Phytoremediation potential of forage grasses in copper-contaminated environments

Phytoremediation potential of forage grasses in copper-contaminated environments | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Phytoremediation potential of forage grasses in copper-contaminated environments Eduardo da Silva Daniel, Daniely Neckel Rosini, Fabio Luis Winter, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4383826/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Human activities have considerably increased copper (Cu). This study evaluated the potential of copper phytoextraction in competing and resource-conserving plants. The experiment was carried out in a greenhouse with eight tropical forage grasses, at two levels of Cu in the nutrient solution: 0.3 and 20 µmol L − 1 . Variables of plant morphogenesis, leaf area measurements, SPAD index, total length, area, volume and average diameter of roots, specific leaf area, specific root area, root density, root length density, specific root length were evaluated, and the relationship between leaf and stem and roots and shoots. Data were submitted to analysis of variance and test of means. Forage grasses did not maintain their functional groups at the highest copper concentrations. The promising species for phytoremediation of copper contaminated areas were marandu, piatã and giant missioneira grass. Plant growth Copper Phytoextraction Forage grasses Phytoremediation Figures Figure 1 Figure 2 Figure 3 Figure 4 1 INTRODUCTION Human activity, especially in the agricultural context, is largely responsible for raising the levels of trace elements in soils and waters, which, in turn, can promote environmental pollution (CONTI et al., 2016 ; LI et al., 2016; LI et al. al., 2015; fiWAN; LEI; CHEN, 2016 ). Copper is one of those chemical elements causing contamination is the. Several products used in agriculture contain copper in their constitution, such as swine manure, chemicals and even by-products of mining activities, which can raise the levels of this element in the soil to toxic levels for plants (FERREIRA et al., 2018, WAN et al., 2020). In vineyards, for example, the fungus that causes downy mildew is controlled through the application of a fungicide composed of CuSO 4 and Ca (OH)2 (GISI et al., 2009). Thus, after the use of fungicides with copper in fruit trees, this metal can accumulate mainly in the superficial organic fraction of the soil (BRUNETTO et al., 2014; COUTO et al., 2014). In plants physiology, copper is an essential element, which helps in protein synthesis and carbohydrate metabolism, regulates processes such as photosynthesis and respiration, and can also act in plant protection (GUIMARÃES et al., 2016). Cu is absorbed from the soil to maintain the plant's functional activities, and non-accumulating plants absorb a dose lower than 10 mg L − 1 of micronutrient (AWA; HADIBARATA, 2020 ). Once absorbed in high concentrations, plants can present damage to their architecture and morphology of the root system, decreasing shoot growth and increasing the average diameter of the roots (AMBROSINI et al., 2015 ) and, consequently, decreasing the absorption of nutrients. water and nutrients (CAMBROLLÉ et al., 2015 ) reducing their growth and production (CHRISTOU et al., 2017 ; RIZVI; KHAN, 2018 ). In soils with a high level of Cu, some agronomic techniques that limit the availability of this element can be applied (BRUNETTO et al., 2016 ), such as phytoremediation. Phytoremediation uses in its process plants with the potential to concentrate and metabolize trace elements in their tissues (SALT et al., 1995 ), constituting an ecological and sustainable technique, marked by ease of application and low cost (AWA; HADIBARATA, 2020 ; CRISTALDI et al., 2017 ), in addition to providing less soil erosion and improving soil structure and biodiversity (Ali et al., 2013 ; Tahir, 2016 ), thus improving the quality of the ecosystem (LIU et al., 2018 ). ; MCCUTCHEON; JØRGENSEN, 2008 ). However, the efficiency of the phytoremediation practice is dependent on the physiological characteristics of the selected plants and the pollutant in question (LI et al., 2014 ). Grasses (Gramineae) are an expressive group in phytoremediation context, as they are fundamentally important from an ecological point of view, involved in recovery, protection and revitalization of the soil (CONTI et al., 2019 ). Gramineae also present efficient photosynthetic performance in various conditions with different levels of soil requirement, high tillering capacity and soil cover, root system that provides high mechanical support for the soil, in addition to high biomass production (DUBIS et al., 2019 ; LAMBRECHTS et al., 2014 ; SPRINGER, 2021 ). Despite belonging to the same botanical family, grasses have a great functional diversity. A relatively classic classification in this sense is the classification of species according to the way they use ecological niches and exploit resources in the environment. In this sense, resource competing and resource conserving plants differ in terms of their ability to capture resources from the environment and their growth strategies (CRUZ et al., 2002 ). Plants classified as resource competitors demonstrate higher performance in environments with little stress, present faster growth, greater nutritional requirement and greater specific leaf area (AFE) while resource conserving species are more adapted to environments with higher levels of stress, being more efficient in using the resources of the environment, they present slower growth rates and lower AFE (CRUZ et al., 2010 ; GRIME, 1977a). To remove the trace element from the soil, its absorption via the root system is necessary (AWA; HADIBARATA, 2020 ; NEDJIMI, 2021 ) and functionally different plants have different abilities in capturing soil resources. Given this context, this study started from the central hypothesis that resource competing and resource conserving plants have different potentials for phytoextraction from areas contaminated with copper. Therefore, this study determined the phytoremediation potential of competing and resource-conserving forage grasses cultivated in environments contaminated with high levels of copper. 2 MATERIALS AND METHODS An experiment was carried out in a greenhouse of the department of soils and natural resources of Santa Catarina State University (UDESC), in Lages, Santa Catarina, Brazil, in 2016. The greenhouse was adapted with photoperiod and luminosity provided by natural light, with temperature and humidity controlled by an automated system, which remained between 15 and 25°C and 70 and 95%, respectively. Seven forage grasses from tropical climate (C4) were cultivated in two concentrations of copper. Plants used were three cultivars of Brachiaria brizantha (Hochst.) Stapf.: 'BRS Piatã' (piatã grass), 'Marandu' (marandu grass) and Xaraés (xaraés grass); one from Brachiaria humidicola (Rendle.) Schweickerdt (B. humidícola); two cultivars of Panicum maximum Jacq.: 'Aruana' (Aruana grass) and 'Tanzania' (Tanzania grass); and one of Axonopus catharinensis Valls (giant missioneira grass). Seedlings of piatã, marandu, xaraés, aruana, tanzania and B. humidicola grasses were obtained by germinating untreated seeds in gerbox boxes and BOD-type chambers, according to the rules for analysis and seed germination of the Brazilian Ministry of Agriculture (MAPA) (BRAZIL, 2009). After germination, seedlings size was standardized and they were transferred to plastic trays with sand. Seedlings size was standardized and the sand underwent a disinfection process with a 5% HCl solution and distilled water. The giant missioneira grass had its seedlings produced through the development of 5 cm propagules with a stem containing a node from the mother plants. During 10 days, the trays were irrigated with Hoagland's nutrient solution (ARNON; HOAGLAND, 1940) with 50% ionic strength and pH 5.5. Subsequently, seedlings were transferred to pots containing Hoagland's nutrient solution at 100% ionic strength and pH 5.5, remaining like this for another 10 days, without contaminants. Experimental units consisted of two-litter polypropylene pots lined with aluminium foil, containing Hoagland's nutrient solution at 100% ionic strength and pH 5.5, and three plants of the same species. The treatments consisted of two levels of Cu in the hydroponic solution: 0.3 and 20 µmol L − 1 , (source Cu(NO3)2) and seven forage species (piatã, marandu, xaraés, aruana, tanzania, humidícola and giant missioneira). composing a completely randomized design, in a 7 x 2 factorial scheme, with three replications. The Cu concentration of 20 µmol L − 1 was selected in a preliminary experiment, where the doses of 0.3, 1, 5, 20 and 80 µmol L − 1 of Cu in the nutrient solution were tested. The criterion used for the selection was the highest concentration of Cu in the nutrient solution in which there was a 50% reduction in the growth rate of stem and pseudo stem height (DC50) among the seven evaluated forages. More details of the preliminary experiment can be obtained in Eduardo (2018). The concentration of 0.3 µmol L − 1 is standard for the nutrient solution proposed by Arnon and Hoagland (1940), used in the present study. After the experiment was implemented in the greenhouse, the plants were maintained for 30 days, with the nutrient solution being replaced weekly and the pH adjusted every 3 days. Oxygenation and turning of the solution were performed using an automatic aeration system, three times a day. During plant growth, from the 15th to the 30th day, measurements were taken of stem and pseudo stem height, length of the last expanded leaf and number of live leaves in one of the tillers of each experimental unit. With these measurements, the culm + pseudo stem growth rate - TCCP (1), leaf appearance rate - TAPF (2) and the leaf expansion rate - TEF (3) were obtained: (1) TCCP = (stem height + final pseudo stem - initial pseudo stem) /15 (2) TAPF = (final number of live leaves – initial number) /15 (3) TEF = (sum of differences in final - initial length of expanding leaves) /number of leaves) /15 After 30 days of growth, the measurements of leaves were taken using the SPAD (Soil Plant Analysis Development), index using a portable chlorophyll meter (SPAD 502; Konica Minolta®, Tokyo, Japan). Measurements were performed on the lower, middle and upper third of the fully expanded leaves, on nine leaves of each experimental unit, between 9 and 10 am. After measurements plants were then harvested and washed with deionized water. Leaves were detached from the stems and integrated into a leaf area integrator (LI-3000C, LI-COR, Lincoln, USA) to obtain the leaf area of ​​each plant. Plants were dried in an oven with forced air circulation at 65 ºC for 72 hours and then the dry mass (DM) of each structure and total dry mass were determined. The oven-dried material was processed in a Wiley mill and sieved through a 20-mesh sieve. The leave dry mass and leaf area data were used to calculate the specific leaf area – AFE (4): AFE = Leaf Area / Dry Mass of Leaves (2) Roots, after being collected, washed and cleaned, were evenly distributed in an acrylic vat filled with a slide of distilled water, without overlapping, and submitted to digitalization in a professional scanner (Epson Expression 10000 XL, Epson America Inc., Long Beach, USA). Images were processed using a computer program (WinRhizoTM Pro 2009, Regent Instruments, Montreal, Canada) and thus, the values of mean diameter, total length, root area and volume were obtained. To extract Cu from roots and shoots of plants, samples were opened by microwave-assisted acid digestion, according to method 3052 of the United States Environmental Protection Agency – USEPA (1996). Quantification was performed using an inductively coupled plasma optical emission spectrometer (ICP-OES) (Optima® 8300, Perkin Elmer, Norwalk, USA), in triplicate. Eight blank tests were used to determine the instrument's detection limit, which corresponded to 0.03 mg L − 1 . The reliability of the analytical method used to determine the concentration of Cu in plants was defined as 100 ± 5%, using the sample SRM 1573a (tomato leaves) certified by the National Institute of Standards and Technology (NIST) as a reference. Values recovered from the reference sample are shown in Table 1 . Table 1 Values recovered by the method used to determine the concentration of Cu in forage plant tissue samples. Sample Triplicate Certified value Recovered value Recovery (mg kg − 1 ) (mg kg − 1 ) (%) SRM 1573a 1 4.7 4.48 95.21 2 4.7 4.84 105.0 3 4.7 4.66 99.05 Average - 4.7 4.66 99.75 With the concentrations of Cu in roots and shoots, the translocation factor (FT) for the trace element was calculated, according to Eq. (5): FT = Cu concentration in shoots/Cu concentration in roots Initially, for the purpose of proving the formation of forage plant groups (CRUZ et al., 2002 ) into conservators and competitors for resources, five variables were selected, namely: AFE, TAF, TEF, TCCP and MS per tiller. Data were tested for each dose of Cu (0.3 and 20.0 µmol L-1). For data analysis, the Minitab 17 program was used, with the Cluster clustering method, complete linkage method, Euclidean distance and standardized variables. Data on AFE, TAF, TEF, TCCP and total DM, Cu content in roots, shoots and total, translocation factor, root area, total root length, root volume, mean diameter, root dry mass and SPAD index were obtained. submitted to analysis of variance, and if there was a difference, their means were tested using the Tukey statistic test, with a 5% error probability. 