Dataset of organic sample near infrared spectra acquired on different spectrometers

ContentslistsavailableatScienceDirect

Data

in

Brief

journalhomepage:www.elsevier.com/locate/dib

Data

Article

Dataset

of

organic

sample

near

infrared

spectra

acquired

on

different

spectrometers

Céline Chauvergne

_{, Laurent Bonnal}

_{, Denis Bastianelli}

_,

Hélène Carrère

_{, Yves Griveau}

_{, Marie-Pierre Jacquemot}

_,

Matthieu Reymond

_{, Valérie Méchin}

_{, Virginie Rossard}

_,

Éric Latrille

a INRAE, Montpellier University, LBE 102 Avenue des Étangs, 11100 Narbonne, France b CIRAD, UMR SELMET, F-34398 Montpellier, France

c Institut Agro, SELMET, University of Montpellier, CIRAD, INRAE, Montpellier, France

d Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 780 0 0 Versailles, France

a

r

t

i

c

l

e

i

n

f

o

Article history: Received 8 July 2020 Revised 18 August 2020 Accepted 27 August 2020 Available online 2 September 2020 Keywords:

Near infrared spectroscopy Spectrum transfer model Chemometrics Organic samples

a

b

s

t

r

a

c

t

Thisdataset presents127 rawnear infraredspectraof dif-ferentorganicsamplesacquiredonthreedifferent spectrom-etersinthreedifferentlabs.Anexampleofdataprocessing isshowntocreatesixspectratransfermodelsbetweenthe threespectrometers(twobytwo).Inordertobuildand val-idatethesetransfer models,thedataset was splitintotwo setsofspectra:afirstset wasusedto computesixspectra transfermodelsthankstothePiecewiseDirect standardisa-tionfunction(PDS).Asecondsetofspectra,independentof thefirstonewasusedtovalidatetransfermodels.Spectrum treatments and models werecreated onChemFlow (https: //vm-chemflow-francegrille.eu/), a free online chemometric softwarethatincludesallthenecessaryfunctions.

© 2020TheAuthors.PublishedbyElsevierInc. ThisisanopenaccessarticleundertheCCBYlicense (http://creativecommons.org/licenses/by/4.0/)

∗ _{Corresponding author.}

E-mail address: [email protected] (É. Latrille). Social media: (É. Latrille)

https://doi.org/10.1016/j.dib.2020.106264

2352-3409/© 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

2 C. Chauvergne, L. Bonnal and D. Bastianelli et al. / Data in Brief 32 (2020) 106264

SpecificationsTable

Subject Spectroscopy

Specific subject area Near infrared spectroscopy, chemometrics

Type of data Table

Figure

How data were acquired Sample spectra were acquired using three different near infrared spectrometers:

NIRFlex N-500 FT-NIR (BUCHI, France, serial number 1,000,001,305) NIR-System50 0 0 (FOSS, Denmark, serial number 94,630,632) ANTARIS II FT-NIR (Thermo Fisher Scientific, USA, serial number AHY0800337)

Data format Raw

Parameters for data collection Near infrared spectra of various organic samples were acquired on the three spectrometers in the standard using conditions. Samples were analysed in either vials or cups.

Description of data collection Organic samples were dried and ground ( < 1 mm) before acquiring near infrared spectra.

Data source location LBE, INRAE, Narbonne, France SELMET, CIRAD, Montpellier, France IJPB, INRAE, Versailles, France

Data accessibility Data are available on public repositories: Repository name: Data INRAE ( https://data.inrae.fr/ ) Data identification number: doi:10.15454/XFTLV4 Direct URL to data: https://doi.org/10.15454/XFTLV4 Repository name: Zenodo

Data identification number: doi:10.15454/XFTLV4

Direct URL to data: https://zenodo.org/record/3908210#.Xvmx _ igzZPY ValueoftheData

• These datacan be usedassupplements forthe descriptionof organicmatter samplesand canbecomparedtootherstudies.

• SpectrawereacquiredusingthreespecificNIRspectrometersandtheycouldbecomparedto spectraprovidedbyotherdevices.Anyresearchercanusethesedatatoperformchemometric analyses.

• This datasetshowsthevalue ofnearinfrared spectroscopycoupledwithchemometrics for inter-laboratoryworks.

1. DataDescription

Dataprovided inthisarticleare127rawnearinfrared spectraofdifferentorganicsamples acquiredonthreedifferentspectrometersinthreedifferentlabs.

