RESIDUES AND TRACE ELEMENTS Development and Validation of Routine Analysis Methods for the Determination of Essential, Nonessential, and Toxic Minor and Trace Elements in Cereal and Cereal Flour Samples by Inductively Coupled Plasma–Atomic Emission Spectrometry AWAD A. MOMEN, GEORGE A. ZACHARIADIS 1 , ARISTIDIS N. ANTHEMIDIS, and JOHN A. STRATIS Aristotle University, Department of Chemistry, Laboratory of Analytical Chemistry, Thessaloniki GR–54124, Greece Various digestion procedures were carefully investigated and accurately evaluated with respect to their effect on the analysis of cereals and cereal flours. Multielement methods were selected and well developed for the determination of essential (Cr, Cu, Fe, Mg, Mn, and Zn), nonessential (Ag, Al, Ba, Bi, In, and Ga), and toxic (Cd and Pb) minor and trace elements by inductively coupled plasma–atomic emission spectrometry. Only Ag could be determined, either with aqueous standard or standard addition calibration methods, while the standard addition methods were more accurate for the determination of other elements. The recoveries were mostly within the range of 84.1–113% for the expected values of all analytes with respect to certified reference material NIST SRM 1586a (rice flour). The results proved that, for cereals and cereal flours, the use of H 2 O 2 for wet digestion and HNO 3 for dry ashing were not necessary. Linear regression analysis and Student’s paired t-test were applied to evaluate the significant differences between different procedures and type of samples. I n recent years, there has been increasing implementation of multielement techniques in the analysis of foodstuffs to establish limits for human exposure from the diet. Regarding general population exposure to essential, nonessential, and toxic minor and trace elements, the relative intake via respiration (inhalation) and ingestion may vary, subject to environmental conditions (1, 2). Cereals, such as wheat, rice, corn, barley, rye, oats, and millet, are grains produced by plants (crops) belonging to the grass family. Wheat, rice, and corn are considered to be the most economically and nutritionally available in the world. They contain abundant amounts of antioxidants, vitamins, fats, minerals, fibers, lipids, carbohydrates, proteins, enzymes, and other beneficial nutrients. Food composition depends on many factors, such as climate, soil, variety, transport, storage, and preparation, that vary from 1 region to another and even within the same country (2, 3). It is now well recognized that minor and trace amounts of many metals play a vital role in several biochemical, clinical, nutritional, toxicological, environmental, and occupational health problems, while overdoses of these metals are usually harmful to health. Depending on the analysis task, several factors should be considered in order to choose the most suitable sample preparation method: levels of contamination introduced during preparation; completeness and reproducibility in analyte recovery from the matrix; possibilities for obtaining a representative sample (i.e., a sufficient amount in relation to homogeneity); suitability of the resulting solution for the instrumental technique; time needed for sample preparation; and economic aspects, including labor and reagent consumption, equipment cost, etc. These factors are very important for analysis of minor and trace elements, from both nutritional and toxicological points of view (4–8). The decomposition of organic materials in food samples can be achieved by either dry ashing and/or wet digestion. Although dry ashing is well established for the decomposition and determination of minor and trace elements with most analytical techniques, it is associated with losses by volatilization and/or retention problems. However, these problems can be overcome or reduced by using oxidizing materials (ashing aids), such as Mg (NO 3 ) 2 , HNO 3 , and H 2 SO 4 , or a mixture of MgO-HNO 3 , or, sometimes, by careful manipulation of the ashing temperature (9–12). In addition, the lower blank levels and the capability of handling large samples, up to 10 g, can make dry ashing methods desirable for minor and trace element determination. On the other hand, wet digestion methods for decomposition of food materials are widely available because of their simplicity. They are fairly rapid and flexible in terms of being applicable to changing sample weights and decomposition conditions, less prone to either volatilization or retention losses, and inexpensive. The main drawbacks are the coprecipitation of sparingly soluble compounds, incomplete digestion of organic material, and formation of insoluble compounds (13–16). Correspondingly, the use of oxidizing .VP, Author’s Galley ª Copyright 2004 by AOAC INTERNATIONAL. This proof is NOT for further distribution. MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005 1 Received March 22, 2005. Accepted by AK June 13, 2005. 1 Author to whom correspondence should be addressed; e-mail: [email protected].
Transcript
RESIDUES AND TRACE ELEMENTS
Development and Validation of Routine Analysis Methods for theDetermination of Essential, Nonessential, and Toxic Minor andTrace Elements in Cereal and Cereal Flour Samples byInductively Coupled Plasma–Atomic Emission Spectrometry
AWAD A. MOMEN, GEORGE A. ZACHARIADIS1, ARISTIDIS N. ANTHEMIDIS, and JOHN A. STRATIS
Aristotle University, Department of Chemistry, Laboratory of Analytical Chemistry, Thessaloniki GR–54124, Greece
Various digestion procedures were carefullyinvestigated and accurately evaluated with respectto their effect on the analysis of cereals and cerealflours. Multielement methods were selected andwell developed for the determination of essential(Cr, Cu, Fe, Mg, Mn, and Zn), nonessential (Ag, Al,Ba, Bi, In, and Ga), and toxic (Cd and Pb) minorand trace elements by inductively coupledplasma–atomic emission spectrometry. Only Agcould be determined, either with aqueous standard or standard addition calibration methods, while the standard addition methods were more accurate forthe determination of other elements. Therecoveries were mostly within the range of84.1–113% for the expected values of all analyteswith respect to certified reference material NISTSRM 1586a (rice flour). The results proved that, forcereals and cereal flours, the use of H2O2 for wetdigestion and HNO3 for dry ashing were notnecessary. Linear regression analysis andStudent’s paired t-test were applied to evaluate thesignificant differences between differentprocedures and type of samples.
In recent years, there has been increasing implementationof multielement techniques in the analysis of foodstuffsto establish limits for human exposure from the diet.
Regarding general population exposure to essential,nonessential, and toxic minor and trace elements, the relative intake via respiration (inhalation) and ingestion may vary,subject to environmental conditions (1, 2).
