A non-targeted metabolomic approach to identify food markers to support discrimination between organic and conventional tomato crops

In the last decade, the consumption trend of organic food has increased dramatically worldwide. However, the lack of reliable chemical markers to discriminate between organic and conventional products makes this market susceptible to food fraud in products labeled as “organic”.

crops

María Jesús Martínez Bueno, Francisco José Díaz-Galiano, Łukasz Rajski, Víctor Cutillas,

Amadeo R Fernández-Alba∗

University of Almería, Department of Physics and Chemistry, Agrifood Campus of International Excellence (ceiA3), Ctra Sacramento s/n, La Ca˜ nada de San

Urbano, 04120, Almería, Spain

a r t i c l e i n f o

Article history:

Received 7 November 2017

Received in revised form 26 February 2018

Accepted 1 March 2018

Available online 3 March 2018

Keywords:

Fingerprint

Authenticity

Natural food components

Pesticides

HRAMS

IRMS

a b s t r a c t

Inthelastdecade,theconsumptiontrendoforganicfoodhasincreaseddramaticallyworldwide How-ever,thelackofreliablechemicalmarkerstodiscriminatebetweenorganicandconventionalproducts makesthismarketsusceptibletofoodfraudinproductslabeledas“organic”.Metabolomicfingerprinting approachhasbeendemonstratedasthebestoptionforafullcharacterizationofmetabolome occur-ringinplants,sincetheirpatternmayreflecttheimpactofbothendogenousandexogenousfactors

Inthepresentstudy,advancedtechnologiesbasedonhighperformanceliquid chromatography-high-resolutionaccuratemassspectrometry(HPLC-HRAMS)hasbeenusedformarkersearchinorganicand conventionaltomatoesgrowningreenhouseundercontrolledagronomicconditions.Thescreeningof unknowncompoundscomprisedtheretrospectiveanalysisofalltomatosamplesthroughoutthe stud-iedperiodanddataprocessingusingdatabases(mzCloud,ChemSpiderandPubChem).Inaddition,stable nitrogenisotopeanalysis(␦15N)wasassessedasapossibleindicatortosupportdiscriminationbetween bothproductionsystemsusingcrop/fertilizercorrelations.Pesticideresidueanalyseswerealsoapplied

asawell-establishedwaytoevaluatetheorganicproduction.Finally,theevaluationbycombined chemo-metricanalysisofhigh-resolutionaccuratemassspectrometry(HRAMS)and␦15Ndataprovidedarobust classificationmodelinaccordancewiththeagriculturalpractices.Principalcomponentanalysis(PCA) showedasampleclusteringaccordingtofarmingsystemsandsignificantdifferencesinthesample pro-filewasobservedforsixbioactivecomponents(L-tyrosyl-L-isoleucyl-L-threonyl-L-threonine,trilobatin, phloridzin,tomatine,phloretinandechinenone)

©2018TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense

(http://creativecommons.org/licenses/by/4.0/)

1 Introduction

∗ Corresponding author.

E-mail address: amadeo@ual.es (A.R Fernández-Alba).

year

https://doi.org/10.1016/j.chroma.2018.03.002

0021-9673/© 2018 The Authors Published by Elsevier B.V This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ).

2 Experimental section

Switzerland)

mea-surements

parti-Table 1

Detailed information on the tomato samples produced under controlled agronomic

conditions, crop system, farms, fertilisation and plant protection carried out in this

study.

Crop system Manure Fertilizer Pest control # samples Name

Conventional Conventional Mineral Pesticides 7 C

clesizeofabout1mm.Driedtomatopowdersamples(0.5±0.01g)

wereweighedina50mLpolypropylenecentrifugetubeandthen

2␮Lofa10mg/Lmethanolicinternalstandardsolutionwasadded

(dichlorvos-d6).Next,thetomatoes wererehydrated by adding

0.5mLofultrapurewater,andthemixturewasvortexedfor30s

Thetubeswerethenautomaticallyshakenfor5min,afterthe

addi-tion5mLofmethanol.Afterthat,0.5gMg2SO4 (anhydrous)plus

0.25gNaClwereaddeddirectlytoeachtubeandthemixturewas

shakenagain(automatically)for5moremin.Finally,a

centrifuga-tionstep(3500rpm/1730×g,5min)wasperformed,and0.5mLof

thesupernatantwasdilutedwith0.5mLofultrapurewater

Sam-pleswerestoredat−20◦CuntilanalysisbyLC-Q-Orbitrap-MS.

