Simultaneous determination of macronutrients, micronutrients and trace elements in mineral fertilizers by inductively coupled plasma optical emission spectrometry

Spectrochimica Acta Part B 96 (2014) 1–7

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Analytical note

Simultaneous determination of macronutrients, micronutrients and trace elements in mineral fertilizers by inductively coupled plasma optical emission spectrometry Sidnei de Oliveira Souza a, Silvânio Silvério Lopes da Costa a,b, Dayane Melo Santos a, Jéssica dos Santos Pinto a, Carlos Alexandre Borges Garcia a, José do Patrocínio Hora Alves a,c, Rennan Geovanny Oliveira Araujo a,d,⁎ a

Laboratório de Química Analítica Ambiental (LQA), Departamento de Química, Centro de Ciências Exatas e Tecnologia, Universidade Federal de Sergipe (UFS), 49100-000, São Cristovão, SE, Brazil Coordenação de Química, Universidade Federal de Alagoas (UFAL), Campus Arapiraca, 57309-005, Arapiraca, AL, Brazil c Instituto Tecnológico e de Pesquisas do Estado de Sergipe (ITPS), 49000-000, Aracaju, SE, Brazil d Departamento de Química Analítica, Instituto de Química, Universidade Federal da Bahia (UFBA), 40170-115 Salvador, BA, Brazil b

a r t i c l e

i n f o

Article history: Received 2 October 2013 Accepted 24 March 2014 Available online 5 April 2014 Keywords: Mineral fertilizers Simultaneous determination Mineral composition Experimental design ICP OES

a b s t r a c t An analytical method for simultaneous determination of macronutrients (Ca, Mg, Na and P), micronutrients (Cu, Fe, Mn and Zn) and trace elements (Al, As, Cd, Pb and V) in mineral fertilizers was optimized. Two-level full factorial design was applied to evaluate the optimal proportions of reagents used in the sample digestion on hot plate. A Doehlert design for two variables was used to evaluate the operating conditions of the inductively coupled plasma optical emission spectrometer in order to accomplish the simultaneous determination of the analyte concentrations. The limits of quantification (LOQs) ranged from 2.0 mg kg−1 for Mn to 77.3 mg kg−1 for P. The accuracy and precision of the proposed method were evaluated by analysis of standard reference materials (SRMs) of Western phosphate rock (NIST 694), Florida phosphate rock (NIST 120C) and Trace elements in multi-nutrient fertilizer (NIST 695), considered to be adequate for simultaneous determination. Twenty-one samples of mineral fertilizers collected in Sergipe State, Brazil, were analyzed. For all samples, the As, Ca, Cd and Pb concentrations were below the LOQ values of the analytical method. For As, Cd and Pb the obtained LOQ values were below the maximum limit allowed by the Brazilian Ministry of Agriculture, Livestock and Food Supply (Ministério da Agricultura, Pecuária e Abastecimento — MAPA). The optimized method presented good accuracy and was effectively applied to quantitative simultaneous determination of the analytes in mineral fertilizers by inductively coupled plasma optical emission spectrometry (ICP OES). © 2014 Elsevier B.V. All rights reserved.

1. Introduction The analysis of mineral fertilizer using a multielement technique is of great importance since the agricultural productivity is directly linked to the use of agricultural input magnifiers, containing many elements, and some of them can be toxic, contaminate soils and ultimately reach food products. These inputs are defined as any substance, mineral or organic, natural or synthetic, which supplies one or more plant nutrients [1]. Concern regarding food security has gained prominence mostly due to the indiscriminate use of agricultural inputs and the consequent contamination of the soil, resulting in the accumulation of chemicals by foodstuffs [2–4]. On the other hand, the control of these inputs results in improvement of the agricultural production, i.e., it requires a more ⁎ Corresponding author at: Departamento de Química Analítica, Instituto de Química, Universidade Federal da Bahia (UFBA), 40170–-115, Salvador, BA, Brazil. Tel./fax: +55 71 3283 6830. E-mail addresses: [email protected], [email protected] (R.G.O. Araujo).

http://dx.doi.org/10.1016/j.sab.2014.03.008 0584-8547/© 2014 Elsevier B.V. All rights reserved.

