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GEOLOGY, ECOLOGY, AND LANDSCAPES 2021, VOL. 5, NO. 1, 53–64 INWASCON https://doi.org/10.1080/24749508.2019.1700671 RESEARCH ARTICLE Copper (Cu) tolerance and accumulation potential in four native plant species: a comparative study for eﬀective phytoextraction technique a a b c a Hira Amin , Basir Ahmed Arain , Taj Muhammad Jahangir , Abdul Rasool Abbasi , Jamaluddin Mangi , d e Muhammad Sadiq Abbasi and Farah Amin a b Institute of Plant Sciences, University of Sindh, Jamshoro, Pakistan; Institute of Advanced Research Studies in Chemical Sciences, University of Sindh, Jamshoro, Pakistan; Department of Fresh Water Biology and Fisheries, University of Sindh, Jamshoro, Pakistan; Department of Mathematics & Statistics, Quaid-e-Awam University of Engineering, Science & Technology, Nawabshah, Pakistan; National Centre of Excellence in Analytical Chemistry, University of Sindh, Jamshoro, Pakistan ABSTRACT ARTICLE HISTORY Received 27 September 2019 Phytoextraction involved the use of plants in rapid, eﬃcient, less expensive, and environment Accepted 27 November 2019 friendly removal of toxic metals from contaminated soil. For this study, a pot experiment was conducted and plant species: Abelmoschus esculentus, Avena sativa, Guizotia abyssinica, and KEYWORDS Glycine max were subjected to six copper concentrations i.e., 25, 50, 100, 150, 200, and 300 mg Soil contamination; −1 Cu kg for the investigation of Cu phytotoxicity, tolerance, and accumulation for 12 weeks phytotoxicity; under green house. Soil without spike were taken as control. After 12 weeks of experiment, Cu bioconcentration; toxicity on growth and chlorophyll contents were determined. Among four plant species, only bioaccumulation; −1 phytoremediation ratio A. sativa, C. tetragonoloba and S. indicum seeds were germinated at 300 mg Cu kg . The growth parameters were signiﬁcantly (p< 0.05) reduced under high Cu stress (from 25 to −1 100 mg Cu kg )in G. abyssinica and G. max. The chlorophyll content found maximum at 25 mg −1 Cu kg in all plant species as compared to control. Signiﬁcantly, high Cu accumulation was found in roots and shoots of A. sativa. The highest values of bioconcentration factor, bioaccu- mulation coeﬃcient, translocation factor (all greater than 1), phytoremediation ratios, and accumulation with high tolerance suggested that A. sativa was a suitable plant for eﬀective Cu phytoextraction. Introduction root and shoot growth, low yield as well as formation of reactive oxygen species (ROS) (Azooz, Abou-Elhamd, Soil pollution has become a serious and challenging &Al-Fredan, 2012; Stadtman & Oliver, 1991). environmental problem all over the world due to rapid Moreover,highCu stresscausedseveredamageto industrialization and urbanization (Li, 2018). Various metabolic pathways, disturbed the process of photo- industries discharged their toxic heavy metals contain- synthesis and biosynthesis of chlorophyll contents that ing wastes directly into soil and water system that in turn reduced the productivity of plants (Hegedus, substantially enhanced the degradation process and Erdei, & Horvath, 2001). Several anthropogenic sources signiﬁcantly aﬀected the ecosystem (Rashid, such as, mining and smelting operations, application of Manzoor, & Mukhtar, 2018; Wu, Zhang, Liu, & inorganic and organic fertilizers, liming treatments, Chen, 2018). These unwanted chemicals cause severe inappropriate use of Cu-containing fungicides and pes- health problems when exceed the permissible limits ticides, sewage sludge as well as wastewater irrigation (Li, Li, & Wang, 2019). system (Herawati, Suzuki, Hayashi, Rivai, & Koyoma, Copper (Cu) is an abundant transition metal on the 2000; Mackie, Müller, & Kandeler, 2012;Muhammad earth’s crust that exists in two diﬀerent oxidation states et al., 2015; Rebecca, 2011) has released a large amount either as monovalent (+1) or divalent (+2) (Rebecca, of Cu in natural environment and created soil contam- 2011). At low concentration, Cu is considered as an ination. Therefore, minimization of excess Cu from soil essential micronutrient for all living organisms proﬁle was needed. (Mahmood & Islam, 2006; Muhammad et al., 2015; Globally, management of soil pollution has become Wintz, Fox, & Vulpe, 2002) and plays several impor- the greatest economic challenge, because after getting tant roles in the number of metabolic activities, act as environmental acceptability, the success and practical catalysts for various homogeneous and heterogeneous implication of remediation techniques mainly depend chemical reactions (Mildvan, 1970). The high concen- upon cost (Padmavathiamma & Li, 2007). Various phy- tration of Cu developed several deleterious eﬀects in sical and chemical remediation methods have been plants (Dresler, Hanaka, Bednarek, & Maksymiec, reported in literature for the reclamation of metal- 2014) for instance, reduced seed germination, stunted contaminated soil. The major drawbacks of CONTACT Hira Amin firstname.lastname@example.org Institute of Plant Sciences, University of Sindh, Jamshoro 76080, Pakistan © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 54 H. AMIN ET AL. conventional methods are the requirement of high cost Program, G. max from the Institute of Oilseeds and technical resources (Wuana & Okieimen, 2011). Research Program, National Agricultural Research Theconventionalmethodseitherphysicalorchemical Centre Islamabad, Pakistan, A. esculentus from were not successful in agricultural lands because of their Komal seed Production, Tandoallahyar, and adverse eﬀects on soil properties. The technical require- G. abyssinica from Vine House Farm, UK. The ment and costs of conventional techniques were also seeds of selected plant species were surface steri- diﬀerent from one another such as physical remediation lized with 0.1% HgCl solution for 10 min to keep required large amount of material resources and man- them away from any microbial infection and then power whereas, chemical remediation like immobiliza- washed many times with tap water followed by tion and soil washing required cost-eﬀective methods distilledwater (Pourakbar,Khayami,Khara,& (Khalid et al., 2017;Ohetal., 2013). Therefore, to over- Farbidina, 2007). come the limitations of aforementioned physicochem- ical methods, it is necessary to develop an eﬃcient, environment compatible, and cost eﬀective remediation Soil samples collection and characterization technique for the removal of toxic contaminants from Soil samples were collected from the uncontaminated soil (Carolin, Kumar, Saravanan, Joshiba, & Naushad, ﬁeld of Jamshoro, Sindh, Pakistan with the help of 2017; Mani & Kumar, 2014). One of the novel hand shovel and brought to laboratory for further approaches referred as phytoremediation particularly study. The collected soil samples were mixed well phytoextraction has been considered an alternative and air dried for 2 weeks. After that, soil samples greensolutiontothe problemofheavy metals contam- were ground with pestle and mortar to pass through ination in soil and involved plants that eﬃciently accu- a size of 2 mm sieve and analyzed for physicochemical mulate toxic metals from surrounding areas and characteristics. Soil pH and electrical conductivity transport them from soil to above ground shoot (Rafati (EC) was measured with the help of pH-meter et al., 2011). The metal-enriched biomass after harvest- (InoLab-WTB GmbH; Weilheim, Germany) using ing can be easily recycled, disposed, treated, and oxidized glass electrode (Yoon, Cao, Zhou, & Ma, 2006) and (Keller, Ludwig, Davoli, & Wochele, 2005; Rawat, EC meter (WTW – 330i) (Rachit, Verma, Meena, Kumar, Mutanda, & Bux, 2011). Phytoextraction tech- Yashveer, & Shreya, 2016) at 1:2 (w/v) ratio of soil to nique particularly suitable for those sites polluted with water suspension, respectively. Soil organic matter low to moderate levels of heavy metal contaminants (OM) and organic carbon (OC) were measured (Malik & Biswas, 2012; Usman et al., 2012). according to Walkley and Black method (Fanrong About 500 vascular plant species have been et al., 2011). The physicochemical properties of soil reported in literature, which are being used for the are presented in Table 1. uptake of metals from heavily contaminated soil. The mechanism of metal uptake and translocation from soil to harvestable parts are diﬀerent in plant species Preparation of copper (Cu) stock solution and soil (Sharma, Singh, & Manchanda, 2014). For eﬀective spiking phytoextraction, the past studies have suggested that −1 The stock solution of Cu (1000 mg L ) was prepared plants with high metal tolerance, accumulation poten- by dissolving 2.683 g of CuCl (cupric chloride) in tial, and translocation rate (i.e., from roots to shoots) 1000 mL (1L) deionized water. Soil in each pot may be preferred (Mehmood, Rashid, Mahmood, & (5 kg/pot) was artiﬁcially spiked with the increased Dawson, 2013). From the said information, the objec- concentration of 25, 50, 100, 150, 200, and 300 mg tives of current research are: −1 Cu kg and kept for 2 weeks to attain equilibrium until soil was dried to attain a constant weight. Each of (1) To observe the phytotoxicity of Cu on growth the above-mentioned dilutions together with control performance and tolerance in A. esculentus, (without spiked) was performed in triplicate. The A. sativa, G. abyssinica and G. max; treatment details are given in Table 2. (2) To evaluate the phytoextraction potential; and (3) To estimate the accumulation potential of bio- fuel plant species under diﬀerent Cu Table 1. The physico-chemical properties of experimental soil. concentrations. Parameter Values obtained pH 6.89 ± 0.04 −1 a E.C. (µS cm ) 1662 ±11 Organic carbon % 2.20 ± 0.04 Materials and methods b Organic matter % 3.79 ± 0.02 −1 Cu (total) mg kg N.D.