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Analytica Chimica Acta 758 (2013) 28– 35

Contents lists available at SciVerse ScienceDirect

Analytica Chimica Acta

jou rn al hom epa ge: www.elsev ier .com/ locate /aca

he effect of cooking and washing rice on the bio-accessibility of As,u, Fe, V and Zn using an on-line continuous leaching method

olan S. Horner, Diane Beauchemin ∗

epartment of Chemistry, Queen’s University, 90 Bader Lane, Kingston, ON K7L 3N6, Canada

i g h l i g h t s

Cooking long grain brown orwhite rice does not affect thebio-accessibility of arsenic.Four toxic As species in saliva andgastric juice leachates were sepa-rated by one method.Washing rice a few min prior tocooking removes about 90% of bio-accessible arsenic.Cooking long grain brown or whiterice appears to convert some speciesto As(III).On-line leaching provides in a fewmin similar results to 2 h/reagentbatch methods.

g r a p h i c a l a b s t r a c t

r t i c l e i n f o

rticle history:eceived 18 July 2012eceived in revised form 3 November 2012ccepted 8 November 2012vailable online 16 November 2012

eywords:

a b s t r a c t

A previously developed method based on continuous on-line leaching with artificial gastro-intestinalfluids was used to determine the bio-accessible fraction of As, Cu, Fe, V and Zn in brown and white ricefrom California by inductively coupled mass spectrometry (ICP-MS). Saliva generally accounted for thelargest percentage of total element leached in comparison to gastric and intestinal juices. Arsenic specia-tion analysis was performed on the saliva and gastric juice leachates using ion exchange chromatographycoupled to ICP-MS. The four most toxic species of As (As(III), monomethylarsonic acid (MMA), dimethy-larsinic acid (DMA) and As(V)), as well as Cl− in the gastric juice leachate, were successfully separated

rseniciceio-accessibilitypeciation analysisnductively coupled plasma masspectrometryn-line leaching

within 5.5 min using a simple nitric acid gradient. While cooking rice had relatively little effect on totalbio-accessibility, a change in species from As(V) and DMA to As(III) was observed for both types of rice.On the other hand, washing the rice with doubly deionized water prior to cooking removed a largepercentage of the total bio-accessible fraction of As, Cu, Fe, V and Zn.

© 2012 Elsevier B.V. All rights reserved.

. Introduction

Rice contains high concentrations of arsenic relative to otherrops and represents a major source of As intake in human diets1]. Yet, chronic exposure to As has the potential to cause several

∗ Corresponding author. Tel.: +1 613 533 2619; fax: +1 613 533 6669.E-mail address: diane.beauchemin@chem.queensu.ca (D. Beauchemin).

003-2670/$ – see front matter © 2012 Elsevier B.V. All rights reserved.ttp://dx.doi.org/10.1016/j.aca.2012.11.011

forms of cancer and various other serious negative health effects inhumans [2–4]. However, the toxicity of As depends heavily on itschemical environment, with the inorganic forms of As (As(III) andAs(V)) being the most toxic, followed by monomethylarsonic acid(MMA) and dimethylarsinic acid (DMA), while the other organic

forms of As are generally considered to be mostly non-toxic [4].Therefore, the potential toxicity of As depends not only on the totalAs concentration, but also on the species of As present in a givenfood sample [4].

lytica Chimica Acta 758 (2013) 28– 35 29

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Table 1Instrumental and separation conditions.

ICP-MS (Varian 820MS)Plasma gas flow Ar, 18.0 L min−1

Auxiliary gas flow Ar, 1.80 L min−1

Aerosol carrier Ar, 0.15 L min−1

Plasma power 1.38 kWSample uptake rate 0.8 mL min−1

Monitored signal 75As+, 56Fe+, 57Fe+, 65Cu+, 63Cu+,64Zn+, 66Zn+, 68Zn+, 51V+

IEC (Dionex GS50 gradient pump)Columns IonPac AG7 and IonPac AS7Column temperature 20 ◦CMobile phase flow rate 1.35 mL min−1

Mobile phase A 0.5 mmol L−1 HNO3, 1% MeOHMobile phase B 50 mmol L−1 HNO3, 1% MeOHGradient elution program 100% A, 3 min; 100% B, 2.5 minStabilization program for water 0.5 mol L−1 HNO3, 2 min; DDW,

N.S. Horner, D. Beauchemin / Ana

To develop an accurate risk assessment method, one must alsoonsider the bio-availability of toxic elements, as total concen-ration is not necessarily a good indicator of toxicity in humans.io-availability refers to the ability of an element to be absorbed

nto the systemic circulation system [5]. While bio-availabilitytudies have been shown to be the most accurate means of riskssessment [6], they remain both complex and time-consumingue to the need to use human or animals in the experiments7]. Therefore, studies measuring bio-accessibility, i.e. the amountf an element that is dissolved in the gastro-intestinal tract [8],re often performed as a more convenient alternative risk assess-ent method since bio-availability can only be smaller than or

qual to bio-accessibility [9,10]. In any case, the method of foodreparation, such as cooking and washing, can have a significant

mpact on bio-accessibility and must therefore also be considered11–13].

