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dc.contributor.authorFrizzarin, Maria
dc.contributor.authorBevilacqua, Antonio
dc.contributor.authorDhariyal, Bhaskar
dc.contributor.authorDomijan, Katarina
dc.contributor.authorFerraccioli, Frederico
dc.contributor.authorHayes, Elena
dc.contributor.authorIfrim, Georgiana
dc.contributor.authorKonkowleska, Agnieszka
dc.contributor.authorLe Nguyễn, Thach
dc.contributor.authorMbaka, Uche
dc.contributor.authorRanzato, Giovanna
dc.contributor.authorSingh, Ashish
dc.contributor.authorStefanucci, Marco
dc.contributor.authorCasa, Alessandro
dc.date.accessioned2021-09-06T13:47:58Z
dc.date.available2021-09-06T13:47:58Z
dc.date.issued2021-09-06
dc.identifier.urihttp://hdl.handle.net/11019/2597
dc.descriptiondataseten_US
dc.description.abstractchemometric data analysis challenge has been arranged during the first edition of the “International Workshop on Spectroscopy and Chemometrics”, organized by the Vistamilk SFI Research Centre and held online in April 2021. The aim of the competition was to build a calibration model in order to predict milk quality traits exploiting the information contained in mid-infrared spectra only. Three different traits have been provided, presenting heterogeneous degrees of prediction complexity thus possibly requiring trait-specific modelling choices. In this paper the different approaches adopted by the participants are outlined and the insights obtained from the analyses are critically discussed.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesChemometrics and Intelligent Laboratory Systems;
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectChemometricsen_US
dc.subjectFourier transform mid-infrared spectroscopyen_US
dc.subjectmachine learningen_US
dc.subjectmilk qualityen_US
dc.titleMid infrared spectroscopy and milk quality traits: a data analysis competition at the “International Workshop on Spectroscopy and Chemometrics 2021”en_US
dc.typeDataseten_US
dc.embargo.terms2021-09-06en_US
dc.contributor.sponsorScience Foundation Irelanden_US
dc.contributor.sponsorDepartment of Agriculture, Food and the Marineen_US
dc.contributor.sponsorEuropean Unionen_US
dc.contributor.sponsorGrantNumber16/RC/3835en_US
dc.contributor.sponsorGrantNumberSFI/12/RC/2289_P2)en_US
dc.contributor.sponsorGrantNumber18/SIRG/5562en_US
dc.contributor.sponsorGrantNumber841882en_US


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    Teagasc LIvestock Systems Department includes Dairy, Cattle and Sheep research.

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Attribution-NonCommercial-ShareAlike 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 4.0 International