* Collection of seeds and process of sterilization Similar letters in same column are statistically non-signiﬁcant according to Duncan’s Multiple Range Test (p<0.05), Data are means (n = 3 ±SD), in Seeds of tested plant species were procured, i.e., superscript represent signiﬁcantly highest followed by later alphabets for lower means. N.D. = Not detected A. sativa, from the Institute of Fodder Research GEOLOGY, ECOLOGY, AND LANDSCAPES 55 Table 2. Cu treatment levels selected for pot experiment. fresh and dry weights of root and shoot were measured −1 Treatments (mg kg soil) and expressed in gram. For dry weights, root and Heavy metal Salt used T1 T2 T3 T4 T5 T6 T7 shoot were ﬁrst air-dried and then oven-dried at Copper (Cu) CuCl 0 25 50 100 150 200 300 80 °C to attain constant weights. Tolerance index (TI) of plants growth parameters Complete randomized experimental design The tolerance index (TI) of plants toward metal stress The experimental pots were arranged in complete was expressed as the ratio of plant growth parameters randomized design (CRD) under greenhouse. Each in Cu-contaminated soil in relation to that of plant pot contains 20 holes with equal distance, and in growth parameters in control soil calculated as: each hole, single seed was sown. After 7 days of sow- (Wilkins, 1978) ing, seeds were germinated in each pot. At two-leaf stage, seedlings were thinned down to ﬁve in each Tolerance indexðÞ % experimental pot. A plastic plate was placed under ½ Plant growth parameter Cu contaminated soil ¼ 100 the pot to collect the drain out liquid, which was ½ Plant growth parameter Control soil returned back to pots at next watering. At the end of experiment (12 weeks), plants were harvested along with soil samples and investigated for Cu accumula- Estimation of chlorophyll contents tion using atomic absorption spectrophotometer. Chlorophyll content was determined through UV- Visible spectrophotometer (Biochrom Libra S22) by Quality assurance and instrumentation Arnon (1949). For chlorophyll extraction, 0.5 g of fresh leaves was ground with 80% acetone and then ﬁltrated by All chemicals and reagents were of analytical grade means of Whatman™ ﬁlter paper No. 42. About 1 mL of with a certiﬁed purity of 99% procured from E. Merck suspension was diluted with an additional acetone (Germany). During sample analysis, high-quality (approximately 2 mL). The optical density (OD) was glassware made up of Pyrex material were utilized recorded using two wavelengths i.e., 663 and 645 nm having good resistance for acids. Working standards against blank. of respective metal were prepared by proper dilutions of standard stock solutions with double-distilled water. Copper (Cu) analysis in plants and soil samples Under optimum analytical conditions, the concen- The Cu content in plants was determined by taking tration of Cu in respective plant tissues and soil was 0.5 g of ground plant sample in crucible and digested determined by atomic absorption spectrophotometer with a mixture of HNO and HClO (3:1, v/v), while (Perkin-Elmer, AAnalyst 800) equipped with a Cu 3 4 forsoil, theCucontentwasdeterminedbytaking1g hallow cathode lamp having current 5.0 mA and of soil sample and digested with aqua regia (3HNO : wavelength 327.4 nm. The standard calibration 1HCl) and heated on a hot plate until the solution method was used for the calculation of results. becomes cleared. The digested solution of plant and Triplicate samples were run to insure the precision soil was ﬁltered through Whatman™ ﬁlter paper of quantitative results. No.42 and made up the volume up to mark 50 mL by adding deionized water. According to Monni, Germination percentage (%) Salemma, and Millar (2000), the concentration and accumulation of Cu in plant root and shoot were For seeds viability, the germination percentage was calculated as: calculated as the total number of seeds germinated to the total numbers of seeds sown and are expressed in 1 Cu concentration mg kg percentage (Talebi, Nabavi, & Sohani, 2014). AAS reading dilution factor Plants dry weight Germination percentageðÞ % Total number of seeds germinated ¼ 100 Cu accumulation μg plant Total number of seeds sown ¼ Cu concentration Plants dry weight Growth parameters Phytoremediation eﬃciency The root and shoot lengths of plant species were measured using a centimeter scale and expressed The phytoremediation eﬃciency was determined by in cm. With the help of analytical weight balance, following metal uptake indices: 56 H. AMIN ET AL. −1 germination was observed at 25 mg Cu kg in all tested Bioconcentration factor plant species but gradual