3 RESULTS Forages that were cultivated in an environment with adequate concentrations of Cu formed two distinct groups (Fig. 1 a). The group of resource conserving species was composed of the giant missioneira, B. humidicola and piatã, while the group of resource competing species was composed of aruana grass, marandu, tanzania and xaraés (Fig. 1 c). When forage grasses were exposed to the highest concentration of Cu (20 µmol L − 1 ) there was no functional segregation (Fig. 1 b; 1 d). In both functional groups, the specific leaf area was not influenced by Cu dose and plant species (P > 0.05). Among competing species, Tanzania grass had the highest leaf appearance rate (0.14 leaves day − 1 tiller − 1 ) while the lowest leaf appearance rate (0.10 leaves day − 1 tiller − 1 ) was observed in marandu, when cultivated with 0.3 µmol L − 1 Cu (Table 2 ). When cultivated at a concentration of 20 µmol L − 1 of Cu, the highest leaf appearance rate was observed for Aruana and Tanzania grasses (0.175 leaves day-1 tiller-1), for Xaraés grass it was 0.11 leaves dia − 1 tiller − 1 and, with a lower rate of leaf appearance, marandu grass (0.07 leaves day − 1 tiller − 1 ). The leaf expansion rate was higher for tanzania and aruana grass, and the lowest rates were observed in marandu, regardless of the copper dose. Aruana grass showed the highest rates of stem and pseudo stem expansion, regardless of Cu dose, while marandu grass showed the lowest rate of stem and pseudo stem expansion when subjected to 0.3 µmol L − 1 of Cu, and marandu and xaraés had the lowest means when cultivated with 20 µmol L − 1 of Cu. For dry mass per tiller, regardless of Cu dose, Tanzania and xaraés had higher mass per tiller, followed by aruana and marandu (Table 2 ). For the resource-conserving species, leaf appearance rate was higher in the giant missioneira, regardless of Cu dose, not differing from the piatã grass in the concentration of 20 µmol L − 1 of Cu. For the leaf expansion rate, piatã grass showed superior results in both doses, not differing only from B. humidicola in the concentration of 0.3 µmol L − 1 of Cu. The expansion rate of culms and pseudo stems, in concentration of 0.3 µmol L − 1 of copper, was lower for the piatã grass, while in the concentration of 20 µmol L − 1 of copper, it was higher for the giant missioneira. Dry mass per tiller was higher for piatã grass, followed by giant missioneira and B. humidicola , regardless of the Cu dose (Table 2 ). The effect of copper doses for each species showed that for arowana grass, the concentration of 20 µmol L − 1 of copper conferred a higher rate of leaf appearance and culm and pseudo stem expansion (1.5 and 1.4 times higher, respectively) and consequently, higher dry mass per tiller, being 25 percent higher in the highest Cu concentration than in the concentration of 0.3 µmol L − 1 . Tanzania grass showed a 15% reduction in leaf expansion rate when cultivated with 20 µmol L − 1 of copper compared with the concentration of 0.3 µmol L − 1 of copper. Marandu grass had heavier tillers when cultivated at the highest dose of copper. Leaf expansion rate and stem and pseudo stem elongation were lower for xaraés grass at the highest copper dose, while for piatã, the variables were lower at the lowest copper concentration. The humidicola was negatively affected by the higher copper concentrations for leaf appearance and expansion rate, stalk and pseudo stem expansion rate and dry mass/tiller. The higher concentration of copper negatively affected the rate of leaf appearance and expansion of stem and pseudo stem and positively affected the rate of leaf expansion and dry mass per tiller of the giant missioneira (Table 2 ). Resource competing species showed leaf expansion rates two and 1.8 times higher than conservative species when cultivated under copper concentrations (0.3 and 20 µmol L − 1 respectively). When cultivated with a nutrient solution containing 0.3 µmol L − 1 , competing species presented a leaf appearance rate 50 percent lower than those presented by conservative species and specific leaf area 1.6 times higher than the resource-conserving group (Table 2 ). Table 2 Descriptive data of variables used in the formation of PCA's for seven forage grasses submitted to two different copper concentrations (0.3 and 20 µmol L -1 ). Groups Grass Species [Cu] AFE Tx Ap.F Tx Exp.F Tx Col + Pseu MS µmol L − 1 cm 2 g − 1 leaves day − 1 tiller − 1 mm day − 1 mm day − 1 tiller − 1 g tiller − 1 Resource Competing Species Aruana 0.3 229.75 aA 0.12 bAB 60.74 aAB 14.82 bA 1.23 bB 20.0 188.61 aA 0.18 aA 51.78 aAB 20.51 aA 1.54 aB Tanzânia 0.3 228.30 aA 0.14 aA 67.70 aA 8.07 aB 3.00 aA 20.0 226.44 aA 0.17 aA 57.64 bA 8.31 aB 2.95 aA Marandu 0.3 182.90 aA 0.10 aB 38.63 aC 4.00 aC 0.68 bB 20.0 123.54 aA 0.07 aC 37.55 aC 5.39 aBC 0.93 aB Xaraés 0.3 138.37 aA 0.11 aAB 51.70 aB 10.71 aB 2.54 aA 20.0 202.37 aA 0.11 aB 45.82 bBC 2.42 bC 2.39 aA Resource Conserving Species Humidícola 0.3 126.32 aA 0.18 aB 33.28 aA 17.34 aA 0.55 aC 20.0 342.32 aA 0.08 bB 22.97 bB 8.12 bB 0.23 bC Piatã 0.3 88.95 aA 0.16 aB 28.93 bA 5.80 bB 1.10 aA 20.0 78.63 aA 0.17 aAB 35.26 aA 8.81 aB 1.47 aA Missi. Giant 0.3 143.88 aA 0.39 aA 17.06 bB 21.25 aA 0.76 bB 20.0 115.01 aA 0.24 bA 22.06 aB 16.12 bA 1.03 aB Average Competing Species 0.3 194.83 aA 0.12 aB 54.69 aA 9.40 aA 1.86 aA 20.0 185.24 aA 0.13 aA 48.20 aA 9.16 aA 1.95 aA Conservating Species 0.3 119.72 aB 0.24 aA 26.43 aB 14.79 aA 0.80 aA 20.0 178.65 aA 0.16 aA 26.76 aB 11.02 aA 0.91 aA AFE: Specific leaf area; TxAp.F: Leaf appearance rate; TxExp.F: Leaf expansion rate; Tx Col + Pseu: Stem + pseudo stem growth rate; MS: Dry mass/tiller; Perf.: Tillers; Missi.: Missioneira. 1 Lowercase letters compare different doses for each forage and average within each group; 2 Capital letters compare foragers within each dose and group and compare group means within the same doses. These comparisons were made using Tukey's statistical test (< 0.05). Root area of ​​aruana, marandu and giant missioneira grasses were not altered by the different copper concentrations. The same happened to the root volume of aruana and giant missioneira grass (Figs. 2 a and 2 c). While tanzania, xaraés and piatã showed an increase in root area of ​​28, 106 and 155%, respectively, when cultivated with the highest concentration of Cu, with an increase in root volume of, respectively, 17, 73 and 112%, when cultivated with 20 µmol L -1 copper (Figs. 2 a and 2 c). Only humidicola grass showed a reduction in root area and volume at the highest concentration of Cu, with a 26% reduction in its root area (Fig. 2 a) and a 46% reduction in its root volume (Fig. 2 c). When cultivated in the presence of 20 µmol L -1 of copper, the tanzânia, marandu, xaraés and piatã grasses showed an increase in root length, being these 1.48; 1.51; 2.55 and 2.92 times higher than that observed when cultivated with 0.3 µmol L -1 of Cu in the nutrient solution, respectively. The giant missioneira had a 17% reduction in root length when exposed to 20 µmol L -1 of Cu (Fig. 2 b). The average root diameter was negatively affected by the higher copper concentration, reducing 24, 12, 22, 20 and 21% for the species of tanzania, marandu, xaraés, humidicola and piatã grass, respectively. Only the giant missioneira showed an increase in the mean diameter of roots when submitted to 20 µmol L -1 of Cu (Fig. 2 d). When cultivated with 20 µmol L -1 of Cu, the species aruana, marandu and missioneira giant presented an increase in the dry mass of roots in the proportions of 1.6; 1.5 and 1.4 times higher than that observed in cultures with 0.3 µmol L -1 of Cu. The other species showed no difference in root dry mass when cultivated in 0.3 or 20 µmol L -1 of Cu (Fig. 2 e). Exposure to the highest concentration of copper (20 µmol L -1 of Cu) increased the SPAD index by 30% for tanzania grass, 40% for piatã grass and 10% for giant missioneira grass. On the other hand, marandu, xaraés and humidícola showed a reduction of 44; 59 and 37% respectively, when cultured with 20 µmol L -1 of Cu (Fig. 3 ). It was possible to observe that the SPAD index decreased in competing resource plants, with the exception of Tanzania grass. For copper concentration in roots, shoots and for its total concentration, all species showed higher content when cultivated with 20 µmol L − 1 of Cu as shown in Fig. 4 a, 4 b and 4 c. When cultivated at a concentration of 0.3 µmol L − 1 of Cu, marandu grass showed higher copper content in the roots and in total. Among the plant species, B. humidicola presented the highest total and root copper content, 90% higher than that observed for marandu and xaraés grasses (1068 mg kg − 1 ), when cultivated in an environment with high copper content. The humidicula had higher Cu concentration and lower root size data. On the other hand, the lowest levels of copper were observed for giant missioneira and tanzania (125 mg kg − 1 ) (Figs. 4 a and 4 c). The copper content of the aerial part represented very little of the total copper content present in the plants, with the highest copper content in the aerial part observed for the giant missioneira (30 mg kg − 1 ) not differing from the humidícola and piatã (21 mg kg − 1 ) at a concentration of 20 µmol L − 1 of Cu (Fig. 4 b). Regardless of the plant species, the translocation factor was higher at the lowest copper concentration (0.3 µmol L − 1 of Cu). In same cooper concentration the highest translocation was observed for B. humidícola , piatã and giant missioneira (128%) while at the highest concentration of Cu (20 µmol L − 1 ) the giant missioneira had the highest translocation factor (25%), followed by Tanzania (13%) and the other species showed the lowest translocation factor (1.8%) at the concentration of 20 µmol L − 1 of copper (Fig. 4 d). Lowercase letters compare doses for each species. Capital letters compare forages within the same dose. Tukey (0.05). Table 3 Summary of the effect of copper on variables analysed for seven forage grasses cultivated for 30 days in a nutrient solution with a concentration of 20 µmol L -1 of copper. Obtained Data Grass Species Aruana Tanzânia Marandu Xaraés Humidicola Piatã M. Giant AFE =* = = = = = = Tx Ap.F +** = = = - = - Tx Exp.F = -*** = - - + + Tx Col + Pseu + = = - - + - MS perf + = + = - = + Root Area = + = + - + = Tot. Root Length = + + + = + - Root Volume = + + + - + = Med. Diameter = - - - - - + Root Dry Mass + = + = = = + SPAD Index = + - - - + + The dominance = = + =/- - + + * =: No efect; ** +: Positive efect; *** -: Negative efect. 