<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">AJPS</journal-id><journal-title-group><journal-title>American Journal of Plant Sciences</journal-title></journal-title-group><issn pub-type="epub">2158-2742</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ajps.2017.810165</article-id><article-id pub-id-type="publisher-id">AJPS-79099</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biomedical&amp;Life Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  Bentonite Effects on Zinc Concentration in Plants Irrigated with Wastewater
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Gilvanise</surname><given-names>Alves Tito</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Lúcia</surname><given-names>Helena Garófalo Chaves</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Francisco</surname><given-names>De Assis Santos e Silva</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Department of Food Engineering, Federal University of Campina Grande, Campina Grande, Brazil</addr-line></aff><aff id="aff1"><addr-line>Department of Agricultural Engineering, Federal University of Campina Grande, Campina Grande, Brazil</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>lhgarofalo@hotmail.com(LHGC)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>04</day><month>09</month><year>2017</year></pub-date><volume>08</volume><issue>10</issue><fpage>2433</fpage><lpage>2444</lpage><history><date date-type="received"><day>21,</day>	<month>August</month>	<year>2017</year></date><date date-type="rev-recd"><day>12,</day>	<month>September</month>	<year>2017</year>	</date><date date-type="accepted"><day>15,</day>	<month>September</month>	<year>2017</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  A greenhouse study was conducted to investigate the effect of bentonite on zinc concentrations in radish and corn irrigated with wastewater. The experimental units were plastic pots with a capacity of 5 kg and 14 kg for radish and corn, respectively. The soil was mixed with increasing doses of bentonite equivalent to 0
  , 30,
   60 and 90 t&#183;ha<sup>-1</sup>. The plants were irrigated with poor quality water with a concentration of 5 mg&#183;L<sup>-1</sup> Zn. On the occasion of the harvest of radish and corn, that is, at 30 and 60 days after the emergence, respectively, the plants were separated in aerial part and roots, dried in a forced circulation oven, weighed and ground for analysis of zinc in the plant tissues. After these analyzes, the translocation factor (TF), the translocation index (TI), the bioaccumulation in the plant (BFP) and in the root (BFR) were calculated. According to the conditions of this research, the incorporation of bentonite to the soil irrigated with water of inferior quality favored the development of radish and corn; allowed the retention of the Zn metal in the soil, reducing the concentrations of this metal in the root of the radish and in the aerial part of the corn; decreased the transfer of zinc from the soil to the plants under study.
 
</p></abstract><kwd-group><kwd>Heavy Metals</kwd><kwd> Corn</kwd><kwd> Radish</kwd><kwd> Remediation</kwd><kwd> Clay</kwd><kwd> Transloca&#231;&#227;o</kwd><kwd> Bioaccumulation</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>In view of the large consumption of water in irrigated crops and the scarcity of water in certain regions, it is essential to use it rationally and avoid waste. Thus the reuse of water has taken up considerable importance. Wastewater has beneficial effects on crops, both as a source of water and as a source of nutrients for plants. However, the use of this water can contribute to the accumulation of heavy metals in the soil, if they have metallic ions even in small concentrations.</p><p>Among the factors that influence the concentration of heavy metals on and within plants, the most important are the nature of the soil on which the plant is grown, and the application of fertilizers, sewage sludge or irrigation with wastewater. This water being used in crop irrigation may not only result in soil contamination, i.e., contamination environmental due to the accumulation of this metal, but lead to elevated heavy metal uptook by crops, which may affect food quality and safety [<xref ref-type="bibr" rid="scirp.79099-ref1">1</xref>] . According to Cambra et al. [<xref ref-type="bibr" rid="scirp.79099-ref2">2</xref>] , soil contaminated with metals is a primary route of toxic element exposure to humans. Toxic metals can enter the human body by consumption of contaminated food crops, water or inhalation of dust.