efficient quality control of the fertilizers used in agricultural production [5]. The fertilizers can be a source of contamination from the raw material or unreliable sources, used as intermediates in the manufacturing process, whose composition may contain, in addition to the essential elements, hazardous substances, namely, contaminants [6–9]. In Brazil, the Ministry of Agriculture, Livestock and Food Supply (Ministério da Agricultura, Pecuária e Abastecimento — MAPA) establishes, through the Normative no. 27 (June 5, 2006), the maximum permitted limits for contaminants, such as As, Cd, Cr, Hg and Pb in mineral fertilizers. In the United States, each American state has its own regulations and one federal law regulates fertilizers and only regarding zinc as a contaminant, as published in July 24, 2002 by the United State Environmental Protection Agency (USEPA). Canada, through the Federal Fertilizers Act, regulates contaminants' content in mineral fertilizers [10–12]. Since the determination of the mineral composition in fertilizers is of great importance, many techniques have been used with this purpose [3,4,13]. Studies using different techniques, such as graphite furnace atomic absorption spectrometry (GF AAS) [3] and cold vapor atomic

2

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absorption spectrometry (CV AAS) [13], have been reported. Even radioactive elements such as uranium, radium and thorium were determined in fertilizers [15,16]. The inductively coupled plasma optical emission spectrometry (ICP OES), which makes it possible simultaneous determinations and allows rapid analysis, is also reported [4,14]. The use of microwave digestion and ICP OES to determine As, Cd, Co, Cr, Pb, Mo, Ni and Se in fertilizers [4] is described by Kane and Hall. ICP OES is recognized as a powerful analytical technique for the determination of chemical elements because its high sensitivity and detection power are relatively free of interference, allow simultaneous or sequential multi-element determination and have wide applicability, among other advantages [17–19]. However, quantitative analysis by ICP OES requires the complete digestion of the samples, otherwise the results can be affected by many factors leading to errors on the analysis [20]. The design of experiments is an important approach and has been successfully employed in sample preparation procedures to identify the optimum conditions and select the proportions between the reactants, allowing a faster acquiring of results, minimizing costs and time involved [21–23]. The use of diluted reagents in decomposition or extraction procedures, which leads to media with reduced acidity and also decreases the amount of corrosive substances, is an example of the experimental design application [24–26]. Chemometric tools were used to establish the appropriate experimental conditions for determination of mercury by CV AAS [27], arsenic (III) and total arsenic by hydride generation atomic absorption spectrometer (HG AAS) in phosphate fertilizer [28] and determination of Se and As in estuarine sediments by ICP OES using a concomitant metal analyzer as a hydride generator [29]. Thus, this paper purpose is a multivariate optimization of an analytical method to determine the mineral composition of mineral fertilizers employing ICP OES. 2. Experimental 2.1. Material and reagents All reagents used were analytical grade, and solutions were prepared with deionized water obtained from a reverse osmosis water purification system (OS 20 LX, GEHAKA, SP—Brazil). The nitric acid and hydrogen peroxide used were of suprapure quality (Merck, USA). External calibration was prepared from multielement stock solution (Ag, Al, B, Ca, Co, Cr, Cu, Fe, Mg, Mn, Na, Ni, P, Pb, Si, Sn, Sr, Ti, V and Zn) of 100 mg L−1 (Specsol®). Also, 1000 mg L−1 stock solutions (Specsol®) of Al, Ca, Fe, Mg, P and S, were diluted according to the working range required. The calibration curves were prepared in a range of concentrations from 0.1 to 5.0 mg L−1 for Al, As, Cd, Cu, Fe, Mn, Pb, V and Zn, and from 5.0 to 200.0 mg L−1 for Al, Ca, Fe, Mg, Na and P. The glassware used in the experiments was previously decontaminated with a nitric acid solution (10% v v−1) for 24 h [29,30], subsequently washed with ultrapure water and dried at room temperature. 2.2. Quality control and mineral fertilizer samples To assess the quality of the data obtained applying the proposed analytical methods, standard reference materials (SRMs) for Trace elements in multi-nutrient fertilizer (NIST 695), Western phosphate rock (NIST 694) and Florida phosphate rock (NIST 120C) [4,27,28] were employed. These materials present similar composition to the fertilizer samples and are adequate as reference material [6]. In addition twenty-one samples of mineral fertilizers sold in Sergipe State, Brazil were analyzed. The samples underwent a preparation in which they were dried in an oven with air circulation for 48 h at a temperature of 40 °C [31,32]. After that, the samples were cooled in a desiccator to room temperature, then weighed and kept inside the desiccator.