increase in copper concentra- The bioconcentration factor (BCF) was calculated as tion signiﬁcantly (p< 0.05) reduced the germination the ratio of Cu concentration in plant root to that of −1 percentage (Table 3). At 200 and 300 mg Cu kg ,the Cu concentration in soil: percentage of seed germination of A. sativa was reduced about 55% in contrast to control, while in G. max no Bioconcentration Factor½ BCF −1 seeds were germinated at 200 and 300 mg Cu kg .On Cu concentration in plant rootðÞ mg kg DW the other hand, no germination was recorded beyond ðÞ Cu concentration in soil mg kg DW −1 −1 100 mg Cu kg in G. abyssinica and at 200 mg Cu kg in A. esculentus. Heavy metal phytotoxicity to seed germination in diﬀerent plant species was signiﬁcant Bioaccumulation coeﬃcient to the metal tolerance and variability of resistance The bioaccumulation coeﬃcient (BAC) was calculated within the same and among diﬀerent plant species. It as the ratio of Cu concentration in plant shoot to that is well documented in the literature that the seed is the of Cu concentration in soil: only stage in the whole life cycle of plant that has well protected against the heavy metal stress. The germina- Bioaccumulation Coefficient½ BAC 1 tion of seeds was considered as the fundamental process Metal concentration in plant shootðÞ mg kg DW that decided the impacts of heavy metal toxicity (Ansari Metal concentration in soilðÞ mg kg DW et al., 2013). The seed coat acted like a barrier between the embryo and environment that protected the young embryo against the heavy metal toxicity. Heavy metal Translocation factor toxicity in terms of seed germination has associated The translocation factor (TF) was calculated as the with the interference of toxic metals with protease and ratio of Cu concentration in plant shoot to that of amylase enzymes, which results in quick breakdown of Cu concentration in plant roots: stored food materials in seed and alteration of selective permeability properties of cell membrane (Singh, Nath, Translocation Factor½ TF & Sharma, 2007). Past studies have suggested that the Cu concentration in plant shootðÞ mg kg DW excess amount of Cu becomes responsible for the Cu concentration in plant rootðÞ mg kg DW reduction of seed germination in most of the plants (Adhikari, Kundu, Biswas, Tarafdar, & Rao, 2012; Ahsan et al., 2007). Phytoremediation ratio (%) The phytoremediation ratio (PR) was used to measure Copper toxic eﬀects on growth of plants the phytoextraction eﬃciency of plants (Awokunmi, The high Cu concentration directly inﬂuenced the plant 2016): growth parameters. The growth parameters i.e., root Phytoremediation ratio½ PR% length, shoot length, root fresh weight, shoot fresh Cu concentration in plantðÞ μgg x dry weight of plantðÞ g weight, root dry weight, and shoot dry weight were all total Cu concentration in soilðÞ μgg x weight of soil in potðÞ g signiﬁcantly (p< 0.05) increased at low Cu concentra- −1 tion (i.e., 25 mg Cu kg ) over the control. At 300 mg −1 Cu kg , growth parameters were adversely aﬀected in all plant species indicated that Cu at higher levels Statistical analysis reduced plants growth (Table 3). Among four plant species, A. esculentus showed better performance in All data were statistically analyzed with PASW® terms of growth parameters. Besides seed germination, Statistics 18 (SPSS Inc., Chicago, IL, USA). Analysis heavy metal stress was related to the process of growth of variance (ANOVA) was performed for the compar- inhibition that produced many morphological changes ison of treatment means. The signiﬁcance diﬀerence during development. Elongation of plant root and shoot among treatment means was determined by Duncan’s demonstrated a notable sensitivity toward excess heavy multiple range Post Hoc tests at a signiﬁcance level of metals in soil. The decrease in root length could be p< 0.05. primarily due to the interference of heavy metals with the uptake of water and mineral nutrient. The Results and discussion decreased rate of water and mineral absorption was induced due to mineral deﬁciency in plants and reduced Copper toxic eﬀects on germination root cell division, cell elongation along with cell cycle Copper was considered as an essential micronutrient at that in turn reduced root length of plants (Muhammad low concentrations, and the maximum values for seed et al., 2015). Toxicity of heavy metal reduced seedling GEOLOGY, ECOLOGY, AND LANDSCAPES 57 Table 3. Eﬀects of Cu on germination and growth parameters of four plant species. Cu Root fresh Shoot fresh Root dry Shoot dry applied Germination Root length Shoot length weight weight weight weight Plant −1 −1 −1 species mg kg % cm plant g plant a ab ab ab b b b A. esculentus 0 100.00 ± 0.00 19.00 ± 1.00 128.00 ± 6.00 17.00 ± 1.00 42.10 ± 1.01 9.30 ± 0.70 18.23 ± 0.75 a a a