Cereals, such as wheat, rice, corn, barley, rye, oats, andmillet, are grains produced by plants (crops) belonging to the grass family. Wheat, rice, and corn are considered to be themost economically and nutritionally available in the world.They contain abundant amounts of antioxidants, vitamins,fats, minerals, fibers, lipids, carbohydrates, proteins,
enzymes, and other beneficial nutrients. Food compositiondepends on many factors, such as climate, soil, variety, transport,storage, and preparation, that vary from 1 region to another andeven within the same country (2, 3). It is now well recognized thatminor and trace amounts of many metals play a vital role in several biochemical, clinical, nutritional, toxicological, environmental,and occupational health problems, while overdoses of these metals are usually harmful to health.
Depending on the analysis task, several factors should beconsidered in order to choose the most suitable samplepreparation method: levels of contamination introducedduring preparation; completeness and reproducibility inanalyte recovery from the matrix; possibilities for obtaining arepresentative sample (i.e., a sufficient amount in relation tohomogeneity); suitability of the resulting solution for theinstrumental technique; time needed for sample preparation;and economic aspects, including labor and reagentconsumption, equipment cost, etc. These factors are veryimportant for analysis of minor and trace elements, from bothnutritional and toxicological points of view (4–8). Thedecomposition of organic materials in food samples can beachieved by either dry ashing and/or wet digestion. Althoughdry ashing is well established for the decomposition anddetermination of minor and trace elements with mostanalytical techniques, it is associated with losses byvolatilization and/or retention problems. However, theseproblems can be overcome or reduced by using oxidizingmaterials (ashing aids), such as Mg (NO3)2, HNO3, andH2SO4, or a mixture of MgO-HNO3, or, sometimes, by careful manipulation of the ashing temperature (9–12). In addition,the lower blank levels and the capability of handling largesamples, up to 10 g, can make dry ashing methods desirablefor minor and trace element determination. On the other hand,wet digestion methods for decomposition of food materialsare widely available because of their simplicity. They arefairly rapid and flexible in terms of being applicable tochanging sample weights and decomposition conditions, lessprone to either volatilization or retention losses, andinexpensive. The main drawbacks are the coprecipitation ofsparingly soluble compounds, incomplete digestion oforganic material, and formation of insolublecompounds (13–16). Correspondingly, the use of oxidizing
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Received March 22, 2005. Accepted by AK June 13, 2005.1Author to whom correspondence should be addressed; e-mail:
acids such as HNO3 and/or H2SO4 is important, especially forwet digestion of food samples high in carbohydrates or fats, toreduce carbonization and ensure completeness of thedecomposition. Also, mixtures of HNO3-HClO4 orHNO3-HCl, or combinations of more than 2 acids, are usuallyemployed in wet digestions, while the use of H2O2 may beneeded when the sample material is difficult todecompose (6, 17, 18).
The different procedures that are commonly applied resultin incongruous results because of inaccuracy due to matrixeffects, sampling errors, contamination and losses duringhandling, pretreatments, decomposition, and other proceduralsteps. Often, inaccuracy in determinations of some elementsmay also be attributed to the sampling, decomposition, ordigestion stages involved. Moreover, the chemical action ofthe reagents, formation of some insoluble compounds,resistance of some element compounds to oxidation, andvolatility of some element species present or formed can cause errors. It follows that methods for determining trace elementsshould involve minimal sample handling, be rapid, and havedetection limits that are relatively low to permit easy andreliable determination of analytes (10, 19). Because minimalsample pretreatment is a key demand in modern analyticalchemistry, we continued our research in this field.Considering these requirements, inductively coupledplasma–atomic emission spectrometry (ICP–AES) is a goodalternative because it allows a multielement determination in a single solution, with sufficiently low detection limits,selectivity, speed, precision, and wide analytical (dynamic)range (5, 17, 20).
The knowledge of metal concentrations in foods canprovide important information on the impact of the use ofchemical products in crops and on levels of environmentalpollution in farms. Furthermore, such a survey may indicatelocal foodstuffs that are important to supply essential metals
for population groups. In this paper, various digestionprocedures were carefully investigated and evaluated withrespect to their effect on the analysis of cereal and cereal floursamples. After preliminary study of (National Institute ofStandards and Technology NIST, Gaithersburg, MD) standard reference material (SRM) 1586a, the 4 most effectiveprocedures (2 wet digestions and 2 dry ashing methods) thatgave complete sample dissolutions (analyte transfer intosolution) were selected and further developed. Theseprocedures were used for sample decomposition and fordetermination of essential (Cr, Cu, Fe, Mg, Mn, and Zn),nonessential (Ag, Al, Ba, Bi, In, and Ga), and toxic (Cd andPb) minor and trace elements by ICP–AES.
Experimental
Instrumentation and Apparatus
A Perkin–Elmer Optima 3100XL ICP–AES instrument(CITY, COUNTRY?) was used for the determination ofelements, according to operating conditions given in Table 1.The analytical wavelengths (nm) were set at the following2 different spectral emission atomic and ionic lines for eachmetal: Ag (I), 328.068; Ag (I), 338.289; Al (I), 308.215;Al (I), 237.313; Ba (II), 233.527; Ba (II), 230.424; Bi (I),223.061; Bi (II), 190.171; Cd (II), 214.440; Cd (II), 226.502;Cr (II), 283.563; Cr (II), 284.325; Cu (I), 324.752; Cu (II),224.700; Ga (I), 294.364; Ga (II), 209.134; In (II), 230.606;In (I), 325.609; Fe (II), 238.204; Fe (II), 239.562; Mg (II),279.077; Mg (II), 280.271; Mn (II), 257.610; Mn (II),259.372; Pb (II), 220.353; Pb (I), 217.000; Zn (I), 213.857;and Zn (II), 202.548. tbl2
A peristaltic pump was used to introduce the samplesolutions into the ICP at a flow rate of 1 mL/min and to discard the wastes at a higher flow rate. A temperature-controlledelectric muffle furnace (Stuart Scientific Co. LTD, (CITY?)England) was used for ashing. A hot plate and precisionvacuum oven (Thermolyne, Sybron Corporation (CITY,COUNTRY?)) were also used. In order to avoidcontamination before use, all glassware,polytetrafluoroethylene (PTFE) digestion vessels, andpolyethylene storage bottles were soaked in freshly prepared10% (v/v) HNO3 for at least 48 h, and finally washed 3 timeswith doubly deionized water. Porcelain crucibles wereimmersed in diluted (AU: GIVE HCI EXACTCONCENTRATION?) HCI for ca 2 days and rinsed withdoubly deionized water several times.