Inordertobuildandvalidatetransfermodels,thedatasetwassplitintotwosetsofspectra. Afirst setof92 organicsamples,listed inAppendix 1,wasselectedto covera wide rangeof variationforcellwallcompositiontopromoteawiderangeofspectra,inordertocreate spec-tratransfer models.First,spectrawere acquiredontheBUCHINIRFlex N-500device,in tripli-cateandthen averaged(Fig.1a). Secondly,samplespectrawere acquiredonthe FOSS NIRSys-tem5000 spectrometerin duplicate andwere automatically averaged (Fig. 1b).Finally, spectra wereacquiredontheThermoScientificANTARISIIdevicetentimesandthenaveraged(Fig.1c).

Fig.1danderepresentsBUCHINIRFlexN-500spectraandThermoScientificANTARISII spectra convertedinnmasusuallyrepresentedintheNIRfield.

Spectrometeracquisitionmodalitieswere specifictoeachequipment:absorbancespectrain wavelengths(nm)forFOSSspectrometer,reflectancespectrainwavenumbers(cm−1)forBUCHI spectrometer andabsorbancespectra in wave numbers (cm−1) for ANTARIS spectrometer. Six spectratransfermodelswerecreatedbasedonthisfirstdatasetwithPiecewiseDirect

Standard-Fig. 1. a. 92 averaged BUCHI NIRFlex N-500 spectra of organic samples of the transfer set (raw spectra in reflectance, cm −1 ₎

b. 71 averaged FOSS NIRSystem50 0 0 spectra of organic samples of the transfer set (raw spectra in absorbance, nm)

c. 53 averaged ThermoScientific ANTARIS II spectra of organic samples of the transfer set (raw spectra in absorbance, cm −1 )

d. 92 averaged BUCHI NIRFlex N-500 spectra of organic samples of the transfer set (converted spectra in reflectance, nm)

e. 53 averaged ThermoScientific ANTARIS II spectra of organic samples of the transfer set (converted spectra in ab- sorbance, nm).

4 C. Chauvergne, L. Bonnal and D. Bastianelli et al. / Data in Brief 32 (2020) 106264

Fig. 2. Schematic representation of the transfer model from a FOSS spectrum to a BUCHI spectrum. SimulFilter: algorithm for interpolations, PDS: Piecewise Direct Standardization.

ization(PDS)[1]:transfermodelfromBUCHItoFOSSandviceversa,transfermodelfromBUCHI toANTARISandviceversaandtransfermodelfromFOSStoANTARISandviceversa.Spectrum treatmentsandmodelswerecreatedonChemFlow(https://vm-chemflow-francegrille.eu/)[2],a freeonlinechemometricsoftwarethatincludesallthenecessaryfunctions.

Fig.2 isaschematicrepresentationofthemainfunctionsusedforthetransfermodelfroma FOSSspectrumtoaBUCHIspectrum.Theresultingspectratransfermodelisatransformmatrix (Appendix2),allowing transformingFOSSspectraintoBUCHIspectraby matrixmultiplication. The other five transfer models were established in a same wayandtransform matriceswere usedalike(datanotshowninthearticlebutavailableintherepository).

Then, a second set, of 11sorghum and24 miscanthus samples, listed in Appendix 3,was selectedtovalidatetransfermodelsandestimate thequalityofthesetransfers.Samplespectra ofvalidationsetwereacquiredonthethreedeviceswiththesamemodalitiesasbefore(Fig.3a– e)andtransferredwithprevioustransfermodels(datanotshowninthearticlebutavailablein therepository).

2. Experimentaldesign,materials,andmethods 2.1. Samplepreparation

The127rawsamplesweredriedeitherbyfreeze-dryingorbyovendryingandthenground to1mmsizebeforebeingpackagedinhermeticbottlesorbags.Allsampleswereeithershared betweenlaboratories quicklyso that the spectra could be acquired on similar conditions (no materialdegradation)orsharedwithalongertimeframe.

2.2.Datacollection

FOSSspectrometer NIRSystem5000 gaveabsorbancespectra inwavelength witharange of 1100nm to 2498nm and a resolution of 2nm. Each spectrum was an average of32 spectral readingsofthesamecup.Allofthe106(71+35)sampleswerepouredinto3.5cmdiametercups (about4g)andspectrawereacquiredinduplicateandautomaticallyaveraged.Theoutputdata formatwas.csv, compatiblewithChemFlow,sodata weredirectlyimported intothe software andconvertedin.tsvformat.

