Soil featuring and preparation
Soil samples were collected in the surface layer (0-10 cm) of a soil classified as Typic Hapludalf (Soil Survey Staff 2014). The collection site comprised a non-disturbed natural field (30°47’23.5” S, 55°22’7.0” W) adjacent to vineyards installed in Santana do Livramento County, Rio Grande do Sul State (RS), far Southern Brazil. Collected soil samples presented sandy texture, granulometry comprising 89.45% of sand, 4.30% of silt and 6.25% of clay. After the collection procedure was over, samples were air-dried, homogenized, sieved in 2-mm mesh and featured based on their fertility (Table 1).
Table 1- Chemical features of the 0.0-0.10 m topsoil layer in a Typic Hapludalf soil under natural grassland.
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pH H2O (1:1)
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5.33
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Soil organic carbon (%)
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0.54
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Available P by Mehlich-1 (mg.kg-1)
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2.97
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Available K by Mehlich-1 (mg.kg-1)
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232.88
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Exchangeable Ca(cmolc.kg-1)
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0.44
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Exchangeable Mg (cmolc.kg-1)
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0.25
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Available Cu by Mehlich-1 (mg.kg-1)
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0.81
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Available Fe by Mehlich-1 (mg.kg-1)
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22.35
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Available Mn by Mehlich-1 (mg.kg-1)
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24.06
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Available Zn by Mehlich-1 (mg.kg-1)
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1.06
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Exchangeable Al (cmolc.kg-1)
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0.20
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H+Al (cmolc.kg-1)
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2.02
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CECef (cmolc.kg-1)
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1.49
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m(%)
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13.46
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CECph7 (cmolc.kg-1)
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2.71
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V(%)
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47.45
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Phosphorus (P) concentration in the soil was corrected based on the addition of 40 mg kg-1 of P in its simple superphosphate form. Next, soil samples were divided into portions of 10 kg and packed in plastic bags, where they remained for 15 days at constant humidity corresponding to 70% of their maximum water retention capacity (MWRC) - they were revolved every three days. Subsequently, soil contamination was carried out with increasing CU doses (0, 35, and 70 mg Cu kg-1 of soil) - CuSO4.5H2O was used as Cu source. After Cu addition, the soil was incubated again for 30 days, as previously described.
Producing Pampa biome native and Cynodon dactylon seedlings
Cynodon dactylon (Bermuda grass), Paspalum notatum (bahiagrass), Paspalum plicatulum (brownseed paspalum) and Axonopus affinis (common carpetgrass) were the plant species tested in the current study. Plants were collected in a vineyard grown for 35 years in Santana do Livramento County (30°46’36” S, 55°22’03” W), Southern Brazil. Bioavailable Cu content at the 0-20 cm layer of the collection site soil was 40.38 mg kg-1 (extracted through EDTA) and the index of Cu pollution in the soil was classified as high (Silva et al. 2020). Collected species were grown in hydroponic sand culture system, based on the protocol suggested by Marques et al. (2020). Vegetative propagation of the investigated species was carried out every two months, for one year, in order to expand the plant bank and increase homogeneity between seedlings deriving from each species. During the propagation period, seedlings were irrigated twice a day with complete nutrient solution comprising 149.80 mg L-1 of NO3-, 24.80 mg L-1 of H2PO4-, 39.27 mg L-1 of SO42-, 41.31 mg L-1 of Mg2+, 288.72 mg L-1 of Ca2+, 234.60 mg L-1 of K+, 0.03 mg L-1 of Mo, 0.26 mg L-1 of B, 0.06 mg L-1 of Cu, 0.50 mg L-1 of Mn, 0.22 mg L-1 of Zn and 4 mg L-1 of Fe.
Conducting the experiment in greenhouse
The investigated plant species were grown in greenhouse from August to November 2019. Fifteen treatments were evaluated, namely: four grass species (Cynodon dactylon, Paspalum notatum, Paspalum plicatulum and Axonopus affinis) cultivated in soil contaminated with three Cu doses (0, 35 and 70 mg Cu kg-1 of soil), whereas the other treatments, which were used as negative control, comprised soil contaminated with the same Cu doses, although without plant cultivation. Treatments have followed a completely randomized design (CRD), with five repetitions.
Experimental units consisted in 2 liter-capacity pots. Two kilograms (2kg) of soil contaminated with Cu were added to all pots in August 2019. Pots were moistened with distilled water at 70% MWRC. Subsequently, three vigorous and healthy seedlings from each species were weighed to find the initial fresh matter (FMi) and transplanted to different experimental units, based on the adopted treatment. Pots were irrigated on a regular basis to keep water content close to 70% MWRC throughout the experiment. Water availability in the soil was monitored by weighing the pots - distilled water was replenished whenever necessary.
Random leaf samples from each plant were collected at 90 days after transplanting (DAT). They were stored in liquid N2 right away and subsequently placed in ultra-freezer, at -80°C, until laboratory analysis time (photosynthetic pigment concentration and activity of enzymes such as superoxide dismutase (SOD) and Guaiacol peroxidase (POD)).
Assessments
Plant growth
Plant shoot was cut close to the soil at 90 DAT. Roots were manually separated from the soil, washed in running water, then in EDTA (0.002 mol L-1) and, soon after that, in distilled water again. Shoots and roots were weighed to find the fresh matter accumulated in the growing period (FMf). Plants’ growth rate (GR) was determined based on variation in the fresh matter of plants per unit of time (T), in months (Equation 1).