Numerous methods have been developed for determining theio-accessibility of elements in food samples. Most commonly usedre batch gastro-intestinal models that involve the sequential off-ine addition of artificial gastro-intestinal fluids to food samples14]. Although relatively simple, these batch methods fail to provideeal-time leaching data and have been shown to give differingio-accessibility results depending on the experimental methodsed [14]. Furthermore, many studies using the batch method haveeglected to include saliva as one of the leaching reagents, despitehe fact that it can be a significant source of leaching in manyamples [15–17]. In addition to the batch models, less commonlysed dynamic models also exists, which often involve a more com-lex experimental design [18–20]. Recently, a simple continuousn-line leaching method was developed for the determination ofio-accessible Zn and Pb in corn bran samples as well as As ineafood and rice samples [15–17]. This continuous on-line leach-ng method shows great potential for risk assessment, while alsoffering quick and easy access to real-time leaching data. It pro-ides several advantages over batch models as it involves shorterample preparation time and reduced risk of contamination due tohe minimal sample manipulation required. Furthermore, becauseresh reagent is constantly being pumped through the food samplesing the on-line leaching method, the dissolution equilibrium isriven to the right. Hence, the maximum amount of a toxic element

s leached, allowing for worst-case scenario risk assessment, and in shorter time than with batch methods.

In previous work, the bio-accessibility of As in white rice, bothooked and uncooked, and a rice flour certified reference mate-ial was determined using the on-line leaching method [16]. In thistudy, the bio-accessibility of some essential elements (Cu, Fe, V,n) and As in brown and white rice grown in California was deter-ined. The results were compared with those obtained using a

ypical batch method to ensure that they were similar. In both cases,lements were detected by inductively coupled plasma mass spec-rometry (ICP-MS), with H2 supplied through a collision reactionnterface (CRI) to mitigate the effect of polyatomic interferences onnalyte signal. This was followed by ion exchange chromatographyIEC) coupled to ICP-MS for the determination of the As speciesresent in the rice samples. Unlike previously published workhere only speciation analysis of the saliva leachate was performed

16], speciation analysis of the gastric juice leachate was also car-ied out because, in many food samples, As leached by gastric juiceccounted for a significant portion of the total bio-accessible frac-ion [15,16], and can thus not be neglected. The effect of washingice on the bio-accessibility of elements was also assessed usinghe on-line leaching method. To the best knowledge of the authors,

his is the first time that the effect of washing rice has been moni-ored in real time. Such information allowed the determination ofhe “ideal” washing time, when most of the As is removed whileetaining a significant portion of the essential elements. Finally,

and saliva matrix 6 minStabilization program for gastric

juice matrix0.5 mol L−1 HNO3, 4 min; DDW,6 min

As speciation analysis of both the washed As and the remainingbio-accessible As after washing was performed.

2. Experimental

2.1. Instrumentation

A Varian 820MS ICP-MS instrument (Mulgrave, Victoria,Australia) equipped with a Scott double-pass spray chamber, a con-centric nebulizer and a CRI was used for all analyses. For speciationanalysis, a DX600/BioLC liquid chromatography system was usedwith a GS50 gradient pump (Dionex, Oakville, Canada), an injectionvalve with a 50-�L injection loop, an IonPac AG7 guard column,and an IonPac AS7 (25-cm long, 4-mm diameter) anion exchangecolumn (all Dionex, Voisins le Bretonneux, France). PEEK tubing(0.17-mm internal diameter) was used to connect the end of theanalytical column with the nebulizer. The instrumental and sepa-ration conditions are summarized in Table 1.

During on-line leaching and speciation analysis, data acquisi-tion was done in time-resolved mode with three points per peak,one scan per replicate, a dwell time of 80,000 ms and 0.025 a.m.u.spacing. For the batch method and the analysis of digests, dataacquisition was done in steady state mode with 10-s integration.

2.2. Reagents

Artificial saliva was prepared with 6.8 g of KH2PO4 (ACS grade;Fisher Scientific, NJ, USA), 77 mL of 0.2 mol L−1 NaOH (ACS grade;BioShop, Burlington, Canada), diluting to 1 L using doubly deion-ized water (DDW) (18.2 M� cm−1) and finally adjusting the pH to6.5 using 0.2 mol L−1 NaOH. All DDW used in this work was puri-fied using an Arium Pro UV|DI water purification system (SartoriusStedim Biotech, Göttingen, Germany). Artificial gastric juice wasprepared by mixing 2.0 g of NaCl (ACS grade; BioShop, BurlingtonCanada), 3.2 g of pepsin (Sigma-Aldrich, Oakville, Canada), 7.0 mL ofsub-boiled HCl (ACS grade; Fisher Scientific, Ottawa, Canada), anddiluting to 1 L using DDW. Artificial intestinal fluid was preparedby adding 6.8 g of KH2PO4, 10 g of pancreatin (Sigma-Aldrich, St.Louis, USA), 77 mL of 0.2 mol L−1 NaOH, diluting to 1 L using DDWand finally adjusting the pH to 6.8. For the digestion of residues,sub-boiled HNO3 (ACS grade; Fisher Scientific, Ottawa, Canada) andH2O2 (J.T. Baker, Phillipsburg, USA) were used. All HNO3 and HCl

were purified prior to use by a DST-1000 Sub-Boiling DistillationSystem (Savillex, Minnetonka, USA).