BUCHIN-500spectrometergavereflectancespectrainwave numbers,witharangeof4000 cm−1 to 10,000 cm−1 andwitha resolution of4 cm−1.Each spectrumwas an average of96 spectral readingsofthe samecupor vial.Allofthe 127(92+35)sampleswere poured either into10cmdiametercups(about30g)orinto1.3cmdiametervials(about3g)andspectrawere acquiredintriplicateandthenaveraged.

ThermoScientificANTARISII spectrometergaveabsorbancespectrainwave numberswitha rangeof4000cm−1 to10,001cm−1 andwitharesolutionof3.86cm−1.Allofthe82(53₊29) samplesweredividedinto3or10subsamples(aliquots) andpouredinto0.8cmdiametervials

Fig. 3. a. 35 averaged BUCHI NIRFlex N-500 spectra of organic samples of the transfer validation set (raw spectra in reflectance, cm −1 )

b. 35 averaged FOSS NIRSystem50 0 0 spectra of organic samples of the transfer validation set (raw spectra in absorbance, nm)

c. 29 averaged ThermoScientific ANTARIS II spectra of organic samples of the transfer validation set (raw spectra in absorbance, cm −1 ₎

d. 35 averaged BUCHI NIRFlex N-500 spectra of organic samples of the transfer validation set (converted spectra in reflectance, nm)

e. 29 averaged ThermoScientific ANTARIS II spectra of organic samples of the transfer validation set (converted spectra in absorbance, nm).

6 C. Chauvergne, L. Bonnal and D. Bastianelli et al. / Data in Brief 32 (2020) 106264

(about2ml)whichwasscannedonce.Foreachsubsample,anaverage(spectrum)of64spectral readingswasrecorded.

The output data format forBUCHI and ANTARIS spectrometers was .jdx, compatible with ChemFlow,sodataweredirectlyimportedintothesoftwareandconvertedin.tsvformat.

2.3.Transfermodelcreation

InordertocreateFOSStoBUCHIspectratransfermodel,spectraofthetransfersetneeded pretreatmentstomatchthespectralmodalities.TousethePDSfunction,thespectralmodalities usedwereabsorbanceandcm−1unit.Therefore,thefirststepwastotransformBUCHIspectrain absorbancewiththelogarithmfunctionandFOSSspectraincm−1 unitwithasimpleunit con-version.Then,asspectradidnothavethesameunitvalues,aSimulFilterfunction(extrapolation functionwithunit widthof2) wasapplied tomatchFOSS spectrawave numberswithBUCHI spectravalues.ThetransfermodelwascreatedwiththePDSfunction,withanumberof chan-nels ineach window equal to 7.Finally,FOSS output spectra were transformed inreflectance spectrawithpowerfunction(10−x)tofitwithBUCHIspectralmodalities.

DeclarationofCompetingInterest

Theauthorsdeclarethattheyhavenoknowncompetingfinancialinterestsorpersonal rela-tionshipswhichhave,orcouldbeperceivedtohave,influencedtheworkreportedinthisarticle.

Acknowledgments

Thiswork wassupported by the BiomassForthe Future projectfromthe French National ResearchAgency (ANR, grantANR-11-BTBR-0006-BFF).The authors acknowledgethe contribu-tionoftheChemHouse ResearchGroup,Montpellier,France.Thiswork hasbenefitedfromthe support of IJPB’s Plant Observatory technological platforms. The IJPB benefits from the sup-port ofSaclay Plant Sciences-SPS(ANR-17-EUR-0007).The authors acknowledge the contribu-tion of Bio2E platform, INRAE, Environemental Biotechnology and Biorefinery Platform (DOI: 10.15454/1.557234103446854E12).

Supplementarymaterials

Supplementarymaterial associated withthisarticlecan be found,inthe onlineversion, at doi:10.1016/j.dib.2020.106264.

Appendix

Appendix1isavailableatthislink:https://doi.org/10.15454/XFTLV4/GCPQ0Z

Appendix2isavailableatthislink:https://doi.org/10.15454/XFTLV4/ZMTH60

Appendix3isavailableatthislink:https://doi.org/10.15454/XFTLV4/89FTMC

References

[1] Y. Wang , D.J. Veltkamp , B.R. Kowalski , Multivariate instrument standardization, Anal. Chem. 63 (23) (1991) 2750–2756 .

[2] V. Rossard, J.C. Boulet, F. Gogé, E. Latrille, J.M. Roger, ChemFlow, chemometrics using Galaxy, in: Proceedings of the Galaxy Community Conference - GCC2016, Bloomington, USA, 2016 (2016-06-24 - 2016-07-29), doi: 10.7490/ f10 0 0research.1112573.1 .