Instrumental Conditions
Standard, reference, and sample solution extracts that wereobtained after the wet digestion and dry ashing procedureswere analyzed by ICP–AES using the operating conditionslisted in Table 1.
Reagents and Reference Solutions
(a) High purity doubly deionized water.—Used fordigestion, preparation of sample and reference materialsolutions, and dilution of all chemicals and reagents. Also,
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Table 1. Operational conditions and description ofICP–AES instrumentation
RF generator 40 MHz, free running
RF power 1300 W
Torch alumina injector, id 2.0 mm
Argon flow rate Auxiliary, 0.5 L/min/ nebulizer,
0.85 L/min/ plasma 15, L/min
Air flow rate 18 L/min
Spray chamber Scott doublepass
Nebulizer Gem tips crossflow
Pump Peristaltic, 3 channel
Sample flow rate 1.0 mL/min
Polychromator Echelle
Resolution 0.006 nm at 200 nm
Detector Segmented–array
charge–coupled (SCD)
deionized water was used for washing and rinsing of allapparatus and glassware.
(b) All reagents and chemicals.—Analytical grade andwere provided by Merck (Darmstadt, Germany), unless statedotherwise.
(c) ICP-AES multielement stock standard solution(23 elements in 0.8M HNO3) containing 1000 mg/L of eachelement.—Used for preparing calibration standards.
(d) Mineral acids, chemical reagents, and oxidizingagents.—[65% (w/v) HNO3 (d = 1.40 kg/L), 37% (w/v) HCI(d = 1.19 kg/L), 30% (w/v) H2O2 (d = 1.11 kg/L), 97% (w/v)H2SO4 (d = 1.84 kg/L), and absolute ethanol (d = 0.79 kg/L)were also used.
(e) Magnesium nitrate.—Used as a 5% (w/v) Mg(NO3)2·6H2O solution in absolute ethanol.
(f) Calibration standard solutions.—Made by appropriate dilution of the stock standard in 0.8M HNO3 to give a range of working standards (0.0, 10, 50, 100, 500, and 1000 mg/L).
(g) Certified reference material NIST SRM 1586a (riceflour).—Supplied by the NIST and used for optimization,setup, and validation of the whole analytical procedure.Certified reference values are available for most of theelements under investigation for assessment of the method’saccuracy.
Preparation of Sample Solutions
Three samples of cereals (rice, wheat, and corn) and 3 ofcereal flours (rice flour, wheat flour, and corn flour) werepurchased from a market. Samples were selected carefully torepresent the major categories that are availablecommercially. All samples were analyzed for essential,nonessential, and toxic minor and trace elements.
Sample preparation is often the rate-determining step in ananalysis. The pretreatment of food items usually involves dryashing of a sample and subsequent dissolution of the ash in anacid medium or, alternatively, direct acid treatment by wetoxidation. Because the grinding of cereals prior to digestioncaused no detectable effects on the determined values ofminor and trace elements (21), cereal samples were groundand sieved into a fine powder (<100 mm). To do this, a fraction of ca 3 g of each cereal sample was subjected to grinding andsieving using an acid-washed agate mortar and pestle. Thefirst 2 fractions were discarded because they were thought tobe more liable to contamination through grinding and sieving.The third aliquot was subsequently dried to a constant mass at50° ± 10°C using a precision vacuum oven, and then cooled in a desiccator and weighed as soon as it reached roomtemperature. Rice, wheat, and corn flour samples were notsubmitted to further sieving (all of them were finely powdered to <100 mm). NIST SRM 1586a was used as bottled, withoutfurther grinding and sieving, but it was dried as described inthe certificate of analysis.
Wet Digestion Procedures
Samples were accurately weighed (ca 0.5 g) into dry, cleanPTFE digestion vessels. One mL H2O was first added (drop by dro, to moisten the sample), and then the appropriate digestion
mixture [HNO3-H2SO4, (2 + 1) for Wet Digestion Method 1(WD1) or HNO3-H2O2-H2SO4, (4 + 1 + 1) for WD2]. Thepresence of water in the mineralization mixture helps toprevent the evolution of gases resulting from the high contentof carbohydrates in the material (21). When the initial reaction subsided, the vessel contents were gently mixed, and themixtures were left for ca 1 h in a clean fume hood at roomtemperature for predigestion. The vessel contents weredigested on a hot plate inside the fume hood at 110° ± 10°Cuntil heavy evolution of brown NO2 fumes ceased. Then, thetemperature was gradually increased and the heating wascontinued until white fumes of SO3 evolved, leaving only aclear, colorless or pale yellow solution of residual sulfuric acid and inorganic constituents (ca 0.5 mL). If carbonization(charring) appeared, the vessel was removed from the hotplate and cooled in a water bath, ca 1 mL HNO3 was added,and the digestion was continued until the solution cleared.Finally, after cooling, the residue were dissolved in 2.5 mLHCl, diluted to 50 mL with H2O, and transferred immediatelyto polyethylene storage bottles for further analysis. Thepresence of 0.6M HCl in the final solutions is necessary forminimizing the formation of insoluble hydroxides andmaintaining an acidic environment. The same acid digestionprocedures were carried out for blanks and NIST SRM 1586ato validate the quality of the analytical procedures.
Matrix effect studies were carried out by spiking some ofthe original undigested samples with various amounts ofstandard solutions of the metals (0.0, 10, 50, 100, 500, and1000 mg/L). The spiked samples were mineralized using thesame digestion procedures as were applied to the nonspikedsamples.