4 DISCUSSION Forage grasses, when subjected to environments with higher copper concentrations, show some differences in their original functional attributes. Two species (piatã and marandu) had a functional group transition when cultivated under a concentration of 20 µmol L-1 of copper, in this study. Although a slight movement was observed within the PCA's, the other species showed no change in their functional groups (Fig. 1 ). That movement indicates the occurrence of changes in the growth patterns of grasses and, regardless of functional group, the studied species presented different behaviours when exposed to a high concentration of copper, as reviewed by ADREES et al. ( 2015 ) and confirmed by Saleem et al. ( 2020 ). Saleem et al. observed different response patterns for four varieties of Corchorus capsularis grown in soil contaminated with copper, indicating that the plant's defence mechanism, antioxidant activity, plays an important role in the choice of phytoremediator (ALVES et al., 2018 ). Cu presence can modify FA growth patterns, stem expansion, dry and fresh mass, as observed for maize (BARBOSA et al., 2013 ), wheat (AZOOZ; ABOU-ELHAMD; AL-FREDAN, 2012 ; COOK; VARDAKA; LANARAS, 1997 ) and rice (THOUNAOJAM et al., 2012 ). A reduction in root length and dry mass of Festuca arundinacea and Lolium perenne when grown in soil with different copper concentrations was observed by Zhao et al. ( 2010 ). In that study, the reductions in root length were more pronounced in fescue (resource conserving species), while shoot dry mass suffered greater reductions in perennial ryegrass (resource competing species). Although resource conserving species are more effective in adapting to environments with stressors (GRIME, 1974 , 1977b ), this fact was not observed in this work. The results obtained with this study suggest that plant response is not exclusively associated with the functional group, but in individual characteristics, such as antioxidant activity, which corroborates with Alves et al. ( 2018 ) and Saleem et al. ( 2020 ), since the root and of aerial expansion were different for species within the same functional group (Table 2 and Fig. 2 ). Observing the effects of the presence of copper (20 µmol L − 1 ) on the seven forage species studied, it can be observed that the missionary giant and piatã showed a greater positive effect in the analysed variables, as well as the marandu grass. The missioneira giant is a native species that tolerates shady areas, being a species with high potential for phytoremediation of contaminated areas. The aruana and tanzania grasses were not efficient for removing copper from the system, while the xaraés grass proved to be null to inefficient in removing copper. The humidiícola was shown to be inefficient in the analysed variables when cultivated in high concentration of copper. Aruana grass is the only plant that did not presented negative effects when cultivated for 30 days in a nutrient solution with 20 µmol L − 1 copper concentration. For aruana, although there was no change in the volume and density of roots, as well as in the leaf area and specific leaf area, there was an increase in the dry mass of roots and leaves, and in the total dry mass. It has no negative effect on aruana, but it removed low amounts of Cu and also had good phyto-stabilization, but it is not a phytoextractor. Aruana and marandu showed low sensitivity to phytotoxicity caused by the trace element, with low translocation compared to other forages, and Cu concentration in the shoot below the critical range. After absorbed by roots, copper accumulates in root tissues, since the trace element has low translocation in the plant (REHMAN et al., 2019c). In roots, the trace element acts negatively on anatomical and root growth characteristics (LIN et al., 2013 ; REHMAN et al., 2019b ), affecting root cell growth, expansion and division (KOLBERT et al., 2012 ; LI et al., 2018 b; LIU; KOTTKE, 2004 ). Plant species with phytoremediator potential to environments contaminated with trace elements need to absorb or degrade the contaminant (AWA; HADIBARATA, 2020 ; LIU et al., 2020 ; NEDJIMI, 2021 ), where, in phytoextraction or phytoaccumulation, plants are able to removal of the trace element from the medium by absorption and accumulation in plant tissues, usually leaves (CRISTALDI et al., 2017 ). In this sense, species with rapid vegetative growth and that can be defoliated frequently are the most apt to be used in these phytoremediation programs (LI et al., 2018a ; STERCKEMAN et al., 2019 ). Thus, plant species that show few root changes when grown in environments with high trace element content should be considered in phytoremediation studies, since having a good root contribution is essential for vegetative growth. For the parameters of root growth, the results showed that the humidicola presented smaller roots when cultivated in 20 µmol L − 1 of copper, being, in this case, disregarded for phytoremediation programmes, due to its low root reach zone (LASAT, 2002 )., although it showed the highest copper concentrations in the present study. Root changes are factors that favour nutrient deficiency in plants (ADREES et al., 2015 ), since it reduces the area of ​​root exploration, especially of fine roots (REHMAN et al., 2019c). In addition, excess copper in roots may be associated with reduced absorption of macronutrients (Ali et al. 2002) and micronutrients (AZEEZ; ADESANWO; ADEPETU, 2015), thus triggering a nutritional imbalance for plants (REHMAN et al., 2019; SAĞLAM et al., 2016 ). SPAD index refers to the chlorophyll content, which is directly related to the nitrogen nutrition of the plant, where a reduction in the SPAD index indicates a lower nitrogen nutrition of plants (BAZAME et al., 2020 ; CORRÊDO et al., 2019 ; RAVIER; QUEMADA; JEU, 2017; YUE et al., 2019 ). Under conditions of cultivation of plants in environments contaminated with Cu, the absorption of this can worsen the nutritional status of the plant, compromising its vegetative growth. The reduction of the SPAD index may also be associated with the reduction in the size of the cells of the chlorophyll parenchyma of the leaf mesophyll induced by Cu, or by the collapse of these parenchyma cells due to the sensitivity to the toxicity of trace elements (SRIDHAR et al., 2005; GOMES). et al., 2011). Furthermore, leaf chlorosis is closely associated with morphological and physiological changes in chloroplasts; according to Yruela (2013), Cu can change the structure and composition of the thylakoid membranes of this organelle. In this study, marandu, xaraés and humidicola grasses presented reductions in the SPAD index when cultivated at the highest dose of Cu (Fig. 3 ). Those reductions in the SPAD index observed in the leaves may be associated with the reduction in the size of the chlorophyll parenchyma cells of the leaf mesophyll induced by Cu, or with the collapse of these parenchyma cells due to sensitivity to the toxicity of trace elements (SRIDHAR et al., 2005). ; GOMES et al., 2011). Furthermore, leaf chlorosis is closely associated with morphological and physiological changes in chloroplasts; according to Yruela (2013), Cu can change the structure and composition of the thylakoid membranes of this organelle. The highest Cu content in the aerial part of the humidicola (2025 mg kg − 1 ) and the lowest content in Marandu and Xaraés (1060 mg kg-1) may indicate a reduction in the nutritional index with the increase in the copper content in the plant, mainly in the roots (Fig. 4 a). However, competition with iron and magnesium cations may be taking place (YRUELA, 2013). With an increase in the availability of copper in the hoagland solution (20 µmol L − 1 ), there was an expected increase in the copper content of all species in the roots, shoots and in the plant, when compared to the standard concentration of Cu (0, 3 µmol L − 1 ), since increasing the concentration of the trace element in the nutrient solution would increase its root absorption (SHAH; DAVEREY, 2020 ) and compartmentalization of the trace element in plant (NEDJIMI, 2021 ). Forage plants cultivated with 20 µmol L − 1 of copper, regardless of the functional group, showed higher copper content in the roots, compared to the shoot (Fig. 4 ). In order to successfully remove trace element from the soil, it is necessary that the root structure of the plant effectively colonizes the soil stratum contaminated with Cu (LASAT, 2002 ) so that the plant species used can absorb and compartmentalize the element. trace in its biomass (MAHAR et al., 2016 ). Pedersen, Kjær and Elmegaard ( 2000 ) had already observed a higher copper content in the plant roots, where, in that case, it was possible to identify that the fine roots of Fallopia convolvulus had the highest levels of Cu. Later, Wei et al. ( 2008 ) observed in plants of Chrysanthemum coronarium and Sorghum sudanense that 90% of the copper present in the plant was in its root organs. Root apparatus has a greater amount of trace element, since Cu is rapidly absorbed by the roots and its translocation to the aerial part of the plant does not follow the same speed of root absorption (REHMAN et al., 2019c), being accumulated in lower proportion in the aerial part of plants (MAHMUD et al., 2013 ; REHMAN et al., 2019a ; THOUNAOJAM et al., 2012 ), as observed in the results of the present study (Figs. 4 a and 4 b). The highest copper content in the shoot was observed for humidícola , piatã and missioneira giant. However, the missioneira giant had the highest translocation factor, regardless of copper concentration (Fig. 4 d). These data demonstrate that the humidicula has a greater ability to translocate the trace element to the shoot, without showing losses in root dry mass (Fig. 2 c) and tiller dry mass (Table 2 ) and also showed a higher SPAD index (Fig. 2 c) 3), when cultured with 20 µmol L − 1 of copper. These results place Missioneira giant in the position of a plant with the potential to phyto-remediate soil contaminated with copper, given that one of the main characteristics of phytoremediation plants is the accumulation of the trace element in their tissues, mainly shoots (NEDJIMI, 2021 ). Plant species with greater root structure and high production of above-ground biomass that can be harvested (NEDJIMI, 2021 ) with the ability to extract trace elements from the soil (CRISTALDI et al., 2017 ) are important characteristics when choosing plant species for programmes of phytoremediation. The results showed that forage grasses do not maintain their functional groups (competitors or resource conservationists) when exposed to environments with copper contamination. After 30 days of cultivation in a nutrient solution with two levels of copper, the plant species presented different responses to the attributes analysed (Table 3 ) regarding the ability to phyto-remediate environments contaminated by copper, where the forage species of marandu, piatã and missionaria giant have the potential to decontaminate Cu-contaminated soils. 