Evaluation of Cu-toxicity in agricultural topsoil

contaminated by different sources in central Chile

J. Tomás Schoffer
Pontificia Universidad Católica de Chile
Humberto Aponte
Universidad de O’Higgins
Alexander Neaman
Universidad de Tarapacá
Luz María de la Fuente
Pontificia Universidad Católica de Chile
Rosanna Ginocchio

Pontificia Universidad Católica de Chile

Article

Keywords: Mining activities, copper-based pesticides, metals, ecotoxicity, field-contaminated soil, orchards

Posted Date: February 29th, 2024

DOI: https://doi.org/10.21203/rs.3.rs-3937690/v1

License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full
License

Additional Declarations: No competing interests reported.

Page 1/15
Abstract
The primary fruit production zone in Chile lies in the lowland areas of the central region, which has a history of soil
copper pollution due to both copper mining (in the highlands) and the use of copper-based pesticides in agriculture.
This study assessed the phytotoxic effect of copper in agricultural topsoil contaminated by different sources in the
region. A total of 13 agricultural sites, including polluted soils and a background unpolluted soil, were sampled, and a
toxicity bioassay was conducted using Lolium perenne. Multiple linear regression models revealed that copper has a
significant negative impact on plant growth, whereas soluble zinc, organic matter, available nitrogen, and clay have
positive effects and mitigate copper toxicity (p < 0.001). The effective concentration at 50% (EC50) of the total soil
copper was 1030 mg kg− 1 for shoot length and 1084 mg kg− 1 for shoot dry mass. These results correspond with the
EC50 values reported in previous studies that also used real-world contaminated soils. Moreover, the findings are
noteworthy as only six studies have estimated copper toxicity thresholds for plants grown in contaminated soils.
Overall, the results highlight the complex nature of copper toxicity in plants grown in soils contaminated by different
sources and underscore the importance of considering multiple factors when assessing the impact of contaminants
on plant growth in soils contaminated by various metals besides copper.

Introduction
Central Chile—a Mediterranean climate-type region—is the primary hub for fruit production in Chile1. Within the lowland
areas of this region, the O'Higgins Region, which extends across 95,082 ha, is notable for its contribution to fruit
production2. However, this particular geographical region has a history of soil copper (Cu) pollution due to either metal
pollution dispersal from Cu mining operations located in the highlands3 or the application of Cu-based pesticides4.
Badilla-Ohlbaum et al.5 sampled agricultural soils downstream of the El Teniente Cu mine and the Caletones smelter
and discovered a wide range of soil total Cu concentrations in the Cachapoal valley, varying between 26 mg kg− 1 and
1,600 mg kg− 1. Meanwhile, Schoffer et al.1 conducted a soil study in the fruit tree orchards of the O´Higgins Region,
and detected total Cu concentrations of 131–432 mg kg− 1, which were attributed solely to the application of Cu-based
pesticides.

Cu solubility indicates the mobility of Cu in soil and, consequently, its potential bioavailability and phytotoxicity6. The
bioavailability of Cu in soil contaminated by different sources varies significantly owing to the distinct chemical
properties of each source7. Badilla-Ohlbaum et al.5 found several Cu minerals, such as chalcopyrite (CuFeS 2),
chalcosine (Cu2S), coveline (CuS), and enargite (Cu3AsS 4), that are associated with mining waste materials, such as
tailings. These minerals are highly insoluble in water8. In contrast, Skeaff et al.9 revealed that the predominant Cu
emission from smelters is CuSO4—a highly soluble and hygroscopic compound8. Considering Cu-based pesticides, the
primary pesticides used in the O'Higgins Region include Bordeaux mixture (CuSO4 + Ca(OH)2), copper hydroxide
(Cu(OH)2), and copper oxychloride (CuCl2·3Cu(OH)2), which account for approximately 26%, 24%, and 20%,
respectively, of the total Cu-based pesticide usage in the region10. Richardson8 referred to copper hydroxide and copper
oxychloride as "fixed copper" owing to their limited solubility. Specifically, copper oxychloride pesticide is typically
applied as a colloidal water suspension11. Consequently, it is transported within the soil matrix as colloidal particles,
which are characterized by their limited solubility12. In contrast, owing to its pronounced solubility, the Bordeaux
mixture exhibits high bioavailability; however, it lacks persistence in the field13.