Standard solutions were prepared from 1000 mg L−1 mono-element solutions (SCP Science, Baie d’Urfé, Québec, Canada). For

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peciation analysis, 1000 mg As L−1 standard stock solutions wereade of each species from the following reagents: arsenic (III)

xide (As(III)) (99.999%), arsenic (V) oxide (As(V)) (99.9%) (alllfa Aesar, Ward Hill, USA), disodium methyl arsenate (MMA)

97.5%) (ChemService, West Chester, USA), and cacodylic acidDMA) (≥98%) (Sigma–Aldrich, St. Louis, USA). All stock solutionsere then further diluted to 10 mg As L−1 and stored at 4 ◦C in theark. From these stock solutions, calibration standards were pre-ared daily. Sub-boiled HNO3, methanol (Fisher Scientific, Ottawa,anada) and DDW were used to prepare the mobile phases forpeciation.

Bags of long grain brown and white rice (Selection brand) wereurchased from a local grocery store and used as purchased. Bothame from a single source in California. The rice (either brown orhite) was cooked by adding 20 g of rice to 50 mL of boiling DDW

nd waiting 15 min. All water was absorbed into the rice during theooking procedure.

.3. CRI optimization

In order to reduce polyatomic interferences while minimiz-ng loss of sensitivity, optimization of the CRI was performed

hile monitoring the ratio of the 40Ar35Cl+ interference signalm/z = 75) to the signal of Ge+ (m/z = 74). This Ge isotope was useds a surrogate analyte because of the closeness of its mass-to-harge ratio to that of As. On-line mixing of gastric juice and

�g L−1 Ge solution was performed using a Y connector. The signalatio of m/z = 75 over m/z = 74 was continuously monitored whilencreasing the CRI hydrogen gas flow rate. At the optimal hydro-en gas flow rate of 85 mL min−1, analyte signal was significantlyeduced. However, the use of CRI was generally found to be nec-ssary in order to obtain accurate results for the analysis of gastricuice leachates, due to the relatively high chloride ion concentra-ion.

.4. On-line continuous leaching

The experimental procedure is depicted in Fig. 1. The continu-us leaching procedure was performed as described in a previoustudy [16], with only minor changes. Specifically, the length of theini-column was extended from 8 cm to 10 cm and the amount of

ample packed into the mini-column was increased from 0.2 g to.25 g. The mini-columns were indeed prepared by packing 0.25 gf rice wrapped in quartz wool into a PTFE tube (10-cm long, 3/15-n outer diameter, 1/8-in inner diameter). In addition, a quartz woollug was inserted at each end of each column. A blank column con-aining only quartz wool and no sample was also used. The artificialaliva, gastric juice and intestinal fluid were all maintained at 37 ◦Chuman physiological temperature) using a thermostatically con-rolled water bath. Saliva, followed by gastric juice, followed byntestinal fluid, was then sequentially pumped through the mini-olumn straight to the nebulizer of the ICP-MS instrument using

peristaltic pump. The leaching time was set to 5 min for saliva,0 min for gastric juice and 5 min for intestinal juice, after first con-rming that no additional leaching occurred beyond those times.he sum of the concentrations of an element leached by the threeastro-intestinal reagents was taken as the bio-accessible fraction.he leachates were monitored in time-resolved mode in order tobtain real-time leaching data. Hydrogen gas was also added to thekimmer cone of the CRI at the optimized flow rate of 85 mL min−1.xternal calibration was performed using flow injection, where the

tandard solutions and blank (prepared in each leaching reagent)ere injected through a 100-�L injection loop connected to a uni-

ersal automatic actuator (Anachem Ltd., Luton, England) into aarrier consisting of the matching leaching reagent (i.e. artificial

Chimica Acta 758 (2013) 28– 35

saliva, gastric juice or intestinal juice). Peak area was then used tocreate a four-point calibration curve, from which sample concen-trations were derived.

2.5. Batch method

The effectiveness of the on-line leaching method was confirmedthrough comparison with a standard batch method. For the latter,approximately 1 g of rice was placed in a centrifuge tube and 6 mL ofartificial saliva (at 37 ◦C) was added. The test tube was then shakenfor 10 min while being maintained at 37 ◦C and then centrifuged.The supernatant was decanted off so that it could later be ana-lyzed by ICP-MS and the process was repeated using gastric juiceand then intestinal fluid. However, a 2-h contact time was used foreach of the gastric juice and intestinal fluid, as opposed to 10 minfor saliva, in order to more accurately reflect contact times in thehuman body. All supernatants were quantitatively analyzed usinga 4-point external calibration and a blank prepared fresh daily ineach reagent. Additionally, internal standardization was performedthrough the on-line addition of 5 �g L−1 In solution through a Y-connector.