Dry Ashing Procedures
Three-gram sample portions were accurately weighed intoporcelain crucibles. Three mL H2O was first added (drop bydrop, to moisten the sample), and then the ashing aids [for Dry Ashing Method 1 (DA1), an ethanol solution of Mg (NO3) 2,and for DA2 5%, (v/v) HNO3-ethanolic Mg (NO3) 2, (2 + 1)].The presence of water in the mineralization mixture is for thesame reason as mentioned above. When the initial reactionsubsided, the crucibles were placed on a hot plate inside afume hood, and heated at 90° ± 10°C to evaporate moistureand excess reagents and carbonize the samples. Then, thecrucibles containing the carbonized materials were transferred into a temperature-controlled electric muffle furnace at 500° ±20°C for ca 2–3 h for ashing. After ashing was completed(white or semigray ash of inorganic residues), the crucibleswere left to cool to room temperature. If carbon particlesremained in the crucible, the black residue was moistenedwith several drops of HNO3 and the suspension was reashed(recalcination) in a muffle furnace for another 30 min at thesame temperature. This procedure yielded a white or semigray ash. The crucibles were then cooled to room temperature. Theashes were first moistened with a few drops of H2O, thendissolved by subsequently adding 2.5 and 1.5 mL HCl andHNO3 to the crucibles and, finally, quantitatively transferredto 50 mL volumetric flasks (volumes were brought to 50 mL
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MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005 3
4 MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005
.VP, Author’s Galley ã Copyright 2004 by AOAC INTERNATIONAL. This proof is NOT for further distribution.
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with H2O). Then, the flasks were shaken well and transferredimmediately to polyethylene storage bottles for furtheranalysis. The presence of both HCl and HNO3 in the case ofdry ashing was necessary to facilitate ash dissolution,minimize formation of insoluble hydroxides, and maintain anacidic environment. The same ashing procedures were carriedout for NIST SRM 1586a to ensure the quality of theanalytical procedures.
Matrix effect studies were carried out by spiking some ofthe original, unashed samples with various amounts ofstandard solutions of the metals (0.0, 10, 50, 100, 500, and1000 mg/L). The spiked samples were ashed using the sameprocedures as were applied to the nonspiked samples.
Statistical Analysis
Significant differences between means were evaluated byStudent’s paired t-test (confidence interval, 95%). Linearregression statistical testing and correlation analysis were also performed (at 99% probability level) for comparison of theslopes of regression lines found by plotting the emissionintensities of aqueous standards vs the emission intensities ofstandard addition solution. Also, these tests have been used toexamine the statistical significance of differences between oramong samples and the different methods of analysis usedwith various experimental conditions.
Results and Discussion
Selection of Emission Lines
All elements were measured using 2 different spectralemission lines (atomic and ionic lines), and the sensitivitiesbased on the emission intensities were calculated. Greaterintensity values indicated higher sensitivity. Therefore, in the
present study, the higher sensitivity for each element wasobserved at the following spectral lines (nm): Ag (I), 328.068;Al (I), 237.313; Ba (II), 233.527; Bi (I), 223.061; Cd (II),226.502; Cr (II), 284.325; Cu (I), 324.752; Ga (I), 294.364;In (I), 325.609; Fe (II), 238.204; Mg (II), 279.077; Mn (II),259.372; Pb (I), 217.000; and Zn (I), 213.857. These emission lines were selected for quantification throughout this study.
Accuracy Control of Digestion Methods
In order to verify the accuracy of the investigated methods,certified reference material NIST SRM 1586a was treated bythe proposed methods and analyzed by ICP–AES using theoperational conditions listed in Table 1. The results (Table 2)indicated that there was good agreement between measuredand certified values within absolute errors of less than16% (Figure 1). Student’s paired t-test showed that there wereinsignificant differences between the means of the certifiedand obtained values for the elements under investigation,using the different digestion techniques at the 95% confidence limit. According to the recovery calculations (Table 2) and theabsolute percentage error comparisons (Figure 1) of elementshaving certified value with respect to NIST SRM 1586a, nosignificant differences were observed in recoveries eitherbetween the WD1 and WD2 or DA1 and DA2 methods asindicated by Student’s paired t-test (at the 95% confidencelimit). Also, taking into account the recovery values, it wasfound that the WD1 and WD2 methods gave the best resultsfor the majority of the elements. Although sufficientrecoveries were obtained for almost all elements using theproposed methods, it was observed that the WD1 method thebest results compared to the other methods (Table 2), i.e., thedigestion mixture HNO3-H2SO4 quantitatively extracted
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MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005 5
Figure 1. Comparison of absolute errors (%) encountered in the determination of certified elements from NIST SRM1586a after wet digestion (WD1 and WD2) and dry ashing (DA1 and DA2) procedures followed by ICP–AES analysis.
6 MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005
.VP, Author’s Galley ã Copyright 2004 by AOAC INTERNATIONAL. This proof is NOT for further distribution.
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69.
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9.0
9
32.
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61
4.0
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19
9.0
0
53.
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5.0
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89
9.0
9
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1±
68
1.0
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0
40
3.1
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N
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99
9.0
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22.
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22.
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0
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0
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8
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0
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0
59
4.0
±
24
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67
9.0
31
1.2
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1S
N
aG
89
9.0
0
81.
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2
91.
0S
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99.
0
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0
42
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99
9.0
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41.
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49
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0
67
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99.
0
43
3.1
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44.
0 S
N4
99.
0
14
0.1
±6
62.
0 S
N4
99.
0
19
0.1
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72.
0 S
N
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59
9.0
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20.
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0
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9.1
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dQ
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QN
dQ
Nd
QN
dQ
Nd
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30.
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68
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89
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9
90.
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85
1.0
SN
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9.0
4
11.
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84
1.0
SN
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9.0
2
01.