Studies on Cu toxicity in plants often employ artificially contaminated soils—an approach that has several limitations.
Santa-Cruz et al.14 demonstrated that toxic metal concentrations in artificially contaminated soils are significantly

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higher than those in industrially contaminated soils. This is because metal toxicity depends on the duration of metal
presence in the soil, which is referred to as "aging"15. In their review, Santa-Cruz et al.16 identified only six studies on Cu
toxicity in plants that used industrially contaminated soils, with three of them conducted in the Valparaíso Region of
Chile, which is known for its mining-related Cu contamination17–19. To the best of our knowledge, there are no studies
evaluating the effects of Cu on plants growing in soils in the O'Higgins Region, which is contaminated by Cu from both
mining and Cu-based pesticides. Thus, the objective of this study is to evaluate the effect of Cu on plants using field-
collected agricultural soils from the O'Higgins Region, which is polluted by different Cu sources.

Materials and Methods

Study sites and soil samples
Topsoil from 13 agricultural sites in the O’Higgins Region, central Chile, were sampled. The sampling sites of the
polluted soils were selected based on prior knowledge of the spatial distribution of soil total Cu concentration in the
Cachapoal River basin (Fig. 1 and Fig. 2). One extra sample was taken from agricultural soil near Chimbarongo town,
which has a low level of soil total Cu (51 mg kg− 1), to represent a background soil sample. The sites were chosen such
that a wide range of total Cu concentrations could be obtained. At each site, the soil sample was taken from a
continuous surface of 2 m2 to a depth of 20 cm. A total of 40–60 kg of soil was obtained and used in further toxicity
assays.

Physical–chemical characterization of soil

Each soil sample was sieved through a 2 mm nylon mesh and dried at 40°C until a constant mass was obtained. The
soil pH (KNO3), electric conductivity (EC), organic matter (OM), and available nitrogen (N), phosphorus (P), and
potassium (K) were determined through routine methods20. The soluble Cu and zinc (Zn) were extracted using a 0.1 M
KNO3 solution21. To determine the total concentrations of Cu, Zn, lead (Pb), and arsenic (As) in the soil, the samples
were subjected to a digestion process for 12 h involving boiling nitric acid, followed by the addition of perchloric acid.
To prevent the volatilization of As during the digestion process, a Teflon stopper was employed along with a 30 cm
glass reflux tube22. The total soil concentrations of Cu, Pb, and Zn were subsequently quantified using atomic
absorption spectroscopy with the GBC SensAA system. The total As concentration was determined using an atomic
absorption spectrophotometer—Thermo iCE 3000 series AA spectrometer (USA)—in conjunction with a hydride vapor
generator (model VP100). To ensure the precision and accuracy of our analysis, duplicate digestion procedures were
carried out on certified reference samples, namely, PACS-2 from the National Research Council of Canada and GRX-2
from the United States Geological Survey. The results obtained using these certified reference samples were accurate
to within 10% of the certified values, thereby validating the reliability of our analytical approach.

Toxicity bioassay with Lolium perenne

The toxicity bioassay was based on the procedure outlined by Verdejo et al. (2015). The experimental unit consisted of
1 L plastic pots (11 cm lower diameter × 12 cm height × 15 cm upper diameter) wrapped in aluminum foil. The pots
were filled with 480 g of sieved sample soils (2 mm) and moistened to 70% of their water-holding capacity (WHC),
respectively. The soils were chemically stabilized by maintaining them in a greenhouse under controlled temperature
conditions (26 ± 2°C) for three weeks; the soil humidity was monitored and controlled on a daily basis to adjust the
WHC to 70%. After three weeks, 60 mg of Lolium perenne seeds were sown in each pot. The temperature and soil
moisture levels were consistently maintained during the 28-day bioassay period. After 28 days of incubation, the L.

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perenne plants were harvested and their shoot length (SL) and shoot dry mass (SDM) were determined as indicators of
the plant's responses to soil pollutants. The procedure was performed in quintuplicate for each soil sample.
Statistical analysis
Multiple linear regression models were used to explain the variance of SL and SDM with the changes in the soil
physicochemical properties. To achieve this, a sequential simplification was performed from a full model. The
physicochemical properties that showed significant correlations with each dependent variable were considered for the
full model. Highly correlated physicochemical properties were partly removed to avoid collinearity. The first model (i.e.,
the full model) was built using the variables obtained after evaluating correlations and collinearity. The selected
variables were obtained after the sequential omission of insignificant variables based on insignificant results obtained
with the model so as to create a model that only comprises significant explanatory variables. The normality and
homoscedasticity of residuals was evaluated for the final model using the packages "nortest" and "lmtest",
respectively. The multicollinearity of the model was evaluated using the function "vif" from the package "vegan". The
effective concentrations of the metals at 25% and 50% (EC25 and EC50) were calculated using the Toxicity Relationship
Analysis Program (TRAP) version 1.30a23. To compute the effective concentration values, a control was established as
the mean of the responses obtained in the background soil.