5 CONCLUSION Species studied did not maintain their functional groups in competing or resource conserving environments with high copper concentrations. Aruana grass is a good phytostabilizer, but it is not a phytoextractor. The humidicola grass did not present any positive effect in its development in high concentrations of copper. Tanzania grass had a reduction in leaf expansion rate and mean diameter, and xaraé grass, in addition to these parameters, also showed a reduction in the growth rate of stem and pseudo stem height. Therefore, these species are not viable for copper phytoextraction in contaminated areas. Marandu, piatã and missionaria giant grasses are promising species to be used in phytoremediation for tropical areas with high concentration of copper. Declarations ACKNOWLEDGMENTS Authors would like to thank the PAP UDESC-FAPESC Research Support Programme and PROAP-CAPES, and UNIEDU-SC for granting the research grant. DECLARATION OF INTEREST Authors claim that there are no competing interests to declare. This study evidenced the behaviour of forage grasses exposed to different concentrations of copper. The text presents new scientific information in relation to the functional groups of grasses that did not remain competitive or conserve resources in environments with high concentrations of copper. In addition, it showed that the species of marandu, piatã and giant missioneira grass are promising to be used in phytoremediation for tropical areas contaminated by copper. NOVELTY STATEMENT This article presents promising plant species for the recovery of areas contaminated with copper. Different species of tropical forage grasses may have different phytoremediation potentials. The promising species for phytoremediation of copper were the marandu, the piatã and the giant missioneira grass. ETHICAL APPROVAL The manuscript was not submitted to more than one journal for simultaneous consideration. It is original and was not published elsewhere. The article is my own authorship and uses data correctly. References are citations honestly. The article meets all of the journal's ethical requirements. CONSENT TO PARTICIPATE AND PUBLISH All authors developed for the article and consent to publish the article in this journal. AUTHORS CONTRIBUTIONS All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Daniel and Campos. The first manuscript was written by Daniel and Rosini and all authors commented on previous versions of the manuscript. All authors: Daniel, Rosini, Winter, Silva, Sbrissia, Premieri and Campos read and approved the final manuscript. FUNDING UDESC (Santa Catarina State University), PROAP (Postgraduate Support Program) and CAPES (Coordination for the Improvement of Higher Education Personnel). COMPETING INTERESTS This study does not have competing interests. References ADREES, M. et al. The effect of excess copper on growth and physiology of important food crops: a review. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4383826","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":308602678,"identity":"0db49203-d455-466b-90d9-daac9073c710","order_by":0,"name":"Eduardo da Silva Daniel","email":"","orcid":"","institution":"UDESC: Universidade do Estado de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Eduardo","middleName":"da Silva","lastName":"Daniel","suffix":""},{"id":308602679,"identity":"9d8e51fc-dded-41f7-9ebc-09544bd8b762","order_by":1,"name":"Daniely Neckel 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Ciencia e Tecnologia de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"Silmar","middleName":"","lastName":"Primieri","suffix":""},{"id":308602684,"identity":"afbb58ed-8d5f-4518-ad64-06f0cc9ad72a","order_by":6,"name":"MARI LUCIA CAMPOS","email":"","orcid":"","institution":"UDESC: Universidade do Estado de Santa Catarina","correspondingAuthor":false,"prefix":"","firstName":"MARI","middleName":"LUCIA","lastName":"CAMPOS","suffix":""}],"badges":[],"createdAt":"2024-05-07 14:56:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4383826/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4383826/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58225363,"identity":"961d2b0a-3c12-44e9-af55-b0c72acbaa7d","added_by":"auto","created_at":"2024-06-12 17:44:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":428146,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis based on specific leaf area, leaf appearance rate, leaf expansion rate, stalk and pseudo stem growth rate and dry mass per tiller for conservative and resource competing forage species subjected to concentrations of 0.3 µmol L\u003csup\u003e-1\u003c/sup\u003e (A) and 20 µmol L\u003csup\u003e-1\u003c/sup\u003e (B) of copper and for the seven plant species submitted to concentrations of 0.3 µmol L\u003csup\u003e-1\u003c/sup\u003e (C) and 20 µmol L\u003csup\u003e-1\u003c/sup\u003e (D) of copper.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4383826/v1/7f0fbcf4061bb74f903e9587.png"},{"id":58224340,"identity":"9d4cd63f-ac2e-478e-b6bd-77ce2996bd43","added_by":"auto","created_at":"2024-06-12 17:36:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":550926,"visible":true,"origin":"","legend":"\u003cp\u003eRoot area (A), total root length (B), root volume (C), mean root diameter (D) and root dry mass (E) for seven forage grasses subjected to two copper concentrations (0.3 and 20 µmol L\u003csup\u003e-1\u003c/sup\u003e). Lowercase letters compare copper concentrations for the same species.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4383826/v1/54f2b638728b7ebf258a2d9b.png"},{"id":58225360,"identity":"5a406021-2e3c-447d-bc0d-0aebb010036a","added_by":"auto","created_at":"2024-06-12 17:44:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":79028,"visible":true,"origin":"","legend":"\u003cp\u003eSPAD index of seven forage grasses submitted to two doses of copper (0.3 and 20 µmol L\u003csup\u003e-1\u003c/sup\u003e). Lowercase letters compare doses for each species.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4383826/v1/d424e1395e411cc84cbb324a.png"},{"id":58224342,"identity":"f1632b29-e4c6-4366-9bee-d3ae9eba844d","added_by":"auto","created_at":"2024-06-12 17:36:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":418804,"visible":true,"origin":"","legend":"\u003cp\u003eCopper contents in roots (A), shoots (B), total in the plant (C) and translocation factor (D) in seven forage grasses exposed to two concentrations of copper (0.3 and 20 µmol L\u003csup\u003e-1\u003c/sup\u003e). Lowercase letters compare doses for each species. Capital letters compare forages within the same dose. Tukey (0.05).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4383826/v1/9831e6ec005f661b3f923788.png"},{"id":59754075,"identity":"8d13122a-4127-4e94-bfc9-a5779dac230e","added_by":"auto","created_at":"2024-07-06 01:16:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2652259,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4383826/v1/a8b37362-133b-4eaf-b30d-5763c1cea2ea.pdf"}],"financialInterests":"","formattedTitle":"Phytoremediation potential of forage grasses in copper-contaminated environments","fulltext":[{"header":"1 INTRODUCTION","content":"\u003cp\u003eHuman activity, especially in the agricultural context, is largely responsible for raising the levels of trace elements in soils and waters, which, in turn, can promote environmental pollution (CONTI et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; LI et al., 2016; LI et al. al., 2015; fiWAN; LEI; CHEN, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Copper is one of those chemical elements causing contamination is the. Several products used in agriculture contain copper in their constitution, such as swine manure, chemicals and even by-products of mining activities, which can raise the levels of this element in the soil to toxic levels for plants (FERREIRA et al., 2018, WAN et al., 2020).\u003c/p\u003e \u003cp\u003eIn vineyards, for example, the fungus that causes downy mildew is controlled through the application of a fungicide composed of CuSO\u003csub\u003e4\u003c/sub\u003e and Ca (OH)2 (GISI et al., 2009). Thus, after the use of fungicides with copper in fruit trees, this metal can accumulate mainly in the superficial organic fraction of the soil (BRUNETTO et al., 2014; COUTO et al., 2014).\u003c/p\u003e \u003cp\u003eIn plants physiology, copper is an essential element, which helps in protein synthesis and carbohydrate metabolism, regulates processes such as photosynthesis and respiration, and can also act in plant protection (GUIMAR\u0026Atilde;ES et al., 2016). Cu is absorbed from the soil to maintain the plant's functional activities, and non-accumulating plants absorb a dose lower than 10 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of micronutrient (AWA; HADIBARATA, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Once absorbed in high concentrations, plants can present damage to their architecture and morphology of the root system, decreasing shoot growth and increasing the average diameter of the roots (AMBROSINI et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and, consequently, decreasing the absorption of nutrients. water and nutrients (CAMBROLL\u0026Eacute; et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) reducing their growth and production (CHRISTOU et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; RIZVI; KHAN, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn soils with a high level of Cu, some agronomic techniques that limit the availability of this element can be applied (BRUNETTO et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), such as phytoremediation. Phytoremediation uses in its process plants with the potential to concentrate and metabolize trace elements in their tissues (SALT et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), constituting an ecological and sustainable technique, marked by ease of application and low cost (AWA; HADIBARATA, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; CRISTALDI et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), in addition to providing less soil erosion and improving soil structure and biodiversity (Ali et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Tahir, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), thus improving the quality of the ecosystem (LIU et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). ; MCCUTCHEON; J\u0026Oslash;RGENSEN, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). However, the efficiency of the phytoremediation practice is dependent on the physiological characteristics of the selected plants and the pollutant in question (LI et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGrasses (Gramineae) are an expressive group in phytoremediation context, as they are fundamentally important from an ecological point of view, involved in recovery, protection and revitalization of the soil (CONTI et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Gramineae also present efficient photosynthetic performance in various conditions with different levels of soil requirement, high tillering capacity and soil cover, root system that provides high mechanical support for the soil, in addition to high biomass production (DUBIS et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; LAMBRECHTS et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; SPRINGER, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite belonging to the same botanical family, grasses have a great functional diversity. A relatively classic classification in this sense is the classification of species according to the way they use ecological niches and exploit resources in the environment. In this sense, resource competing and resource conserving plants differ in terms of their ability to capture resources from the environment and their growth strategies (CRUZ et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Plants classified as resource competitors demonstrate higher performance in environments with little stress, present faster growth, greater nutritional requirement and greater specific leaf area (AFE) while resource conserving species are more adapted to environments with higher levels of stress, being more efficient in using the resources of the environment, they present slower growth rates and lower AFE (CRUZ et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; GRIME, 1977a).\u003c/p\u003e \u003cp\u003eTo remove the trace element from the soil, its absorption via the root system is necessary (AWA; HADIBARATA, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; NEDJIMI, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and functionally different plants have different abilities in capturing soil resources. Given this context, this study started from the central hypothesis that resource competing and resource conserving plants have different potentials for phytoextraction from areas contaminated with copper. Therefore, this study determined the phytoremediation potential of competing and resource-conserving forage grasses cultivated in environments contaminated with high levels of copper.\u003c/p\u003e"},{"header":"2 MATERIALS AND METHODS","content":"\u003cp\u003eAn experiment was carried out in a greenhouse of the department of soils and natural resources of Santa Catarina State University (UDESC), in Lages, Santa Catarina, Brazil, in 2016. The greenhouse was adapted with photoperiod and luminosity provided by natural light, with temperature and humidity controlled by an automated system, which remained between 15 and 25\u0026deg;C and 70 and 95%, respectively.