2.6. Mass balance

A mass balance was performed on all on-line leaching and batchresidues in order to ensure that the sum of the bio-accessiblefraction and that remaining in the residue was the same as thetotal concentration of that element in the sample. The residueswere digested by adding 2.5 mL of sub-boiled HNO3 and 0.5 mL ofH2O2, followed by heating to 50 ◦C for 1 h. The solution was thendiluted to 25 mL before analysis by ICP-MS. Total digestions of 1-grice aliquots were also carried out using the same procedure. Alldigestions were quantitatively analyzed using a 4-point externalcalibration and a blank prepared fresh daily in the same matrix asthe samples. Additionally, internal standardization was performedthrough the on-line addition of 5 �g L−1 In solution through a Y-connector.

2.7. Arsenic speciation analysis

Aliquots (4.0 mL) of saliva leachates (37 ◦C) were collected, fol-lowed by 4.0 mL of gastric leachates (37 ◦C), at a flow rate of0.8 mL min−1 from a packed mini-column off-line, by leaching dur-ing 5 min, as this was the time required by each of saliva and gastricjuice to release the maximal amount of As with on-line leaching.The saliva leachates were diluted fivefold, and the gastric juiceleachates were left undiluted before being analyzed by modifiedversions of a previously published speciation analysis method [16].Gradient elution using two HNO3 mobile phases (pH 3.3 and 1.1in 1% methanol) (program shown in Table 1) separated the fourAs species of interest in a single chromatographic run. Matrix-matched standards and blanks were also injected through the IECcolumn in order to create a 4-point external calibration curve (frompeak areas), which was used for the quantitative analysis of thesamples.

2.8. Washing

In order to monitor the effect of washing one’s rice with water,the same on-line leaching procedure was used as described ear-lier in Section 2.4, with the only modification being that roomtemperature DDW was pumped through the mini-column on-line

for 10 min and monitored by ICP-MS before sequentially pumpingthe three bodily fluids through the mini-column. The same pro-cedure as described in Section 2.7 was used to determine the Asspecies released by DDW as well as the remaining bio-accessible

N.S. Horner, D. Beauchemin / Analytica Chimica Acta 758 (2013) 28– 35 31

exper

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added gain of real-time leaching data.Although the total As concentrations in the two rice samples

in this study were significantly higher than that measured in a

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s released by saliva and gastric juice, except that 4.0 mL of DDWeachate (room temperature) was first collected (i.e. before begin-ing the saliva leaching) after being pumped through an off-lineini-column, and analyzed without dilution.

. Results and discussion

The on-line leaching method provides access to real-time leach-ng data, through continuous monitoring of analyte signal as aunction of time, resulting in what is referred to as an on-line leach-ng profile. Typical on-line leaching profiles for Zn, Cu and V inncooked brown rice by the three bodily fluids are shown in Fig. 2.imilar leaching profiles were obtained for other elements. In mostases, saliva resulted in the largest peak, followed by gastric juice,nd little to no peak with intestinal juice. In other words, salivaeleased the majority of the bio-accessible fraction of each element.his is consistent with the results obtained for As with a certifiedeference material of rice flour and a different white rice sample16].

The amount of each element leached by the artificial gastro-ntestinal reagents using the on-line leaching and batch methodsre compared in Table 2. In general, the two leaching methodsave similar results, within error. Furthermore, the portion releasedy each reagent was slightly different, with a somewhat greaterroportion of each element being released by gastric and intesti-al juice using the batch method than by on-line leaching. This

s likely in large part due to small amounts of saliva (or gastricuice) remaining in the container or being temporarily absorbedy the rice after centrifuging and decanting the supernatant. Thesemall amounts of reagent may contain significant concentrations oflements, thereby “contaminating” the following gastro-intestinaluid and resulting in a significant elevation of the observed leachedoncentration. In any case, cooking generally had little effect onio-accessibility in both the brown and white rice. For both con-inuous on-line leaching and the batch method, the sum of the

io-accessible fraction and that remaining in the residue gener-lly agreed with the concentration found through total digestiont the 95% confidence level using a Student’s t-test. Hence, the on-ine leaching method provides similar results as obtained through

imental set-up used in this work.

the batch method, but in a much shorter time frame, and with the

0 50 100 150 200 250 300Time (s)

Fig. 2. Continuous on-line leaching profile of uncooked white rice using saliva (A),gastric juice (B) and intestinal fluids (C).

32N

.S. H

orner, D

. Beauchem

in /

Analytica

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758 (2013) 28– 35

Table 2Concentrations in ng g−1 of leached and total As, Cu, Fe, V and Zn obtained by the on-line leaching and batch methods for uncooked white rice, cooked white rice, uncooked brown rice, cooked brown rice.

