C/C | bdl |
T | 45.9 ± 7.2 | T/nt | 32.7 ± 8.2 | T/nt/nt | 25.9 ± 6.5 | T/nt/nt/nt | 12.3 ± 1.6 | |
T/T | 108 ± 15 | T/T/nt | 37.2 ± 5.4 | T/T/nt/nt | 14.2 ± 0.8 | |||
T/T/T | 85.1 ± 15 | T/T/T/nt | 25.9 ± 5.2 | |||||
T/T/T/T | 60.5 ± 4.8 | |||||||
P | 97.5 ± 6.3 | P/nt | 86.1 ± 11 | P/nt/nt | 80.2 ± 12 | P/nt/nt/nt | 71.3 ± 14 | |
P/P | 154 ± 19 | P/P/nt | 96.2 ± 9.8 | P/P/nt/nt | 66.4 ± 14 | |||
P/P/P | 105 ± 12 | P/P/P/nt | 59.2 ± 12 | |||||
P/P/P/P | 68.8 ± 10 | |||||||
bdl: below detection limits. |
Millán et al. [40] | ||
NH4Cl | (NH4)2S2O3 | |
Hg | Bdl | 10.4 ± 2.3 |
Wenzel et al. [41] | ||
NaNO3 | KH2PO4 | |
As | Bdl | 7.2 ± 0.7 |
bdl: below detection limits. |
Growing Cycle 1 | Growing Cycle 2 | Growing Cycle 3 | Growing Cycle 4 | |||||
Treatment | Biomass | Treatment | Biomass | Treatment | Biomass | Treatment | Biomass | |
Shoot | C | 0.43 ± 0.11 | C/C | 0.52 ± 0.12 | C/C/C | 0.41 ± 0.14 | C/C/C/C | 0.34 ± 0.18 |
T | 0.52 ± 0.15 | T/nt | 0.10 ± 0.04 | T/nt/nt | 0.38 ± 0.10 | T/nt/nt/nt | 0.33 ± 0.12 | |
T/T | 0.30 ± 0.05 | T/T/nt | 0.29 ± 0.08 | T/T/nt/nt | 0.25 ± 0.08 | |||
T/T/T | 0.22 ± 0.12 | T/T/T/nt | 0.29 ± 0.10 | |||||
T/T/T/T | 0.12 ± 0.04 | |||||||
P | 0.49 ± 0.08 | P/nt | 0.37 ± 0.08 | P/nt/nt | 0.43 ± 0.11 | P/nt/nt/nt | 0.25 ± 0.13 | |
P/P | 0.68 ± 0.11 | P/P/nt | 0.50 ± 0.13 | P/P/nt/nt | 0.35 ± 0.09 | |||
P/P/P | 0.40 ± 0.09 | P/P/P/nt | 0.42 ± 0.11 | |||||
P/P/P/P | 0.39 ± 0.08 | |||||||
Root | C | 0.11 ± 0.08 | C/C | 0.04 ± 0.005 | C/C/C | 0.03 ± 0.02 | C/C/C/C | 0.03 ± 0.01 |
T | 0.10 ± 0.02 | T/nt | 0.03 ± 0.004 | T/nt/nt | 0.03 ± 0.01 | T/nt/nt/nt | 0.08 ± 0.02 | |
T/T | 0.02 ± 0.005 | T/T/nt | 0.04 ± 0.01 | T/T/nt/nt | 0.06 ± 0.02 | |||
T/T/T | 0.02 ± 0.005 | T/T/T/nt | 0.07 ± 0.02 | |||||
T/T/T/T | 0.02 ± 0.005 | |||||||
P | 0.11 ± 0.04 | P/nt | 0.05 ± 0.01 | P/nt/nt | 0.06 ± 0.02 | P/nt/nt/nt | 0.08 ± 0.01 | |
P/P | 0.02 ± 0.005 | P/P/nt | 0.05 ± 0.03 | P/P/nt/nt | 0.07 ± 0.02 | |||
P/P/P | 0.06 ± 0.02 | P/P/P/nt | 0.08 ± 0.02 | |||||
P/P/P/P | 0.09 ± 0.03 |