\u003c/p\u003e \u003cp\u003eSeven forage grasses from tropical climate (C4) were cultivated in two concentrations of copper. Plants used were three cultivars of Brachiaria brizantha (Hochst.) Stapf.: 'BRS Piat\u0026atilde;' (piat\u0026atilde; grass), 'Marandu' (marandu grass) and Xara\u0026eacute;s (xara\u0026eacute;s grass); one from Brachiaria humidicola (Rendle.) Schweickerdt (B. humid\u0026iacute;cola); two cultivars of Panicum maximum Jacq.: 'Aruana' (Aruana grass) and 'Tanzania' (Tanzania grass); and one of Axonopus catharinensis Valls (giant missioneira grass). Seedlings of piat\u0026atilde;, marandu, xara\u0026eacute;s, aruana, tanzania and \u003cem\u003eB. humidicola\u003c/em\u003e grasses were obtained by germinating untreated seeds in gerbox boxes and BOD-type chambers, according to the rules for analysis and seed germination of the Brazilian Ministry of Agriculture (MAPA) (BRAZIL, 2009).\u003c/p\u003e \u003cp\u003eAfter germination, seedlings size was standardized and they were transferred to plastic trays with sand. Seedlings size was standardized and the sand underwent a disinfection process with a 5% HCl solution and distilled water. The giant missioneira grass had its seedlings produced through the development of 5 cm propagules with a stem containing a node from the mother plants. During 10 days, the trays were irrigated with Hoagland's nutrient solution (ARNON; HOAGLAND, 1940) with 50% ionic strength and pH 5.5. Subsequently, seedlings were transferred to pots containing Hoagland's nutrient solution at 100% ionic strength and pH 5.5, remaining like this for another 10 days, without contaminants.\u003c/p\u003e \u003cp\u003eExperimental units consisted of two-litter polypropylene pots lined with aluminium foil, containing Hoagland's nutrient solution at 100% ionic strength and pH 5.5, and three plants of the same species. The treatments consisted of two levels of Cu in the hydroponic solution: 0.3 and 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, (source Cu(NO3)2) and seven forage species (piat\u0026atilde;, marandu, xara\u0026eacute;s, aruana, tanzania, humid\u0026iacute;cola and giant missioneira). composing a completely randomized design, in a 7 x 2 factorial scheme, with three replications.\u003c/p\u003e \u003cp\u003eThe Cu concentration of 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was selected in a preliminary experiment, where the doses of 0.3, 1, 5, 20 and 80 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu in the nutrient solution were tested. The criterion used for the selection was the highest concentration of Cu in the nutrient solution in which there was a 50% reduction in the growth rate of stem and pseudo stem height (DC50) among the seven evaluated forages. More details of the preliminary experiment can be obtained in Eduardo (2018). The concentration of 0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e is standard for the nutrient solution proposed by Arnon and Hoagland (1940), used in the present study.\u003c/p\u003e \u003cp\u003eAfter the experiment was implemented in the greenhouse, the plants were maintained for 30 days, with the nutrient solution being replaced weekly and the pH adjusted every 3 days. Oxygenation and turning of the solution were performed using an automatic aeration system, three times a day. During plant growth, from the 15th to the 30th day, measurements were taken of stem and pseudo stem height, length of the last expanded leaf and number of live leaves in one of the tillers of each experimental unit. With these measurements, the culm\u0026thinsp;+\u0026thinsp;pseudo stem growth rate - TCCP (1), leaf appearance rate - TAPF (2) and the leaf expansion rate - TEF (3) were obtained:\u003c/p\u003e \u003cp\u003e(1) TCCP = (stem height\u0026thinsp;+\u0026thinsp;final pseudo stem - initial pseudo stem) /15\u003c/p\u003e \u003cp\u003e(2) TAPF = (final number of live leaves \u0026ndash; initial number) /15\u003c/p\u003e \u003cp\u003e(3) TEF = (sum of differences in final - initial length of expanding leaves) /number of leaves) /15\u003c/p\u003e \u003cp\u003eAfter 30 days of growth, the measurements of leaves were taken using the SPAD (Soil Plant Analysis Development), index using a portable chlorophyll meter (SPAD 502; Konica Minolta\u0026reg;, Tokyo, Japan). Measurements were performed on the lower, middle and upper third of the fully expanded leaves, on nine leaves of each experimental unit, between 9 and 10 am. After measurements plants were then harvested and washed with deionized water. Leaves were detached from the stems and integrated into a leaf area integrator (LI-3000C, LI-COR, Lincoln, USA) to obtain the leaf area of ​​each plant. Plants were dried in an oven with forced air circulation at 65 \u0026ordm;C for 72 hours and then the dry mass (DM) of each structure and total dry mass were determined. The oven-dried material was processed in a Wiley mill and sieved through a 20-mesh sieve. The leave dry mass and leaf area data were used to calculate the specific leaf area \u0026ndash; AFE (4):\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAFE\u0026thinsp;=\u0026thinsp;Leaf Area / Dry Mass of Leaves\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e(2) Roots, after being collected, washed and cleaned, were evenly distributed in an acrylic vat filled with a slide of distilled water, without overlapping, and submitted to digitalization in a professional scanner (Epson Expression 10000 XL, Epson America Inc., Long Beach, USA). Images were processed using a computer program (WinRhizoTM Pro 2009, Regent Instruments, Montreal, Canada) and thus, the values of mean diameter, total length, root area and volume were obtained.\u003c/p\u003e \u003cp\u003e To extract Cu from roots and shoots of plants, samples were opened by microwave-assisted acid digestion, according to method 3052 of the United States Environmental Protection Agency \u0026ndash; USEPA (1996). Quantification was performed using an inductively coupled plasma optical emission spectrometer (ICP-OES) (Optima\u0026reg; 8300, Perkin Elmer, Norwalk, USA), in triplicate. Eight blank tests were used to determine the instrument's detection limit, which corresponded to 0.03 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The reliability of the analytical method used to determine the concentration of Cu in plants was defined as 100\u0026thinsp;\u0026plusmn;\u0026thinsp;5%, using the sample SRM 1573a (tomato leaves) certified by the National Institute of Standards and Technology (NIST) as a reference. Values recovered from the reference sample are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eValues recovered by the method used to determine the concentration of Cu in forage plant tissue samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTriplicate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCertified\u003c/p\u003e \u003cp\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRecovered value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRecovery\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSRM 1573a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e105.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e With the concentrations of Cu in roots and shoots, the translocation factor (FT) for the trace element was calculated, according to Eq.\u0026nbsp;(5):\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFT\u0026thinsp;=\u0026thinsp;Cu concentration in shoots/Cu concentration in roots\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eInitially, for the purpose of proving the formation of forage plant groups (CRUZ et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) into conservators and competitors for resources, five variables were selected, namely: AFE, TAF, TEF, TCCP and MS per tiller. Data were tested for each dose of Cu (0.3 and 20.0 \u0026micro;mol L-1). For data analysis, the Minitab 17 program was used, with the Cluster clustering method, complete linkage method, Euclidean distance and standardized variables. Data on AFE, TAF, TEF, TCCP and total DM, Cu content in roots, shoots and total, translocation factor, root area, total root length, root volume, mean diameter, root dry mass and SPAD index were obtained. submitted to analysis of variance, and if there was a difference, their means were tested using the Tukey statistic test, with a 5% error probability.\u003c/p\u003e"},{"header":"3 RESULTS","content":"\u003cp\u003eForages that were cultivated in an environment with adequate concentrations of Cu formed two distinct groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). The group of resource conserving species was composed of the giant missioneira, \u003cem\u003eB. humidicola\u003c/em\u003e and piat\u0026atilde;, while the group of resource competing species was composed of aruana grass, marandu, tanzania and xara\u0026eacute;s (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). When forage grasses were exposed to the highest concentration of Cu (20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) there was no functional segregation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb; \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn both functional groups, the specific leaf area was not influenced by Cu dose and plant species (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Among competing species, Tanzania grass had the highest leaf appearance rate (0.14 leaves day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e tiller\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) while the lowest leaf appearance rate (0.10 leaves day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e tiller\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was observed in marandu, when cultivated with 0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e Cu (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). When cultivated at a concentration of 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu, the highest leaf appearance rate was observed for Aruana and Tanzania grasses (0.175 leaves day-1 tiller-1), for Xara\u0026eacute;s grass it was 0.11 leaves dia\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e tiller\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and, with a lower rate of leaf appearance, marandu grass (0.07 leaves day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e tiller\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe leaf expansion rate was higher for tanzania and aruana grass, and the lowest rates were observed in marandu, regardless of the copper dose. Aruana grass showed the highest rates of stem and pseudo stem expansion, regardless of Cu dose, while marandu grass showed the lowest rate of stem and pseudo stem expansion when subjected to 0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu, and marandu and xara\u0026eacute;s had the lowest means when cultivated with 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu. For dry mass per tiller, regardless of Cu dose, Tanzania and xara\u0026eacute;s had higher mass per tiller, followed by aruana and marandu (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor the resource-conserving species, leaf appearance rate was higher in the giant missioneira, regardless of Cu dose, not differing from the piat\u0026atilde; grass in the concentration of 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu. For the leaf expansion rate, piat\u0026atilde; grass showed superior results in both doses, not differing only from \u003cem\u003eB. humidicola\u003c/em\u003e in the concentration of 0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu. The expansion rate of culms and pseudo stems, in concentration of 0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of copper, was lower for the piat\u0026atilde; grass, while in the concentration of 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of copper, it was higher for the giant missioneira. Dry mass per tiller was higher for piat\u0026atilde; grass, followed by giant missioneira and \u003cem\u003eB. humidicola\u003c/em\u003e, regardless of the Cu dose (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe effect of copper doses for each species showed that for arowana grass, the concentration of 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of copper conferred a higher rate of leaf appearance and culm and pseudo stem expansion (1.5 and 1.4 times higher, respectively) and consequently, higher dry mass per tiller, being 25 percent higher in the highest Cu concentration than in the concentration of 0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Tanzania grass showed a 15% reduction in leaf expansion rate when cultivated with 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of copper compared with the concentration of 0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of copper. Marandu grass had heavier tillers when cultivated at the highest dose of copper.