Frizzarin, Maria and Bevilacqua, Antonio and Dhariyal, Bhaskar and Domijan, Katarina and Ferraccioli, Federico and Hayes, Elena and Ifrim, Georgiana and Konkolewska, Agnieszka and Le Nguyen, Thach and Mbaka, Uche and Ranzato, Giovanna and Singh, Ashish and Stefanucci, Marco and Casa, Alessandro (2021) Mid infrared spectroscopy and milk quality traits: A data analysis competition at the “International Workshop on Spectroscopy and Chemometrics 2021”. Chemometrics and Intelligent Laboratory Systems, 219. p. 104442. ISSN 0169-7439

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Abstract

A chemometric 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.

Item Type:	Article
Additional Information:	Cite as: Maria Frizzarin, Antonio Bevilacqua, Bhaskar Dhariyal, Katarina Domijan, Federico Ferraccioli, Elena Hayes, Georgiana Ifrim, Agnieszka Konkolewska, Thach Le Nguyen, Uche Mbaka, Giovanna Ranzato, Ashish Singh, Marco Stefanucci, Alessandro Casa, Mid infrared spectroscopy and milk quality traits: A data analysis competition at the “International Workshop on Spectroscopy and Chemometrics 2021”, Chemometrics and Intelligent Laboratory Systems, Volume 219, 2021, 104442, ISSN 0169-7439, https://doi.org/10.1016/j.chemolab.2021.104442
Keywords:	Chemometrics; Fourier transform mid-infrared spectroscopy; Machine learning; Milk quality;
Academic Unit:	Faculty of Science and Engineering > Mathematics and Statistics Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	17949
Identification Number:	https://doi.org/10.1016/j.chemolab.2021.104442
Depositing User:	Katarina Domijan
Date Deposited:	14 Dec 2023 09:28
Journal or Publication Title:	Chemometrics and Intelligent Laboratory Systems
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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