1±
71
2.0
SN
almost all of the minor and trace elements in the standard riceflour. However, some losses of analytes were observed duringdry ashing procedures, especially of Bi, Fe, and Cd, probablydue to volatilization and/or retention on the crucibles. tbl2,fig1
Study of Matrix Effects
To check for possible interferences due to the samplematrix, linear regression statistical tests at the 99% probability level were applied to compare the slopes of the regressionlines found by plotting the emission intensities of aqueousstandards versus the emission intensities of standard additionsolutions (Tables 3–5). The theoretical model assumes that the values of the slope are equal to unity (absence of additive ormultiplicative effects; 17). If the calculated slopes did notdiffer significantly from unity, then the sensitivities of the2 techniques were similar; otherwise, the 2 techniques weresignificantly different. It was found that almost all analyteswere shown to have both significant (S) andnonsignificant (NS) differences (at the 99% probability level), depending on the type of sample matrix and the digestionprocedure applied. Comparison of emission intensity slopesindicated that only Ag could be determined, either withaqueous standards or standard additions calibration methods(i.e., NS in all cases). This is evidence of the absence ofadditive or multiplicative effects, and that the measurementprocess was not affected by nonspectral interferences.Therefore, calibration with aqueous standards was valid forAg determination. In contrast, Cu and Mg showed significantdifferences in the sensitivity of the determination in all cases(i.e., S in all cases), so only calibrations with standardadditions were valid for Cu and Mg determinations. However, for Al, Ba, Bi, Cd, Cr, Ga, In, Fe, Mn, Pb, and Zn, thedifferences in slope values of the regression lines plottedbetween the emission intensities of aqueous standards andstandard addition solutions of these elements (i.e., either Sor NS) may be attributed to both additives and matrix effects.These deviations hinder direct calibrations using aqueousstandards, and make it necessary to use the standard additionmethod for determination of these elements in order toeliminate the errors due to nonlinearity and/or matrixinterferences. Moreover, the emission intensity slope valuesof some elements (e.g., Fe, Cu, Bi, Mg, and Zn) indicated thatthere are systematic deviations due to sample matrixes and/orreagents used. This causes constant errors that lead to higheror lower slope values (i.e., either higher or lower than unity)and decrease the sensitivity. Furthermore, the theoreticalmodel assumes that the values of the coefficientcorrelation (R) are equal to unity (maximum agreement; 17).It was found that the calculated R values varied in the range of0.773 to 0.999. Overall, the results proved that all of thetechniques are useful for analysis of cereal and cereal floursamples for these analytes, with acceptable precision andaccuracy (22, 23). tbls3-5
Analysis of Cereal and Cereal Flour Samples
All cereal and cereal flour samples were pretreated usingthe different digestion procedures (WD1, WD2, DA1, and
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MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005 7
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8 MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005
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84.
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9.0
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62.
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29
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5
51.
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43
3.0
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28
9.0
8
58.
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58
3.0
SN
56
9.0
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65.
1±
38
9.0
SN
58
9.0
0
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29
3.0
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52
9.0
6
81.
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91
1.1
SN
32
9.0
9
60.
1±
72
0.1
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45
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80
4.0
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0
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6.0
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27
9.0
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12.
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83
6.0
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77
9.0
3
21.
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36
5.0
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9.0
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40.
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3.0
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DA2) and analyzed by ICP–AES using the operationalconditions described in Table 1. Overall, the resultsdemonstrated that all of the methods can be used for analyzing cereal and cereal flour samples with acceptable accuracy. Theelemental contents and uncertainty of the measurements aregiven in Tables 6–8 for each analyzed sample. The relativestandard deviation values in almost all cases ranged between1–9%, proving sufficient reproducibility of the developedmethods. With respect to cereal and cereal flour samples,Student’s t-test (P < 0.05) did not reveal significantdifferences in efficiency between WD1 and WD2 or DA1 andDA2. Also, it was proven that the digestion of cereals andcereal flours did not require the addition of H2O2 for wetdigestion or HNO3 for dry ashing procedures to quantitativelyextract the analyte elements in cereal and cereal flour samples. This helps to minimize problems of contamination and highblank values and also reduce sample pretreatment. tbls6-8
(THIS LISTING OF EACH METAL TAKES MUCHSPACE AND IS REPETATIVE. YOU FOUND ALLMETALS IN ALL SAMPLES. YOU FOUND NOSIGNIFICANT DIFFERENCES IN ANY SAMPLE FOR ANY ELEMENT. THIS COULD BE STATED IN ASINGLE SENTENCE. THE SAMPLES CONTAININGTHE HIGHTEST AND LOWEST LEVELS OF EACHMETAL COULD BE SUMMARIZED IN A NEWTABLE, BUT THIS INFORMATION MUST ALREADYBE IN THE PRESENT TABLES.)
(a) Silver.—Multiple comparisons among cereal andcereal flour samples showed that Ag was present in allsamples at very low concentrations. Student’s paired t-test (P< 0.05) between all samples showed that Ag levels were notsignificantly different. However, it was found that the Aglevel was highest in corn (0.027 ± 0.002 mg/g) and lowest inwheat (0.011 ± 0.001 mg/g).
(b) Aluminium.—Al was abundant in both cereals andcereal flours. Student’s paired t-test indicated that Al levelswere not significantly different between all samples.Moreover, the Al level was highest in rice(4.247 ± 0.246 mg/g) and lowest in wheat flour(3.212 ± 0.218 mg/g).
(c) Barium.—Ba was present in both cereals and cerealflours at relatively low concentrations. Student’s paired t-testshowed no significant differences between them for allsamples. The Ba level was highest in rice (0.106 ± 0.015 mg/g) and lowest in corn flour (0.077 ± 0.006 mg/g).
(d) Bismuth.—The highest level of Bi was found in rice(0.221 ± 0.018 mg/g) and the lowest level in corn flour(0.096 ± 0.010 mg/g). It was found that Bi was present in allsamples at very low concentrations. Student’s paired t-testshowed no significant differences between them.
(e) Cadmium.—Cd was present in both cereals and cerealflours. Student’s paired t-test between all samples showed that Cd levels were not significantly different. The highest level ofCd was found in wheat (0.027 ± 0.003 mg/g), while the lowestlevel was found in wheat flour (0.017 ± 0.002 mg/g).
(f) Chromium.—The highest concentration of Cr wasobserved in corn flour (0.560 ± 0.026 mg/g), and the lowest
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MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005 9
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10 MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005
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concentration in rice flour (0.155 ± 0.014 mg/g). It was foundthat Cr was present in all cereals and cereal flours. Student’spaired t-test indicated no significant difference between allsamples.
(g) Copper.—Cu was also present in both cereals andcereal flours. Student’s paired t-test showed insignificantdifferences between them. The highest level of Cu was foundin wheat (2.505 ± 0.131 mg/g), while the lowest level wasfound in corn flour (1.892 ± 0.140 g/g).