a a a a 25 100.00 ± 0.00 21.00 ± 3.00 138.00 ± 8.00 18.00 ± 1.00 46.00 ± 2.00 10.50 ± 0.50 21.17 ± 1.85 b bc ab bc c c c 50 90.00 ± 5.00 17.20 ± 1.80 123.33 ± 7.51 15.00 ± 1.00 35.00 ± 2.00 8.00 ± 1.00 16.00 ± 1.00 bc c b cd c cd cd 100 85.00 ± 5.00 16.27 ± 0.87 115.00 ± 4.00 13.47 ± 1.50 33.00 ± 2.00 7.20 ± 0.80 14.00 ± 1.00 c d c d d de d 150 80.00 ± 5.00 13.30 ± 0.76 99.00 ± 19.00 11.60 ± 0.40 27.00 ± 1.00 6.50 ± 0.50 13.47 ± 1.50 d d c e e e e 200 70.00 ± 5.00 12.23 ± 0.75 91.00 ± 7.00 9.00 ± 2.00 23.00 ± 2.00 5.80 ± 0.20 10.00 ± 1.00 300 N.A N.A N.A N.A N.A N.A N.A a b ab b b b b A. sativa 0 100.00 ± 0.00 15.28 ± 0.63 110.00 ± 4.00 16.00 ± 1.00 41.00 ± 1.00 9.00 ± 2.00 16.00 ± 1.00 a a a a a a a 25 100.00 ± 0.00 18.30 ± 0.70 120.00 ± 9.00 18.33 ± 0.58 45.00 ± 2.00 11.00 ± 1.00 19.00 ± 1.00 a bc b b c bc bc 50 100.00 ± 0.00 14.80 ± 1.20 109.00 ± 5.00 15.00 ± 2.00 35.03 ± 2.00 8.30 ± 0.70 15.00 ± 1.00 b bc bc bc c bcd cd 100 75.00 ± 5.00 14.10 ± 1.90 105.00 ± 7.00 14.00 ± 1.00 33.00 ± 2.00 7.50 ± 0.50 13.00 ± 1.00 c cd cd cd d cd de 150 60.00 ± 5.00 12.77 ± 1.25 95.00 ± 5.00 12.00 ± 1.00 29.00 ± 1.00 7.03 ± 0.55 12.00 ± 1.00 c d d de d de ef 200 55.00 ± 5.00 11.40 ± 1.60 92.00 ± 5.00 10.00 ± 1.00 26.00 ± 2.00 5.93 ± 0.60 10.00 ± 1.00 c d e e e e f 300 55.00 ± 5.00 10.60 ± 1.51 81.00 ± 3.00 9.00 ± 1.00 20.23 ± 1.75 4.50 ± 0.50 8.00 ± 1.00 b a a a a a a G. abyssinica 0 95.00 ± 0.00 15.00 ± 1.00 98.33 ± 4.51 10.700 ± 0.30 32.00 ± 1.00 7.00 ± 1.00 14.60 ± 1.50 a b a a a a a 25 100.00 ± 0.00 12.33 ± 1.70 101.00 ± 8.00 10.500 ± 0.500 34.00 ± 2.00 7.50 ± 0.50 14.90 ± 0.10 c c b b b b b 50 85.00 ± 5.00 10.10 ± 0.90 75.33 ± 5.51 8.00 ± 1.00 23.00 ± 2.00 5.00 ± 1.00 10.10 ± 0.90 d d c b c c c 100 70.00 ± 5.00 8.13 ± 0.85 64.00 ± 5.00 7.10 ± 0.90 17.00 ± 2.00 3.27 ± 0.70 6.80 ± 2.20 150 N.A N.A N.A N.A N.A N.A N.A 200 N.A N.A N.A N.A N.A N.A N.A 300 N.A N.A N.A N.A N.A N.A N.A a a ab b a a a G. max 0 90.00 ± 5.00 35.00 ± 2.00 88.00 ± 6.00 19.00 ± 1.00 28.00 ± 1.00 12.00 ± 1.00 13.40 ± 0.60 a a a a a a a 25 95.00 ± 0.00 36.60 ± 2.51 93.00 ± 4.00 24.00 ± 1.00 30.00 ± 2.00 13.00 ± 1.00 14.00 ± 1.00 a b b b b b b 50 95.00 ± 0.00 28.20 ± 1.80 80.00 ± 10.00 20.00 ± 1.00 21.00 ± 2.00 10.00 ± 1.00 10.00 ± 100 b c c c c c c 100 75.00 ± 5.00 21.20 ± 1.80 69.00 ± 4.00 17.00 ± 1.00 17.00 ± 2.00 8.00 ± 1.00 8.00 ± 1.00 c c d d c d c 150 55.00 ± 5.00 19.70 ± 1.30 58.00 ± 7.00 13.00 ± 1.00 15.00 ± 1.00 6.27 ± 0.25 7.00 ± 1.00 200 N.A N.A N.A N.A N.A N.A N.A 300 N.A N.A N.A N.A N.A N.A N.A Similar letters in same column are statistically non-signiﬁcant according to Duncan’s Multiple Range Test (p < 0.05), Data are means (n = 3 ±SD), in superscript represent signiﬁcantly highest followed by later alphabets for lower means, N.A = Not available. height and aﬀected root growth and development with all tested plant species, the maximum chlorophyll −1 the interference of plant metabolic activities (Barbosa contents (a,b,and total mg g FW) were observed at −1 et al., 2013). The increased transport rate of heavy low Cu concentration (i.e., 25 mg Cu kg ) as compared metals toward shoot region directly aﬀected sensitive to control, while the lowest value for chlorophyll con- −1 parts of plants such as leaves and disturbed the process tents was found at 300 mg Cu kg . The heavy metal of photosynthesis as well as the cellular metabolism stress negatively aﬀected the photosynthesis process of shoot and thereby reduced plants’ height (Shaikh, and decreased the chlorophyll-a, chlorophyll-b, and Shaikh, Shaikh, & Shaikh, 2013). The hydrolytic enzyme total chlorophyll contents in all plant species at higher activities was also aﬀected as a result of heavy metal concentration. Heavy metal at toxic levels interfered toxicity, and the food was not reached to the developing with normal enzyme functions in plants and drastically embryo that aﬀected the seedlings length and ultimately aﬀected the process of photosynthesis (Ali et al., 2015). led to the reduction of plants growth (Luo et al., 2010; The decreased rate of photosynthetic pigment was asso- Mukhopadhyay et al., 2013). The high plant biomass ciated with metals that have the consequence of perox- (i.e., fresh weight and dry weight) has the ﬁrst pre- idation of chloroplast membranes due to increased level requisite for high plant yield. The biomass was mainly of ROS generation (Srinivasan, Sahi, Paulo, & based on the growth performance of particular plant Venkatachalam, 2014). The production of ROS upon (Muhammad et al., 2015). Under severe metal toxicity, metal interference, directly and indirectly with photo- the plants displayed obvious symptoms of growth inhi- synthesis process induced structural alteration to the bition. The decrease in plant biomass was associated pigment protein complexes by degradation and desta- with disturbed