2.3 HRAMSanalysis

Toevaluatethedifferencesbetweenorganicandconventional

productionsystems,anon-targetedanalysiswasappliedusingan

LC-ESI-Q-Orbitrap.FortheLCseparation,UHPLCDionexTM

Ulti-mate3000(ThermoScientificTM,SanJose,USA)wasused.Mobile

phaseAwas98%waterand2%methanolwhereasmobilephase

Bwas98%methanoland2%water;bothmobilephasescontained

5mMofammoniumformateand0.1%formicacid.Separationwas

carriedoutonaPhenomenexLunaC8column(mobilephaseflow:

350␮L/min).Thelength,diameterandparticlesizewere100mm,

2.0mmand3␮m,respectively.Thecolumnwasthermostatedat

30◦C.Themobilephasegradientstartedform100%ofmobilephase

Aandmaintainedfor1min,from1to2min,theamountofmobile

phaseBincreasedto30%,from2to3minto50%,from3to11min

to100%.100%ofBwasmaintaineduntil14min.Followingthis,the

mobilephasewaschangedto100%Aandmaintainedover3minfor

re-equilibration.Theinjectionvolumewas10␮L.Theautosampler

wasthermostatedat10◦C

AQ-Orbitrap(ThermoScientific,Bremen,Germany)mass

spec-trometerwasequippedwithHeatedElectrosprayIonizationSource

(HESIII).TheHESIparametersinpositivepolaritywereasfollows:

sheathgas flow rate:40;auxiliary gasflow rate: 5;sweepgas

flowrate:1;sprayvoltage:3.00kV;capillarytemperature:280◦C;

S–lensRFlevel:55.0;heatertemperature:350◦C.Theinstrument

wasoperatedinfullscan/allionfragmentationMS2(AIF).AIFisan

acquisitionmodeinwhichallprecursorionsarefragmented

with-outapreselectioninthequadrupole.Fragmentationisobtained

with the higher energy collision-induced dissociation (HCD) cell,

locatedatthefarside ofthequadrupoleiontrap“C-trap”

Dur-ingfillingoftheHCDcollisioncell,theenergycanbesettostep

betweenvaluesatspecifiedpercentvaluesaroundthechosen

mid-dleenergyregardlessoftheion’scharacteristics.Theparametersof

fullscananalysiswereasfollows:scanrange74−1100m/z,

resolu-tion70,000FWHMandautomaticgaincontrol(AGC)target1×106

AGCisusedtoregulatethetotalnumberifionscollectedinthe

C-trapbeforebeinginjectedintotheorbitrapforanalysis.The

max-imumioninjectiontime(maxIT)wassetto‘AUTO’,Parametersof

“AllIonFragmentationMS2mode”wereasfollows:resolution70

000FWHM,collisionenergyCE30V,AGCtarget1×106,maxIT

auto,scan range74–1100m/z.Anexternalmasscalibrationand

quadrupolecalibration were carried out daily, using a mixture

ofn−butylamine,caffeine,Ultramark1621andMet-Arg-Phe-Ala

(MRFA)

2.4 IRMSanalysis Driedtomato powder samples(2±0.1g) were weighedinto tincapsules.Nitrogenisotopecompositionwasdeterminedusing

aFlashEA1112elementalanalyzercoupledtoa Finnigan Delta-plusisotoperatiomassspectrometer(ThermoScientific,Bremen, Germany) Allsampleswere analyzed in duplicate, and forthe majority of samples the absolutedifference between duplicate measurementswas<0.2‰.Eachbatchofsamplesincluded repli-cateanalysesofthein-housestandard,IAEA-N-1(␦15N=+0.4‰) and IAEA-N-2 (␦15N=+20.3‰), which was used for the drift correctionofrawanalyticalmeasurementdata.Thelong-term per-formanceofthemassspectrometerwasmonitoredbyanalysisofa secondaryreferencematerial,acetanilide(␦15N=±0.15‰),which wasincludedwitheverybatchofsamples.Nitrogenisotoperatios werereportedwithrespecttoairnitrogen

2.5 Dataprocessingandchemometricanalysis CompoundDiscoverersoftwareversion2.1(ThermoScientific)

incombinationwithlibrarysearchingwastheworkflowusedto identifypotentialmarkercompounds.Thistoolallowsautomatic analytedetectionbasedonthepresenceoftheexactmassof pre-cursorions,withamasstoleranceof5ppm.Toreducechemical interferencesfromthematrix,amasstoleranceforalignmentof

5ppm,anintensitytoleranceof30%,a totalintensitythreshold

of1×105,amaximumshiftof0.5minandasignal-to-noise(S/N) thresholdof10werethefiltersset

In a second step,the datawere manuallyprocessed forthe comprehensiveidentificationofchemicalmarkers.The identifica-tionofeachcompoundwasbasedontheacquisitionofatleast3 diagnosticions(oneprecursorionandtwo fragmentions) with

amassaccuracy<5ppm.Forthat,Xcalibur4.0,MassFrontier7.0 and TraceFinder4.1 software’s(ThermoScientific) werefurther employedtodatareviewandcheckthediagnosticionsobtained

inMSandMS2spectra

Finally,chemometrictoolswereemployedfortheprocessingof

MSand␦15NdataPrincipalcomponentanalysis(PCA)wasusedto differentiatethestatisticalsignificancebetweenfarmingsystems ThestatisticalanalyseswereperformedusingRsoftware(version 3.3.3)

2.6 Methodvalidation RigorousvalidationassaysaccordingtoSANTE/11945/2015and ISO/IEC 17025:2005Guidelines wereperformed toensure high qualityanalyticalmeasurements[26,27].Therefore,aftera

evaluated

3 Results and discussion

<www.metlin.scripps.edu>

Table2,threediagnosticions(oneprecursorionandatleasttwo

Table 2

Natural food components (NFCs) identified as markers in tomatoes by HRAMS.