2.3. Preparation of mineral fertilizer samples A mass of approximately 0.20 g (dry weight) of the samples was placed in Teflon pumps, suitable for block digestion. Into these containers, 1.4 mL of concentrated HNO3 (65% w v−1), 1.0 mL of H2O2 (30% w v−1) and 7.6 mL of deionized water were added to a final volume of 10.0 mL. The system was closed and the samples were heated and kept at 180 °C for 2 h. After digestion the samples were transferred to 50.0 mL polyethylene tubes (falcon), and completed to a final volume of 25.0 mL with deionized water. All procedures were performed in triplicate, including the blank solutions and SRMs [27,33]. In this procedure, the reactant ratio was optimized through a two-level full factorial design, in order to minimize the use of concentrated reagents. The use of diluted reagents presents a great attractiveness in the decomposition of solid samples and also is in agreement with the principles of green chemistry, minimizing the generation of acid wastes [34]. 2.4. Instrumentation For the analysis of the fertilizer samples an inductively coupled plasma optical emission spectrometer with axial view (ICP OES, Vista Pro, Varian, Mulgrave, Australia) was used, and the operating conditions are detailed in Table 1. 2.5. Optimization strategy and analysis of the data The sample preparation procedure, using a digestion block, was optimized using a full two-level factorial design. The factors were the concentrations of the three diluted reagents: hydrochloric acid, hydrogen peroxide and nitric acid. The concentrations of Fe, Cr and Mn and Mg were used as the multiple response of the factorial design. The Doehlert design was employed to optimize the ICP OES operational conditions. The response was the ratio between the intensities of the magnesium emission lines, Mg II 280.265 nm/Mg I 285.208 nm. Triplicates of the central point were performed to evaluate experimental error. The analysis of the data obtained from the experimental designs was performed using Statistica® 8.0 software (StatSoft, USA). The measurements were performed in triplicate and the data are expressed as mean ± 95% confidence interval (CI). 3. Results and discussion 3.1. Multivariate optimization 3.1.1. Evaluation of sample digestion conditions using a two-level full factorial design The application of diluted reagents for digestion of the fertilizers is justified because they are salts easily dissolvable. Moreover, the sample preparation method proposed is environmentally friendly, compared to the standard procedure of USEPA 3050B and the method proposed by Nziguheba and Smolders, which use large amounts of reagents in the process, generating more acidic wastes [34–36]. The matrix of the 23 factorial design with triplicate of the central point was used to evaluate the different reactant ratios, using as variables the concentration of diluted reagents: nitric acid, hydrochloric acid and hydrogen peroxide in order to minimize the amounts of reagents required for sample preparation in digestion block as shown in Table 2. The experiments were performed in random order. The triplicate of the central point was used to estimate the experimental error in the factorial design. Approximately 0.20 g portions of commercial mineral fertilizer were used in these experiments. After applying the factorial design in the study, the concentration of the elements Fe, Cr, Mn and Mg in the solutions obtained in each experiment was used to calculate the responses for the mineral fertilizer sample. To optimize the analytical procedure, in order to achieve an efficient and simultaneous digestion of all elements of interest, a multiple response (MR) desirability

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multiple responses. The combination of higher response and less use of reagents was chosen as an optimum condition (Eq. (1)). After the simultaneous analysis of the data, the conditions for the digestion of fertilizer samples were 0.20 g of dry mineral fertilizer samples and addition of a solution containing 2.0 mol L−1 HNO3 and 3.0% (w v−1) H2O2 in a volume of 10.0 mL. After digestion, the extract was completed to a final volume of 25.0 mL with deionized water. The use of lower acid concentration solutions in the digestion procedure leads to a lower dilution factor, since the final solution is less acidic. It can thus be introduced directly into equipment, avoiding the wear and tear of the ICP OES components [35]. The residual acidity of the samples was determined by acid–base titration using NaOH (0.1 mol L−1) solution previously standardized with potassium hydrogen phthalate, obtaining an average concentration of 1.0 ± 0.4 mol L−1. This sample preparation procedure can be applied for analysis by ICP OES and also by inductively coupled plasma mass spectrometry (ICP-MS), first of all because it does not use HCl minimizing interference problems. Also the combination of HNO3 with H2O2 in closed system increases the efficiency of digestion due to the high oxidizing power of the mixture and the higher pressure and temperature generated inside the container. Besides, a lower dilution factor favors a better performance of the instrument and lowers LODs [32,35].