\u003c/p\u003e \u003cp\u003eLeaf expansion rate and stem and pseudo stem elongation were lower for xara\u0026eacute;s grass at the highest copper dose, while for piat\u0026atilde;, the variables were lower at the lowest copper concentration. The \u003cem\u003ehumidicola\u003c/em\u003e was negatively affected by the higher copper concentrations for leaf appearance and expansion rate, stalk and pseudo stem expansion rate and dry mass/tiller. The higher concentration of copper negatively affected the rate of leaf appearance and expansion of stem and pseudo stem and positively affected the rate of leaf expansion and dry mass per tiller of the giant missioneira (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResource competing species showed leaf expansion rates two and 1.8 times higher than conservative species when cultivated under copper concentrations (0.3 and 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e respectively). When cultivated with a nutrient solution containing 0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, competing species presented a leaf appearance rate 50 percent lower than those presented by conservative species and specific leaf area 1.6 times higher than the resource-conserving group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive data of variables used in the formation of PCA's for seven forage grasses submitted to two different copper concentrations (0.3 and 20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGrass Species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Cu]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAFE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTx Ap.F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTx Exp.F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTx Col\u0026thinsp;+\u0026thinsp;Pseu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecm\u003csup\u003e2\u003c/sup\u003e g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eleaves day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e tiller\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emm day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003emm day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e tiller\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eg tiller\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eResource\u003c/p\u003e \u003cp\u003eCompeting\u003c/p\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAruana\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e229.75 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12 bAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.74 aAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.82 bA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.23 bB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188.61 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.78 aAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.51 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.54 aB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTanz\u0026acirc;nia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e228.30 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67.70 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.07 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e226.44 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.64 bA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.31 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.95 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMarandu\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e182.90 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.63 aC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.00 aC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.68 bB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e123.54 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07 aC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.55 aC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.39 aBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.93 aB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eXara\u0026eacute;s\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e138.37 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11 aAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.70 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.71 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.54 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202.37 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.82 bBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.42 bC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.39 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eResource Conserving Species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eHumid\u0026iacute;cola\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e126.32 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.28 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.34 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.55 aC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e342.32 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08 bB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.97 bB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.12 bB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.23 bC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePiat\u0026atilde;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.95 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.93 bA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.80 bB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.10 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.63 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17 aAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.26 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.81 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.47 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMissi. Giant\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e143.88 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.06 bB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.25 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.76 bB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115.01 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24 bA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.06 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.12 bA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.03 aB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCompeting Species\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e194.83 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.69 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.40 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.86 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e185.24 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.20 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.16 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.95 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eConservating Species\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e119.72 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.43 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.79 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.80 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e178.65 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.76 aB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.02 aA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.91 aA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAFE: Specific leaf area; TxAp.F: Leaf appearance rate; TxExp.F: Leaf expansion rate; Tx Col\u0026thinsp;+\u0026thinsp;Pseu: Stem\u0026thinsp;+\u0026thinsp;pseudo stem growth rate; MS: Dry mass/tiller; Perf.: Tillers; Missi.: Missioneira. \u003csup\u003e1\u003c/sup\u003e Lowercase letters compare different doses for each forage and average within each group; \u003csup\u003e2\u003c/sup\u003eCapital letters compare foragers within each dose and group and compare group means within the same doses. These comparisons were made using Tukey's statistical test (\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRoot area of ​​aruana, marandu and giant missioneira grasses were not altered by the different copper concentrations. The same happened to the root volume of aruana and giant missioneira grass (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). While tanzania, xara\u0026eacute;s and piat\u0026atilde; showed an increase in root area of ​​28, 106 and 155%, respectively, when cultivated with the highest concentration of Cu, with an increase in root volume of, respectively, 17, 73 and 112%, when cultivated with 20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e copper (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Only \u003cem\u003ehumidicola\u003c/em\u003e grass showed a reduction in root area and volume at the highest concentration of Cu, with a 26% reduction in its root area (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) and a 46% reduction in its root volume (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). When cultivated in the presence of 20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of copper, the tanz\u0026acirc;nia, marandu, xara\u0026eacute;s and piat\u0026atilde; grasses showed an increase in root length, being these 1.48; 1.51; 2.55 and 2.92 times higher than that observed when cultivated with 0.3 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of Cu in the nutrient solution, respectively. The giant missioneira had a 17% reduction in root length when exposed to 20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of Cu (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eThe average root diameter was negatively affected by the higher copper concentration, reducing 24, 12, 22, 20 and 21% for the species of tanzania, marandu, xara\u0026eacute;s, humidicola and piat\u0026atilde; grass, respectively. Only the giant missioneira showed an increase in the mean diameter of roots when submitted to 20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of Cu (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). When cultivated with 20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of Cu, the species aruana, marandu and missioneira giant presented an increase in the dry mass of roots in the proportions of 1.6; 1.5 and 1.4 times higher than that observed in cultures with 0.3 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of Cu. The other species showed no difference in root dry mass when cultivated in 0.3 or 20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of Cu (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee).\u003c/p\u003e \u003cp\u003eExposure to the highest concentration of copper (20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of Cu) increased the SPAD index by 30% for tanzania grass, 40% for piat\u0026atilde; grass and 10% for giant missioneira grass. On the other hand, marandu, xara\u0026eacute;s and humid\u0026iacute;cola showed a reduction of 44; 59 and 37% respectively, when cultured with 20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of Cu (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). It was possible to observe that the SPAD index decreased in competing resource plants, with the exception of Tanzania grass.