(f) Iron.—Fe was present in cereals and cereal flours,generally at high concentrations. Student’s paired t-testindicated that Fe levels did not vary significantly between allsamples. The highest level of Fe was found in wheat(20.61 ± 1.212 mg/g), while the lowest level was found in riceflour (8.880 ± 0.693 mg/g).
(g) Indium.—In was present in both cereals and cerealflours in low concentrations. Student’s paired t-test indicatedthat In levels were not significantly different between allsamples. The highest level of In was found in rice(0.337 ± 0.018 mg/g), while the lowest level was found inwheat flour (0.194 ± 0.014 mg/g).
(h) Gallium.—The concentration of Ga was highest incorn flour (0.063 ± 0.005 mg/g) and lowest in wheat flour(0.030 ± 0.004 mg/g). It was found that Ga was present in allsamples at very low concentrations. Student’s paired t-testshowed no significant differences between them.
(i) Magnesium.—Mg was highly abundant in cereals andcereal flours, with no significant differences between them, asproved by using Student’s paired t-test. The highest level ofMg was found in corn flour (663.2 ± 20.89 mg/g), while thelowest level was found in wheat flour (414.4 ± 12.46 mg/g).Mg was not quantified in all samples using the dry ashingmethods (DA1, DA2) due to method limitations, i.e. anethanolic solution of Mg (NO3)2 was used as an ashing aid.
(j) Manganese.—Mn was present in cereals and cerealflours at relatively high concentrations. Student’s paired t-testindicated that Mn levels did not vary significantly between allsamples. The highest level of Mn was found in rice(11.99 ± 0.832 mg/g), while the lowest level was found in cornflour (5.795 ± 0.353 mg/g).
(k) Lead.—Pb was present in both cereals and cerealflours at relatively low levels. Student’s paired t-test did notreveal significant differences between them. The Pb level washighest in rice (0.041 ± 0.004 mg/g) and the lowest in cornflour (0.017 ± 0.002 mg/g).
(l) Zinc.—Zn was highly abundant in both cereals andcereal flours. Student’s paired t-test indicated that Zn levelswere not significantly different between all samples. The Znlevel was highest in rice (22.74 ± 1.301 mg/g) and lowest incorn flour (10.01 ± 0.812 mg/g).
Conclusions
The analytical methods that have been developed andvalidated for cereal and cereal flour sample digestion provedto be simple, accurate, robust, (IS THERE DATA TOPROVE ROBUSTNESS?) and reliable. They can be
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MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005 11
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12 MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005
.VP, Author’s Galley ã Copyright 2004 by AOAC INTERNATIONAL. This proof is NOT for further distribution.
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noit
ani
mret
eD
a
noit
artn
ecn
oC
b( m
)eci
R ,g/
gn
oitart
nec
no
Cb
( m
) ru
olf eci
R ,g/
g
tn
em
elE
1D
W2
DW
1A
D2
AD
1D
W2
DW
1A
D2
AD
gA
7
10.
0±
10
0.0
5
10.
0±
10
0.0
4
10.
0±
10
0.0
4
10.
0±
10
0.0
2
10.
0±
10
0.0
4
10.
0±
10
0.0
2
10.
0±
10
0.0
1
10.
0±
10
0.0
lA
9
44.
4±
51
1.0
1
32.
4±
10
1.0
3
03.
4±
63
1.0
3
00.
4±
24
1.0
2
34.
4±
53
1.0
0
30.
4±
72
1.0
6
60.
4±
03
1.0
8
35.
4±
15
1.0
aB
0
11.
0±
50
0.0
4
11.
0±
60
0.0
1
01.
0±
60
0.0
0
01.
0±
50
0.0
7
01.
0±
40
0.0
6
90.
0±
30
0.0
9
90.
0±
40
0.0
8
90.
0±
40
0.0
iB
6
22.
0±
80
0.0
8
22.
0±
90
0.0
6
12.
0±
90
0.0
2
12.
0±
01
0.0
1
32.
0±
80
0.0
4
22.
0±
90
0.0
9
91.
0±
70
0.0
7
91.
0±
70
0.0
dC
9
20.
0±
20
0.0
7
20.
0±
20
0.0
0
20.
0±
20
0.0
9
10.
0±
10
0.0
3
20.
0±
20
0.0
1
20.
0±
20
0.0
9
10.
0±
10
0.0
7
10.
0±
10
0.0
rC
6
02.
0±
21
0.0
2
02.
0±
11
0.0
4
91.
0±
90
0.0
6
81.
0±
80
0.0
8
71.
0±
70
0.0
4
51.
0±
80
0.0
8
41.
0±
70
0.0
1
41.
0±
60
0.0
uC
7
22.
2±
23
1.0
6
61.
2±
12
1.0
0
14.
2±
16
1.0
5
23.
2±
05
1.0
7
84.
2±
14
1.0
2
92.
2±
33
1.0
1
14.
2±
54
1.0
7
89.
1±
70
1.0
eF
3
9.3
1±
76
5.0
9
8.2
1±
34
5.0
9
3.1
1±
99
4.0
9
8.2
1±
50
4.0
3
23.
9±
18
3.0
5
08.
9±
42
3.0
4
89.
8±
64
2.0
0
04.
7±
91
2.0
aG
9
50.
0±
30
0.0
7
50.
0±
30
0.0
5
50.
0±
20
0.0
3
50.
0±
20
0.0
7
50.
0±
20
0.0
9
50.
0±
30
0.0
7
50.
0±
30
0.0
2
50.
0±
20
0.0
nI
84
3.0
±7
10.
0
63
3.0
±8
10.
0
33
3.0
±8
10.
0
13
3.0
±7
10.
0
48
2.0
±4
10.
0
87
2.0
±3
10.
0
96
2.0
±4
10.
0
74
2.0
±3
10.
0
gM
4.
05
5±
91.
41
8.
34
5±
01.
61
QN
cQ
Nc
7.
41
5±
91.
51
5.
30
5±
01.
31
QN
cQ
Nc
nM
9
0.2
1±
84
7.0
0
0.2
1±
41
6.0
7
9.1
1±
55
5.0
1
9.1
1±
21
4.0
6
8.0
1±
42
4.0
9
8.0
1±
90
5.0
0
68.