Results and Discussion

The mean and maximum EC soil values were 0.13 dS m− 1 and 0.32 dS m− 1 (Table 1), respectively, which is considered
non-saline soil24. These values are significantly lower than that recorded by Badilla-Ohlbaum et al.5 (2.3 dS m− 1) in a
similar sampling area. The pH of the sampled soils varied from acidic (5.3) to neutral (7.2), averaging 6.3, which
indicates slight acidity (Table 1). Badilla-Ohlbaum et al.5 reported a pH value of 7.6, which is higher than ours.
However, the average pH value obtained in this study is in accordance with the background value for the region of 6.5,
as reported by Luzio25. The mean soil OM content was 2.4%, ranging from 1.3–4.3% (Table 1). Only two soils exhibited
values exceeding the OM content reported by Luzio25 for the region (3.4%). In contrast, Badilla-Ohlbaum et al.5 reported
an OM content of 1.8%, which is slightly lower than our value. Considering the total soil Cu, Zn, and Pb (Table 1)
concentrations, they are consistent with those reported by Badilla-Ohlbaum et al. (2001). Notably, only the total soil Cu
concentration exhibited a wide range of variation (up to 24× higher). However, the soil soluble Cu content exhibited a
negligible variation (less than 1×), with a mean value of 0.16 mg kg− 1, which is the same value obtained in a previous
study by Schoffer et al. 2022 that was conducted in the same region.

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 Table 1
General physicochemical properties of background and agricultural polluted
topsoils under study (n = 13).
Soil property Unit Median Mean ± SD* Range

Electrical conductivity dS m− 1 0.10 0.13 ± 0.07 0.07–0.32

pH in KNO3 6.3 6.3 ± 0.57 5.3–7.2

Organic matter % 2.2 2.4 ± 1.08 1.3–4.3

Available N mg kg− 1 20 22 ± 11 9.1–45

Available P mg kg− 1 30 36 ± 27 9.4–100

Available K cmol + kg− 1 0.61 0.68 ± 0.44 0.25–1.4

Total Cu mg kg− 1 452 487 ± 312 51-1245

Total As mg kg− 1 33 34 ± 13 17–65

Total Zn mg kg− 1 156 149 ± 26 79–189

Total Pb mg kg− 1 31 29 ± 5.2 17–36

Soluble Cu mg kg− 1 0.06 0.16 ± 0.25 0-0.92

Soluble Zn mg kg− 1 0.09 0.08 ± 0.07 0-0.24

Sand % 34 34 ± 13 14–54

Clay % 18 20 ± 6.9 10–31

Silt % 46 46 ± 8.3 36–59

*SD, standard deviation

As discussed previously, the topsoil in the study region is influenced by Cu-mining activity, as indicated by the
polymetallic (Cu, Zn, As, and Pb) pollution detected in the soil, which is in agreement with corresponding literature
related to the study area26. However, we were unable to discriminate between mining and agricultural sources for the
total Cu concentration. An inherent challenge in toxic assessments involving field-collected soils lies in determining the
specific metal responsible for inducing the observed effects27. Santa-Cruz et al.16, provided a comprehensive summary
of the mean effective concentrations (EC50) of Cu and Zn pertaining to the detrimental effects observed in plants
grown in industrially contaminated soils. They reported EC50 values of 987 mg kg− 1 for Cu and 1561 mg kg− 1 for Zn.
In this study, the total soil Cu concentration was 51–1245 mg kg− 1, whereas the total Zn concentration was 79–189
mg kg− 1 (Table 1). Thus, the total Cu is expected to be toxic, whereas the total Zn is not. Notably, the total soil Cu
exhibited a significant and negative effect on SDM (F = 11, p = 0.002, R2 = 0.15) and SL (F = 32, p < 0.001, R2 = 0.33),
albeit with relatively low coefficients of determination. We were unable to find reference literature relating to a toxicity
threshold for Pb (EC50) pertaining to plants grown in field-contaminated soils. The total soil Pb was 17–36 mg kg− 1
and did not affect the plant responses (p > 0.05). Mojsilovic et al.28 reported an EC50 for As of 407 mg kg− 1,
considering Triticum aestivum grown in field-contaminated soils—a toxicity threshold that is significantly higher than

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the maximum concentration of arsenic found in our soil samples (17–65 mg kg− 1). Thus, we do not expect As to have
toxic effects.