Table 1 Characteristics and operating conditions used for analysis by ICP OES with axial view. Parameter

Characteristics

Radio frequency power (W) Plasma gas flow rate (L min−1) Auxiliary gas flow rate (L min−1) Sample uptake rate (mL min−1) Nebulizer gas flow rate (L min−1) Nebulizer type Spray chamber Replicates Injector tube diameter (mm) Signal integration time (s)

1200 15.0 1.5 0.8 0.8 Concentric, sea spray Type cyclone 3 2.4 1.0

Wavelength (nm)

Al I 308.215 As I 188.980 Ca I 373.690 Cd I 228.802 Cu I 327.595 Fe II 259.940 Mg I 285.213

Mg II 280.265 Mn II 257.610 Na I 589.592 P I 213.618 Pb II 217.000 V II 292.403 Zn II 206.200

(I) Atomic line. (II) Ionic line.

function approach was employed. For the MR calculation Eq. (1) was used [37,38]: MR ¼

Conc:Fe Conc:Cr Conc:Mn Conc:Mg þ þ þ MaxConc:Fe MaxConc:Cr MaxConc:Mn MaxConc:Mg

3

3.1.2. Evaluation of the operating conditions obtained for the ICP OES using a Doehlert design In order to obtain a robust plasma condition, the main parameters, radiofrequency power (RFP) and nebulizer gas flow (NGF), can be adjusted and this adjustment is critical as regards the energizing of the atoms and ions in the simultaneous determination, due to the different excitation energy required by each element. These factors affect the intensity of the emission line, which depends on the number of atoms or ions emitted. The RFP and NGF parameters are independent, i.e., when they change the intensity of the emission line is affected, and both affect the intensity of the signal-to-background ratio. So, the selection of an appropriate combination of these parameters is required for an efficient use of the ICP OES [19,39]. Therefore, a Doehlert design for two variables was applied to optimize the operating conditions of the ICP OES [22]. The Doehlert matrix is shown in Table S1 in Appendix A. The experiments were carried out randomly with three central points, to estimate the experimental error. The experimental data were treated using Statistica 8.0 software. The Doehlert matrix was applied to a commercial mineral fertilizer sample digested under the pre-established conditions described above. The response of the Doehlert design was evaluated considering the ratio of the emission intensities of ionic and atomic magnesium lines (Mg II 280.265 nm/Mg I 285.213 nm), and a value greater than 8.0 indicates a robust plasma condition. Under these conditions the interference effects are minimal and any change in the concentrations of

ð1Þ

where, Conc.Fe is iron concentrations found in each experiment, and the MaxConc.Fe is the maximum concentration of iron found in the factorial design. The same logic applies to concentrations of Cr, Mn and Mg. After applying the factorial design, the factors or their interactions, that cause a significant variation in the multiple response, was identified. The values were obtained from the Pareto chart for the effects of the factors and their interactions within a 95% confidence interval, as shown in Fig. 1. The graph shows the effect of the HNO3, HCl and H2O2 concentrations on the multiple response. The magnitude of the effects is represented by columns, and the vertical line indicates the statistical significance for p = 0.05, i.e., the factors, which values are higher than the vertical line are statistically significant at 95% confidence level. The graphical representation (Fig. 1) shows that no major factors are significant, as well as the interactions between them. Also a non-significant effect was observed in the estimation of curvature, indicating the absence of curvature in the linear model. The values obtained for the concentrations of trace elements in mineral fertilizer samples may present a significant discrepancy in some cases, because the combination of reagents used in the experiment, and some elements in the fertilizers are recalcitrant [4]. But in this case the combination was assessed using the concentrations of four elements to compose the

Table 2 Matrix of the 23 full factorial design with triplicate of the central point used in the evaluation of the reactants ratios. Experiment

Actual values

Found values

−1

HNO3 (mol L 1 2 3 4 5 6 7 8 9 10 11

0.50 2.00 0.50 2.00 0.50 2.00 0.50 2.00 1.25 1.25 1.25

)