Analyte Sample Leaching method Saliva Gastric juice Intestinalfluid

Bio-accessiblefraction

Bio-accessiblefraction + residue

Expectedb Student’st found

Student’s ttable value

As Uncooked brown On-line (n = 5) 120 ± 20 8 ± 4 0.5 ± 0.4 130 ± 20 600 ± 100 500 ± 100 1.08 2.26Batch (n = 5) 90 ± 10 16 ± 8 2.9 ± 0.4 110 ± 20 600 ± 100 500 ± 100 1.26 2.26

Uncooked white On-line (n = 6) 100 ± 10 4 ± 2 0.39 ± 0.05 100 ± 10 600 ± 200 560 ± 70 0.25 2.23Batch (n = 5) 100 ± 30 16 ± 8 3 ± 2 120 ± 30 620 ± 90 560 ± 70 1.26 2.26

Cooked browna On-line (n = 6) 110 ± 13 2.0 ± 0.5 1.2 ± 0.3 110 ± 10 610 ± 20 500 ± 100 0.78 2.55Batch (n = 5) 90 ± 40 8 ± 5 9 ± 4 100 ± 40 540 ± 50 500 ± 100 1.56 2.48

Cooked whitea On-line (n = 6) 110 ± 20 2.7 ± 0.3 0.7 ± 0.7 110 ± 30 700 ± 100 560 ± 70 3.77 2.23Batch (n = 5) 70 ± 20 2 ± 1 3 ± 2 80 ± 20 630 ± 90 560 ± 70 1.45 2.26

Cu Uncooked brown On-line (n = 5) 400 ± 100 150 ± 70 n.d.c 600 ± 100 1600 ± 300 2100 ± 400 2.23 2.31Batch (n = 5) 200 ± 90 200 ± 40 50 ± 20 400 ± 100 2500 ± 500 2100 ± 400 0.54 2.31

Uncooked white On-line (n = 6) 170 ± 90 100 ± 40 15 ± 6 300 ± 100 2000 ± 200 2100 ± 300 0.72 2.31Batch (n = 5) 210 ± 40 200 ± 50 80 ± 20 490 ± 60 2300 ± 500 2100 ± 300 1.06 2.31

Cooked browna On-line (n = 6) 120 ± 40 300 ± 80 n.d. 380 ± 90 1700 ± 400 2100 ± 400 1.45 2.31Batch (n = 5) 520 ± 30 300 ± 100 n.d. 800 ± 100 1700 ± 400 2100 ± 400 1.30 2.26

Cooked whitea On-line (n = 6) 250 ± 30 300 ± 100 2 ± 3 600 ± 100 2400 ± 500 2100 ± 300 1.11 2.36Batch (n = 5) 400 ± 90 500 ± 100 100 ± 100 1000 ± 200 2000 ± 300 2100 ± 300 0.40 2.26

Fe Uncooked brown On-line (n = 5) 1100 ± 400 400 ± 100 n.d. 1500 ± 500 9900 ± 600 12,000 ± 2000 1.28 2.72Batch (n = 5) 500 ± 200 1600 ± 600 40 ± 50 2200 ± 700 10,000 ± 2000 12,000 ± 2000 1.29 2.31

Uncooked white On-line (n = 6) 500 ± 200 300 ± 200 8 ± 9 800 ± 300 5900 ± 800 6000 ± 2000 0.47 2.55Batch (n = 5) 240 ± 70 900 ± 300 n.d. 1100 ± 300 4000 ± 1000 6000 ± 2000 1.30 2.31

Cooked browna On-line (n = 6) 500 ± 200 500 ± 200 n.d. 1000 ± 300 15,000 ± 5000 12,000 ± 2000 1.1 2.31Batch (n = 5) 700 ± 200 1300 ± 200 200 ± 100 2200 ± 300 10,000 ± 3000 12,000 ± 2000 0.93 2.26

Cooked whitea On-line (n = 6) 880 ± 90 700 ± 200 10 ± 20 1500 ± 200 5900 ± 800 6000 ± 2000 0.48 2.56Batch (n = 5) 290 ± 60 700 ± 300 60 ± 50 1000 ± 300 5000 ± 1000 6000 ± 2000 0.89 2.26

V Uncooked brown On-line (n = 5) 9 ± 2 4 ± 2 n.d. 13 ± 3 16 ± 4 7 ± 3 3.52 2.31Batch (n = 5) 1 ± 1 5.2 ± 0.7 n.d. 6 ± 1 8 ± 2 7 ± 3 1.10 2.31

Uncooked white On-line (n = 6) 6 ± 5 3 ± 1 n.d. 10 ± 5 11 ± 6 9 ± 2 0.51 2.56Batch (n = 5) 0.8 ± 0.6 6.3 ± 0.6 n.d. 7.0 ± 0.8 12 ± 5 9 ± 2 1.12 2.31

Cooked browna On-line (n = 6) 4 ± 3 1 ± 2 n.d. 5 ± 4 6 ± 4 7 ± 3 0.57 2.31Batch (n = 5) 1 ± 1 0.3 ± 0.7 1 ± 1 3 ± 2 7 ± 4 7 ± 3 0.13 2.26

Cooked whitea On-line (n = 6) 2.2 ± 0.3 11 ± 8 n.d. 13 ± 8 13 ± 8 9 ± 2 0.94 2.64Batch (n = 5) 2 ± 2 1 ± 2 1.4 ± 0.9 5 ± 3 7 ± 3 9 ± 2 1.09 2.26

Zn Uncooked brown On-line (n = 5) 1400 ± 500 400 ± 200 400 ± 100 2100 ± 500 14,000 ± 1000 13,000 ± 4000 0.35 2.70Batch (n = 5) 800 ± 400 3000 ± 1000 300 ± 100 4000 ± 1000 17,000 ± 5000 13,000 ± 4000 1.78 2.31