9±
24
4.0
8
27.
9±
63
4.0
bP
9
40.
0±
30
0.0
2
40.
0±
20
0.0
8
40.
0±
30
0.0
6
30.
0±
20
0.0
5
30.
0±
20
0.0
2
30.
0±
20
0.0
3
30.
0±
20
0.0
9
20.
0±
20
0.0
nZ
9
0.4
2±
25
2.1
6
5.3
2±
63
2.1
2
6.0
2±
07
1.1
9
6.2
2±
64
2.1
8
2.0
2±
46
1.1
8
8.0
2±
93
2.1
3
7.7
1±
07
8.0
6
1.8
1±
16
9.0
a.)
gni
hsa yr
d( 2
AD ,
1A
D ;)n
oitse
gid t
ew(
2D
W ,1
DW
b
na
eM
±(
noit
aive
d dr
ad
nats
n.)
3 =
cO
N( g
M ot
eu
d d
eifitn
au
q to
N =
QN
3)
2
.di
a g
nihs
a sa
noiti
dd
a
.VP, Author’s Galley ã Copyright 2004 by AOAC INTERNATIONAL. This proof is NOT for further distribution.
MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005 13
.7
el
ba
Ts
eu
qin
hc
et n
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d s
uoir
av
gni
su
sis
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na
SE
A–
PCI
yb
sel
pm
as r
uolf t
ae
hw
dn
a ta
eh
w ni
sn
oitart
ne
cn
oc
etyl
an
a fo
noit
ani
mret
eD
a
noit
artn
ecn
oC
b( m
)ta
eh
W ,g/
gn
oitart
nec
no
Cb
( m
)ru
olf ta
eh
W ,g/
g
tn
em
elE
1D
W2
DW
1A
D2
AD
1D
W2
DW
1A
D2
AD
gA
2
10.
0±
10
0.0
2
10.
0±
10
0.0
1
10.
0±
10
0.0
0
10.
0±
10
0.0
2
10.
0±
10
0.0
2
10.
0±
10
0.0
1
10.
0±
10
0.0
1
10.
0±
10
0.0
lA
5
75.
3±
79
0.0
8
14.
3±
10
1.0
8
93.
3±
60
1.0
2
03.
3±
71
1.0
5
33.
3±
0
01.
0
69
6.3
±3
11.
0
71
1.3
±0
11.
0
00
1.3
±8
11.
0
aB
2
01.
0±
40
0.0
1
01.
0±
50
0.0
4
90.
0±
40
0.0
0
90.
0±
40
0.0
3
90.
0±
40
0.0
0
90.
0±
30
0.0
7
80.
0±
40
0.0
9
80.
0±
30
0.0
iB
9
41.
0±
60
0.0
6
41.
0±
70
0.0
8
21.
0±
60
0.0
7
11.
0±
50
0.0
6
11.
0±
50
0.0
7
11.
0±
50
0.0
1
11.
0±
50
0.0
2
01.
0±
40
0.0
dC
1
30.
0±
20
0.0
0
30.
0±
20
0.0
6
20.
0±
20
0.0
2
20.
0±
20
0.0
9
10.
0±
10
0.0
8
10.
0±
10
0.0
6
10.
0±
10
0.0
4
10.
0±
10
0.0
rC
3
91.
0±
90
0.0
8
91.
0±
01
0.0
7
81.
0±
90
0.0
8
81.
0±
90
0.0
4
81.
0±
70
0.0
5
71.
0±
80
0.0
2
71.
0±
70
0.0
4
71.
0±
80
0.0
uC
0
76.
2±
45
1.0
5
47.
2±
66
1.0
8
53.
2±
77
1.0
5
42.
2±
14
1.0
1
63.
2±
81
1.0
4
12.
2±
62
1.0
1
14.
2±
55
1.0
9
20.
2±
20
1.0
eF
1
3.1
2±
34
8.0
5
5.2
2±
61
9.0
8
0.8
1±
21
7.0
0
5.0
2±
57
8.0
1
4.0
2±
87
8.0
9
4.8
1±
35
7.0
2
2.7
1±
70
6.0
5
0.8
1±
10
7.0
aG
8
40.
0±
20
0.0
5
40.
0±
20
0.0
6
40.
0±
20
0.0
4
40.
0±
20
0.0
2
30.
0±
20
0.0
3
30.
0±
20
0.0
9
20.
0±
20
0.0
7
20.
0±
20
0.0
nI
47
2.0
±4
10.
0
86
2.0
±3
10.
0
54
2.0
±2
10.
0
93
2.0
±3
10.
0
80
2.0
±9
00.
0
59
1.0
±0
10.
0
88
1.0
±9
00.
0
48
1.0
±8
00.
0
gM
6.
19
4±
62.
31
7.
08
4±
22.
21
QN
cQ
Nc
1.
51
4±
99.
11
6.
31
4±
39.
21
QN
cQ
Nc
nM
5
08.
8±
76
3.0
8
19.
8±
57
3.0
0
97.
8±
81
3.0
0
08.
8±
42
3.0
1
55.
7±
63
2.0
4
14.
7±
91
2.0
4
53.
7±
74
2.0
3
11.
7±
17
2.0
bP
4
20.
0±
20
0.0
7
20.
0±
20
0.0
9
20.
0±
20
0.0
1
20.
0±
20
0.0
9
10.
0±
10
0.0
0
20.
0±
20
0.0
8
10.
0±
10
0.0
6
10.
0±
10
0.0
nZ
2
2.7
1±
21
4.0
0
9.6
1±
30
4.0
9
3.7
1±
91
4.0
9
9.5
1±
63
4.0
7
9.4
1±
04
4.0
2
4.3
1±
15
3.0
2
9.3
1±
47
4.0
4
5.2
1±
80
3.0
a.)
gni
hsa yr
d( 2
AD ,
1A
D ;)n
oitse
gid t
ew(
2D
W ,1
DW
b
na
eM
±(
noit
aive
d dr
ad
nats
n.)