−1

HCl (mol L 0.00 0.00 1.00 1.00 0.00 0.00 1.00 1.00 0.5 0.50 0.50

)

−1

H2O2 (% w v 0.00 0.00 0.00 0.00 3.00 3.00 3.00 3.00 1.50 1.50 1.50

)

−1

Fe (mg kg 568 790 756 656 554 635 685 655 600 623 766

)

Multiple response −1

Cr (mg kg 1.37 1.80 2.00 1.81 1.32 1.60 2.04 2.29 1.71 1.27 1.94

)

−1

Mn (mg kg 7.9 3.3 6.9 4.4 5.8 7.3 7.3 7.2 8.6 7.4 8.4

)

−1

Mg (mg kg 20.2 19.5 23.4 19.4 18.9 20.4 21.7 21.4 18.2 18.3 18.6

) 3.10 3.00 3.63 2.96 2.76 3.22 3.53 3.58 3.28 2.99 3.59

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Fig. 1. Pareto chart for the 23 factorial design.

major elements, acids, and other components is compensated by the ICP OES system, without any significant variation in the intensities of the lines between the excitation potential of 4.35 eV (corresponding to Mg I line) and the potential sum of 14.35 eV (corresponding to Mg II line) [40,41]. The results obtained experimentally are shown in Table S1 in Appendix A. The Pareto chart used to assess the factors affecting the response in a significant way is shown in Fig. S1 in Appendix A. The graphic representation was constructed on the basis of RFP and NGF, and the magnitude of the effects is represented by columns while the vertical line indicates the statistical significance at p = 0.05, i.e. the factors larger than the vertical cross line are statistically significant at the 95% confidence level. The Pareto chart shows that the interaction between the parameters (RFP linear by NGF linear) is not a significant factor in the applied design. Both parameters are important and both are positive, i.e., the response is maximized as the RFP and NGF are increased, confirming that this optimization is really important [37,38,42]. To evaluate the fitting of the model to the data analysis of variance (ANOVA) was applied. A summary of the ANOVA results is given in Table S2 in Appendix A. The regression model was significant for a 95% confidence level (F calculated 2.6 = 16.8; F tabulated 2.6 = 5.14; p-value = 3.45 × 10− 3). The lack of fit was evaluated through the F-test, where the Fcalculated (7.61) was less than Ftabulated (18.51), indicating that, there was a good agreement between the model prediction and the experimental data and showing that there was no lack of fit (p-value 0.05) [21,22]. The contour chart (Fig. S1 in Appendix A) shows that as the RFP and the NGF increase the response for Mg II/Mg I ratio also increases, and the response for a NGF of 0.9 L min−1 and a RFP of 1400 W is the maximum region. After the simultaneous analysis of the data through a visual inspection, as shown in Fig. S2 in Appendix A the operating conditions

established in this study, for the ICP OES instrument, were radiofrequency power of 1200 W and nebulizer gas flow of 0.8 L min−1, evaluated through the Mg II/Mg I ratio, since a value ≥ 8.0 for this ratio corresponds to a robust plasma, i.e., there may be minor modifications in the plasma without any significant change in the emission intensities of analytes [42,43]. 3.2. Analytical method validation The following elements present in the SRMs were determined in different wavelengths, Al: 237.312, 308.215 and 396.152 nm, As: 188.980, 193.696 and 197.198 nm, Ca: 315.887, 317.933, 370.602, 373.690 and 422.673 nm, Cd: 214.439, 226.502 and 228.802 nm, Cu: 324.754 and 327.395 nm, Fe: 238.204, 259.940 and 261.947 nm, Mg: 279.800, 280.270 and 285.213 nm, Mn: 257.610, 259.372, 260.568 and 294.921 nm, Na: 568.821 and 589.592 nm, P: 177.434, 178.222 and 213.618 nm, Pb: 182.143, 217.000 and 220.353 nm, V: 292.401 and 311.837 nm and Zn: 202.548 and 213.857 nm. This procedure made it possible to select the more sensitive lines, free of interference (Table 1), that were used to calculate the limits of detection (LOD) and the limits of quantification (LOQ) through the background equivalent concentration (BEC) and the signal-to-background ratio (SBR). The LOD and LOQ values were calculated using the BEC and the SBR, according to International Union of Pure and Applied Chemistry (IUPAC); BEC = Cstandard / SBR, where SBR = (Istandard − Iblank) / Iblank; Cstandard is the reference element concentration in the solution; and Istandard and Iblank are the emission intensities for the reference element and blank solutions, respectively at the selected wavelength [38,40]. The LOD was then calculated as (3 × RSDblank × BEC / 100) and the LOQ as (3.3 × LOD), where RSDblank is the relative standard deviation of ten measurements of the emission intensity of the blank solution