The SL of L. perenne is well explained by the total soil Cu concentrations, soil organic matter, soluble Zn, and available
N, with all variables being significant (p < 0.05). Specifically, we found that the total soil Cu has a negative effect,
whereas soluble Zn, soil organic matter, and available N have a positive effect on SL, as described by the following
regression equation:

SL = 9.6 − 0.008totalsoilC u + 19solubleZn + 1.3soilorganicmatter + 0.088availableN ; (R2 = 0.53; p

< 0.001) (1)

where SL is in cm; total soil Cu, soluble Zn, and available N are in mg kg− 1; and soil organic matter is in %. Notably,
there was no collinearity among the independent variables according to the calculated variance inflation factors
(1.08–1.13). Considering the SDM of L. perenne, the model that best fits the observed response is:

SDM = −0.01 − 0.0001totalsoilC u + 1.4solubleZn + 0.05soilorganicmatter + 0.005soilclaycontent

; (R2 = 0.58; p < 0.001) (2)

where SDM is in g; total soil Cu and soluble Zn are in mg kg− 1; and soil organic matter and soil clay content are in %.
All the variables were significant (p < 0.05). The calculated variance inflation factors (1.12–1.25) indicated no
collinearity among the independent variables.

From a biological perspective, both models are suitable for elucidating the response of L. perenne. In this context, the
influence of excessive Cu on plants is primarily linked to the production and exposure of reactive oxygen species,
which can interact with proteins, lipids, and DNA, resulting in oxidative harm and perturbing typical cellular functions29.
These disruptions ultimately translate into reduced plant yield and productivity30. The beneficial impacts of soluble
zinc on plants is twofold: first, Zn2+ competes with Cu2+ for binding sites on plant biotic ligands, as demonstrated by
Liu et al.31; second, it protects plants from Cu-induced oxidative degradation by promoting antioxidant enzyme activity,
as recently evidenced by Faizan et al.32 and Behtash et al.30. Moreover, Zn enhances the production of photosynthetic
pigments, thereby stimulating plant growth33. The primary form of Cu in the soil is associated with soil OM34. However,
the rate at which soil elements are released from the solid phase into the soil solution decreases as the concentration
of soil OM increases35. Consequently, reducing the copper flux from the solid phase to the soil solution can reduce Cu
phytoavailability36. As shown in Eq. (1), the available N has a positive effect on SL. This is because N serves as a
proline promoter37. Proline—an osmoregulator amino acid—plays a crucial role in enhancing plant tolerance to Cu-
induced oxidative stress by helping sustain plant sub-cell structures38. Furthermore, proline has a pivotal function in
maintaining the proper NADP/NADPH ratio to ensure effective carbon fixation, thereby alleviating the excess acidosis
caused by Cu toxicity in the cytoplasm39. Additionally, proline can also safeguard plant cells from Cu-induced
oxidative damage by neutralizing reactive oxygen species40. Soil clay content has a positive effect on SDM (Eq. (2)).
Wu et al.41 established that Cu2+ is sequestered by clay components in soil after the removal of soil OM, highlighting
its significant affinity for Cu2+. This affinity can be primarily ascribed to the higher intensity of surface negative
charges42, which results in low Cu bioavailability43.

The calculated copper toxicity thresholds (EC50) for SL and SDM were 1030 mg kg− 1 and 1084 mg kg− 1, respectively
(Fig. 3). These thresholds are in agreement with the average EC50 value for plants reported by Santa-Cruz et al.16 (987
mg kg− 1) in anthropogenically contaminated soils for various plant responses (Table 2). Additionally, this value is

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consistent with the EC50 value documented by Verdejo et al.17, thereby reinforcing the validity of our findings.
Specifically, Verdejo et al.17 reported an EC50 of 1031 mg kg− 1 for SL response using a similar L. perenne bioassay
method in soils affected by copper mining operations (Table 2).

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 Table 2
Effective concentration at 50% (EC50) of copper that causes a toxic effect in plants. We focused on studies that used
anthropogenically contaminated soils rather than artificially contaminated (metal-spiked) soils.