</p><p>Heavy metal, such as, zinc, is essential for normal body growth and functions of living organisms and is referred to as essential elements [<xref ref-type="bibr" rid="scirp.79099-ref3">3</xref>] . This element, detected in the wastewater, may come from petrochemicals industries, sewage, trash, among other sources, for example, the use of zinc-based fertilizers such as zinc oxide, zinc sulfate, zinc nitrate and zinc chloride.</p><p>The ability of a metal species to migrate from the soil into plant tissues is referred to as bioaccumulation factor (BF). It is calculated as a ratio of concentration of a specific metal in plant tissue to the concentration of the same metal in soil, both represented in the same units [<xref ref-type="bibr" rid="scirp.79099-ref4">4</xref>] . Higher BF values (≥1) indicate higher absorption of metal from soil by the plant and higher suitability of the plant for phytoextraction and phytoremediation. On the contrary, lower values indicate poor response of plants towards metal absorption and the plant can be used for human consumption [<xref ref-type="bibr" rid="scirp.79099-ref5">5</xref>] .</p><p>The maximum tolerable value for vegetables, roots and tubers and other fresh foods, according to Brazilian legislation for the zinc element is 50 mg∙kg<sup>−1</sup> [<xref ref-type="bibr" rid="scirp.79099-ref6">6</xref>] . However, the heavy metal contents in the dry matter causing symptoms of plant phytotoxicity are 70 - 400 mg∙kg<sup>−1</sup> [<xref ref-type="bibr" rid="scirp.79099-ref7">7</xref>] .</p><p>For treatment of wastewater there are several technologies, and among these, adsorption of heavy metal is an effective method. Recent studies have emphasized the efficiency of zeolite and bentonite in the immobilization of heavy metals by the adsorption method, minimizing contamination by these metals in soils and waters [<xref ref-type="bibr" rid="scirp.79099-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.79099-ref9">9</xref>] . Sheta et al. [<xref ref-type="bibr" rid="scirp.79099-ref10">10</xref>] found that zeolite and bentonite have a high Zn and Fe retention potential.</p><p>Bentonite, found in large quantities in the municipality of Boa Vista, State of Para&#237;ba, is predominantly composed of clay minerals from the group of smectite and quartz impurities. Some varieties are also composed of kaolinite and ilite [<xref ref-type="bibr" rid="scirp.79099-ref11">11</xref>] . The bentonite material, from the Primavera deposit, of inferior quality, has been studied for a long time as a soil conditioner, mainly by adsorbing heavy metals. The results of these studies have shown favorable effects both on the adsorption of these metals and on the chemical and physical properties of the soils [<xref ref-type="bibr" rid="scirp.79099-ref12">12</xref>] .</p><p>The efficiency of each clay-mineral in removing the metal cations from the soil/effluent systems should be evaluated for each of these cations separately. Thus, this research aimed to study the effect of bentonite on zinc concentrations in radish and corn irrigated with wastewater.</p></sec><sec id="s2"><title>2. Material and Methods</title><p>This experiment was carried out in a greenhouse at the Agricultural Engineering Department, Federal University of Campina Grande, Paraiba, Brazil, using soil samples collected in the superficial layer (0 - 20 cm) of Eutrophic Red Latosol [<xref ref-type="bibr" rid="scirp.79099-ref13">13</xref>] . These samples were air-dried, crushed, sieved through a 2 mm sieve and chemically characterized according to [<xref ref-type="bibr" rid="scirp.79099-ref14">14</xref>] presenting the following attributes: pH (H<sub>2</sub>O) = 6.0; electrical conductivity = 0.16 mmhos∙cm<sup>−1</sup>; Ca = 2.10 cmolc∙kg<sup>−1</sup>; Mg = 2.57 cmolc kg<sup>−1</sup>; Na = 0.06 cmolc∙kg<sup>-1</sup>; K = 0.14 cmolc∙kg<sup>−1</sup>; H + Al = 1.78 cmolc∙kg<sup>−1</sup>; organic carbon = 5.5 g∙kg<sup>−1</sup>; P = 45.0 mg∙kg<sup>−1</sup> and Zn = 14.16 mg∙kg<sup>−</sup><sup>1</sup>.