Uncooked white On-line (n = 6) 900 ± 200 1100 ± 900 3 ± 7 2000 ± 900 17,000 ± 1000 15,000 ± 3000 1.32 2.56Batch (n = 5) 2100 ± 500 2100 ± 400 100 ± 200 4400 ± 700 19,000 ± 6000 15,000 ± 3000 1.29 2.31

Cooked browna On-line (n = 6) 900 ± 300 900 ± 500 n.d. 1800 ± 500 13,000 ± 2000 13,000 ± 4000 0.26 2.54Batch (n = 5) 2000 ± 500 4000 ± 2000 500 ± 600 6000 ± 2000 11,000 ± 4000 13,000 ± 4000 1.00 2.26

Cooked whitea On-line (n = 6) 3000 ± 1000 4600 ± 200 200 ± 400 8000 ± 1000 9000 ± 1000 15,000 ± 3000 3.89 2.52Batch (n = 5) 5000 ± 2000 5000 ± 2000 n.d. 10,000 ± 3000 11,000 ± 3000 15,000 ± 3000 2.03 2.26

a Concentrations of cooked rice reported per gram of dry rice.b Expected values obtained through total digestion of dry rice.c Not detected.

N.S. Horner, D. Beauchemin / Analytica

Fig. 3. Chromatogram for a standard solution containing 5 �g L−1 of each As speciesin fivefold diluted saliva (A) and a fivefold diluted saliva leachate of uncooked brownr

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the additional salts present in saliva not being expected to greatly

ice (B).

revious study on white rice of a different source [16], theyonetheless fall within the range of 90 ± 4 ng g−1 to 850 ± 30 ng g−1

eported by another study for 31 different rice samples [21]. Despitehe high total As concentration, only a relatively small As concen-ration was found to be bio-accessible, which is in contrast to arevious study by the authors where approximately 90% of the Asas bio-accessible in a white rice sample from a different source

16]. This is not surprising because the bio-accessibility of As inice is known to vary greatly between samples [21,22]. Althoughhe present rice contained 5 times as much As as the previous whiteice, the same total amount of As was bio-accessible. This highlightshe importance of performing risk assessment by determining bio-ccessible As instead of simply monitoring total As concentrations.n general, the bio-accessibility of most elements was less than 50%,

ith a few exceptions.The speciation analysis of As was carried out using a modified

ersion of the gradient program previously optimized by Dufaillyt al. [23]. After confirming that the As in the rice samples wasnly present in the form of As(III), MMA, DMA and As(V), the gradi-nt program was shortened to only the first 5.5 min, as those fourpecies eluted within the first 5 min of the program. As observedreviously [16], injection of saliva leachates often resulted in co-lution of As(III) and MMA, unless first diluted with DDW. However,he dilution could be reduced from 10-fold to fivefold and stillrovide good resolution of the two peaks (Fig. 3), as long as theolumn was cleaned regularly with 2 mol L−1 HNO3.

Furthermore, the same elution program could effectively sepa-

ate the four As species of concern in both the saliva leachate andhe gastric juice leachate. In the latter case, a 5th peak was observed,hich eluted during the stabilization program with a retention

Chimica Acta 758 (2013) 28– 35 33

time of approximately 450 s, and was attributed to the elution ofchloride (observed as 40Ar35Cl+), which is present in significant con-centration in gastric juice. The attribution of this peak was madeby injecting a saliva blank spiked with NaCl, which resulted in asingle peak at the same retention time as for the 5th peak in gas-tric juice leachates. The fact that chloride was effectively separatedfrom the As species by the gradient elution program meant thathigh sensitivity ICP-MS settings could be used for speciation anal-ysis, as opposed to CRI settings. This was particularly importantgiven the very low concentrations of As found in the gastric juiceleachate. However, because the background signal would climbover time due to increasing 40Ar35Cl+ interference from the highchloride concentration in gastric juice, the stabilization programwas modified by increasing the 0.5 mol L−1 HNO3 rinsing time from2 min to 4 min prior to injecting gastric juice leachates so as tomore effectively remove chloride from the IEC system. Alterna-tive solutions to the climbing background, which would have beenmore time-efficient, such as diluting the gastric juice leachate tolower the chloride concentration or using CRI, were not practicalbecause of the concurrent degradation in detection limit that wouldhave resulted, which would then have been insufficient. The detec-tion limits for the As species were between 0.02 and 0.06 ng g−1

in both the gastric juice and saliva matrices, which is similar tothose reported in a previous study using the same instrument[16].