3 =
cO
N( g
M ot
eu
d d
eifitn
au
q to
N =
QN
3)
2
.di
a g
nihs
a sa
noiti
dd
a
14 MOMEN ET AL.: JOURNAL OF AOAC INTERNATIONAL VOL. 88, NO. 6, 2005
.VP, Author’s Galley ã Copyright 2004 by AOAC INTERNATIONAL. This proof is NOT for further distribution.
.8
el
ba
Tsi
syl
an
a S
EA
–P
CI y
b s
elp
ma
s ru
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oc
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no
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na f
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eu
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su
a
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b( m
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oC ,
g/g
noit
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b( m
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oC ,
g/g
tn
em
elE
1D
W2
DW
1A
D2
AD
1D
W2
DW
1A
D2
AD
gA
8
20.
0±
20
0.0
9
20.
0±
20
0.0
7
20.
0±
20
0.0
5
20.
0±
20
0.0
2
20.
0±
10
0.0
1
20.
0±
10
0.0
9
10.
0±
10
0.0
0
20.
0±
20
0.0
lA
8
09.
3±
12
1.0
4
47.
3±
01
1.0
5
39.
3±
80
1.0
5
96.
3±
89
0.0
4
45.
3±
78
0.0
4
83.
3±
87
0.0
1
42.
3±
57
0.0
6
12.
3±
96
0.0
aB
9
90.
0±
40
0.0
4
90.
0±
40
0.0
2
90.
0±
40
0.0
6
80.
0±
30
0.0
3
80.
0±
30
0.0
1
80.
0±
30
0.0
3
70.
0±
30
0.0
1
70.
0±
30
0.0
iB
8
01.
0±
40
0.0
6
01.
0±
40
0.0
4
90.
0±
30
0.0
1
90.
0±
30
0.0
1
01.
0±
40
0.0
2
01.
0±
40
0.0
0
90.
0±
30
0.0
9
80.
0±
30
0.0
dC
7
20.
0±
20
0.0
5
20.
0±
20
0.0
1
20.
0±
10
0.0
0
20.
0±
20
0.0
6
20.
0±
20
0.0
4
20.
0±
20
0.0
8
10.
0±
10
0.0
9
10.
0±
10
0.0
rC
9
44.
0±
82
0.0
4
64.
0±
92
0.0
0
34.
0±
72
0.0
1
24.
0±
62
0.0
3
75.
0±
23
0.0
2
95.
0±
43
0.0
6
45.
0±
92
0.0
8
25.
0±
13
0.0
uC
0
55.
2±
55
1.0
6
93.
2±
24
1.0
1
53.
2±
54
1.0
9
26.
2±
76
1.0
4
89.
1±
91
1.0
3
79.
1±
40
1.0
1
99.
1±
11
1.0
0
08.
1±
29
0.0
eF
3
2.5
1±
07
6.0
9
3.4
1±
21
5.0
0
7.4
1±
66
5.0
1
7.3
1±
88
4.0
2
1.0
1±
34
3.0
1
0.0
1±
71
3.0
6
14.
9±
16
3.0
0
00.
9±
86
2.0
aG
5
60.
0±
30
0.0
3
60.
0±
30
0.0
9
50.
0±
30
0.0
0
60.
0±
30
0.0
1
70.
0±
40
0.0
6
60.
0±
40
0.0
9
50.
0±
30
0.0
7
50.
0±
30
0.0
nI
55
2.0
±4
10.
0
74
2.0
±3
10.
0
93
2.0
±2
10.
0
63
2.0
±3
10.
0
01
2.0
±2
10.
0
20
2.0
±1
10.
0
59
1.0
±1
10.
0
69
1.0
±0
10.
0
gM
6.
71
6±
04.
71
7.
31
6±
33.
81
QN
cQ
Nc
5.
46
6±
76.
91
9.
16
6±
01.
81
QN
cQ
Nc
nM
5
65.
6±
60
2.0
9
10.
6±
40
2.0
5
12.
6±
71
2.0
6
22.
6±
00
2.0
9
99.
5±
41
2.0
6
18.
5±
42
2.0
4
57.
5±
24
2.0
2
16.
5±
33
2.0
bP
5
20.
0±
20
0.0
3
20.
0±
20
0.0
2
20.
0±
20
0.0
9
10.
0±
20
0.0
0
20.
0±
20
0.0
9
10.
0±
10
0.0
5
10.
0±
10
0.0
4
10.
0±
10
0.0
nZ
9
3.1
1±
22
3.0
6
9.1
1±
87
3.0
2
7.0
1±
40
2.0
7
8.0
1±
96
2.0
3
5.0
1±
54
2.0
9
1.0
1±
04
2.0
1
96.
9±
38
2.0
0
16.
9±
97
2.0
a.)
gni
hsa yr
d( 2
AD ,
1A
D ;)n
oitse
gid t
ew(
2D
W ,1
DW
b
na
eM
±(
noit
aive
d dr
ad
nats
n.)
3 =
cO
N( g
M ot
eu
d d
eifitn
au
q to
N =
QN
3)
2
.di
a g
nihs
a sa
noiti
dd
a
considered as useful techniques for routine analysis of minorand trace elements and in the quality control process.Calibrations after standard addition were preferable over theaqueous standard calibrations. No statistically significantdifferences were observed in efficiencies, either betweenHNO3-H2SO4 or HNO3-H2O2-H2SO4 in wet digestionmethods or between Mg (NO3) 2 and HNO3-Mg (NO3) 2 in dryashing methods. It was concluded, therefore, that the use ofH2O2 for wet digestion and HNO3 for dry ashing is notcritical. In addition, although acceptable results were obtained from all of the developed methods, the wet digestionprocedure with HNO3-H2SO4 is recommended for increasedanalyte recovery. The dynamic range of the method covers the range of concentrations usually found in cereal, and cerealflours, and the reproducibility of the method is sufficient.
Acknowledgments
This research, which is part of Awad Momen’s Ph.D.thesis, was financially supported by the Greek StateScholarship Foundation.
References
(1) Tripathi, R.M., Raghunath, R., Sastry, V.N., & Krishnamoorthy,T.M. (1999) Sci. Total Environ. 227, 229–235
(2) Santos, E.E., Lauria, D.C., & Porto da Silveira, C.L. (2004) Sci.Total Environ. 327, 69–79