</p><p>The bentonite clay samples collected in the Primavera mine, Paraiba State, Brazil, were air dried and sieved with 0.074 mm mesh in order to precede X-ray diffraction analysis. According to this analysis bentonite samples, presents picks of smectite clays, of tridymite (a silicate mineral and polymorph of high temperature of quartz) and of quartz (low quantity).</p><p>The two independent experiments, that is, for each plant (radish and corn) consisted of four doses of bentonite 0, 30, 60 and 90 t∙ha<sup>−1</sup> corresponding to 10.7, 21.4 and 32.1 g∙kg<sup>−1</sup> of soil, with four replications, in a completely randomized design.</p><p>Initially, during the conduction of the experiments, the soil was dried, sieved and mixed with the dose of bentonite corresponding to the treatments. The mixtures of soil with bentonite were conditioned in plastic vessels, placed in field capacity with water supply and incubated for 20 days. Planting fertilization was carried out, according to Novais et al. [<xref ref-type="bibr" rid="scirp.79099-ref15">15</xref>] , so as to provide in the vessels of 5 and 14 kg of soil, cultivated with radish (Raphanus sativus) and maize (Zea mays L.), respectively, 1.11 and 3.11 g of urea at 1.25 and 3.5 g of potassium chloride (KCl) and 8.3 and 23.33 g of single superphosphate (P<sub>2</sub>O<sub>5</sub>), respectively. Then, the sowing was done, in each experimental unit, according to the cultures. After 8 days of emergence, thinning was done, leaving two plants per experimental unit and beginning irrigation with water of inferior quality. The concentration of zinc contained in the water used was 5 mg∙L<sup>−</sup><sup>1</sup>, resulting in a cumulative concentration in the soil for cultivation of radish and of 6.0 and 13.04 mg∙kg<sup>−</sup><sup>1</sup> of Zn, respectively, at the end of the cycle of each culture.</p><p>On the occasion of the harvest of radish and corn, that is, at 30 and 60 days after the emergence of the plants, respectively, the plants were separated in aerial part and roots, washed in distilled and deionized water and dried in a forced circulation oven at 65˚C in paper bags until constant weight and, the dry biomass of the shoots (DBS) and roots (DMR) were subsequently weighed. Thereafter the dried material was milled for analysis of the plant tissues. These tissues (0.3 g) were digested using HNO<sub>3</sub> (8 ml) and HClO<sub>4</sub> (6 ml) i.e., nitroperchloric digestion (3:1) [<xref ref-type="bibr" rid="scirp.79099-ref14">14</xref>] . After the digestion, Zn concentration in plant tissue was analyzed by plasma mass spectrometry (ICP-OES) according to the methodology performed by Oliva et al. [<xref ref-type="bibr" rid="scirp.79099-ref16">16</xref>] .</p><p>The amount of zinc accumulated in the shoots (AS) and roots (AR) of the plant (mg/pot) was calculated according to Equation (1).</p><p>A S   or   A R ( mg pot ) = [ drybiomassoftheshoots ( g ) orofroots   ( g ) ] &#215; [ concentrationofelement ( mg / kg ) ] 1000 (1)</p><p>The translocation factor (TF) gives the leaf/root zinc concentration and depicts the ability of the plant to translocate the metal species from roots to leaves (shoot) at different concentrations. This index was calculated according to Equation (2) [<xref ref-type="bibr" rid="scirp.79099-ref17">17</xref>] .</p><p>T F = zincconcentrationintheshoot ( mg / kg ) zincconcentrationintheroot ( mg / kg ) (2)</p><p>The translocation index (TI) was determined according to Equation (3) [<xref ref-type="bibr" rid="scirp.79099-ref18">18</xref>] .</p><p>T I = A S amountofZnaccumulatedinthecompleteplant &#215; 100 (3)</p><p>The bioaccumulation factor (BF), an index of the ability of the plant to accumulate a particular metal with respect to its concentration in the soil substrate [<xref ref-type="bibr" rid="scirp.79099-ref19">19</xref>] , was calculated according to Equation (4) or Equation (5).</p><p>B F P = zincconcentrationinthecompleteplant ( mg / kg ) zincconcentrationinthesoil ( mg / kg ) (4)</p><p>B F R = zincconcentrationintheplantroot ( mg / kg ) zincconcentrationinthesoil ( mg / kg ) (5)</p><p>The Assistat Software version 7.7 [<xref ref-type="bibr" rid="scirp.79099-ref20">20</xref>] was employed to analyze the obtained results, by using the F test and regression polynomials, which were used to adjust the data when significant.