Growing Cycle 1 | Growing Cycle 2 | Growing Cycle 3 | Growing Cycle 4 | |||||
Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | |
Shoot | C | 0.52 ± 0.1 | C/C | 1.47 ± 0.6 | C/C/C | 1.42 ± 0.5 | C/C/C/C | 0.80 ± 0.4 |
T | 121 ± 20 | T/nt | 52.8 ± 12 | T/nt/nt | 21.4 ± 4.8 | T/nt/nt/nt | 16.9 ± 2.3 | |
T/T | 173 ± 26 | T/T/nt | 63.8 ± 9.8 | T/T/nt/nt | 15.2 ± 1.7 | |||
T/T/T | 104 ± 16 | T/T/T/nt | 61.4 ± 14 | |||||
T/T/T/T | 96.4 ± 15 | |||||||
Roots | C | 33.1 ± 12 | C/C | 18.6 ± 2.3 | C/C/C | 12.8 ± 1.8 | C/C/C/C | 4.23 ± 0.3 |
T | 834 ± 42 | T/nt | 161 ± 15 | T/nt/nt | 99.5 ± 10 | T/nt/nt/nt | 56.0 ± 2.8 | |
T/T | 399 ± 28 | T/T/nt | 151 ± 16 | T/T/nt/nt | 104 ± 11 | |||
T/T/T | 558 ± 29 | T/T/T/nt | 452 ± 34 | |||||
T/T/T/T | 561 ± 22 |
Growing Cycle 1 | Growing Cycle 2 | Growing Cycle 3 | Growing Cycle 4 | |||||
Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | Treatment | Concentration | |
Shoot | C | bdl | C/C | bdl | C/C/C | bdl | C/C/C/C | bdl |
T | 7.32 ± 1.0 | T/nt | 5.53 ± 1.2 | T/nt/nt | 3.21 ± 0.8 | T/nt/nt/nt | 2.17 ± 0.8 | |
T/T | 6.62 ± 0.9 | T/T/nt | 4.70 ± 1.2 | T/T/nt/nt | 3.12 ± 1.2 | |||
T/T/T | 9.68 ± 1.3 | T/T/T/nt | 7.5 ± 0.3 | |||||
T/T/T/T | 13.1 ± 0.9 | |||||||
P | 7.35 ± 1.2 | P/nt | 4.75 ± 0.8 | P/nt/nt | 2.81 ± 0.4 | P/nt/nt/nt | 1.59 ± 0.6 | |
P/P | 7.81 ± 1.4 | P/P/nt | 6.6 ± 0.9 | P/P/nt/nt | 4.8 ± 0.1 | |||
P/P/P | 15.4 ± 1.5 | P/P/P/nt | 12.1 ± 0.7 | |||||
P/P/P/P | 18.6 ± 1.1 | |||||||
Roots | C | bdl | C/C | bdl | C/C/C | bdl | C/C/C/C | bdl |
T | 45.9 ± 7.2 | T/nt | 32.7 ± 8.2 | T/nt/nt | 25.9 ± 6.5 | T/nt/nt/nt | 12.3 ± 1.6 | |
T/T | 108 ± 15 | T/T/nt | 37.2 ± 5.4 | T/T/nt/nt | 14.2 ± 0.8 | |||
T/T/T | 85.1 ± 15 | T/T/T/nt | 25.9 ± 5.2 | |||||
T/T/T/T | 60.5 ± 4.8 | |||||||
P | 97.5 ± 6.3 | P/nt | 86.1 ± 11 | P/nt/nt | 80.2 ± 12 | P/nt/nt/nt | 71.3 ± 14 | |
P/P | 154 ± 19 | P/P/nt | 96.2 ± 9.8 | P/P/nt/nt | 66.4 ± 14 | |||
P/P/P | 105 ± 12 | P/P/P/nt | 59.2 ± 12 | |||||
P/P/P/P | 68.8 ± 10 | |||||||
bdl: below detection limits. |