(Equation 1)
Plant shoots were separated into leaves and stem. Leaves, stem and roots were dried in forced air circulation oven, at 65°C, until they reached constant mass in order to find their dry matter (LDM, SDM and RDM).
Copper (Cu) concentration and accumulation in plant tissues
Leaf, stem and root dry matter was ground and subjected to nitro-perchloric digestion to determine total Cu levels in them, based on the methodology by Embrapa (1999). Total Cu concentrations were read in atomic absorption spectrophotometer (EAA; Varian SpectrAA-600, Australia). The total amount of Cu extracted from the soil by plants was calculated by multiplying Cu concentration in the leaves, stem and roots by the dry matter of these organs.
Photosynthetic pigment concentrations
Samples were prepared to determine the photosynthetic pigment concentrations in leaves, based on the methodology by Hiscox and Israelstam (1979). Tissue samples (0.05 g) were incubated with dimethylsulfoxide (DMSO) at 65°C, until full pigment removal. The supernatant extract was subjected to absorbance reading in spectrophotometer, at wavelengths of 663, 645 and 470 nm. Chlorophyll a (Chl a), chlorophyll b (Chl b) and carotenoid concentrations were estimated based on the equation by Lichtenthaler (1987); results were expressed as mg g-1 FM (fresh matter).
Gas exchange
Gas exchange parameters in the last fully expanded leaf of each plant were quantified with the aid of Photosynthesis Analyzer - IRGA (Li-6400, Li-COR Inc., Neb., USA). Net CO2 assimilation rate (Anet), stomatal CO2 conductivity (Gs), intercellular CO2 concentration (Ci) and instant carboxylation efficiency (A/Ci) (based on ribulose-1,5-bisphosphate-carboxylase/oxygenase) were the herein evaluated parameters. These variables were determined in chamber, at CO2 concentration of 400 µmol mol-1, temperature ranging from 20°C to 25°C, relative humidity of 50 ± 5% and photon flow density of 1,500 µmol m-2 s-1.
Enzyme activity
The activity of enzymes such as superoxide dismutase (SOD) and Guaiacol peroxidase (POD) was determined in leaf samples that had been previously frozen and macerated with liquid nitrogen. Leaf samples (1.0 g) were homogenized in 3 mL of 0.05 M sodium phosphate buffer (pH 7.8) added with 1 mM EDTA and 1% Triton X-100. The homogenate was centrifuged at 13,000 g, at 4°C, for 20 min. Supernatant was used for enzyme activity and protein content assays, based on Zhu et al. (2004). Superoxide dismutase (SOD) activity was assessed based on the spectrophotometric method described by Giannopolitis and Ries (1977). One SOD unit was defined as the number of enzymes inhibiting nitroblue tetrazolium (NBT) at 50% photoreduction. Guaiacol peroxidase (POD) enzyme activity in leaves was determined based on the methodology by Zeraik et al. (2008). The reaction mix comprised 1.0 mL of potassium phosphate buffer (100 mM (pH 6.5), 1.0 mL of guaiacol (15 mM) and 1.0 mL of H2O2 (3 mM)). After the homogenization process was over, the solution was added with 50 µL of plant extract. Guaiacol oxidation into tetraguaiacol was measured through absorbance increase at 470 nm.
Copper (Cu) concentration in the soil and indices
The soil of each pot was removed and homogenized at plant removal time (90 DAT). Next, soil samples were collected to determine Cu concentrations available in them (extracted through Mehlich-1).
Some indices were calculated to evaluate species’ tolerance to Cu and their ability to accumulate it. Among them, one finds: Translocation Factor (TF), which indicates plants’ ability to translocate metals from the roots to the shoot – it is calculated as: TF = [CuS] / [CuR] * 100, wherein CuS (mg kg-1 ) is Cu concentration in the shoot and CuR (mg kg-1) is Cu concentration in the root; Tolerance Index (TI), which is based on biomass production and was used to assess the tolerance of all four investigated species to each Cu concentration – it was calculated as: TI = Bt/Bc, wherein Bt (g plant-1) is the biomass of plants grown in soils contaminated with 35 or 70 mg Cu kg-1 and Bc (g plant-1) is the biomass of control plants; Bioconcentration Factor (BCF), which corresponds to the root Cu/soil Cu ratio and is calculated as: BCF = [CuR] / [CuSo], wherein CuR (mg kg-1) is Cu concentration in the root and CuSo (mg kg-1) is soil Cu concentration available to plants.
Statistical analysis
The experiment has followed a completely randomized design (CRD), with 5 repetitions. Twelve (12) treatments resulting from grass species cultivation at each Cu concentration (Cu was used as contaminant agent) were taken into consideration at the time to analyze plant variables. Fifteen (15) treatments resulting from soil cultivated with plants and from the negative control without plant were taken into consideration at the time to analyze Cu content in the soil. First, results were subjected to variance normality and homogeneity tests such as the Lilliefors and Shapiro-Wilk tests. Once the variance normality and homogeneity assumptions were confirmed, data were subjected to analysis of variance. Means recorded for treatments showing significant effect in the F test (p≤0.05) were compared to each other through Scott-Knott test (p≤0.05). All analyses were performed in the SISVAR software (Ferreira, 2011).