</p></sec><sec id="s3"><title>3. Results and Discussion</title><p>Radish dry root biomass (DBR), ranging from 1.79 g (0 t∙ha<sup>−1</sup> of bentonite) to 2.72 g (90 t∙ha<sup>−1</sup> of bentonite), was influenced by the doses of bentonite (<xref ref-type="table" rid="table1">Table 1</xref>), corresponding to an increase of 51.56% of the highest dose relative to the control (<xref ref-type="fig" rid="fig1">Figure 1</xref>(a)).</p><p>In the case of corn, application of bentonite to the soil resulted in an increase of root dry weight of around 3.14% (<xref ref-type="fig" rid="fig1">Figure 1</xref>(b)) corroborating [<xref ref-type="bibr" rid="scirp.79099-ref21">21</xref>] who found that bentonite and zeolite mixed with soil provided an increase in biomass and corn and bean crop development. Similarly, Youssef [<xref ref-type="bibr" rid="scirp.79099-ref22">22</xref>] working with these clays verified a significant increase in growth, productivity and chemical composition of potato (Solanum tuberosum L.).</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Summary of the analyses of variance for the dry biomass of the shoots (DBS) and root part (DBR) of the radish and corn irrigated with lower quality water with increasing doses of bentonite</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="3"  >Source of Variation</th><th align="center" valign="middle"  rowspan="3"  >DF</th><th align="center" valign="middle"  colspan="4"  >Mean Squares</th></tr></thead><tr><td align="center" valign="middle"  colspan="2"  >Radish</td><td align="center" valign="middle"  colspan="2"  >Corn</td></tr><tr><td align="center" valign="middle" >DBS</td><td align="center" valign="middle" >DBR</td><td align="center" valign="middle" >DBS</td><td align="center" valign="middle" >DBR</td></tr><tr><td align="center" valign="middle" >Bentonite</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >0.04 ns</td><td align="center" valign="middle" >0.70**</td><td align="center" valign="middle" >73.03 ns</td><td align="center" valign="middle" >6.87 ns</td></tr><tr><td align="center" valign="middle" >Linear</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.02 ns</td><td align="center" valign="middle" >1.88**</td><td align="center" valign="middle" >70.16 ns</td><td align="center" valign="middle" >18.65*</td></tr><tr><td align="center" valign="middle" >Quadratic</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.01 ns</td><td align="center" valign="middle" >0.14 ns</td><td align="center" valign="middle" >41.15 ns</td><td align="center" valign="middle" >0.38 ns</td></tr><tr><td align="center" valign="middle" >Error</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >0.13</td><td align="center" valign="middle" >0.07</td><td align="center" valign="middle" >25.91</td><td align="center" valign="middle" >2.45</td></tr><tr><td align="center" valign="middle"  colspan="2"  >VC (%)</td><td align="center" valign="middle" >12.27</td><td align="center" valign="middle" >11.67</td><td align="center" valign="middle" >5.71</td><td align="center" valign="middle" >7.08</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Mean (g)</td><td align="center" valign="middle" >2.94</td><td align="center" valign="middle" >2.26</td><td align="center" valign="middle" >89.21</td><td align="center" valign="middle" >22.10</td></tr></tbody></table></table-wrap><p>DF = Degree of Freedom, ns, * and ** no significant, significant at 5% and 1% level, respectively. VC = Variation Coefficient.</p><p>The significant effect of the addition of bentonite to the soil in the development of several plants may be due to its positive effect on the cation exchange capacity (CEC), thus favoring the release of nutrients to the plant. Bentonite, according to Marschner [<xref ref-type="bibr" rid="scirp.79099-ref23">23</xref>] , also performs as a fertilizer, increasing micronutrients and macronutrients in soil as well as other biochemical processes related to plant growth.</p><p>The concentration of Zn in radish roots, which was significantly influenced by the doses of bentonite (<xref ref-type="table" rid="table2">Table 2</xref>), ranged from 75.49 to 48.28 mg∙kg<sup>−1</sup>, reducing the order by 36.04% when comparing the control with the highest dose (<xref ref-type="fig" rid="fig2">Figure 2</xref>(a)).</p><p>The average concentration of zinc in roots of radish (<xref ref-type="table" rid="table2">Table 2</xref>) is above the tolerable maximum value for human consumption of vegetables, roots and tubers and other fresh foods which is 50 mg∙kg<sup>−1</sup> of zinc [<xref ref-type="bibr" rid="scirp.79099-ref6">6</xref>] .