metabolic activities, low photosynthetic bilization of proteins in antenna complex as well as reactions, and reduced uptake of essential mineral complete distortion of thylakoid membranes that nutrients under heavy metal stress (Li et al., 2012). reduced the pigment contents and plant growth (Wodala, Eitel, Gyula, Ördög, & Horváth, 2012). The excess supply of toxic metals also impaired the uptake of Copper toxic eﬀects on chlorophyll contents essential photosynthetic pigment elements, such as −1 potassium, calcium, magnesium, iron, and prevented Chlorophyll contents (a, b, and total mg g FW) were the incorporation of divalent cations with heavy metals, decreased signiﬁcantly (p< 0.05) with steady raise of Cu −1 therefore responsible for the reduction of chlorophyll concentration from 25 to 300 mg Cu kg (Figure 1). In 58 H. AMIN ET AL. Figure 1. Eﬀect of Cu stress on photosynthetic pigments chlorophyll-a (a) chlorophyll-b (b) and total chlorophyll (a + b) (c), of four plant species after 12 weeks of growth in soil contaminated with varying concentrations of applied Cu. Bars with the similar letters are statistically non-signiﬁcant according to Duncan’s multiple range test (p < 0.05), Data are means (n = 3 ± SD), in superscript represent signiﬁcantly highest followed by later alphabets for lower means. pigments (Gopal & Rizvi, 2008). Literature has reported species (Table 4). For Cu-treated soil, the tolerance that the reduction of chlorophyll biosynthesis with the indices (TIs) in terms of growth parameters i.e., root destruction of photosynthetic organization at thylakoid length, shoot length, root fresh weight, shoot fresh level has involved the hindrance of toxic metals with weight, root dry weight, and shoot dry weight were organized system of chlorophyll in plants (Kabata- signiﬁcantly (p< 0.05) higher in A. sativa than Pendias & Pendias, 2001). A. esculentus, G. abyssinica and G. max from 25 to −1 300 mg Cu kg . Metal tolerance was considered as basic prerequisite for metal accumulation and conse- Copper toxic eﬀects on tolerance index quently for phytoremediation. Literature has reported that plant species utilized for phytoremediation must The growth parameters were signiﬁcantly (p< 0.05) have high tolerance and metal accumulation capacity aﬀected at higher Cu concentration in all tested plant GEOLOGY, ECOLOGY, AND LANDSCAPES 59 Table 4. Eﬀect of Cu stress on the tolerance indices (TIs) of four plant species. Tolerance indices Cu applied Root length Shoot length Root fresh weight Shoot fresh weight Root dry weight Shoot dry weight −1 Plant species mg kg % a a a a a a A. esculentus 25 110.18 ± 10.00 107.78 ± 1.20 105.90 ± 0.35 109.23 ± 2.20 113.06 ± 3.14 115.94 ± 5.40 b b b b b b 50 90.36 ± 4.72 96.31 ± 1.35 88.21 ± 0.69 83.09 ± 2.80 85.81 ± 4.31 87.70 ± 1.89 b b c c c c 100 85.73 ± 5.60 89.88 ± 1.09 79.05 ± 4.17 78.34 ± 2.91 77.28 ± 2.79 76.72 ± 2.34 c c d d d c 150 69.99 ± 0.54 76.99 ± 11.25 68.30 ± 1.67 64.12 ± 0.89 69.89 ± 0.12 73.72 ± 5.19 c c e e e d 200 64.37 ± 0.57 71.03 ± 2.14 52.60 ± 8.69 54.58 ± 3.46 62.49 ± 2.56 54.76 ± 3.24 300 N.A N.A N.A N.A N.A N.A a a a a a a A. sativa 25 119.78 ± 1.64 108.99 ± 4.22 114.75 ± 4.56 109.72 ± 2.20 124.72 ± 17.02 118.80 ± 1.18 b b b b b b 50 96.77 ± 4.30 99.07 ± 0.94 93.47 ± 6.67 85.40 ± 2.80 94.20 ± 13.49 93.73 ± 0.39 bc b b c bc c 100 92.06 ± 8.90 95.38 ± 2.90 87.47 ± 0.78 80.44 ± 2.92 85.35 ± 13.75 80.94 ± 7.46 cd c c d bc c 150 83.44 ± 5.11 86.33 ± 1.41 74.93 ± 1.57 70.72 ± 0.71 79.91 ± 12.03 74.67 ± 7.85 de c d e cd d 200 74.42 ± 7.61 83.60 ± 1.51 62.40 ± 2.35 63.36 ± 3.33 67.16 ± 8.32 62.40 ± 2.35 e d d f d e 300 69.21 ± 7.44 73.64 ± 0.050 56.14 ± 2.75 49.30 ± 3.07 50.87 ± 5.89 49.87 ± 3.14 a a a a a a G. abyssinica 25 81.96 ± 5.92 102.61 ± 3.47 98.10 ± 1.92 106.19 ± 2.93 107.94 ± 8.36 102.76 ± 10.21 b b b b b b 50 67.27 ± 1.52 76.55 ± 2.09 74.63 ± 7.26 71.79 ± 4.01 71.03 ± 4.18 69.25 ± 1.34 c c c c c c 100 54.13 ± 2.06 65.02 ± 2.13 66.23 ± 6.56 53.03 ± 4.60 46.35 ± 3.38 45.86 ± 10.43 150 N.A N.A N.A N.A N.A N.A 200 N.A N.A N.A N.A N.A N.A 300 N.A N.A N.A N.A N.A N.A a a a a a a G. max 25 104.53 ± 1.30 105.80 ± 2.67 126.36 ± 1.39 107.06 ± 3.32 108.37 ± 0.70 104.39 ± 2.79 b b b b b b 50 80.55 ± 0.54 90.67 ± 5.19 105.27 ± 0.28 74.89 ± 4.47 83.26 ± 1.40 74.50 ± 4.13 c c c c c c 100 60.51 ± 1.69 78.45 ± 0.80 89.45 ± 0.56 60.60 ± 4.98 66.51 ± 2.80 59.56 ± 4.80 d d d d d d 150 56.27 ± 0.50 65.75 ± 3.48 68.36 ± 1.67 53.53 ± 1.66 52.35 ± 2.28 52.09 ± 5.14 200 N.A N.A N.A N.A N.A N.A 300 N.A N.A N.A N.A N.A N.A Similar letters in same column are statistically non-signiﬁcant according to Duncan’s Multiple Range Test (p < 0.05), Data are means (n = 3 ±SD), in superscript represent signiﬁcantly highest followed by later alphabets for lower means, N.A = Not available. Figure 2. Cu concentrations