Table 3 Values obtained for BEC, LOD and LOQ in the analysis of mineral fertilizer samples by ICP OES.a Analytical parameter −1

BEC (mg L ) LOD (mg kg−1) LOQ (mg kg−1) a

Al

As

Ca

Cd

Cu

Fe

Mg

Mn

Na

P

Pb

V

Zn

0.05 5.4 18.2

0.1 5.0 16.7

0.2 21.5 72.0

0.004 3.3 11.0

0.004 3.0 10.0

0.02 14.3 47.7

0.02 6.3 21.0

0.001 0.6 2.0

0.03 14.0 46.7

0.05 23.2 77.3

0.006 3.0 10.0

0.002 1.2 4.0

0.01 5.0 16.7

Analytical parameters obtained for mass of 0.20 g of mineral fertilizers and completed to 25.0 mL with deionized water.

33.34 ± 0.06 28.46 ± 0.90 85.4 ± 3.0 3.0 0.32 ± 0.01 0.33 ± 0.01 103.2 ± 3.0 3.0 1.08 ± 0.03 0.92 ± 0.03 85.5 ± 3.0 3.0

P2O5 (%) MgO (%) Fe2O3 (%)

0.260 ± 0.072 80.0 ± 1.0 1.0 101 ± 2 82.8 ± 1.0 1.0

Recoveryð% Þ ¼ ½found value=certified value  100

Al2O3 (%)

1.30 ± 0.04 1.10 ± 0.03 84.4 ± 3.0 3.0 Certified value Found value Recovery (%) RSD (%) NIST 120C

ð2Þ

where found value is the analyte concentration determined by the proposed method and the certified value is the concentration value of the analyte reported in the SRM certification document. The precision and accuracy expressed as RSD (%) and recovery (%), respectively, obtained for the optimized analytical method, can be observed in Table 4, as well as the certified values and the found values for SRMs. The recovery between the certified values and the found values ranged from 80.0% ± 1.0 (Al, Fe and Zn) to 120.0% ± 5.0 (Na), and the RSD values obtained were better than 5% (n = 3). The limit of detection values for the determination of elements by other techniques, are given in Table 5. The sensitivity of the method proposed in this study is comparable to that of the methods reported in the literature. The ICP OES technique can be used in routine analysis for the determination of Al, As, Ca, Cd, Cu, Fe, Mg, Mn, Na, P, Pb, V and Zn in mineral fertilizer samples with great advantages. NIST 694: Western phosphate rock, NIST 695: Trace elements in multi-nutrient fertilizer and NIST 120C: Florida phosphate rock. a All results were expressed as mean ± 95% confidence interval (n = 3). b Relative standard deviation (RSD, n = 3).

0.295 ± 0.009 96.7 ± 1.0 1.0 1.50 ± 0.09 83.8 ± 2.0 2.0 3.20 ± 0.05 80.0 ± 1.0 1.0 14.0 ± 1.0 82.8 ± 2.0 2.0 1028 ± 16 91.4 ± 1.0 1.0 2.32 ± 0.05 102.6 ± 1.0 1.0 179 ± 4 89.5 ± 1.0 1.0 0.49 ± 0.01 80.0 ± 1.0 1.0

5

at the selected wavelength [38,40]. The LOD values ranged from 0.6 μg g− 1 , for Mn, to 23.2 μg g − 1 for P, and LOQ values ranged from 2.0 μg g− 1, for Mn to 77.3 μg g− 1 for P, as shown in Table 3. The precision of the method was evaluated via the repeatability and can be expressed as the relative standard deviation (RSD) of a set of measurements. Accuracy expresses the difference between the value found experimentally and a reference value. In this study, Trace elements in multi-nutrient fertilizer (NIST 695), phosphate rocks (NIST 694 and NIST 120C) and SRMs were used to establish the accuracy through the values calculated using the Eq. (2). This approach is directly related to international standards.