Rt Accurate mass

value [M+H] +

Proposed formula [M+H] +

Mass deviation a (ppm)

Accurate mass value (m/z)

Proposed formula Mass deviation a

(ppm)

Identified compounds

L-tyrosyl-L- isoleucyl-L-threonyl-L-threonine b

277.1547 C 15 H 21 N 2 O 3 −2.8 221.1132 C 8 H 17 N 2 O 5 −3.3

185.0420 C 6 H 10 O 5 Na −0.2

740.4580 C 39 H 66 NO 12 −1.4 578.4051 C 33 H 56 NO 7 −1.1 416.3523 C 27 H 46 NO 2 −1.5

Rt: retention time.

a Values reported in the worst case.

b marker tentatively identified.

c marker identified with the injection of the reference standard.

Fig 1.Comparison of the spectral obtained for trilobatin in an organic tomato sample using both acquisition modes (AIF vs PRM) by HRAMS.

Table 3

Method validation Results.

Name Matrix Effect (%) Inter/intra-day (R.S.D, %) Rec (%, ±␴) LOD (␮g/kg DW) LOQ (␮g/kg DW) MDL (␮g/kg FW) MQL (␮g/kg FW)

Inter/intra-day:repeatability/reproducibility of the instrumental method (R.S.D,%);Rec:recovery average values (n = 6);␴:dispersion from the average recovery values;

LOQ:limit of quantification;LOD:limit of detection;DW:dry weight;MQL:method quantification limit;MDL:method detection limit,FW:fresh weight.

a Matrix effect evaluated using one of the fragment ions (578.4051 for tomatine; 398.3410 for tomatidine).

available

samples

satisfac-tory

Table 4

Estimated concentration ranges and mean concentrations of the markers identified in organic and conventional tomato samples during a full harvest cycle (␮g/kg FW).

a compounds semi-quantified with catechin as standard.

b compounds semi-quantified with phloridzin as standard.

c compounds semi-quantified with tomatidine as standard.

Table4showstheconcentrationrangesandmean

literature

Fig 2. Seasonal trend corresponding to a complete farming campaign for all bioactive compounds identified as markers in organic tomato crops by HRAMS.

Table 5

Pesticide residues levels (␮g/kg FW) found in conventional and organic tomato samples, chemical class and main use.

Pesticide Chemical class Main use Sample

type

MRLs in Tomato (␮g/kg)

Concentration levels in samples (␮g/kg FW) Positive

samples

Spinosad: sum of spinosyn A + D; C: conventional tomatoes; O: organic tomatoes; MRL: Maximun residue limit.

Bycontrast,onlyonepesticide(spinosad)wasdetectedinthe

organicallygrowntomatoes.Spinosadisanovelmode-of-action

insecticide derived from a family of natural products obtained

from the fermentation of Saccharopolyspora spinosa According

totheRegulation(EC) No834/2007,its usein organic

produc-tionisallowed[4 Thegreaterconcentrationsoftheinsecticide

appli-cations

Table 6

␦ 15 N values found in organic and conventional tomato grown in greenhouse under

controlled agronomic conditions during a complete farming campaign.

␦ 15 N (‰) – Organic 15.7 15.3 13.5 11.8 11.7 11.7 9.8

␦ 15 N (‰) – Conventional 6.7 7.5 4.9 2.5 5.2 5.0 4.5

fertilizers.Inaccordancewithpreviouslypublishedscientific

stud-ies,tomatoesfromorganicproductionshowedhigher␦15Nvalues

(+9.8to+15.7‰)thanthosetomatoesgrownusingsynthetic

fer-tilizers,suchaspotashandammonia(+2.5to+7.5‰).Therefore,

inviewoftheseresultsitispossibletothinkthat␦15Ndataare

appropriatefordistinguishingtheuseoforganicversussynthetic

fertilizers,and thusprovidea linkagetotheproductionsystem

However,areliablethresholdcouldnotbeestablishedafterafull

harvestcycle.Batemanetal.[34]evaluatedorganicand

Fig 3. PCA graphs employing software R using only markers’ HRAMS data (A) and (C); and including HRAMS & IRMS data (B) and (D) PCs: Number of principal components

4 Conclusions

Acknowledgements

Appendix A Supplementary data

002

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