</p><p>It is important to emphasize that this culture was irrigated with water having zinc in the maximum concentration allowed to discharge effluents. Even so, it is</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Summary of the analysis of variance of zinc concentration in the shoot (CS) and zinc concentration in the root (CR) of radish and corn, irrigated with lower quality water with increasing doses of bentonite</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="3"  >Source of Variation</th><th align="center" valign="middle"  rowspan="3"  >DF</th><th align="center" valign="middle"  colspan="4"  >Mean Squares</th></tr></thead><tr><td align="center" valign="middle"  colspan="2"  >Radish</td><td align="center" valign="middle"  colspan="2"  >Corn</td></tr><tr><td align="center" valign="middle" >CS</td><td align="center" valign="middle" >CR</td><td align="center" valign="middle" >CS</td><td align="center" valign="middle" >CR</td></tr><tr><td align="center" valign="middle" >Bentonite</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >43.32 ns</td><td align="center" valign="middle" >730.95**</td><td align="center" valign="middle" >310.49 ns</td><td align="center" valign="middle" >28.60 ns</td></tr><tr><td align="center" valign="middle" >Linear</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >100.35 ns</td><td align="center" valign="middle" >1678.11**</td><td align="center" valign="middle" >879.14*</td><td align="center" valign="middle" >82.42 ns</td></tr><tr><td align="center" valign="middle" >Quadratic</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >25.00 ns</td><td align="center" valign="middle" >416.16*</td><td align="center" valign="middle" >42.25 ns</td><td align="center" valign="middle" >1.69 ns</td></tr><tr><td align="center" valign="middle" >Error</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >4.61</td><td align="center" valign="middle" >49.95</td><td align="center" valign="middle" >97.51</td><td align="center" valign="middle" >72.01</td></tr><tr><td align="center" valign="middle"  colspan="2"  >VC (%)</td><td align="center" valign="middle" >14.08</td><td align="center" valign="middle" >12.48</td><td align="center" valign="middle" >16.04</td><td align="center" valign="middle" >13.34</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Mean (mg∙kg<sup>−1</sup>)</td><td align="center" valign="middle" >46.35</td><td align="center" valign="middle" >56.65</td><td align="center" valign="middle" >61.57</td><td align="center" valign="middle" >63.62</td></tr></tbody></table></table-wrap><p>DF = Degree of Freedom, ns, * and ** no significant, significant to the 5% and 1% level, respectively. VC = Variation Coefficient.</p><p>worrying the consumption of food products irrigated with water of inferior quality, with the presence of this metal, since this metal and others participate in the food chain [<xref ref-type="bibr" rid="scirp.79099-ref24">24</xref>] [<xref ref-type="bibr" rid="scirp.79099-ref25">25</xref>] .</p><p>Plants grown in soils irrigated with wastewater contaminated with heavy metals can cause great risk to human health [<xref ref-type="bibr" rid="scirp.79099-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.79099-ref26">26</xref>] [<xref ref-type="bibr" rid="scirp.79099-ref27">27</xref>] . However, at the 90 t∙ha<sup>−</sup><sup>1</sup> dose of bentonite, the concentration was 42.91 mg∙kg<sup>−1</sup>, i.e., less than the maximum tolerable value for human consumption, showing the beneficial effect of the bentonite incorporation into the soil.</p><p>The application of bentonite to the soil influenced the concentration of Zn in the aerial part (CS) of the corn, with a reduction of 27.81% in this concentration when the control was compared with the highest dose (<xref ref-type="fig" rid="fig2">Figure 2</xref>(b)). However, this reduction, in this case, was not effective enough to make the concentration below the maximum tolerable, contrary to what was observed by Khan et al. [<xref ref-type="bibr" rid="scirp.79099-ref28">28</xref>] . These authors, studying soil contamination by heavy metals through irrigation with water containing heavy metals and uptake of these metals by food crops, found that the concentration in the soil and in the edible parts of plants for zinc were below the allowable limits (100 mg∙kg<sup>−1</sup>) according to the State Environmental Protection Administration (SEPA) in China, in the cultures Raphanus sativus L., Zea mays, Brassica juncea L., Brassica oleracea L., Brassica napus and Lactuca sativa L.