0.430 ± 0.010 106.2 ± 1.0 1.0

6.5 ± 0.2 90.3 ± 1.0 1.0

250 ± 7 91.6 ± 1.0 1.0

0.325 ± 0.005 122 ± 3 0.305 ± 0.005 200 ± 5 NIST 695

Certified value Found value Recovery (%) RSD (%)

0.61 ± 0.03

2.26 ± 0.04

1125 ± 9

16.9 ± 0.2

3.99 ± 0.08

1.79 ± 0.05

0.405 ± 0.005

7.2 ± 0.1

273 ± 17

Zn (%) V (mg kg−1) Pb (mg kg−1) Mn (%) Mg (%) Fe (%) Cd (mg kg−1) Cu (mg kg−1) Ca (%) As (mg kg−1) Al (%)

0.79 ± 0.06 0.66 ± 0.04 84.0 ± 3.0 4.0 0.96 ± 0.05 0.84 ± 0.07 87.5 ± 3.0 3.0 Certified value Found value Recovery (%) RSD (%)b

0.013 ± 0.003 0.014 ± 0.001 93.3 ± 3.0 3.0

Al2O3 (%) Parameters

NIST 694

SRMa

Table 4 Results obtained for the SRM analysis by ICP OES using the proposed method.

CdO (%)

Fe2O3 (%)

Na (%)

P (%)

P2O5 (%)

30.2 ± 0.1 25.9 ± 0.7 85.8 ± 3.0 3.0 0.0116 ± 0.0012 0.0103 ± 0.0011 88.9 ± 3.0 3.0 0.33 ± 0.02 0.35 ± 0.04 106.0 ± 4.0 4.0

Na2O (%) MnO (%) MgO (%)

0.86 ± 0.04 1.04 ± 0.06 120.0 ± 5.0 3.0

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3.3. Application of optimized method to mineral fertilizer samples The optimized analytical method for the determination of Al, As, Ca, Cd, Cu, Fe, Mg, Mn, Na, P, Pb, V and Zn by ICP OES which was applied to twenty-one samples of mineral fertilizers marketed in the Sergipe State, Brazil was analyzed. The concentrations of macronutrients (Ca, Mg, Na and P), micronutrients (Cu, Fe, Mn and Zn) and trace elements (Al, As, Cd, Pb and V) are shown in Table S3 in Appendix A. The concentration ranges found for the elements were: b 0.02– 2.22 ± 0.09% for Al; b 9.4–40.0 ± 1.2 mg kg−1 for Cu; b0.05–9.46 ± 0.33% for Fe; b0.02–9.52 ± 0.56% for Mg; b 2.0–1825.0 ± 13.7 mg kg−1 for Mn; b 0.05–20.4 ± 0.4% for Na; b0.08–12.2 ± 4.0% for P; b4.0– 600.0 ± 15.0 mg kg−1 for V and b16.7–75.0 ± 20.0 mg kg−1 for Zn. The concentrations of As, Ca, Cd and Pb were also determined, but the values obtained for these elements were below the limits of quantification of the proposed method. Brazilian legislation regulates the maximum concentrations of toxic elements in mineral fertilizers, containing nitrogen, potassium, and secondary macronutrients, up to 5% of P2O5, through Norm no. 27 of MAPA. The maximum values are: As (10.0 mg kg−1); Cd (20.0 mg kg−1) and Pb (100.0 mg kg−1). It is known that ICP OES is not so sensitive as ICP-MS and GF AAS and usually is not adequate to the determination of As, Cd and Pb at low concentrations, but depending on the concentration of the analytes in the sample and the optimization of the digestion procedure, minimizing the dilution, it is possible to perform the determination [49,50], with good accuracy. The method developed in this work presented good accuracy as confirmed by the results obtained for the SRMs and, since the LOD values are below the maximum values established by Brazilian legislation of MAPA, it can be applied to the determination of the elements in mineral fertilizer samples. 4. Conclusions The two and three-level factorial designs proved to be effective in the optimization of the acid digestion conditions for mineral fertilizers,

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Table 5 Detection limits obtained by different techniques in the determination of macronutrients, micronutrients and trace elements in mineral fertilizers. LOD (mg (mg (mg (mg (mg (mg (mg (mg

kg−1) kg−1) kg−1) kg−1) kg−1) kg−1) kg−1) kg−1)