The results of the speciation analysis of both the saliva leachatesand the gastric juice leachates for the brown and white rice, bothcooked and uncooked, are summarized in Table 3. The sum of theconcentrations of As species in the saliva and gastric juice leachatesobtained through speciation analysis was compared using a Stu-dent’s t-test with the total As concentration obtained by on-lineleaching with each reagent to verify mass balance. The sum of theconcentrations of As species agreed with the total amount leachedby the saliva and gastric juice at the 95% confidence level for allsamples, except in the case of the gastric juice leachate of uncookedwhite rice. In this latter case, a two-sample Zscore of 3.31 suggeststhat the sample is an outlier. In any case, the majority of bio-accessible As was in the form of DMA and As(V) in both uncookedrice samples, whereas the two most prominent species were As(III)and As(V) in cooked rice. Consequently, in these samples, cookingthe rice may actually increase toxicity. This increase in As(III) con-centration from the cooking process is consistent with a similarobservation obtained from a white rice sample used in a previousstudy [16]. These results indicate that the cooking process seemsto facilitate a species change from one or both of As(V) and DMA toAs(III). However, a much larger variety of samples would need to betested in order to determine how general this observation is. Also,analysis should be repeated immediately after cooking to elimi-nate the possibility that species transformation occurred while thecooked rice sat in the mini-column (sometimes for several days)prior to analysis.

The results of on-line leaching with DDW followed by the threebodily fluids are presented in Table 4. Only the uncooked rice sam-ples were used, as people generally only wash their rice beforecooking. With only a few exceptions, the sum of the concentra-tion of elements leached by DDW and by three reagents as well asthat remaining in the residue agrees with the total concentrationobtained through full digestion for both the uncooked brown riceand the uncooked white rice at the 95% confidence level using a Stu-dent’s t-test. In general, leaching with DDW reduced the amountleached by saliva to close to nothing. This is unsurprising, as theartificial saliva consists mostly of DDW, at near neutral pH (pH 6.5),

affect its leaching ability. The minor amount of elements leachedby saliva following leaching with DDW is likely due to the slightdifference in pH between DDW and artificial saliva and to the fact

34 N.S. Horner, D. Beauchemin / Analytica Chimica Acta 758 (2013) 28– 35

Table 3Concentrations in ng g−1 obtained for the speciation analysis of bio-accessible As in white and brown rice, both cooked and uncooked.

Sample Leachingreagent

As(III) MMA DMA As(V) Sum of Asspecies

Total As leached byreagenta

Student’s t-testfound

Student’s t-testtable value

Uncooked brown (n = 5)Saliva 6 ± 6 0.5 ± 0.8 50 ± 20 90 ± 20 140 ± 30 120 ± 20 0.55 2.26Gastric 0.9 ± 0.6 0.2 ± 0.3 8 ± 5 5 ± 2 15 ± 5 8 ± 4 1.22 2.26

Uncooked white (n = 5)Saliva 6 ± 10 7 ± 8 70 ± 40 90 ± 40 170 ± 60 100 ± 10 2.71 2.73Gastric 2 ± 3 n.d.b 8 ± 5 7 ± 6 17 ± 9 4 ± 2 3.31 2.71

Cooked brown (n = 4)Saliva 60 ± 20 5.2 ± 0.8 13 ± 8 60 ± 12 140 ± 20 110 ± 13 1.46 2.31Gastric 2 ± 2 0.04 ± 0.04 0.2 ± 0.2 2 ± 1 4 ± 3 2.0 ± 0.5 1.63 3.13

Cooked white (n = 5)Saliva 40 ± 20 3 ± 1 39 ± 6 40 ± 10 130 ± 20 110 ± 20 0.49 2.23Gastric 2 ± 1 0.06 ± 0.02 0.6 ± 0.9 2 ± 1 5 ± 1 2.7 ± 0.3 2.55 2.69

a Obtained by independent total analysis of saliva and gastric leachate using on-line leaching method.b Not detected.

Table 4Concentrations in ng g−1 of washed, leached and total As, Cu, Fe, V and Zn obtained by the on-line leaching method for uncooked white rice and uncooked brown rice.

Analyte Sample DDW Saliva Gastric juice Intestinalfluid

Bio-accessiblefraction

Washed + bio-accessiblefrac-tion + residue

Expecteda Student’st-testfound

Student’st-test tablevalue

As Uncooked brown (n = 4) 80 ± 30 0.1 ± 0.1 3 ± 1 n.d. b 3 ± 1 600 ± 100 500 ± 100 1.33 2.31Uncooked white (n = 5) 70 ± 10 0.8 ± 0.5 8 ± 3 n.d. 9 ± 3 610 ± 60 560 ± 70 1.21 2.26

Cu Uncooked brown (n = 4) 500 ± 200 5 ± 5 100 ± 60 2 ± 3 110 ± 60 2300 ± 400 2100 ± 400 0.84 2.26Uncooked white (n = 5) 400 ± 200 11 ± 7 180 ± 70 3 ± 4 190 ± 70 2500 ± 900 2100 ± 300 0.99 2.31

Fe Uncooked brown (n = 4) 2000 ± 1000 20 ± 30 500 ± 400 2 ± 1 500 ± 400 10,000 ± 1000 12,000 ± 2000 1.04 2.26Uncooked white (n = 5) 800 ± 300 80 ± 70 700 ± 100 n.d. 700 ± 100 6000 ± 1000 6000 ± 2000 0.72 2.43

V Uncooked brown (n = 4) 25 ± 18 n.d. 5 ± 5 n.d. 5 ± 5 30 ± 20 7 ± 3 2.55 2.53Uncooked white (n = 5) 6 ± 5 0.2 ± 0.4 4 ± 4 n.d. 4 ± 4 14 ± 6 9 ± 2 1.73 2.55

Zn Uncooked brown (n = 4) 900 ± 300 20 ± 10 700 ± 400 n.d. 700 ± 400 18,000 ± 4000 13,000 ± 4000 1.67 2.26Uncooked white (n = 5) 900 ± 200 20 ± 20 1400 ± 400 21 ± 9 1400 ± 400 15,000 ± 2000 15,000 ± 3000 0.01 2.31

a Concentrations of cooked rice reported per gram of dry rice.b Not detected.