</p><p>The amount zinc accumulated in the radish root (AR) (<xref ref-type="fig" rid="fig3">Figure 3</xref>(a)) had a quadratic behavior ranging from 0.139 to 0.094 mg/pot, promoting a reduction of 32.26% as a function of increasing doses of bentonite, which means that the application of this clay to the soil was beneficial (<xref ref-type="table" rid="table3">Table 3</xref>).</p><p>In the case of corn, the bentonite incorporated into the soil promoted a reduction of 23.38% in the Zn accumulation in the aerial part of the crop (<xref ref-type="fig" rid="fig3">Figure 3</xref>(b)).</p><p>By the analysis of variance (<xref ref-type="table" rid="table4">Table 4</xref>), the bentonite doses did not significantly influence the transfer factor of the Zn of the cultures, however the regression showed by the linear behavior, the significance in the culture of radish and corn (<xref ref-type="fig" rid="fig4">Figure 4</xref>). In the case of radish, the transfer factor of Zn ranged from 0.723 to 0.975 that is, an increase of 34.85%, while in the corn, a decrease from 1.08 to 0.86, around 20.04% was observed. Most TF values obtained for Zn in this study were less than 1.0 suggesting that roots may regulate the transport of Zn to shoots.</p><p>Bentonite applied to the soil had a significant effect, at a 5% probability level in IT for corn (<xref ref-type="table" rid="table4">Table 4</xref>), showing a linear behavior (<xref ref-type="fig" rid="fig4">Figure 4</xref>) ranging from 82.01% to 75.92%, that is, a reduction in the order of 7.42% when comparing the control with the highest dose. This reduction showed that the concentration of Zn in the aerial part, where the edible part of the corn is located, decreased, thus avoiding entry into the food chain.</p><p>The zinc bioaccumulation factor (BFP) in the radish was significantly reduced in a quadratic manner 23.29% (<xref ref-type="table" rid="table5">Table 5</xref>) with the incorporation of bentonite doses varying from 3.01 to 2.31 of the control at the highest dose (<xref ref-type="fig" rid="fig5">Figure 5</xref>(a)). The BFP of corn reduced linearly around 24.29% (<xref ref-type="fig" rid="fig5">Figure 5</xref>(b)). Bentonite doses positively favored BFR only for the radish reducing 38.93%, according to <xref ref-type="fig" rid="fig5">Figure 5</xref>(c).</p><p>The BFP and BFR values were higher than those observed by Mirecki et al. [<xref ref-type="bibr" rid="scirp.79099-ref29">29</xref>] that is, these authors found BF for corn from 0.1 to 0.2. Most BF values obtained</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Summary of the analysis of variance of amount zinc accumulated in the shoot (AS) and root (AR) of radish and corn, irrigated with lower quality water with increasing doses of bentonite</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="3"  >Source of Variation</th><th align="center" valign="middle"  rowspan="3"  >DF</th><th align="center" valign="middle"  colspan="4"  >Mean Squares</th></tr></thead><tr><td align="center" valign="middle"  colspan="2"  >Radish</td><td align="center" valign="middle"  colspan="2"  >Corn</td></tr><tr><td align="center" valign="middle" >AS</td><td align="center" valign="middle" >AR</td><td align="center" valign="middle" >AS</td><td align="center" valign="middle" >AR</td></tr><tr><td align="center" valign="middle" >Bentonite</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >0.0005 ns</td><td align="center" valign="middle" >0.001 ns</td><td align="center" valign="middle" >2.31 ns</td><td align="center" valign="middle" >0.004 ns</td></tr><tr><td align="center" valign="middle" >Linear</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.0006 ns</td><td align="center" valign="middle" >0.0001 ns</td><td align="center" valign="middle" >4.65*</td><td align="center" valign="middle" >0.005 ns</td></tr><tr><td align="center" valign="middle" >Quadratic</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.000 4 ns</td><td align="center" valign="middle" >0.003**</td><td align="center" valign="middle" >0.98 ns</td><td align="center" valign="middle" >0.005 ns</td></tr><tr><td