Al

As

Ca

Cd

Cu

Fe

Mg

Mn

Na

P

Pb

V

Zn

Technique

Reference

– – – – – – – 5.40

4.82 – – – – 1.00 – 5.00

– – – – – – 0.03 21.5

0.77 0.24 4.30 – – 0.22 – 3.30

– 0.60 19.3 0.44 0.34 0.60 – 3.00

– – – 0.82 0.36 1.40 – 14.3

– – – – – – 0.02 6.30

– 0.62 – 0.30 1.08 0.15 – 0.60

– – – – – – – 14.0

– – – – – – 0.05 23.2

1.35 2.39 12.9 – – 1.10 – 3.00

– – – – – 0.45 – 1.20

– 1.15 – 0.36 0.36 0.45 0.02 5.00

ICP OESa FS FAASb FAASc MP AESd ICP OESd ICP OESe ICP-MSf ICP OESg

[4] [44] [45] [46] [46] [47] [48] This study

ICP OES: inductively coupled plasma optical emission spectrometry//FAAS: Flame Atomic Absorption Spectrometry//FS FAAS: Fast Sequential Flame Atomic Absorption Spectrometry//MP AES: Microwave plasma atomic emission spectrometry//ICP-MS: Inductively coupled plasma mass spectrometry. a Analytical parameters obtained using 1.00 g of mineral fertilizers in a final volume of 100 mL with deionized water. b Analytical parameters obtained using 0.12 g of organic fertilizers in a final volume of 10.0 mL with ultrapure water. c Analytical parameters obtained using 0.07 g of inorganic fertilizers in a final volume of 15.0 mL with deionized water. d Analytical parameters obtained using 1.00 g of animal feed and fertilizers in a final volume of 200 mL with deionized water. e Analytical parameters obtained using 1.00 g of mineral fertilizers in a final volume of 50.0 mL with double-distilled water. f Analytical parameters obtained using 0.40 g of mineral fertilizers in a final volume of 25.0 mL with deionized water. g Analytical parameters obtained using 0.20 g of mineral fertilizers in a final volume of 25.0 mL with deionized water.

and optimization of the operating conditions for ICP OES in the simultaneous determination of Al, As, Ca, Cu, Cd, Fe, Mg, Mn, Na, P, Pb, V and Zn. The precision, expressed as relative standard deviation (RSD), was less than 5.0% for all elements (n = 3). The optimized analytical method presented low LOD and LOQ values, leading to reliable results due to its good precision and accuracy in the multielement determination of macronutrients (Ca, Mg, Na and P), micronutrients (Cu, Fe, Mn and Zn) and trace elements (Al, As, Cd, Pb and V) in commercial mineral fertilizer samples by ICP OES. The accuracy of the method was confirmed through the analysis of the SRM for Trace elements in multi-nutrient fertilizer (NIST 695), Western phosphate rock (NIST 694) and Florida phosphate rocks (NIST 120). The concentrations found showed good agreement with the certified values for Al, As, Ca, Cu, Cd, Fe, Mg, Mn, Na, P, Pb, V and Zn ranging from 80.0% ± 1.0 (Al, Fe e Zn) to 120.0% ± 5.0 (Na). The concentrations of the elements As, Ca, Cd and Pb were also determined in fertilizer samples, but the values were lower than the LOQ obtained for the proposed analytical method. However, since the limits of quantification for As, Cd and Pb were below the maximum values established in the current legislation of the MAPA, the method developed in this work can be considered suitable for the determination of these analytes. The ICP OES technique is not usually applicable for the determination of As, Cd and Pb in low concentrations, but the analytical method developed can be effectively applied in determining the maximum levels allowed by the Brazilian legislation. Acknowledgments The study was financially supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Apoio a Pesquisa e Inovação Tecnológica do Estado de Sergipe (FAPITEC — Process no. 019.203.01713/2010-4) and Instituto Tecnológico e de Pesquisa do Estado de Sergipe (ITPS), which provided fellowships and infrastructure. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.sab.2014.03.008. References [1] SSSA — Soil Science Society of America, Glossary of Soil Science Terms, 2014. (Retrieved in January 06, 2014).

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