Adapted from Santa-Cruz et al.16

Study Soil Copper source Specie tested Test Endpoint Total Cu
origin duration EC50 (mg
(days)
kg− 1)

Hamels et Sweden Timber treatment Hordeum vulgare 14 TDM 1260

al.44 (CuSO4) (Barley)

Kolbas et France Timber treatment Helianthus annuus 28 CC 759

al.45 (CuSO4) (Sunflower)
ChlTot 691

LA 954

RDM 677

SDM 717

Verdejo et Chile Mining activities Lolium perenne 21 SL 1031

al.17 (Ryegrass)
RL 1144

Verdejo et Chile Mining activities Lactuca sativa 21 SL 1805

al.19 (Letucce)

Mondaca Chile Mining activities Avena sativa (Oat) 21 SDM 1230

et al.18
SL 1802

62 RDM 853

SDM 798

SL 889

Brassica rapa 21 SDM 452

(Turnip)
SL 526

42 RL 809

SDM 506

SL 616

NSP 480

Kolbas et France Timber treatment Helianthus annuus 28 ChlTot 329

al.46 (CuSO4) (Sunflower)
RDM 203

SDM 333

SL 407

CC: carotenoid content; ChlTot: total chlorophyll; LA: leaf asymmetry; NSP: number of seed pods; RDM: root dry
mass; RL: root length; SDM: shoot dry mass; SL: shoot length; TAC: total antioxidant capacity; TDM: total dry mass;
TLA: total leaf area.
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 Study Soil Copper source Specie tested Test Endpoint Total Cu
origin duration EC50 (mg
(days)
kg− 1)

TAC 301

TLA 335

This Chile Mining activities and Cu- Lolium perenne 26 SL 1030

study based pesticide (Ryegrass)
SDM 1084

CC: carotenoid content; ChlTot: total chlorophyll; LA: leaf asymmetry; NSP: number of seed pods; RDM: root dry
mass; RL: root length; SDM: shoot dry mass; SL: shoot length; TAC: total antioxidant capacity; TDM: total dry mass;
TLA: total leaf area.

Conclusions
Our results underscore the intricate nature of metal toxicity in plants and emphasizes the importance of considering
multiple factors for assessing its impact on plant growth and development in polymetallic contaminated soils. Cu is
the primary driver of adverse growth responses in Lolium perenne. Notably, contrasting effects were observed between
contaminants, such as between Cu and Zn, with the latter acting as a mitigator of Cu toxicity. Considering this finding,
further studies are required to evaluate the alleviating effect of Zn on Cu toxicity in field-contaminated soils using a
more sensitive bioindicator, such as earthworms. The EC50 for total soil Cu concentration was determined to be 1030
mg kg− 1 and 1084 mg kg− 1 for SL and SDM, respectively. This finding is important in the field of ecotoxicology, as the
obtained EC50 value aligns with results documented in previous studies using naturally contaminated soils.
Furthermore, the unique contribution of this study is emphasized by the fact that few prior investigations have
attempted to establish copper toxicity thresholds for plants grown in real-world contaminated soils that are polluted by
different copper sources (Table 2).

Declarations
Data availability

The datasets used and/or analyzed during the study can be obtained from the corresponding author upon reasonable
request.

Author contribution

J. T. S.: Conceptualization, methodology, formal analysis, writing—original draft, funding acquisition. H. A.: Writing—
review and editing, formal analysis. A. N.: Conceptualization, writing—review and editing, supervision, funding
acquisition. L. M. F: Investigation. R. G.: Conceptualization, methodology, formal analysis, writing—review and editing,
supervision, funding acquisition.

Acknowledgement

We are grateful to the Center of Applied Ecology and Sustainability (CAPES) for the opportunity to conduct this
research and for the funding received through projects ANID PIA/BASAL FB0002 and ANID/FONDECYT 3220026. We
also acknowledge the project ANID/FONDECYT 3210752.

Funding
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Financial support was obtained from the ANID PIA/BASAL FB0002 project (Center of Applied Ecology and
Sustainability, CAPES) and from ANID/FONDECYT 3220026.

Competing interests

The authors declare no competing interests.

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Figures

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Figure 1

General location of the study area in the O’Higgins Region, central Chile (red square). Location of copper mine pollution
sources (mine tailings and mine activities) inside the region are shown as well.

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Figure 2

Topsoil sampling locations in agricultural lands located in the lowlands of the study area (O’Higgins Region, central
Chile).

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Figure 3

Lolium perenne shoot length response (A) and shoot dry mass response (B) as a function of total soil Cu. The
responses of Lolium perenne were assessed by calculating the ratio of the average observed response in the studied
soils to the average response in the background soil, which is expressed as a percentage. The effective concentrations
at 25% (SL EC25: 941 mg kg−1; SDM EC25: 1032 mg kg−1) and 50% (SL EC50: 1030 mg kg−1; SDM EC25: 1084 mg kg−1)
are also shown.

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