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor copper concentration in roots, shoots and for its total concentration, all species showed higher content when cultivated with 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec. When cultivated at a concentration of 0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu, marandu grass showed higher copper content in the roots and in total. Among the plant species, \u003cem\u003eB. humidicola\u003c/em\u003e presented the highest total and root copper content, 90% higher than that observed for marandu and xara\u0026eacute;s grasses (1068 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), when cultivated in an environment with high copper content. The \u003cem\u003ehumidicula\u003c/em\u003e had higher Cu concentration and lower root size data. On the other hand, the lowest levels of copper were observed for giant missioneira and tanzania (125 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). The copper content of the aerial part represented very little of the total copper content present in the plants, with the highest copper content in the aerial part observed for the giant missioneira (30 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) not differing from the \u003cem\u003ehumid\u0026iacute;cola\u003c/em\u003e and piat\u0026atilde; (21 mg kg \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) at a concentration of 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Regardless of the plant species, the translocation factor was higher at the lowest copper concentration (0.3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of Cu). In same cooper concentration the highest translocation was observed for B. \u003cem\u003ehumid\u0026iacute;cola\u003c/em\u003e, piat\u0026atilde; and giant missioneira (128%) while at the highest concentration of Cu (20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) the giant missioneira had the highest translocation factor (25%), followed by Tanzania (13%) and the other species showed the lowest translocation factor (1.8%) at the concentration of 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of copper (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLowercase letters compare doses for each species. Capital letters compare forages within the same dose. Tukey (0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of the effect of copper on variables analysed for seven forage grasses cultivated for 30 days in a nutrient solution with a concentration of 20 \u0026micro;mol L\u003csup\u003e-1\u003c/sup\u003e of copper.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eObtained Data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eGrass Species\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAruana\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTanz\u0026acirc;nia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMarandu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eXara\u0026eacute;s\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHumidicola\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePiat\u0026atilde;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM. Giant\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e=*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTx Ap.F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTx Exp.F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTx Col\u0026thinsp;+\u0026thinsp;Pseu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMS\u003csub\u003eperf\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTot. Root Length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot Volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMed. Diameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot Dry Mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSPAD Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThe dominance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e=/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* =: No efect; ** +: Positive efect; *** -: Negative efect.\u003c/p\u003e"},{"header":"4 DISCUSSION","content":"\u003cp\u003eForage grasses, when subjected to environments with higher copper concentrations, show some differences in their original functional attributes. Two species (piat\u0026atilde; and marandu) had a functional group transition when cultivated under a concentration of 20 \u0026micro;mol L-1 of copper, in this study. Although a slight movement was observed within the PCA's, the other species showed no change in their functional groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). That movement indicates the occurrence of changes in the growth patterns of grasses and, regardless of functional group, the studied species presented different behaviours when exposed to a high concentration of copper, as reviewed by ADREES et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and confirmed by Saleem et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Saleem et al. observed different response patterns for four varieties of Corchorus capsularis grown in soil contaminated with copper, indicating that the plant's defence mechanism, antioxidant activity, plays an important role in the choice of phytoremediator (ALVES et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Cu presence can modify FA growth patterns, stem expansion, dry and fresh mass, as observed for maize (BARBOSA et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), wheat (AZOOZ; ABOU-ELHAMD; AL-FREDAN, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; COOK; VARDAKA; LANARAS, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) and rice (THOUNAOJAM et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA reduction in root length and dry mass of \u003cem\u003eFestuca arundinacea\u003c/em\u003e and \u003cem\u003eLolium perenne\u003c/em\u003e when grown in soil with different copper concentrations was observed by Zhao et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In that study, the reductions in root length were more pronounced in fescue (resource conserving species), while shoot dry mass suffered greater reductions in perennial ryegrass (resource competing species). Although resource conserving species are more effective in adapting to environments with stressors (GRIME, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1974\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1977b\u003c/span\u003e), this fact was not observed in this work. The results obtained with this study suggest that plant response is not exclusively associated with the functional group, but in individual characteristics, such as antioxidant activity, which corroborates with Alves et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Saleem et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), since the root and of aerial expansion were different for species within the same functional group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eObserving the effects of the presence of copper (20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) on the seven forage species studied, it can be observed that the missionary giant and piat\u0026atilde; showed a greater positive effect in the analysed variables, as well as the marandu grass. The missioneira giant is a native species that tolerates shady areas, being a species with high potential for phytoremediation of contaminated areas. The aruana and tanzania grasses were not efficient for removing copper from the system, while the xara\u0026eacute;s grass proved to be null to inefficient in removing copper. The \u003cem\u003ehumidi\u0026iacute;cola\u003c/em\u003e was shown to be inefficient in the analysed variables when cultivated in high concentration of copper.\u003c/p\u003e \u003cp\u003eAruana grass is the only plant that did not presented negative effects when cultivated for 30 days in a nutrient solution with 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e copper concentration. For aruana, although there was no change in the volume and density of roots, as well as in the leaf area and specific leaf area, there was an increase in the dry mass of roots and leaves, and in the total dry mass. It has no negative effect on aruana, but it removed low amounts of Cu and also had good phyto-stabilization, but it is not a phytoextractor. Aruana and marandu showed low sensitivity to phytotoxicity caused by the trace element, with low translocation compared to other forages, and Cu concentration in the shoot below the critical range.\u003c/p\u003e \u003cp\u003eAfter absorbed by roots, copper accumulates in root tissues, since the trace element has low translocation in the plant (REHMAN et al., 2019c). In roots, the trace element acts negatively on anatomical and root growth characteristics (LIN et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; REHMAN et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e), affecting root cell growth, expansion and division (KOLBERT et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; LI et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003eb; LIU; KOTTKE, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Plant species with phytoremediator potential to environments contaminated with trace elements need to absorb or degrade the contaminant (AWA; HADIBARATA, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; LIU et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; NEDJIMI, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), where, in phytoextraction or phytoaccumulation, plants are able to removal of the trace element from the medium by absorption and accumulation in plant tissues, usually leaves (CRISTALDI et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this sense, species with rapid vegetative growth and that can be defoliated frequently are the most apt to be used in these phytoremediation programs (LI et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e; STERCKEMAN et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Thus, plant species that show few root changes when grown in environments with high trace element content should be considered in phytoremediation studies, since having a good root contribution is essential for vegetative growth. For the parameters of root growth, the results showed that the \u003cem\u003ehumidicola\u003c/em\u003e presented smaller roots when cultivated in 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of copper, being, in this case, disregarded for phytoremediation programmes, due to its low root reach zone (LASAT, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2002\u003c/span\u003e)., although it showed the highest copper concentrations in the present study.\u003c/p\u003e \u003cp\u003eRoot changes are factors that favour nutrient deficiency in plants (ADREES et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), since it reduces the area of ​​root exploration, especially of fine roots (REHMAN et al., 2019c). In addition, excess copper in roots may be associated with reduced absorption of macronutrients (Ali et al. 2002) and micronutrients (AZEEZ; ADESANWO; ADEPETU, 2015), thus triggering a nutritional imbalance for plants (REHMAN et al., 2019; SAĞLAM et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSPAD index refers to the chlorophyll content, which is directly related to the nitrogen nutrition of the plant, where a reduction in the SPAD index indicates a lower nitrogen nutrition of plants (BAZAME et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; CORR\u0026Ecirc;DO et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; RAVIER; QUEMADA; JEU, 2017; YUE et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Under conditions of cultivation of plants in environments contaminated with Cu, the absorption of this can worsen the nutritional status of the plant, compromising its vegetative growth. The reduction of the SPAD index may also be associated with the reduction in the size of the cells of the chlorophyll parenchyma of the leaf mesophyll induced by Cu, or by the collapse of these parenchyma cells due to the sensitivity to the toxicity of trace elements (SRIDHAR et al., 2005; GOMES). et al., 2011). Furthermore, leaf chlorosis is closely associated with morphological and physiological changes in chloroplasts; according to Yruela (2013), Cu can change the structure and composition of the thylakoid membranes of this organelle.