Table 5Concentrations in ng g−1 obtained for the speciation analysis of white and brown rice both cooked and uncooked with a washing step.

Sample Leachingreagent

As(III) MMA DMA As(V) Sum of As species Total Asleacheda

Student’s t-testfound

Student’s t-testtable value

Uncooked brown (n = 5) DDW 8 ± 6 2 ± 2 10 ± 4 120 ± 30 140 ± 30 80 ± 30 1.49 2.26Saliva n.d. b n.d. n.d. 1 ± 1 1 ± 1 0.1 ± 0.1 1.85 4.56Gastric 1.7 ± 0.6 n.d. 0.4 ± 0.8 5 ± 3 7 ± 3 3 ± 1 2.83 4.06

Uncooked white (n = 5) DDW 8 ± 4 5 ± 4 30 ± 10 80 ± 10 120 ± 20 80 ± 10 1.76 2.26Saliva n.d. n.d. n.d. 0.6 ± 0.6 0.6 ± 0.6 0.8 ± 0.5 0.68 2.26Gastric 3 ± 3 0.6 ± 0.6 0.2 ± 0.4 10 ± 5 13 ± 6 8 ± 3 1.49 2.26

ine leaching method.

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hat saliva is maintained at 37 ◦C whereas leaching with DDW wasone at room temperature. Other studies have included digestivenzymes in their artificial saliva, which could potentially result in

more significant concentration of arsenic being leached by salivafter DDW leaching [15,24].

The on-line leaching profiles revealed that the time required toelease the maximum amount of each element with DDW variedetween elements and samples. In general, the release time was

onger for elements in high concentration than for elements at lowoncentrations (illustrated with DDW leaching profiles of As andn in Fig. 4). The fact that As was present at a lower concentrationhan Zn, Cu and Fe can be used to determine an “ideal” washingime, when most of the As is released but a significant amount ofn, Cu and Fe remains. Given that the As signal returned to baseline

ithin 100–150 s of DDW leaching, whereas Zn, Cu and Fe required

50–500 s to return to baseline, an “ideal” washing time of 150 should be used to maximize extraction of As, while minimizing theoss of Zn, Cu and Fe.

0 100 200 300 400 500Time (s)

Fig. 4. Continuous on-line leaching profile of As and Zn in uncooked white rice usingDDW.

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[25] Joint FAO/WHO Expert committee for Food additives, Evaluation of CertainFood Additives and Contaminants, 1989, pp. 27–38.

[26] M. Bae, C. Watanabe, T. Inaoka, M. Sekiyama, N. Sudo, M.H. Bokul, R. Ohtsuka,Lancet 7 (2002) 1839–1840.

N.S. Horner, D. Beauchemin / Ana

The speciation analysis results of the leaching with H2O followedy saliva and gastric juice are shown in Table 5. They all agree withhe on-line leaching results for all leachates at the 95% confidenceevel using a Student’s t-test. Including a H2O washing step reducedhe total inorganic arsenic concentration in the uncooked rice sam-les by close to 90%. These results suggest that simply washingne’s uncooked rice for a few minutes prior to consumption canignificantly reduce the potential toxicity of As in the rice.

. Conclusions

The Food and Agriculture Organization/World Health’s provi-ional tolerable daily intake (PTDI) of inorganic arsenic in rice is.1 �g kg−1 of body weight per day [25]. In this study, although

high total concentration of As was present in the rice sam-les, As bio-accessibility was quite low, making the rice sampleson-toxic to most demographics, with the exception of peopleho consume rice in extremely large quantities, or cook their rice

n As contaminated water [26]. These results highlight the facthat bio-accessibility must be considered in order to obtain anccurate measure of the potential harm to humans. In this work,he addition of a washing step to the on-line leaching methodas shown to provide significant extra health safety information.

ndeed, using the real-time leaching data obtained through on-ine leaching, an “ideal” washing time, which minimizes the lossf essential elements while maximizing the release of arsenic,ould be determined. The results also highlight the effectivenessf the on-line leaching method in comparison to the batch method,s it allows for faster sample preparation and analysis, whilelso providing valuable real-time leaching data. A comparison ofesults obtained in this work and previous work demonstrateshat both the total As concentration and fraction of bio-accessibles in rice can vary largely between samples. Finally, this workemonstrated that As speciation analysis can easily be adjustedo include DDW and gastric juice leachates in addition to salivaeachates in order to provide a more comprehensive analysis ofhe As species in the bio-accessible fraction of rice. Future workill focus on the application of the method to a broader range

f samples, as well as the determination of an ideal washingemperature.

cknowledgement

Funding from the Natural Sciences and Engineering Researchouncil of Canada is gratefully acknowledged.

Chimica Acta 758 (2013) 28– 35 35

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