in root (a), stem (b), leaf (c), and pod/fruit (d) of four plant species after 12 weeks of growth in soil contaminated with varying concentrations of applied Cu. Bars with the similar letters are statistically non-signiﬁcant according to Duncan’s multiple range test (p < 0.05), Data are means (n = 3 ± SD), in superscript represent signiﬁcantly highest followed by later alphabets for lower means. in their harvested biomass (Monni et al., 2000). Plants Ensley, 2000), cell wall binding, active transport of have various mechanisms for heavy metal tolerance ions into the vacuole, chelation through the induction for instance, exclusion and inclusion (Raskin & of metal-binding peptides, and the formation of metal 60 H. AMIN ET AL. Figure 3. Accumulation of Cu in root (a) and shoot (b) of four plant species after 12 weeks of growth in soil contaminated with varying concentrations of applied Cu. Bars with the similar letters are statistically non-signiﬁcant according to Duncan’s multiple range test (p < 0.05), Data are means (n = 3 ± SD), in superscript represent signiﬁcantly highest followed by later alphabets for lower means. complexes (Memon & Schroder, 2009). Growth inhi- Charest, 2007). Therefore, plants’ tolerance to sub- bition represented the common response to heavy stantial metal toxicity was evaluated in accordance to metal stress and therefore considered as an important their roots or shoots development limited by the toxic factor among the major agricultural indices used for metal in soil. toxic metal stress tolerance (Tong, Kneer, & Zhu, 2004). Plant tolerance to heavy metal stress was esti- Copper distribution in diﬀerent plant tissues mated on their root and/or shoot development and growth inhibition as aﬀected by the heavy metal toxi- The Cu concentration in diﬀerent parts of four plant city (Srinivasan et al., 2014). Literature has reported species is presented in Figure 2. The concentration of that the plants with TI values <1 experienced stress Cu in all plant parts i.e., root, stem leaves, and pod/fruit because of metal contamination along with a net were increased with increased Cu levels in soil. In reduction of plant biomass. By contrast, the plant A. esculentus, A. sativa, G. abyssinica, and G. max,the species with TI > 1 developed tolerance along with maximum Cu concentration were in the order of root −1 a net increase of biomass (hyper-accumulator). On the followed by stem, leaf, and pod/fruit at 300 mg Cu kg other hand, the plant species with TI values equals to 1 treated soil. Studies demonstrated that phytoremedia- was unaﬀected by metal toxicity and indicated no tion eﬃciency depended on the take-up of metals, as diﬀerence in relation to control treatment (Audet & well as their distribution and translocation to diﬀerent GEOLOGY, ECOLOGY, AND LANDSCAPES 61 plant tissues. The extent of metal tolerance in plants are from substrate and compared the plant species for reliant on metal bioavailability, plant species, and meta- phytoremediation potentials (McGrath & Zhao, bolic systems (Rohan, Mayank, João, & Paul, 2013). The 2003; Odjegba & Fasidi, 2007). The BAC has another metal concentrations was also varied among diﬀerent useful parameter for evaluating the ratio of heavy plant species and inﬂuenced by the concentration and metal in shoot to that in soil (Yoon et al., 2006) availability of heavy metal in soil as well as diﬀerent whereas, TF helped to evaluate the ratio of heavy condition of soil (Seregin & Ivanov, 2001). metals in plant shoot to that in plant root (Cui, Zhou, & Chao, 2007; Li, Luo, & Su, 2007). For phy- toextraction purpose, the plant species with all factors, Copper accumulation in roots and shoots the BCF, BAC, and TF values >1 was supposed to be a good phytoextractor and suitable for phytoextrac- For all plant species, the highest Cu accumulation tion of metal-contaminated soil, while plant species was found in shoots than roots per plant because of with BCF and TF values <1 was probably not suitable high shoot biomass (Figure 3). The results showed for phytoextraction purpose (Fitz & Wenzel, 2002). that A. sativa accumulated the greatest amount of Cu −1 Following the criteria, the plant species with BCF in both root and shoot from 25 to 300 mg Cu kg values >1 and TF values <1 was suitable for phytost- treatment whereas, minimum was accumulated in abilziation (Mendez & Maier, 2008). G. abyssinica. Overall, the results suggested that A. sativa was the eﬀective candidate to extract Cu from contaminated soil than other tested plant spe- Phytoremediation ratio (%) cies especially at higher Cu concentration i.e., 300 mg −1 Cu kg . Beside concentrations, the accumulation of The PRs of four plant species, grown under diﬀerent heavy metals in the above ground biomass (shoot) Cu-treated soil are reported in Figure 