align="center" valign="middle" >Error</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >0.0006</td><td align="center" valign="middle" >0.0002</td><td align="center" valign="middle" >0.79</td><td align="center" valign="middle" >0.03</td></tr><tr><td align="center" valign="middle"  colspan="2"  >VC (%)</td><td align="center" valign="middle" >17.71</td><td align="center" valign="middle" >12.34</td><td align="center" valign="middle" >16.21</td><td align="center" valign="middle" >11.95</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Mean (mg/pot)</td><td align="center" valign="middle" >0.14</td><td align="center" valign="middle" >0.12</td><td align="center" valign="middle" >5.47</td><td align="center" valign="middle" >1.40</td></tr></tbody></table></table-wrap><p>DF = Degree of Freedom, ns, * and ** no significant, significant to the 5% and 1% level, respectively. VC = Variation Coefficient.</p><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Summary of the analysis of variance of transfer factor (TF) and translocation index (TI) of the Zn of the cultures radish and corn, irrigated with lower quality water with increasing doses of bentonite</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="3"  >Source of Variation</th><th align="center" valign="middle"  rowspan="3"  >DF</th><th align="center" valign="middle"  colspan="4"  >Mean Squares</th></tr></thead><tr><td align="center" valign="middle"  colspan="2"  >Transfer Factor (TF)</td><td align="center" valign="middle"  colspan="2"  >Translocation Index (TI)</td></tr><tr><td align="center" valign="middle" >Radish</td><td align="center" valign="middle" >Corn</td><td align="center" valign="middle" >Radish</td><td align="center" valign="middle" >Corn</td></tr><tr><td align="center" valign="middle" >Bentonite</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >0.06 ns</td><td align="center" valign="middle" >0.04 ns</td><td align="center" valign="middle" >64.91 ns</td><td align="center" valign="middle" >30.05*</td></tr><tr><td align="center" valign="middle" >Linear</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.13*</td><td align="center" valign="middle" >0.10*</td><td align="center" valign="middle" >51.14 ns</td><td align="center" valign="middle" >82.18**</td></tr><tr><td align="center" valign="middle" >Quadratic</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.09 ns</td><td align="center" valign="middle" >0.01 ns</td><td align="center" valign="middle" >122.77 ns</td><td align="center" valign="middle" >3.40 ns</td></tr><tr><td align="center" valign="middle" >Erro</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >0.02</td><td align="center" valign="middle" >0.02</td><td align="center" valign="middle" >43.92 ns</td><td align="center" valign="middle" >6.61</td></tr><tr><td align="center" valign="middle"  colspan="2"  >VC (%)</td><td align="center" valign="middle" >17.98</td><td align="center" valign="middle" >14.49</td><td align="center" valign="middle" >12.92</td><td align="center" valign="middle" >3.26</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Mean</td><td align="center" valign="middle" >0.85</td><td align="center" valign="middle" >0.97</td><td align="center" valign="middle" >51.31%</td><td align="center" valign="middle" >78.97%</td></tr></tbody></table></table-wrap><p>DF = Degree of Freedom, ns, * and ** no significant, significant to the 5% and 1% level, respectively. VC = Variation Coefficient.</p><table-wrap id="table5" ><label><xref ref-type="table" rid="table5">Table 5</xref></label><caption><title> Summary of the analyses of variance for bioaccumulation factor of zinc in plant (BFP) and in roots (BFR) of the radish and corn irrigated with poor quality water with increasing doses of bentonite</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="3"  >Source of Variation</th><th align="center" valign="middle"  rowspan="3"  >DF</th><th align="center" valign="middle"  colspan="4"  >Mean Squares</th></tr></thead><tr><td align="center" valign="middle"  colspan="2"  >BFP</td><td align="center" valign="middle"  colspan="2"  >BFR</td></tr><tr><td align="center" valign="middle" >Radish</td><td align="center" valign="middle" >Corn</td><td align="center" valign="middle" >Radish</td><td align="center" valign="middle" >Corn</td></tr><tr><td align="center" valign="middle" >Bentonite</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >0.40*</td><td