\u003c/p\u003e \u003cp\u003eIn this study, marandu, xara\u0026eacute;s and \u003cem\u003ehumidicola\u003c/em\u003e grasses presented reductions in the SPAD index when cultivated at the highest dose of Cu (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Those reductions in the SPAD index observed in the leaves may be associated with the reduction in the size of the chlorophyll parenchyma cells of the leaf mesophyll induced by Cu, or with the collapse of these parenchyma cells due to sensitivity to the toxicity of trace elements (SRIDHAR et al., 2005). ; GOMES et al., 2011). Furthermore, leaf chlorosis is closely associated with morphological and physiological changes in chloroplasts; according to Yruela (2013), Cu can change the structure and composition of the thylakoid membranes of this organelle.\u003c/p\u003e \u003cp\u003eThe highest Cu content in the aerial part of the \u003cem\u003ehumidicola\u003c/em\u003e (2025 mg kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and the lowest content in Marandu and Xara\u0026eacute;s (1060 mg kg-1) may indicate a reduction in the nutritional index with the increase in the copper content in the plant, mainly in the roots (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). However, competition with iron and magnesium cations may be taking place (YRUELA, 2013).\u003c/p\u003e \u003cp\u003eWith an increase in the availability of copper in the hoagland solution (20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), there was an expected increase in the copper content of all species in the roots, shoots and in the plant, when compared to the standard concentration of Cu (0, 3 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), since increasing the concentration of the trace element in the nutrient solution would increase its root absorption (SHAH; DAVEREY, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and compartmentalization of the trace element in plant (NEDJIMI, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Forage plants cultivated with 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of copper, regardless of the functional group, showed higher copper content in the roots, compared to the shoot (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In order to successfully remove trace element from the soil, it is necessary that the root structure of the plant effectively colonizes the soil stratum contaminated with Cu (LASAT, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) so that the plant species used can absorb and compartmentalize the element. trace in its biomass (MAHAR et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Pedersen, Kj\u0026aelig;r and Elmegaard (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) had already observed a higher copper content in the plant roots, where, in that case, it was possible to identify that the fine roots of \u003cem\u003eFallopia convolvulus\u003c/em\u003e had the highest levels of Cu. Later, Wei et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) observed in plants of \u003cem\u003eChrysanthemum coronarium\u003c/em\u003e and \u003cem\u003eSorghum sudanense\u003c/em\u003e that 90% of the copper present in the plant was in its root organs. Root apparatus has a greater amount of trace element, since Cu is rapidly absorbed by the roots and its translocation to the aerial part of the plant does not follow the same speed of root absorption (REHMAN et al., 2019c), being accumulated in lower proportion in the aerial part of plants (MAHMUD et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; REHMAN et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e; THOUNAOJAM et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), as observed in the results of the present study (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eThe highest copper content in the shoot was observed for \u003cem\u003ehumid\u0026iacute;cola\u003c/em\u003e, piat\u0026atilde; and missioneira giant. However, the missioneira giant had the highest translocation factor, regardless of copper concentration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). These data demonstrate that the \u003cem\u003ehumidicula\u003c/em\u003e has a greater ability to translocate the trace element to the shoot, without showing losses in root dry mass (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec) and tiller dry mass (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and also showed a higher SPAD index (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec) 3), when cultured with 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of copper. These results place Missioneira giant in the position of a plant with the potential to phyto-remediate soil contaminated with copper, given that one of the main characteristics of phytoremediation plants is the accumulation of the trace element in their tissues, mainly shoots (NEDJIMI, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePlant species with greater root structure and high production of above-ground biomass that can be harvested (NEDJIMI, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) with the ability to extract trace elements from the soil (CRISTALDI et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) are important characteristics when choosing plant species for programmes of phytoremediation. The results showed that forage grasses do not maintain their functional groups (competitors or resource conservationists) when exposed to environments with copper contamination. After 30 days of cultivation in a nutrient solution with two levels of copper, the plant species presented different responses to the attributes analysed (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) regarding the ability to phyto-remediate environments contaminated by copper, where the forage species of marandu, piat\u0026atilde; and missionaria giant have the potential to decontaminate Cu-contaminated soils.\u003c/p\u003e"},{"header":"5 CONCLUSION","content":"\u003cp\u003eSpecies studied did not maintain their functional groups in competing or resource conserving environments with high copper concentrations. Aruana grass is a good phytostabilizer, but it is not a phytoextractor. The humidicola grass did not present any positive effect in its development in high concentrations of copper. Tanzania grass had a reduction in leaf expansion rate and mean diameter, and xara\u0026eacute; grass, in addition to these parameters, also showed a reduction in the growth rate of stem and pseudo stem height. Therefore, these species are not viable for copper phytoextraction in contaminated areas.\u003c/p\u003e \u003cp\u003eMarandu, piat\u0026atilde; and missionaria giant grasses are promising species to be used in phytoremediation for tropical areas with high concentration of copper.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eACKNOWLEDGMENTS\u003c/p\u003e\n\u003cp\u003eAuthors would like to thank the PAP UDESC-FAPESC Research Support Programme and PROAP-CAPES, and UNIEDU-SC for granting the research grant.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;DECLARATION OF INTEREST\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Authors claim that there are no competing interests to declare.\u003c/p\u003e\n\u003cp\u003eThis study evidenced the behaviour of forage grasses exposed to different concentrations of copper. The text presents new scientific information in relation to the functional groups of grasses that did not remain competitive or conserve resources in environments with high concentrations of copper. In addition, it showed that the species of marandu, piat\u0026atilde; and giant missioneira grass are promising to be used in phytoremediation for tropical areas contaminated by copper.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eNOVELTY STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article presents promising plant species for the recovery of areas contaminated with copper. Different species of tropical forage grasses may have different phytoremediation potentials. The promising species for phytoremediation of copper were the marandu, the piat\u0026atilde; and the giant missioneira grass.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eETHICAL APPROVAL\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe manuscript was not submitted to more than one journal for simultaneous consideration. It is original and was not published elsewhere.\u0026nbsp;The article is my own authorship and uses data correctly. References are citations honestly. The article meets all of the journal\u0026apos;s ethical requirements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCONSENT TO PARTICIPATE AND PUBLISH\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors developed for the article and consent to publish the article in this journal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAUTHORS CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Daniel and Campos. The first manuscript was written by Daniel and Rosini and all authors commented on previous versions of the manuscript. All authors: Daniel, Rosini, Winter, Silva, Sbrissia, Premieri and Campos read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUDESC (Santa Catarina State University), PROAP (Postgraduate Support Program) and CAPES (Coordination for the Improvement of Higher Education Personnel).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study does not have competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eADREES, M. et al. The effect of excess copper on growth and physiology of important food crops: a review. \u003cstrong\u003eEnvironmental Science and Pollution Research\u003c/strong\u003e, v. 22, n. 11, p. 8148\u0026ndash;8162, 2015. \u003c/li\u003e\n\u003cli\u003eALI, H.; KHAN, E.; SAJAD, M. 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Responses of root growth and protective enzymes to copper stress in turfgrass. \u003cstrong\u003eActa Biologica Cracoviensia Series Botanica\u003c/strong\u003e, v. 52, n. 2, p. 7\u0026ndash;11, 2010. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Plant growth, Copper, Phytoextraction, Forage grasses, Phytoremediation","lastPublishedDoi":"10.21203/rs.3.rs-4383826/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4383826/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHuman activities have considerably increased copper (Cu). This study evaluated the potential of copper phytoextraction in competing and resource-conserving plants. The experiment was carried out in a greenhouse with eight tropical forage grasses, at two levels of Cu in the nutrient solution: 0.3 and 20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Variables of plant morphogenesis, leaf area measurements, SPAD index, total length, area, volume and average diameter of roots, specific leaf area, specific root area, root density, root length density, specific root length were evaluated, and the relationship between leaf and stem and roots and shoots. Data were submitted to analysis of variance and test of means. Forage grasses did not maintain their functional groups at the highest copper concentrations. The promising species for phytoremediation of copper contaminated areas were marandu, piat\u0026atilde; and giant missioneira grass.\u003c/p\u003e","manuscriptTitle":"Phytoremediation potential of forage grasses in copper-contaminated environments","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-12 17:36:50","doi":"10.21203/rs.3.rs-4383826/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"35e474c7-b30a-4e7e-9628-d7be80fcbfcc","owner":[],"postedDate":"June 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-16T12:37:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-12 17:36:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4383826","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4383826","identity":"rs-4383826","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}