4. The highest PR has an important factor that determined the plant value for Cu was found in A. sativa, (5.33%) followed capability for appropriate phytoremediation (Hanen by A. esculentus (4.39%), G. max (2.97%) and et al., 2010) and aﬀected plant remediation eﬃciency. −1 G. abyssinica (0.66%) at 25 mg Cu kg .However,the Previous study has reported that the plant species PR (%) value was decreased by 2.10% for A. sativa at suitable for successive phytoremediation have high −1 300 mg Cu kg .In A. esculentus the PR (%) value was metal tolerance and accumulation capacity in har- −1 decreased by 2.08% at 200 mg Cu kg ,while in vestable parts(Salt,Smith,&Raskin, 1998). The −1 G. max, decreased by 1.45% at 150 mg Cu kg .On accumulation potential of plants depends on two main factors, i.e., metal concentration in soil and plants biomass for accurate metal quantity measure- Table 5. Bioconcentration factor (BCF), bioaccumulation coef- ﬁcient (BAC) and translocation factor (TF) for Cu in four plant ments (Vymazal, 2016). Past study reported that species. increased treatment level leads to enhanced metal Cu concen- accumulation in plants (Sun, Zhou,Wang,&Liu, tration 2009). Previous study showed that the uptake of applied Plant −1 metals, partition, and translocation to diﬀerent species mg kg BCF BAC TF ab a a plant partsaswellasthe degree of tolerance A. esculentus 25 1.20 ± 0.08 1.48 ± 0.20 1.23 ± 0.08 b ab a 50 1.16 ± 0.06 1.36 ± 0.10 1.17 ± 0.02 depends on the metal concentration and availability, b b b 100 1.16 ± 0.03 1.18 ± 0.05 1.02 ± 0.02 b b b the plant species, and metabolism. The plant biomass 150 1.12 ± 0.02 1.22 ± 0.06 1.09 ± 0.03 a ab b 200 1.27 ± 0.04 1.34 ± 0.07 1.05 ± 0.02 was also considered for the evaluation of metal accu- 300 N.A N.A N.A a a a mulation potential (Yue-bing, Qixing, Jing, Wei-tao, A. sativa 25 1.60 ± 0.16 1.91 ± 0.28 1.19 ± 0.06 a a a 50 1.58 ± 0.053 1.61 ± 0.15 1.02 ± 0.06 &Rui, 2009). a a a 100 1.55 ± 0.25 1.80 ± 0.56 1.21 ± 0.57 a a a 150 1.59 ± 0.24 1.6 ± 0.25 1.05 ± 0.32 a a a 200 1.44 ± 0.20 1.58 ± 0.14 1.12 ± 0.26 a a a Phytoextraction eﬃciency 300 1.60 ± 0.23 1.72 ± 0.68 1.14 ± 0.64 a a a G. abyssinica 25 0.40 ± 0.08 0.24 ± 0.12 0.58 ± 0.19 b a a For all Cu treatments, A. sativa, A. esculentus, and 50 0.30 ± 0.02 0.22 ± 0.06 0.73 ± 0.15 c a a 100 0.20 ± 0.02 0.16 ± 0.04 0.81 ± 0.27 G. max had BCF, BAC, and TF values > 1 among the 150 N.A N.A N.A tested plant species, which suggested that the studied 200 N.A N.A N.A 300 N.A N.A N.A plant species have high capacity to transport Cu from a a a G. max 25 1.05 ± 0.14 1.15 ± 0.27 1.08 ± 0.20 a a a roots to shoots and suitable for phytoextraction 50 1.03 ± 0.17 1.16 ± 0.28 1.13 ± 0.24 a a a 100 1.05 ± 0.07 1.14 ± 0.41 1.10 ± 0.41 (Table 5). On the other hand, G. abyssinica has BCF, a a a 150 1.03 ± 0.03 1.15 ± 0.18 1.11 ± 0.17 BAC, and TF values <1 and signiﬁed that G. abyssinica 200 N.A N.A N.A 300 N.A N.A N.A has not categorized exclusively as Cu phytoextractor Similar letters in same column are statistically non-signiﬁcant according to or phytostabilizer. BCF has an excellent indicator of Duncan’s Multiple Range Test (p < 0.05), Data are means (n = 3 ± SD), in metal accumulation capacity because it was taken into superscript represent signiﬁcantly highest followed by later alphabets account that the plants ability to extract heavy metals for lower means, N.A = Not available. 62 H. AMIN ET AL. Figure 4. Phytoremediation ratio (%) of four plant species after 12 weeks of growth in soil contaminated with varying concentrations of applied Cu. Bars with the similar letters are statistically non-signiﬁcant according to Duncan’s multiple range test (p < 0.05), Data are means (n = 3 ± SD), in superscript represent signiﬁcantly highest followed by later alphabets for lower means. scale composting or phytomining process. the other hand, in G. abyssinica the PR (%) value was −1 Furthermore, people of aﬀected areas also took advan- decreased by 0.17% at 100 mg Cu kg .The plants’ eﬃciency for metal removal and reclamation of soil tage from the natural safe method by toxic metals removal from contaminated agricultural soil up to polluted with metals depended on plants’ biomass pro- acceptable safe limits that irrigated with untreated duction and the metal distribution among plant tissues. Previous study suggested that the plants used for phy- water. toremediation must have fast growth rate, developed large biomass as well as easy to cultivate and harvest (Ciura, Poniedziałek, Sękara, & Jędrszczyk, 2005). 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Geology Ecology and Landscapes – Taylor & Francis
Published: Jan 2, 2021
Keywords: Soil contamination; phytotoxicity; bioconcentration; bioaccumulation; phytoremediation ratio
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