align="center" valign="middle" >0.31*</td><td align="center" valign="middle" >1.80**</td><td align="center" valign="middle" >0.04 ns</td></tr><tr><td align="center" valign="middle" >Linear</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.53 ns</td><td align="center" valign="middle" >0.89*</td><td align="center" valign="middle" >4.13**</td><td align="center" valign="middle" >0.11 ns</td></tr><tr><td align="center" valign="middle" >Quadratic</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.65*</td><td align="center" valign="middle" >0.03 ns</td><td align="center" valign="middle" >1.02*</td><td align="center" valign="middle" >0.002 ns</td></tr><tr><td align="center" valign="middle" >Erro</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >0.11</td><td align="center" valign="middle" >0.11</td><td align="center" valign="middle" >0.12</td><td align="center" valign="middle" >0.10</td></tr><tr><td align="center" valign="middle"  colspan="2"  >VC (%)</td><td align="center" valign="middle" >13.05</td><td align="center" valign="middle" >14.36</td><td align="center" valign="middle" >12.48</td><td align="center" valign="middle" >13.34</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Mean (%)</td><td align="center" valign="middle" >2.56</td><td align="center" valign="middle" >2.28</td><td align="center" valign="middle" >2.81</td><td align="center" valign="middle" >2.34</td></tr></tbody></table></table-wrap><p>DF = Degree of Freedom, ns, * and ** no significant, significant at 5% and 1% level, respectively. VC = Variation Coefficient.</p><p>for Zn in this study were higher than 1.0 indicating that this metal is easily taken up by plants and higher suitability of the plant for phytoextraction and phytoremediation [<xref ref-type="bibr" rid="scirp.79099-ref4">4</xref>] .</p><p>According to Sajjad et al. [<xref ref-type="bibr" rid="scirp.79099-ref30">30</xref>] if the transfer coefficient of a metal is greater than 0.5, the plant will have a greater chance of the metal contamination by anthropogenic activities. However, the reductions in both BFP and BFR as a function of bentonite applied to the soil, were beneficial; due to the large surface area and high cation exchange capacity, this clay has a high adsorption potential of metallic cations, such as zinc, reducing the absorption of this element by the roots of the plants and consequently, reducing its transport to the edible part of the plant. These results had the same behavior in relation to the effect of bentonite in the removal of copper and cadmium of soil irrigated with low quality water [<xref ref-type="bibr" rid="scirp.79099-ref31">31</xref>] [<xref ref-type="bibr" rid="scirp.79099-ref32">32</xref>] .</p></sec><sec id="s4"><title>4. Conclusion</title><p>According to the conditions of this research, the incorporation of bentonite to the soil irrigated with water of inferior quality favored the development of radish and corn; allowed the retention of the Zn metal in the soil, reducing the concentrations of this metal in the root of the radish and in the aerial part of the corn; decreased the transfer of zinc from the soil to the plants under study.</p></sec><sec id="s5"><title>Acknowledgements</title><p>Special thanks to the Coordination for the Superior Level Personal Improvement (CAPES) for the scholarship granted to the first author.</p></sec><sec id="s6"><title>Cite this paper</title><p>Tito, G.A., Chaves, L.H.G. and Silva, F.A.S. (2017) Bentonite Effects on Zinc Concentration in Plants Irrigated with Wastewater. American Journal of Plant Sciences, 8, 2433-2444. https://doi.org/10.4236/ajps.2017.810165</p></sec></body><back><ref-list><title>References</title><ref id="scirp.79099-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Muchuweti, M., Birkett, J.W., Chinyanga, E., Zvauya, R., Scrimshaw, M.D. and Lester, J.N. (2006) Heavy Metal Content of Vegetables Irrigated with Mixtures of Wastewater and Sewage Sludge in Zimbabwe: Implications for Human Health. Agriculture, Ecosystems &amp; Environment, 112, 41-48. https://doi.org/10.1016/j.agee.2005.04.028</mixed-citation></ref><ref id="scirp.79099-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Cambra, K., Martínez, T., Urzelai, A. and Alonso, E. (1999) Risk Analysis of a Farm Area near a Lead- and Cadmium-Contaminated Industrial Site. 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